diff --git a/docs/404.html b/docs/404.html index 65eb510..9aac88a 100644 --- a/docs/404.html +++ b/docs/404.html @@ -1,76 +1,33 @@ - - - - + + + + - Page not found (404) • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + - - - - - + + + - - - -
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Page not found (404)

@@ -155,31 +112,33 @@

Page not found (404)

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+ + - - diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 700419f..68adae7 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -1,76 +1,18 @@ - - - - - - - -License • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -License • RLumModel - - - - - - + + - - -
-
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+

License

@@ -829,31 +762,29 @@

License

+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel.html b/docs/articles/RLumModel_-_Getting_started_with_RLumModel.html index 9953e40..f9f8ecd 100644 --- a/docs/articles/RLumModel_-_Getting_started_with_RLumModel.html +++ b/docs/articles/RLumModel_-_Getting_started_with_RLumModel.html @@ -25,6 +25,8 @@ + +
+

RLumModel - Getting started with RLumModel

-

Johannes Friedrich (University of Bayreuth, DE) & Sebastian Kreutzer (Earth Sciences and Geography, Abersytwyth University, UK)

+

Johannes +Friedrich (University of Bayreuth, DE) & Sebastian Kreutzer +(Geography and Earth Sciences, Aberystwyth University, UK)

-

2021-11-08

+

2022-02-20

- Source: vignettes/RLumModel_-_Getting_started_with_RLumModel.Rmd + Source: vignettes/RLumModel_-_Getting_started_with_RLumModel.Rmd
-
-

-Introduction

-

This vignette shows a few examples for the R-package ‘RLumModel’. The main function model_LuminescenceSignals() and their arguments will be explained. All calculations were done with ‘RLumModel’ (version: 0.2.9) and ‘Luminescence’ (version: 0.9.16.9000.30).

+
+

Introduction +

+

This vignette shows a few examples for the R-package +‘RLumModel’. The main function model_LuminescenceSignals() +and their arguments will be explained. All calculations were done with +‘RLumModel’ (version: 0.2.10) and ‘Luminescence’ (version: +0.9.19.9000.7).

-
-

-Object structure of RLumModel

-

The output from the main function model_LuminescenceSignals() is of class RLum.Analysis (Kreutzer et al. 2012) and contains data of class RLum.Data.Curve in the slot ‘records’. The advantage of this infrastructure is that the package ‘Luminescence’ offers a lot of methods to visualize and manipulate data.

-

All simulated data are stored in the slot ‘records’: TL/OSL/RF curves as well as the concentrations of every energy level from every step.

-

The following code loads a data set provided by the ‘RLumModel’ package and shows how to separate TL/OSL/RF data from concentrations and how to visualize them.

+
+

Object structure of RLumModel +

+

The output from the main function +model_LuminescenceSignals() is of class +RLum.Analysis (Kreutzer et al. +2012) and contains data of class RLum.Data.Curve in +the slot ‘records’. The advantage of this infrastructure is that the +package ‘Luminescence’ offers a lot of methods to visualize and +manipulate data.

+

All simulated data are stored in the slot ‘records’: TL/OSL/RF curves +as well as the concentrations of every energy level from every step.

+

The following code loads a data set provided by the ‘RLumModel’ +package and shows how to separate TL/OSL/RF data from concentrations and +how to visualize them.

-data("ExampleData.ModelOutput", package = "RLumModel")
+data("ExampleData.ModelOutput", package = "RLumModel")
 
 ##show class
-class(model.output)
+class(model.output)
 
 ##show structure
-Luminescence::structure_RLum(model.output)
+Luminescence::structure_RLum(model.output)
 
 ##separate TL-curve from TL-concentrations
-TL_curve <- Luminescence::get_RLum(model.output, recordType = "TL$")
-TL_conc <- Luminescence::get_RLum(model.output, recordType = "(TL)", drop = FALSE)
+TL_curve <- Luminescence::get_RLum(model.output, recordType = "TL$")
+TL_conc <- Luminescence::get_RLum(model.output, recordType = "(TL)", drop = FALSE)
 
 ##also possible: TL_curve <- get_RLum(model.output, record.id = 1)
 
 ##plot results
-Luminescence::plot_RLum(TL_curve)
-Luminescence::plot_RLum(TL_conc)
+Luminescence::plot_RLum(TL_curve) +Luminescence::plot_RLum(TL_conc)

Some notes to the code example above:

    -
  • in ‘TL_curve <- …’ appears “TL$”. This is necessary to match the pattern “TL” without any sign after “TL”, e.g. a bracket. The brackets are used (by default) for the concentrations.
    • -
  • in ‘TL_conc <- …’ the pattern “(TL)” will match all concentrations with “(TL)”, see structure.
    • +
  • in ‘TL_curve <- …’ appears “TL$”. This is necessary to match the +pattern “TL” without any sign after “TL”, e.g. a bracket. The brackets +are used (by default) for the concentrations.
    • +
  • in ‘TL_conc <- …’ the pattern “(TL)” will match all +concentrations with “(TL)”, see structure.
  • -drop = FALSE was used to keep the RLum.Analysis class for ‘TL_conc’.
    • -
  • To see a single plot of every energy-level, use the option plot.single = TRUE in plot_RLum(). For more details see the manual of ‘Luminescence’.
    • +drop = FALSE was used to keep the +RLum.Analysis class for ‘TL_conc’. +
  • To see a single plot of every energy-level, use the option +plot.single = TRUE in plot_RLum(). For more +details see the manual of ‘Luminescence’.
 ##plot every energy-level by an extra plot
-Luminescence::plot_RLum(TL_conc, plot.single = TRUE)
-

It is also possible to choose a RLum.Data.Curve by their ‘record.id’, which can be seen with:

+Luminescence::plot_RLum(TL_conc, plot.single = TRUE)
+

It is also possible to choose a RLum.Data.Curve by their +‘record.id’, which can be seen with:

 ##see structure of model.output
-Luminescence::structure_RLum(model.output)
+Luminescence::structure_RLum(model.output)
-
-

-Selecting a quartz luminescence model

-

The first argument required for the function model_LuminescenceSignals() is the name of a quartz luminescence model to be used, respectively the used parameter set in this quartz luminescence model. All currently implemented quartz luminescence models were described in Friedrich, Kreutzer, and Schmidt (2016). The command to select a set of parameters from a specific model in RLumModel is a character string with the name of the author and the year, e.g.

+
+

Selecting a quartz luminescence model +

+

The first argument required for the function +model_LuminescenceSignals() is the name of a quartz +luminescence model to be used, respectively the used parameter set in +this quartz luminescence model. All currently implemented quartz +luminescence models were described in Friedrich, +Kreutzer, and Schmidt (2016). The command to select a set of +parameters from a specific model in RLumModel is a +character string with the name of the author and the year, e.g.

 model <- "Bailey2001"
-

The available models are “Bailey2001”, “Bailey2002”, “Bailey2004”, “Pagonis2007”, “Pagonis2008”,“Friedrich2017” and “customized” (R. M. Bailey (2001), R. Bailey (2002), R. Bailey (2004), V. Pagonis, Chen, and Wintle (2007), V. Pagonis et al. (2008b), Friedrich et al. (2017)). For customized or own parameter sets, see vignette RLumModel - Using own parameter sets

-

The corresponding parameter set will be loaded automatically with the function call.

+

The available models are “Bailey2001”, “Bailey2002”, “Bailey2004”, +“Pagonis2007”, “Pagonis2008”,“Friedrich2017” and “customized” (R. M. Bailey (2001), R. +Bailey (2002), R. Bailey (2004), +V. Pagonis, Chen, and Wintle (2007), V. Pagonis et al. (2008b), Friedrich et al. (2017)). For customized or own +parameter sets, see vignette RLumModel - Using own +parameter sets

+

The corresponding parameter set will be loaded automatically with the +function call.

-
-

-Creating a sequence

-

The second argument in the model_LuminescenceSignals() function is the sequence to be simulated. There are three different ways of creating a sequence.

-

For all sequences, temperature differences between sequence steps are automatically simulated with a heating or cooling step in between. Also, after irradiating the sample, it is automatically kept at irradiation temperature for further 5 s to allow the system to relax prior to the next step (R. M. Bailey 2001).

-
-

-Risø SEQ files

-

The first one is to use the popular and freely available Risø to build a personal sequence and to save it as a SEQ-file (*.seq). Files created by the Sequence Editor can be imported directly using the path of the SEQ-file. The package comes along with an example SEQ-file in the package folder in ‘extdata’. Thus, a potential sequence is created with

+
+

Creating a sequence +

+

The second argument in the model_LuminescenceSignals() +function is the sequence to be simulated. There are three different ways +of creating a sequence.

+

For all sequences, temperature differences between sequence steps are +automatically simulated with a heating or cooling step in between. Also, +after irradiating the sample, it is automatically kept at irradiation +temperature for further 5 s to allow the system to relax prior to the +next step (R. M. Bailey 2001).

+
+

Risø SEQ files +

+

The first one is to use the popular and freely available Risø to +build a personal sequence and to save it as a SEQ-file (*.seq). Files +created by the Sequence Editor can be imported directly using the path +of the SEQ-file. The package comes along with an example SEQ-file in the +package folder in ‘extdata’. Thus, a potential sequence is created +with

-sequence <- system.file(
+sequence <- system.file(
   "extdata",
   "example_SAR_cycle.SEQ",
   package = "RLumModel")
-

or wherever the SEQ-file is stored. While in the Sequence Editor irradiation is commonly defined in seconds, performing the simulation requires a dose transformation to Gray. Therefore, the function model_LuminescenceSignals() offers a special argument called lab.dose_rate, representing the dose rate of the irradiation unit in the laboratory. By default, this dose rate is 1 Gy/s, but can be modified, e.g.,

+

or wherever the SEQ-file is stored. While in the Sequence Editor +irradiation is commonly defined in seconds, performing the simulation +requires a dose transformation to Gray. Therefore, the function +model_LuminescenceSignals() offers a special argument +called lab.dose_rate, representing the dose rate of the +irradiation unit in the laboratory. By default, this dose rate is 1 +Gy/s, but can be modified, e.g.,

 lab.dose_rate <-  0.105
-
-

-Keywords

-

The second way of creating a sequence is by referring to a list with keywords and a certain order of code numbers or named values, which are shown in Table 1. With these keywords, it is possible to create quickly an R object of type list, which can be read by the model_LuminescenceSignals() function.

- +
+

Keywords +

+

The second way of creating a sequence is by referring to a list with +keywords and a certain order of code numbers or named values, which are +shown in Table 1. With these keywords, it is possible to create quickly +an R object of type list, which can be read by the +model_LuminescenceSignals() function.

+
@@ -249,7 +307,8 @@

Linear modulated OSL

@@ -271,7 +330,8 @@

RF during heating/cooling

@@ -322,20 +382,33 @@

Keywords in RLumModel for creating sequences
-’temp’ [°C], ’duration’ [s], optional: ’start_power’ [%], ’end_power’ [%] +’temp’ [°C], ’duration’ [s], optional: ’start_power’ [%], ’end_power’ +[%]
-’temp_begin’ [°C], ’temp_end’ [°C], ‘heating rate’ [°C/s], ‘dose_rate’ [Gy/s] +’temp_begin’ [°C], ’temp_end’ [°C], ‘heating rate’ [°C/s], ‘dose_rate’ +[Gy/s]

Some examples to this kind of sequence creating:

-sequence <- list(
- IRR = c(temp = 20, dose = 10, dose_rate = 1),
- TL = c(temp_begin = 20, temp_end = 400 , heating_rate = 5))
-

This sequences describes an irradiation simulation at 20 °C with a dose of 10 Gy and a dose rate of 1 Gy/s, which is followed by a TL simulation from 20 °C to 400 °C with a heating rate of 5 °C/s. Note that it is important that for each sequence keyword like ‘IRR’ or ‘TL’ either the vector has to be named or the correct order of arguments is used, see ‘sub-arguments’ in Table 1. Thus the above mentioned code is equivalent to the following one:

+sequence <- list( + IRR = c(temp = 20, dose = 10, dose_rate = 1), + TL = c(temp_begin = 20, temp_end = 400 , heating_rate = 5))
+

This sequences describes an irradiation simulation at 20 °C with a +dose of 10 Gy and a dose rate of 1 Gy/s, which is followed by a TL +simulation from 20 °C to 400 °C with a heating rate of 5 °C/s. Note that +it is important that for each sequence keyword like ‘IRR’ or ‘TL’ either +the vector has to be named or the correct order of arguments is used, +see ‘sub-arguments’ in Table 1. Thus the above mentioned code is +equivalent to the following one:

-sequence <- list(
-  IRR = c(20, 10, 1),
-  TL = c(20, 400, 5))
+sequence <- list( + IRR = c(20, 10, 1), + TL = c(20, 400, 5))
-
-

-Creating a SAR/DRT sequence

-

However, to create a SAR or dose-recovery-test (DRT) sequence with the Risø Sequence Editor or with keywords is time-consuming, because it contains a lot of individual sequence steps (preheat, optical stimulation, irradiation, …). Therefore, a third way was implemented in ‘RLumModel’ to create a (SAR) sequence after Murray and Wintle (2000) with the (required) keywords RegDose, TestDose, PH, CH and OSL temp. In addition to these keywords, the user is able to set more detailed parameters for the SAR sequence, see Table 2:

- +
+

Creating a SAR/DRT sequence +

+

However, to create a SAR or dose-recovery-test (DRT) sequence with +the Risø Sequence Editor or with keywords is time-consuming, because it +contains a lot of individual sequence steps (preheat, optical +stimulation, irradiation, …). Therefore, a third way was implemented in +‘RLumModel’ to create a (SAR) sequence after Murray and Wintle (2000) +with the (required) keywords RegDose, TestDose, PH, CH and OSL temp. In +addition to these keywords, the user is able to set more detailed +parameters for the SAR sequence, see Table 2:

+
@@ -476,29 +549,40 @@

Keywords in RLumModel for creating SAR sequences

So a possible DRT sequence could be the next code example:

-sequence <- list(
-  RegDose = c(0,10,20,50,90,0,10),
+sequence <- list(
+  RegDose = c(0,10,20,50,90,0,10),
   TestDose = 2,
   PH = 220,
   CH = 220,
   OSL_temp = 125,
   Irr_2recover = 20)
-

This sequence describes a DRT, where a dose of 20 Gy will be recovered with this test. The regenerative doses are defined as 0 (natural), 10 Gy, 20 Gy, 50 Gy, 90 Gy and for recuperation and recycling ratio 0 Gy and 10 Gy, respectively. The test dose is defined as 2 Gy. Preheat and cutheat are at 220 °C and all OSL measurements are simulated at 125 °C. There are more options to set, see Table 2.

-

The ‘RLumModel’ function model_LuminescenceSignals() is able to interpret this (sequence-) list as a DRT sequence.

+

This sequence describes a DRT, where a dose of 20 Gy will be +recovered with this test. The regenerative doses are defined as 0 +(natural), 10 Gy, 20 Gy, 50 Gy, 90 Gy and for recuperation and recycling +ratio 0 Gy and 10 Gy, respectively. The test dose is defined as 2 Gy. +Preheat and cutheat are at 220 °C and all OSL measurements are simulated +at 125 °C. There are more options to set, see Table 2.

+

The ‘RLumModel’ function model_LuminescenceSignals() is +able to interpret this (sequence-) list as a DRT sequence.

-
-

-Working examples

-
-

-Simulate a TL measurement

-

First of all, a sequence is needed, which produces a TL signal after the sample has received a dose:

+
+

Working examples +

+
+

Simulate a TL measurement +

+

First of all, a sequence is needed, which produces a TL signal after +the sample has received a dose:

-sequence <- list (
-IRR = c (20 , 10 , 1) ,
-TL = c (20 , 400 , 5))
-

Here, at a temperature of 20 °C a dose of 10 Gy was applied with a dose rate of 1 Gy/s followed by a TL measurement from 20 °C to 400 °C with a heating rate of 5 °C/s. Running this sequence with the model_LuminescenceSignals() function produces a model output:

+sequence <- list ( +IRR = c (20 , 10 , 1) , +TL = c (20 , 400 , 5))
+

Here, at a temperature of 20 °C a dose of 10 Gy was applied with a +dose rate of 1 Gy/s followed by a TL measurement from 20 °C to 400 °C +with a heating rate of 5 °C/s. Running this sequence with the +model_LuminescenceSignals() function produces a model +output:

 model.output <- model_LuminescenceSignals(
   model = "Bailey2001",
@@ -509,18 +593,21 @@ 

 TL curve with parameter set ‘Bailey2001’ after 10 Gy laboratory dose
-

This results in a TL curve like the one published in (R. M. Bailey (2001), Fig. 1), see figure above. In a further step, it is easy to produce known TL phenomena like the shift of the TL peak with varying heating rate. For this purpose, a loop over a TL simulation changes the heating rate in each run.

+

This results in a TL curve like the one published in (R. M. Bailey (2001), Fig. 1), see figure above. +In a further step, it is easy to produce known TL phenomena like the +shift of the TL peak with varying heating rate. For this purpose, a loop +over a TL simulation changes the heating rate in each run.

 ##set heating rate
-heating.rate <- seq(from = 2, to = 10, by = 2)
+heating.rate <- seq(from = 2, to = 10, by = 2)
 
 ##model signals
 ##"verbose = FALSE" for no terminal output
 ## "TL$" for exact matching TL and not (TL)
-model.output <- lapply(heating.rate, function(x){
-  sequence <- list(
-   IRR = c(20, 10, 1),
-   TL = c(20, 400, x))
+model.output <- lapply(heating.rate, function(x){
+  sequence <- list(
+   IRR = c(20, 10, 1),
+   TL = c(20, 400, x))
 
 
   TL_data <- model_LuminescenceSignals(
@@ -529,7 +616,7 @@ 

       plot = FALSE,
       verbose = FALSE)
   
-  return(Luminescence::get_RLum(TL_data, recordType = "TL$", drop = FALSE))
+  return(Luminescence::get_RLum(TL_data, recordType = "TL$", drop = FALSE))
 
 })
 
@@ -542,7 +629,7 @@ 

  xlab = "Temperature [\u00B0C]",
  ylab = "TL signal [a.u.]",
  main = "TL signal with different heating rates",
- legend.text = paste(heating.rate, "°C/s"),
+ legend.text = paste(heating.rate, "°C/s"),
  combine = TRUE)
TL signal with different heating rates

@@ -551,32 +638,46 @@

Some notes to the code above:

    -
  • the return of the lapply function is a RLum.Analysis object, because of drop = FALSE
    • +
  • the return of the lapply function is a RLum.Analysis +object, because of drop = FALSE
  • -recordType = TL$ is necessary to match the character TL exact and not the concentrations
    • +recordType = TL$ is necessary to match the character TL +exact and not the concentrations
  • -merge_RLum is necessary to merge all the single RLum.Analysis objects in the list ‘model.output’ together to one RLum.Analysis object
    • -
  • to see the results with another parameter set, only model = "..." has to be changed (see Sec. 2)
    • +merge_RLum is necessary to merge all the single +RLum.Analysis objects in the list ‘model.output’ together +to one RLum.Analysis object +
  • to see the results with another parameter set, only +model = "..." has to be changed (see Sec. 2)
-
-

-Simulating thermal activation characteristics (TACs)

-

Another frequently simulated phenomenon is the sensitisation of quartz TL by \(\beta\)- or \(\gamma\)-irradiation followed by activation at high temperatures Adamiec et al. (2004), termed as thermal activation characteristics (TACs). For a simulation sequence, the reader is referred to V. Pagonis et al. (2008a), Tab. 1. To simulate this phenomenon with the model_LuminescenceSignals() function, a loop causing a stepwise increase of the activation temperature is needed. The resulting intensity of the 110 °C TL peak can be plotted against the activation temperature, which shows TAC for the model parameters of “Pagonis2007”.

+
+

Simulating thermal activation characteristics (TACs) +

+

Another frequently simulated phenomenon is the sensitisation of +quartz TL by \(\beta\)- or \(\gamma\)-irradiation followed by activation +at high temperatures Adamiec et al. +(2004), termed as thermal activation characteristics (TACs). For +a simulation sequence, the reader is referred to V. Pagonis et al. (2008a), Tab. 1. To simulate +this phenomenon with the model_LuminescenceSignals() +function, a loop causing a stepwise increase of the activation +temperature is needed. The resulting intensity of the 110 °C TL peak can +be plotted against the activation temperature, which shows TAC for the +model parameters of “Pagonis2007”.

 ##set temperature
-act.temp <- seq(from = 80, to = 600, by = 20)
+act.temp <- seq(from = 80, to = 600, by = 20)
 
 ##loop over temperature
-model.output <- vapply(X = act.temp, FUN = function(x) {
+model.output <- vapply(X = act.temp, FUN = function(x) {
   
   ##set sequence, note: sequence includes sample history
-  sequence <- list(
-    IRR = c(20, 1, 1e-11),
-    IRR = c(20, 10, 1),
-    PH = c(x, 1),
-    IRR = c(20, 0.1, 1),
-    TL = c(20, 150, 5)
+  sequence <- list(
+    IRR = c(20, 1, 1e-11),
+    IRR = c(20, 10, 1),
+    PH = c(x, 1),
+    IRR = c(20, 0.1, 1),
+    TL = c(20, 150, 5)
     )
 
   ##run simulation
@@ -589,10 +690,10 @@ 

     )
   
   ## "TL$" for exact matching TL and not (TL)
-  TL_curve <- Luminescence::get_RLum(temp, recordType = "TL$")
+  TL_curve <- Luminescence::get_RLum(temp, recordType = "TL$")
 
   ##return max value in TL curve
-  return(max(get_RLum(TL_curve)[,2]))
+  return(max(get_RLum(TL_curve)[,2]))
 
 }, FUN.VALUE = 1)
@@ -601,22 +702,26 @@

-
-

-Simulating dependency of the OSL signal on the illumination power density

-

The function model_LuminescenceSignals() is also capable of simulating OSL phenomena. The next figure shows the dependency of the OSL signal on the power density of illumination for the model “Bailey2004”.

+
+

Simulating dependency of the OSL signal on the illumination power +density +

+

The function model_LuminescenceSignals() is also capable +of simulating OSL phenomena. The next figure shows the dependency of the +OSL signal on the power density of illumination for the model +“Bailey2004”.

 ##set optical power [%]
-optical_power <- c(0,20,40,60,80,100)
+optical_power <- c(0,20,40,60,80,100)
 
 ##loop over power 
-model.output <- lapply(optical_power, function(x){
+model.output <- lapply(optical_power, function(x){
 
   ##set sequence
-  sequence <- list(
-    IRR = c(20, 50, 1),
-    PH = c(220, 10, 5),
-    OSL = c(125, 50, x))
+  sequence <- list(
+    IRR = c(20, 50, 1),
+    PH = c(220, 10, 5),
+    OSL = c(125, 50, x))
 
   
   data <-  model_LuminescenceSignals(
@@ -626,44 +731,56 @@ 

     verbose = FALSE)
   
   ##"OSL$" for exact matching OSL and not (OSL)
-  return(Luminescence::get_RLum(data, recordType = "OSL$", drop = FALSE))
+  return(Luminescence::get_RLum(data, recordType = "OSL$", drop = FALSE))
   
 })
 
 ##merge output
-model.output.merged <- Luminescence::merge_RLum(model.output)
+model.output.merged <- Luminescence::merge_RLum(model.output)
 
 ##plot results
-Luminescence::plot_RLum(
+Luminescence::plot_RLum(
   object = model.output.merged,
   xlab = "Illumination time [s]",
   ylab = "OSL signal [a.u.]",
-  legend.text = paste("Optical power ", 20 * optical_power / 100," mW/cm^2"),
+  legend.text = paste("Optical power ", 20 * optical_power / 100," mW/cm^2"),
   combine = TRUE 
   )
OSL measurement with different optical power densities with the parameter set of 'Bailey2004'

-OSL measurement with different optical power densities with the parameter set of ‘Bailey2004’ +OSL measurement with different optical power densities with the +parameter set of ‘Bailey2004’

-
-

-Simulating and analysing SAR measurements

-

For simulating a DRT, it is necessary to define a sequence with the keyword Irr_2recover, as mentioned in Section 4.3.

-

It should be mentioned that a simulation of a combinded PHPT and DRT may be very time-consuming, because for every preheat temperature a complete SAR cycle has to be run. A typical DRT sequence featuring various PH temperatures in ‘RLumModel’ is listed below. Note that in such a DRT simulation a loop over different preheat temperatures has to be written, utilising characteristic parameters from the literature. The test dose is set to 10% and the regeneration dose points to 40%, 70%, 130%, 160%, 0% and 40% of the recovery dose.

-

The data created by ‘RLumModel’ can be directly passed to the functions Luminescence::analyse_SAR.CWOSL() and Luminescence::plot_DRTResults() for routine analyses and plotting.

+
+

Simulating and analysing SAR measurements +

+

For simulating a DRT, it is necessary to define a sequence with the +keyword Irr_2recover, as mentioned in Section 4.3.

+

It should be mentioned that a simulation of a combinded PHPT and DRT +may be very time-consuming, because for every preheat temperature a +complete SAR cycle has to be run. A typical DRT sequence featuring +various PH temperatures in ‘RLumModel’ is listed below. Note that in +such a DRT simulation a loop over different preheat temperatures has to +be written, utilising characteristic parameters from the literature. The +test dose is set to 10% and the regeneration dose points to 40%, 70%, +130%, 160%, 0% and 40% of the recovery dose.

+

The data created by ‘RLumModel’ can be directly passed to the +functions Luminescence::analyse_SAR.CWOSL() and +Luminescence::plot_DRTResults() for routine analyses and +plotting.

 ##set PH temperatures
-PH_temp <- seq(from = 160, to = 300, by = 20)
+PH_temp <- seq(from = 160, to = 300, by = 20)
 
 ##set regeneration doses
-RegDose = c(0, 80, 140, 260, 320, 0, 80)
+RegDose = c(0, 80, 140, 260, 320, 0, 80)
 
 ##loop over PH temperatures
-DRT.output <- lapply(PH_temp, function(x){
+DRT.output <- lapply(PH_temp, function(x){
 
-  sequence <- list(
+  sequence <- list(
        RegDose = RegDose,
        TestDose = 20,
        PH = x,
@@ -677,7 +794,7 @@ 

        plot = FALSE,
        verbose = FALSE)
 
-  results <- Luminescence::analyse_SAR.CWOSL(
+  results <- Luminescence::analyse_SAR.CWOSL(
        object = model.output,
        signal.integral.min = 1,
        signal.integral.max = 7,
@@ -688,26 +805,26 @@ 

        plot = FALSE)
                                                             
   temp <- get_RLum(results)
-  out <- data.frame(
+  out <- data.frame(
     De = temp$De, 
     De.error = temp$De.Error)
     
-  return(out)
+  return(out)
 })
-
## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 179.1 | D01 = 101.51
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 179.46 | D01 = 101.46
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 180.18 | D01 = 101.4
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 180.6 | D01 = 101.41
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 182.24 | D01 = 101.44
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 179.85 | D01 = 102.26
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 166.73 | D01 = 111.51
-## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 159.15 | D01 = 161.2
+
## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 179.1 | D01 = 101.51
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 179.46 | D01 = 101.46
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 180.18 | D01 = 101.4
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 180.6 | D01 = 101.41
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 182.24 | D01 = 101.44
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 179.85 | D01 = 102.26
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 166.73 | D01 = 111.51
+## [plot_GrowthCurve()] Fit: EXP (interpolation) | De = 159.15 | D01 = 161.2
 ##output as data.frame for plot_DRTResults
-DRT.result <- as.data.frame(do.call(rbind, DRT.output))
+DRT.result <- as.data.frame(do.call(rbind, DRT.output))
 
 ##plot DRT.results
-Luminescence::plot_DRTResults(
+Luminescence::plot_DRTResults(
      DRT.result, 
      preheat = PH_temp,
      given.dose = 200)
@@ -716,13 +833,24 @@

Dose recovery test (DRT) with the parameter set of ‘Pagonis2008’

-

In the code above, plot = FALSE was chosen, because a single OSL plot is not necessary to analyse a SAR sequence. To calculate a De from the produced RLum.Analysis object ‘model.output’, the function Luminescence::analyse_SAR.CWOSL() is suitable. After specifying a number of evaluation parameters (signal and background integration interval, dose points and fit function for the dose response curve) and the analysis process, the reduced data are stored in an RLum.Results object, here termed ‘results’ . A background integration interval from 301 to 401 translates to the signal from 30 s to 40 s, because a channel has the default width of 0.1 s. Accordingly, the signal integral ranges from 0.1 s to 0.7 s.

+

In the code above, plot = FALSE was chosen, because a +single OSL plot is not necessary to analyse a SAR sequence. To calculate +a De from the produced RLum.Analysis object +‘model.output’, the function +Luminescence::analyse_SAR.CWOSL() is suitable. After +specifying a number of evaluation parameters (signal and background +integration interval, dose points and fit function for the dose response +curve) and the analysis process, the reduced data are stored in an +RLum.Results object, here termed ‘results’ . A background +integration interval from 301 to 401 translates to the signal from 30 s +to 40 s, because a channel has the default width of 0.1 s. Accordingly, +the signal integral ranges from 0.1 s to 0.7 s.

 ##set RegDose
-RegDose = c(0, 80, 140, 260, 320, 0, 80)
+RegDose = c(0, 80, 140, 260, 320, 0, 80)
 
 ##set sequence
-sequence <- list(
+sequence <- list(
   RegDose = RegDose,
   TestDose = 20,
   PH = 220,
@@ -739,7 +867,7 @@ 

   )
         
 ##analyse SAR sequence and plot only the resulting growth curve 
-results <- Luminescence::analyse_SAR.CWOSL(
+results <- Luminescence::analyse_SAR.CWOSL(
   model.output,
   signal.integral.min = 1,
   signal.integral.max = 7,
@@ -748,7 +876,7 @@ 

   fit.method = "EXP",
   dose.points = RegDose, 
   verbose = FALSE, 
-  plot.single = c(6)
+  plot.single = c(6)
   )
SAR protocol with the parameter set of 'Pagonis2008'

@@ -757,283 +885,163 @@

-
-

-Miscellaneous

-
-

-Accessing applied modelling parameters

-

Sometimes it is useful to extract the used modelling parameters. Since the output is an RLum.Analysis-object compatible with the R package ‘Luminescence’, this can be achieved with the following code lines:

+
+

Miscellaneous +

+
+

Accessing applied modelling parameters +

+

Sometimes it is useful to extract the used modelling parameters. +Since the output is an RLum.Analysis-object compatible with +the R package 'Luminescence', this can be achieved with the +following code lines (note: we have shorted the terminal output below +using the function head()):

-Luminescence::get_RLum(model.output, info = "parms")
-
## $parms.N1
-## [1] 1.5e+07
-## 
-## $parms.N2
-## [1] 1e+07
-## 
-## $parms.N3
-## [1] 4e+07
-## 
-## $parms.N4
-## [1] 2.5e+08
-## 
-## $parms.N5
-## [1] 5e+10
-## 
-## $parms.N6
-## [1] 5e+09
-## 
-## $parms.N7
-## [1] 4e+09
-## 
-## $parms.N8
-## [1] 3e+08
-## 
-## $parms.N9
-## [1] 1e+10
-## 
-## $parms.N10
-## [1] 1.2e+12
-## 
-## $parms.N11
-## [1] 3e+10
-## 
-## $parms.E1
-## [1] 0.97
-## 
-## $parms.E2
-## [1] 1.55
-## 
-## $parms.E3
-## [1] 1.73
-## 
-## $parms.E4
-## [1] 1.8
-## 
-## $parms.E5
-## [1] 2
-## 
-## $parms.E6
-## [1] 1.65
-## 
-## $parms.E7
-## [1] 1.6
-## 
-## $parms.E8
-## [1] 1.43
-## 
-## $parms.E9
-## [1] 1.75
-## 
-## $parms.E10
-## [1] 5
-## 
-## $parms.E11
-## [1] 5
-## 
-## $parms.s1
-## [1] 5e+12
-## 
-## $parms.s2
-## [1] 5e+14
-## 
-## $parms.s3
-## [1] 6.5e+13
-## 
-## $parms.s4
-## [1] 1.5e+13
-## 
-## $parms.s5
-## [1] 1e+10
-## 
-## $parms.s6
-## [1] 6.5e+13
-## 
-## $parms.s7
-## [1] 5e+12
-## 
-## $parms.s8
-## [1] 5e+13
-## 
-## $parms.s9
-## [1] 5e+14
-## 
-## $parms.s10
-## [1] 1e+13
-## 
-## $parms.s11
-## [1] 1e+13
-## 
-## $parms.A1
-## [1] 1e-08
-## 
-## $parms.A2
-## [1] 1e-08
-## 
-## $parms.A3
-## [1] 5e-09
-## 
-## $parms.A4
-## [1] 5e-10
-## 
-## $parms.A5
-## [1] 1e-10
-## 
-## $parms.A6
-## [1] 1e-11
-## 
-## $parms.A7
-## [1] 6e-12
-## 
-## $parms.A8
-## [1] 5e-07
-## 
-## $parms.A9
-## [1] 1e-09
-## 
-## $parms.A10
-## [1] 1e-14
-## 
-## $parms.A11
-## [1] 1e-10
-## 
-## $parms.B1
-## [1] 0
-## 
-## $parms.B2
-## [1] 0
-## 
-## $parms.B3
-## [1] 0
-## 
-## $parms.B4
-## [1] 0
-## 
-## $parms.B5
-## [1] 0
-## 
-## $parms.B6
-## [1] 0
-## 
-## $parms.B7
-## [1] 0
-## 
-## $parms.B8
-## [1] 5e-09
-## 
-## $parms.B9
-## [1] 5e-10
-## 
-## $parms.B10
-## [1] 3e-10
-## 
-## $parms.B11
-## [1] 1e-10
-## 
-## $parms.Th1
-## [1] 0.75
-## 
-## $parms.Th2
-## [1] 0
-## 
-## $parms.Th3
-## [1] 6
-## 
-## $parms.Th4
-## [1] 4.5
-## 
-## $parms.Th5
-## [1] 0
-## 
-## $parms.Th6
-## [1] 0.01
-## 
-## $parms.Th7
-## [1] 0
-## 
-## $parms.E_th1
-## [1] 0.1
-## 
-## $parms.E_th2
-## [1] 0
-## 
-## $parms.E_th3
-## [1] 0.1
-## 
-## $parms.E_th4
-## [1] 0.13
-## 
-## $parms.E_th5
-## [1] 0
-## 
-## $parms.E_th6
-## [1] 0.2
-## 
-## $parms.E_th7
-## [1] 0
-## 
-## $parms.n
-## 
-##  [RLum.Results-class]
-##   originator: .set_pars()
-##   data: 2
-##       .. $n : numeric
-##   .. $temp : numeric
-##   additional info elements:  0 
-## 
-## $parms.k_B
-## [1] 8.617e-05
-## 
-## $parms.W
-## [1] 0.64
-## 
-## $parms.K
-## [1] 2.8e+07
-## 
-## $parms.model
-## [1] "Pagonis2008"
+head(Luminescence::get_RLum(model.output, info = "parms"))
+
## $parms.N1
+## [1] 1.5e+07
+## 
+## $parms.N2
+## [1] 1e+07
+## 
+## $parms.N3
+## [1] 4e+07
+## 
+## $parms.N4
+## [1] 2.5e+08
+## 
+## $parms.N5
+## [1] 5e+10
+## 
+## $parms.N6
+## [1] 5e+09
+
+
+

Trace parameter state evolution +

+

An exciting feature of 'RLumModel' is that it allows you +to gain insight into the evolution of different parameter states beyond +a single simulation, which would show you how numerical parameters +change if the solver runs over the equations. For instance, assume you +have a sequence of different stimulation steps (TL, OSL etc.). You want +to know how the system, for which the solver has to find a solution, +changes from one sequence step to another. This is of interest because +the initial state of the system of each step will determine the shape of +the curve. Let’s think of the following sequence that, after an initial +TL readout, adds a dose followed by a TL measurement, then another +irradiation, another TL measurement and so on.

+
+dose_points <- seq(8,600, length.out = 50)
+sequence <- c(
+  list(TL = c(20 , 500 , 2)),
+  unlist(lapply(dose_points, function(d){
+    list(
+      IRR = c(20 , d , 0.03),
+      TL = c(20 , 250, 2))
+    
+  }), recursive = FALSE))
+

This sequence can modelled as shown above, here we use again the +Baily2001 model:

+
+results <- model_LuminescenceSignals(
+  model = "Bailey2001",
+  sequence = sequence,
+  plot = FALSE,
+  show_structure = FALSE,
+  simulate_sample_history = FALSE,
+  verbose = FALSE)
+

What we did already above was to show the resulting TL curves, and we +do this again, just to see how they look like.

+
+Luminescence::plot_RLum(
+  get_RLum(results, recordType = "^TL$", drop = FALSE),
+  combine = TRUE,
+  xlim = c(20,120), 
+  records_max = 10,
+  legend.pos = "topleft",
+  plot.single = TRUE)
+

+

Now we go one step further and focus our interest on the evolution of +each parameter set at the end of each sequence step. Extracting all the +data manually is possible, but a little cumbersome, so instead, we will +use the function trace_StateParameterEvoluation() (this +function was introduced with 'RLumModel' v0.2.10).

+ +

-
-

-References

+
+

References +

-Adamiec, Grzegorz, Marta Garcia-Talavera, Richard M Bailey, and Pilar Iniguez de La Torre. 2004. “Application of a Genetic Algorithm to Finding Parameter Values for Numerical Simulation of Quartz Luminescence.” Geochronometria 23: 9–14. +Adamiec, Grzegorz, Marta Garcia-Talavera, Richard M Bailey, and Pilar +Iniguez de La Torre. 2004. “Application of a Genetic Algorithm to +Finding Parameter Values for Numerical Simulation of Quartz +Luminescence.” Geochronometria 23: 9–14.
-Bailey, R M. 2001. “Towards a General Kinetic Model for Optically and Thermally Stimulated Luminescence of Quartz.” Radiation Measurements 33: 17–45. +Bailey, R M. 2001. “Towards a General Kinetic Model for Optically +and Thermally Stimulated Luminescence of Quartz.” Radiation +Measurements 33: 17–45.
-Bailey, R. 2002. “Simulations of Variability in the Luminescence Characteristics of Natural Quartz and Its Implications for Estimates of Absorbed Dose.” Radiation Protection Dosimetry 100: 33–38. +Bailey, R. 2002. “Simulations of Variability in the Luminescence +Characteristics of Natural Quartz and Its Implications for Estimates of +Absorbed Dose.” Radiation Protection Dosimetry 100: +33–38.
-———. 2004. “Paper I - Simulation of dose absorption in quartz over geological timescales and its implications for the precision and accuracy of optical dating.” Radiation Measurements 38: 299–310. +———. 2004. “Paper I - Simulation of dose +absorption in quartz over geological timescales and its implications for +the precision and accuracy of optical dating.” +Radiation Measurements 38: 299–310.
-Friedrich, Johannes, Sebastian Kreutzer, and Christoph Schmidt. 2016. “Solving ordinary differential equations to understand luminescence: ’RLumModel’, an advanced research tool for simulating luminescence in quartz using R .” Quaternary Geochronology 35: 88–100. +Friedrich, Johannes, Sebastian Kreutzer, and Christoph Schmidt. 2016. +“Solving ordinary differential equations to +understand luminescence: ’RLumModel’, an advanced research tool for +simulating luminescence in quartz using R .” +Quaternary Geochronology 35: 88–100.
-Friedrich, Johannes, Vasilis Pagonis, Reuven Chen, Sebastian Kreutzer, and Christoph Schmidt. 2017. “Quartz Radiofluorescence: A Modelling Approach.” Journal of Luminescence 186: 318–25. +Friedrich, Johannes, Vasilis Pagonis, Reuven Chen, Sebastian Kreutzer, +and Christoph Schmidt. 2017. “Quartz Radiofluorescence: A +Modelling Approach.” Journal of Luminescence 186: +318–25.
-Kreutzer, Sebastian, Christoph Schmidt, Margret C Fuchs, Michael Dietze, Manfred Fischer, and Markus Fuchs. 2012. “Introducing an R package for luminescence dating analysis.” Ancient TL 30: 1–8. +Kreutzer, Sebastian, Christoph Schmidt, Margret C Fuchs, Michael Dietze, +Manfred Fischer, and Markus Fuchs. 2012. “Introducing an R package for luminescence dating +analysis.” Ancient TL 30: 1–8.
-Pagonis, Vasilis, George Kitis, and Reuven Chen. 2003. “Applicability of the Zimmerman predose model in the thermoluminescence of predosed and annealed synthetic quartz samples.” Radiation Measurements 37 (3): 267–74. +Pagonis, Vasilis, George Kitis, and Reuven Chen. 2003. “Applicability of the Zimmerman predose model in the +thermoluminescence of predosed and annealed synthetic quartz +samples.” Radiation Measurements 37 (3): 267–74.
-Pagonis, V, E Balsamo, C Barnold, K Duling, and S McCole. 2008a. “Simulations of the Predose Technique for Retrospective Dosimetry and Authenticity Testing.” Radiation Measurements 43 (8): 1343–53. +Pagonis, V, E Balsamo, C Barnold, K Duling, and S McCole. 2008a. +“Simulations of the Predose Technique for Retrospective Dosimetry +and Authenticity Testing.” Radiation Measurements 43 +(8): 1343–53.
-Pagonis, V, R Chen, and AG Wintle. 2007. “Modelling Thermal Transfer in Optically Stimulated Luminescence of Quartz.” Journal of Physics D: Applied Physics 40 (4): 998. +Pagonis, V, R Chen, and AG Wintle. 2007. “Modelling Thermal +Transfer in Optically Stimulated Luminescence of Quartz.” +Journal of Physics D: Applied Physics 40 (4): 998.
-Pagonis, V., A. G. Wintle, R. Chen, and X. L. Wang. 2008b. “A theoretical model for a new dating protocol for quartz based on thermally transferred OSL (TT-OSL).” Radiation Measurements 43: 704–8. +Pagonis, V., A. G. Wintle, R. Chen, and X. L. Wang. 2008b. “A theoretical model for a new dating protocol for quartz +based on thermally transferred OSL (TT-OSL).” +Radiation Measurements 43: 704–8.
-Zimmerman, J. 1971. “The Radiation-Induced Increase of the 100\(\,^\circ\)c Thermoluminescence Sensitivity of Fired Quartz.” Journal of Physics C: Solid State Physics 4 (18): 3265–76. +Zimmerman, J. 1971. “The Radiation-Induced Increase of the +100\(\,^\circ\)c Thermoluminescence +Sensitivity of Fired Quartz.” Journal of Physics C: Solid +State Physics 4 (18): 3265–76.
@@ -1050,11 +1058,15 @@

-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+

+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown +2.0.2.

@@ -1063,5 +1075,7 @@

+ + diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/DRT-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/DRT-1.png index b3465fe..eaa4649 100644 Binary files a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/DRT-1.png and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/DRT-1.png differ diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/SAR-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/SAR-1.png index 21ee241..37ded04 100644 Binary files a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/SAR-1.png and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/SAR-1.png differ diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-14-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-14-1.png index 002e843..8cbe15e 100644 Binary files a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-14-1.png and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-14-1.png differ diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-15-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-15-1.png index ac759a2..c0cf0ea 100644 Binary files a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-15-1.png and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-15-1.png differ diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-17-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-17-1.png index d910ac7..292aaa8 100644 Binary files a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-17-1.png and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-17-1.png differ diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-21-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-21-1.png new file mode 100644 index 0000000..a84b4ea Binary files /dev/null and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-21-1.png differ diff --git a/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-22-1.png b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-22-1.png new file mode 100644 index 0000000..29c0516 Binary files /dev/null and b/docs/articles/RLumModel_-_Getting_started_with_RLumModel_files/figure-html/unnamed-chunk-22-1.png differ diff --git a/docs/articles/RLumModel_-_Models_and_parameters.html b/docs/articles/RLumModel_-_Models_and_parameters.html new file mode 100644 index 0000000..9a75d2f --- /dev/null +++ b/docs/articles/RLumModel_-_Models_and_parameters.html @@ -0,0 +1,8257 @@ + + + + + + + +RLumModel - Models and parameters • RLumModel + + + + + + + + + + + + +
+
+ + + + +
+
+
+

RLumModel - Models and parameters

+

Sebastian +Kreutzer (Earth Sciences and Geography, Abersytwyth University, UK) +& Johannes Friedrich (University of Bayreuth, DE)

+ +

2022-02-20

+ + Source: vignettes/RLumModel_-_Models_and_parameters.Rmd + + +
+ + + +
+

Models and parameters +

+

The table lists the parameters used in the different models +implemented in 'RLumModel'. The tables are automatically +extracted from the output of the function .set_pars() to +provide a better human-readable output format.

+

It is common in the published literature to assign descriptive names +to the energy levels. Obviously, this labelling is open to +interpretation and has nothing carved in stone. Moreover, it depends +partly on the model and the authors’ understanding.

+

Although different models are implemented in +'RLumModel', we did not assess whether they are meaningful +but implemented them to allow direct comparison. Please remember that +the main differences between models narrow down to the assumed +concentration of specific levels (for instance, \(N\)). Sometimes models have different +concentration levels underpinned by experiments that were or were not +suitable to validate those changes. However, sometimes concentration +levels differ because the authors modified them by try and error. Either +way, we strongly recommend double-checking the +underlying assumption of each model in the original article.

+ +++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
LEVELLABELDESCRIPTION
trap_1110ºC TLElectron trap associated with the 110ºC TL peak
trap_2230ºC TLElectron trap associated with the 230ºC TL peak
trap_3OSL_fastElectron trap feeding the OSL fast component
trap_4OSL_mediumElectron trap linked to the OSL medium component
(trap_5)OSL_deep/OSL_slow1Electron trap linked to the first OSL slow component or the deep OSL +trap
(trap_6)OSL_slow2/TT-OSLElectron trap linked to the second OSL slow component or the TT-OSL +trap
(trap_7)OSL_slow3/BT-OSLElectron trap linked to the third OSL slow component or the BT-OSL +trap
(trap_8)OSL_deepElectron trap linked to the deep OSL trap
centre_1R1 centreReservoir centre 1, non-radiative, thermally unstable
centre_2R2 centreReservoir centre 2, non-radiative, thermally unstable
centre_3K centreKiller centre, non-radiative recombination centre
centre_4L centreLuminescence centre
+

The levels given in parentheses change according to the maximum +number of levels in the model. For instance, if the model has only five +electron traps, level trap_5 is associated with the deep +OSL electron trap. However, if the model has traps associated with slow +components, as in Bailey (2001), the OSL +deep trap is associated with the trap_8 (cf. Friedrich, Kreutzer, and Schmidt 2016).

+

Please note that, unlike in the table above, the parameter tables +below are generated automatically from the models implemented in +'RLumModel'. Therefore the labelling is kept very +general.

+
+

Parameter: N +

+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+N (cm^-3) +
+concentration of electron traps +
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Parameter: B +

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Parameter: Th +

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Parameter: E_th +

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Parameter: k_B +

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Parameter: W +

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Parameter: K +

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Parameter: n +

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+
+
+
+
+

References +

+
+
+Bailey, R M. 2001. “Towards a General Kinetic Model for Optically +and Thermally Stimulated Luminescence of Quartz.” Radiation +Measurements 33: 17–45. +
+
+Friedrich, Johannes, Sebastian Kreutzer, and Christoph Schmidt. 2016. +“Solving ordinary differential equations to +understand luminescence: ’RLumModel’, an advanced research tool for +simulating luminescence in quartz using R .” +Quaternary Geochronology 35: 88–100. +
+
+
+
+ + + +
+ + + +
+

+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

+
+ +
+

+

Site built with pkgdown +2.0.2.

+
+ +
+
+ + + + + + + + diff --git a/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3.html b/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3.html index 927a8ee..f8e55a5 100644 --- a/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3.html +++ b/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3.html @@ -25,6 +25,8 @@ + +
+
-

RLumModel - Simulating luminescence in Al2O3 +

RLumModel - Simulating luminescence in +Al2O3

-

Johannes Friedrich, University of Bayreuth

+

Johannes +Friedrich, University of Bayreuth

-

2021-11-08

+

2022-02-20

- Source: vignettes/RLumModel_-_Simulating_luminescence_in_Al2O3.Rmd + Source: vignettes/RLumModel_-_Simulating_luminescence_in_Al2O3.Rmd
-
-

-Introduction

-

This vignette describes the usage of the R-package ‘RLumModel’ for simulating Al2O3 behaviour. In literature a lot of parameters for describing the thermoluminescence (TL) and/or optical stimulated luminescence (OSL) are given. We give same examples for simulating different phenomena of luminescence in Al2O3. Note that most of the model do not support TL and OSL simulations. So please be careful when creating sequences. The models presented in Sec. 2.1 and 2.2 support TL simulations, but no OSL because parameters for E_th (Thermal assistance energy) and Th (Photo-eviction constant or photoionisation cross section).

+
+

Introduction +

+

This vignette describes the usage of the R-package +‘RLumModel’ for simulating Al2O3 behaviour. In +literature a lot of parameters for describing the thermoluminescence +(TL) and/or optical stimulated luminescence (OSL) are given. We give +same examples for simulating different phenomena of luminescence in +Al2O3. Note that most of the model do not support +TL and OSL simulations. So please be careful when +creating sequences. The models presented in Sec. 2.1 and 2.2 support TL +simulations, but no OSL because parameters for E_th +(Thermal assistance energy) and Th (Photo-eviction constant +or photoionisation cross section).

-
-

-Examples

-

All examples need the R package RLumModel, so let’s load it!

+
+

Examples +

+

All examples need the R package RLumModel, so let’s +load it!

-
-

-Akselrod 1998

-

Akselrod et al. (1998) presented parameters for modelling the effect of quenching TL signals. This model was built for Al2O3, but the rate equations are identical with describing electron movements in quartz. Below is a step-by-step introduction for involving these parameters in ‘RLumModel’ and re-calculating the simulationa from Figure 9 in Akselrod et al. (1998).

-
-

-Set own starting parameters

-

For a detailed introduction to own parameter sets in RLumModel, see vignette RLumModel - Using own parameter sets.

-

As a next step it is possible to set own starting-parameters, also called state parameters. In the case of Akselrod et al. (1998) they submitted initial concentrations of electrons and holes. This can be done via:

+library(RLumModel)
+
+

Akselrod 1998 +

+

Akselrod et al. (1998) presented +parameters for modelling the effect of quenching TL signals. This model +was built for Al2O3, but the rate equations are +identical with describing electron movements in quartz. Below is a +step-by-step introduction for involving these parameters in ‘RLumModel’ +and re-calculating the simulationa from Figure 9 in Akselrod et al. (1998).

+
+

Set own starting parameters +

+

For a detailed introduction to own parameter sets in RLumModel, see +vignette RLumModel - +Using own parameter sets.

+

As a next step it is possible to set own starting-parameters, also +called state parameters. In the case of Akselrod +et al. (1998) they submitted initial concentrations of electrons +and holes. This can be done via:

-own_state_parameters <- c(0, 0, 1e11)
-

Here the first entry is the first electron trap, the second entry the second electron trap and the third entry the luminescence centre responsible for the TL signal. The vector own_state_parameters needs as much entries as energy levels used in the model.

+own_state_parameters <- c(0, 0, 1e11)
+

Here the first entry is the first electron trap, the second entry the +second electron trap and the third entry the luminescence centre +responsible for the TL signal. The vector +own_state_parameters needs as much entries as energy levels +used in the model.

-
-

-Calculate thermal quenching effect

-

The effect of quenching luminescence signals will be simulated. In RLumModel it is possible to submit the parameter K as an indicator for recognising thermal quenching or not. If the parameter is set to 0 thermal quenching will be neglected. Otherwise it wil be calculated.

+
+

Calculate thermal quenching effect +

+

The effect of quenching luminescence signals will be simulated. In +RLumModel it is possible to submit the parameter K as an +indicator for recognising thermal quenching or not. If the parameter is +set to 0 thermal quenching will be neglected. Otherwise it +wil be calculated.

-W <- c(0, 1.05)
+W <- c(0, 1.05)
 
-TL_Akselrod_1998 <- lapply(W, function(W){
+TL_Akselrod_1998 <- lapply(W, function(W){
   
-  own_parameters <- list(
-    N = c(1e18, 1e17, 1e18),
-    E = c(1.25, 0, 0),
-    s = c(1e13, 0, 0),
-    A = c(1e-16, 1e-16, 2e-17),
-    B = c(0, 0, 1e-16),
-    K = ifelse(W == 0, 0, 1e12),
+  own_parameters <- list(
+    N = c(1e18, 1e17, 1e18),
+    E = c(1.25, 0, 0),
+    s = c(1e13, 0, 0),
+    A = c(1e-16, 1e-16, 2e-17),
+    B = c(0, 0, 1e-16),
+    K = ifelse(W == 0, 0, 1e12),
     W = W,
     model = "customized",
     R = 1e13)
   
-  sequence <- list(
-    IRR = c(20, 0.225, 0.01),
-    TL = c(20, 300, 1))
+  sequence <- list(
+    IRR = c(20, 0.225, 0.01),
+    TL = c(20, 300, 1))
   
   model_output <- model_LuminescenceSignals(
     model = "customized", 
@@ -172,14 +205,14 @@ 

     verbose = FALSE,
     plot = FALSE)
   
-  return(get_RLum(model_output, recordType = "TL$", drop = FALSE))
+  return(get_RLum(model_output, recordType = "TL$", drop = FALSE))
 })
 
-merge_results <- merge_RLum.Analysis(TL_Akselrod_1998)
+merge_results <- merge_RLum.Analysis(TL_Akselrod_1998)
 
-plot_RLum.Analysis(
+plot_RLum.Analysis(
   merge_results,
-  legend.text = c("Unquenched", "Quenched"),
+  legend.text = c("Unquenched", "Quenched"),
   combine = T)
The effect of thermal quenching for TL signals

@@ -188,40 +221,46 @@

-
-

-Pagonis 2007

-

Pagonis, Chen, and Lawless (2007) published three different parameter sets for Al2O3 chips. Here we analyse ‘Chip101’ and show how to re-calculate the results presented in the publication.

-
-

-Set parameters for Chip101

+
+

Pagonis 2007 +

+

Pagonis, Chen, and Lawless (2007) +published three different parameter sets for Al2O3 +chips. Here we analyse ‘Chip101’ and show how to re-calculate the +results presented in the publication.

+
+

Set parameters for Chip101 +

-own_parameters <- list(
-  N = c(2e15, 2e15, 2.4e16, 1e17),
-  E = c(1.3,0, 0, 0),
-  s = c(1e13, 0, 0, 0),
-  A = c(2e-8, 2e-9, 4e-9, 1e-8),
-  B = c(0, 0, 5e-11, 4e-8),
+own_parameters <- list(
+  N = c(2e15, 2e15, 2.4e16, 1e17),
+  E = c(1.3,0, 0, 0),
+  s = c(1e13, 0, 0, 0),
+  A = c(2e-8, 2e-9, 4e-9, 1e-8),
+  B = c(0, 0, 5e-11, 4e-8),
   K = 1e11,
   W = 1.1,
   model = "customized",
   R = 1.7e15)
 
-own_state_parameters <- c(0, 0, 0, 9.4e15)
+own_state_parameters <- c(0, 0, 0, 9.4e15)
-
-

-Caclualte TL signal dependend on the given dose

-

We now have to define the sequence for simulating the TL behaviour. For that purpose different doses are given before the TL measurement. To handle this a lapply command was used. The result is the combined plot of all simulated TL measurements.

+
+

Caclualte TL signal dependend on the given dose +

+

We now have to define the sequence for simulating the TL behaviour. +For that purpose different doses are given before the TL measurement. To +handle this a lapply command was used. The result is the +combined plot of all simulated TL measurements.

-dose <- 10^seq(-1, 3.5, 0.5)
+dose <- 10^seq(-1, 3.5, 0.5)
 
-Pagonis_2007 <- lapply(dose, function(dose){
+Pagonis_2007 <- lapply(dose, function(dose){
   
-  sequence <- list(
-    IRR = c(20, dose, 1),
-    PAUSE = c(20, 60),
-    TL = c(20, 250, 1))
+  sequence <- list(
+    IRR = c(20, dose, 1),
+    PAUSE = c(20, 60),
+    TL = c(20, 250, 1))
   
   model_output <- model_LuminescenceSignals(
     model = "customized", 
@@ -231,16 +270,16 @@ 

     verbose = FALSE,
     plot = FALSE)
 
-  return(Luminescence::get_RLum(model_output, recordType = "TL", drop = FALSE))
+  return(Luminescence::get_RLum(model_output, recordType = "TL", drop = FALSE))
 })
 
-merge_results <- Luminescence::merge_RLum.Analysis(Pagonis_2007)
+merge_results <- Luminescence::merge_RLum.Analysis(Pagonis_2007)
 
-Luminescence::plot_RLum.Analysis(
+Luminescence::plot_RLum.Analysis(
   merge_results,
-  subset =  list(recordType = "TL$"),
-  xlim = c(100, 250),
-  legend.text = paste0(round(dose, digits = 2), " Gy"),
+  subset =  list(recordType = "TL$"),
+  xlim = c(100, 250),
+  legend.text = paste0(round(dose, digits = 2), " Gy"),
   combine = T)
TL signal for different given doses

@@ -248,28 +287,32 @@

-
-

-Calculate maximum TL signal and concentration of L-centre

-

Figure 2 in the original publiction by Pagonis, Chen, and Lawless (2007) will be plotted with the following commands. The following code commands are able to calculate the maximum of the TL signal of all curves.

+
+

Calculate maximum TL signal and concentration of L-centre +

+

Figure 2 in the original publiction by Pagonis, Chen, and Lawless (2007) will be +plotted with the following commands. The following code commands are +able to calculate the maximum of the TL signal of all curves.

-TL_max <- vapply(1:length(Pagonis_2007), function(x){
+TL_max <- vapply(1:length(Pagonis_2007), function(x){
   
-  TL <- get_RLum(get_RLum(Pagonis_2007[[x]], recordType = "TL$"))
+  TL <- get_RLum(get_RLum(Pagonis_2007[[x]], recordType = "TL$"))
   
-  return(max(TL[,2]))
+  return(max(TL[,2]))
   
 }, FUN.VALUE = 1)

Now the calculation of the concentration:

-m1_max <- vapply(1:length(Pagonis_2007), function(x){
+m1_max <- vapply(1:length(Pagonis_2007), function(x){
   
-  m1 <- get_RLum(get_RLum(Pagonis_2007[[x]], recordType = "conc. level 4"))
+  m1 <- get_RLum(get_RLum(Pagonis_2007[[x]], recordType = "conc. level 4"))
   
-  return(m1[1,2])
+  return(m1[1,2])
 
 }, FUN.VALUE = 1)
-

When plotting L-centre concentration vs. dose or TLmax vs. dose the same results as presented in Fig. 2 in Pagonis, Chen, and Lawless (2007) are reached.

+

When plotting L-centre concentration vs. dose or TLmax +vs. dose the same results as presented in Fig. 2 in Pagonis, Chen, and Lawless (2007) are +reached.

TL max vs. dose

TL max vs. dose @@ -281,16 +324,16 @@

-
-

-Concentration at the end of irradiation

+
+

Concentration at the end of irradiation +

-dose <- seq(1,400, 1)
+dose <- seq(1,400, 1)
 
-Fig_5 <- lapply(dose, function(dose){
+Fig_5 <- lapply(dose, function(dose){
   
-  sequence <- list(
-    RF = c(20, dose, 1))
+  sequence <- list(
+    RF = c(20, dose, 1))
   
   model_output <- model_LuminescenceSignals(
     model = "customized", 
@@ -302,45 +345,45 @@ 

 
 })
-n1 <- vapply(1:length(Fig_5), function(x){
+n1 <- vapply(1:length(Fig_5), function(x){
   
-  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 1"))
+  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 1"))
   
-  return(temp[nrow(temp),2])
+  return(temp[nrow(temp),2])
   
 }, FUN.VALUE = 1)
 
-n2 <- vapply(1:length(Fig_5), function(x){
+n2 <- vapply(1:length(Fig_5), function(x){
   
-  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 2"))
+  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 2"))
   
-  return(temp[nrow(temp),2])
+  return(temp[nrow(temp),2])
   
 }, FUN.VALUE = 1)
 
-m1 <- vapply(1:length(Fig_5), function(x){
+m1 <- vapply(1:length(Fig_5), function(x){
   
-  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 4"))
+  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 4"))
   
-  return(temp[nrow(temp),2])
+  return(temp[nrow(temp),2])
   
 }, FUN.VALUE = 1)
 
-m2 <- vapply(1:length(Fig_5), function(x){
+m2 <- vapply(1:length(Fig_5), function(x){
   
-  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 3"))
+  temp <- get_RLum(get_RLum(Fig_5[[x]], recordType = "conc. level 3"))
   
-  return(temp[nrow(temp),2])
+  return(temp[nrow(temp),2])
   
 }, FUN.VALUE = 1)
-plot(dose, m2, type = "l", ylim = c(0, 1.5e16), xlim = c(0, 500), xlab= "Dose [Gy]", ylab = "Concentration [a.u.]")
-lines(dose, n2, col = "red")
-lines(dose, m1, col = "green")
-lines(dose, n1, col = "blue")
+plot(dose, m2, type = "l", ylim = c(0, 1.5e16), xlim = c(0, 500), xlab= "Dose [Gy]", ylab = "Concentration [a.u.]")
+lines(dose, n2, col = "red")
+lines(dose, m1, col = "green")
+lines(dose, n1, col = "blue")
 
-legend("topright", legend = c("n1", "n2", "m1", "m2"), col = c("blue", "red", "green", "black"), lwd = 1, bty = "n")
-grid()
+legend("topright", legend = c("n1", "n2", "m1", "m2"), col = c("blue", "red", "green", "black"), lwd = 1, bty = "n") +grid()
Concentration in different traps at the end of the irradiation

Concentration in different traps at the end of the irradiation @@ -349,20 +392,28 @@

-
-

-Summary

-

This vignette showed the potential of the R package ‘RLumModel’ to simulate Al2O3 behaviour. Two different models known from literature were re-compiled in the framework of RLumModel.

+
+

Summary +

+

This vignette showed the potential of the R package +‘RLumModel’ to simulate Al2O3 behaviour. Two +different models known from literature were re-compiled in the framework +of RLumModel.

-
-

-References

+
+

References +

-Akselrod, MS, N Agersnap Larsen, V Whitley, and SWS McKeever. 1998. “Thermal Quenching of F-Center Luminescence in Al\({_2}\)O\({_3}\):C.” Journal of Applied Physics 84 (6): 3364–73. +Akselrod, MS, N Agersnap Larsen, V Whitley, and SWS McKeever. 1998. +“Thermal Quenching of F-Center Luminescence in +Al\({_2}\)O\({_3}\):C.” Journal of +Applied Physics 84 (6): 3364–73.
-Pagonis, V, R Chen, and J L Lawless. 2007. “A Quantitative Kinetic Model for Al\({_2}\)O\({_3}\):C: TL Response to Ionizing Radiation.” Radiation Measurements 42 (2): 198–204. +Pagonis, V, R Chen, and J L Lawless. 2007. “A Quantitative Kinetic +Model for Al\({_2}\)O\({_3}\):C: TL Response to Ionizing +Radiation.” Radiation Measurements 42 (2): 198–204.
@@ -379,11 +430,15 @@

-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+

+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown +2.0.2.

@@ -392,5 +447,7 @@

+ + diff --git a/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-3-1.png b/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-3-1.png index 959363e..8bcbfee 100644 Binary files a/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-3-1.png and b/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-3-1.png differ diff --git a/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-4-1.png b/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-4-1.png index 4a051e0..7ebcfee 100644 Binary files a/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-4-1.png and b/docs/articles/RLumModel_-_Simulating_luminescence_in_Al2O3_files/figure-html/unnamed-chunk-4-1.png differ diff --git a/docs/articles/RLumModel_-_Using_own_parameter_sets.html b/docs/articles/RLumModel_-_Using_own_parameter_sets.html index 1113649..120d788 100644 --- a/docs/articles/RLumModel_-_Using_own_parameter_sets.html +++ b/docs/articles/RLumModel_-_Using_own_parameter_sets.html @@ -25,6 +25,8 @@ + +
+

RLumModel - Using own parameter sets

-

Johannes Friedrich, University of Bayreuth

+

Johannes +Friedrich, University of Bayreuth

-

2021-11-08

+

2022-02-20

- Source: vignettes/RLumModel_-_Using_own_parameter_sets.Rmd + Source: vignettes/RLumModel_-_Using_own_parameter_sets.Rmd
-
-

-Introduction

-

With ‘RLumModel’ ≥ 0.2.0 is it possible to simulate quartz luminescence behaviour of own parameters or parameter sets, which are not included in the package but also known in literature. Widely used OTOR (One-Trap-One-Recombination-center) models can be included, too. This vignette gives three comprehensive examples how to implement parameter sets and proves the results recalculating the original simulations.

-

‘RLumModel’ offers maximum flexibility and fast calculation of ordinary first-order differential equations (ODEs) describing luminescence behaviour, because of:

+
+

Introduction +

+

With ‘RLumModel’ ≥ 0.2.0 is it possible to simulate quartz +luminescence behaviour of own parameters or parameter sets, which are +not included in the package but also known in literature. Widely used +OTOR (One-Trap-One-Recombination-center) models can be included, too. +This vignette gives three comprehensive examples how to implement +parameter sets and proves the results recalculating the original +simulations.

+

‘RLumModel’ offers maximum flexibility and fast calculation of +ordinary first-order differential equations (ODEs) describing +luminescence behaviour, because of:

    -
  • flexible handling of different numbers of electron traps and hole centres in generating the model equations. The user has not to care about coding ODEs in R.
    • -
  • Solving these equations is performed with C++ (Eddelbuettel 2013) and offers a fast calculation.
    • +
  • flexible handling of different numbers of electron traps and hole +centres in generating the model equations. The user has not to care +about coding ODEs in R.
    • +
  • Solving these equations is performed with C++ (Eddelbuettel 2013) and offers a fast +calculation.
-
-

-Examples

-

This chapter shows the handling of own parameter sets with ‘RLumModel’. For this purpose three model parameters known from literature were taken: Pagonis et al. (2009), Lawless, Chen, and Pagonis (2009) and Chen and Pagonis (2013).

-
-

-Pagonis 2009

-

Pagonis et al. (2009) presented parameters for their luminescence modelling of radioluminescence. This model was built for Al2O3, but the rate equations are identical with describing electron movements in quartz. Below is a step-by-step manual for involving these parameters in ‘RLumModel’ and re-calculating the simulationa made by Pagonis et al. (2009). Note that in the original publication Figure 3 and Figure 6 are inconsistent with each other. For a doserate of 0.1 Gy/s an initial RL intensity of ca. 1.5e14 is obtained (see Figure 6 in original publication and simulations below).

-
-

-Set parameters

-

First of all the model parameters had to be set. In ‘RLumModel’ this can be done via . The list has to contain the following items:

+
+

Examples +

+

This chapter shows the handling of own parameter sets with +‘RLumModel’. For this purpose three model parameters known from +literature were taken: Pagonis et al. +(2009), Lawless, Chen, and Pagonis +(2009) and Chen and Pagonis +(2013).

+
+

Pagonis 2009 +

+

Pagonis et al. (2009) presented +parameters for their luminescence modelling of radioluminescence. This +model was built for Al2O3, but the rate equations +are identical with describing electron movements in quartz. Below is a +step-by-step manual for involving these parameters in ‘RLumModel’ and +re-calculating the simulationa made by Pagonis et +al. (2009). Note that in the original publication Figure 3 and +Figure 6 are inconsistent with each other. For a doserate of 0.1 Gy/s an +initial RL intensity of ca. 1.5e14 is obtained (see Figure 6 in original +publication and simulations below).

+
+

Set parameters +

+

First of all the model parameters had to be set. In ‘RLumModel’ this +can be done via . The list has to contain the following items:

  • N: Concentration of electron- and hole traps [cm-3]
  • E: Electron/Hole trap depth [eV]
  • s: Frequency factor [s-1]
    • -
  • A: Conduction band to electron trap and valence band to hole trap transition probability [s-1 cm 3].
    • -
  • B: Conduction band to hole centre transition probability [s-1 cm 3].
    • -
  • Th: Photo-eviction constant or photoionisation cross section, respectively. If not set: by default 0.
    • +
  • A: Conduction band to electron trap and valence band to hole trap +transition probability [s-1 cm 3].
    • +
  • B: Conduction band to hole centre transition probability +[s-1 cm 3].
    • +
  • Th: Photo-eviction constant or photoionisation cross section, +respectively. If not set: by default 0.
  • E_th: Thermal assistence energy [eV]. If not set: by default 0.
    • -
  • k_B: Boltzman constant 8.617e-05 [eV/K]. If not set: by default 8.617e-05.
    • -
  • W: activation energy 0.64 [eV] (for UV). If not set: by default 0.64.
    • -
  • K: 2.8e7 (dimensionless constant). If not set: by default 2.8e7.
    • +
  • k_B: Boltzman constant 8.617e-05 [eV/K]. If not set: by default +8.617e-05.
    • +
  • W: activation energy 0.64 [eV] (for UV). If not set: by default +0.64.
    • +
  • K: 2.8e7 (dimensionless constant). If not set: by default +2.8e7.
  • model: “customized”
    • -
  • R (optional): Ionisation rate (pair production rate) equivalent to 1 Gy/s [s-1 cm -3]
    • +
  • R (optional): Ionisation rate (pair production rate) equivalent to 1 +Gy/s [s-1 cm -3]

Note:

    -
  • Not every publication uses the same definition of parameter A and B.
    • -
  • When no thermal quenching is expected, set K = 0. A numerical value of W is necessary, if .
    • -
  • The parameter model = "customized" is necessary to not load a stored model within the RLumModel pacakge.
    • -
  • The luminescence center, which is responsible for the luminescence production (TL-, OSL-, RF-signal), has to be the last entry in the model parameters, see examples below.
    • -
  • For further details of the parameter see Bailey (2001) and Wintle (1975).
    • -
  • The first two entries in N, A and B belong to the electron traps and the last two entries to the hole centres. This order is necessary.
    • -
  • The first entry in N, E, s, A, B, Th and E_th belong to the first energy level (e.g. 110°C), the second, third, … entries to second, third, … energy levels.
    • -
  • The entries Th and E_th are not necessary, because when they miss in the definition of the own parameters they will automatically be set to 0.
    • +
  • Not every publication uses the same definition of parameter +A and B.
    • +
  • When no thermal quenching is expected, set K = 0. A +numerical value of W is necessary, if .
    • +
  • The parameter model = "customized" is necessary to not +load a stored model within the RLumModel pacakge.
    • +
  • The luminescence center, which is responsible for the luminescence +production (TL-, OSL-, RF-signal), has to be the last entry in the model +parameters, see examples below.
    • +
  • For further details of the parameter see Bailey (2001) and Wintle +(1975).
    • +
  • The first two entries in N, A and +B belong to the electron traps and the last two entries to +the hole centres. This order is necessary.
    • +
  • The first entry in N, E, s, +A, B, Th and E_th +belong to the first energy level (e.g. 110°C), the second, third, … +entries to second, third, … energy levels.
    • +
  • The entries Th and E_th are not necessary, +because when they miss in the definition of the own parameters they will +automatically be set to 0.
-own_parameters <- list(
-  N = c(2e15, 2e15, 2.4e16, 1e17),
-  E = c(0, 0, 0, 0),
-  s = c(0, 0, 0, 0),
-  A = c(2e-8, 2e-9, 4e-9, 1e-8),
-  B = c(0, 0, 5e-11, 4e-8),
+own_parameters <- list(
+  N = c(2e15, 2e15, 2.4e16, 1e17),
+  E = c(0, 0, 0, 0),
+  s = c(0, 0, 0, 0),
+  A = c(2e-8, 2e-9, 4e-9, 1e-8),
+  B = c(0, 0, 5e-11, 4e-8),
   K = 0,
   model = "customized",
   R = 1.7e15)
-

It is important to notice, that in Pagonis et al. (2009) B is the valence band to hole centre probability, but in Bailey (2001) this is Aj. The default setting of RLumModel is the definition by Bailey (2001) and so the values of B (in Pagonis et al. (2009)) are A in the notation above.

-

As a next step it is possible to set own starting-parameters, also called state parameters. In the case of Pagonis et al. (2009) they submitted initial concentrations of electrons and holes. This can be done via:

+

It is important to notice, that in Pagonis et +al. (2009) B is the valence band to hole centre +probability, but in Bailey (2001) this is +Aj. The default setting of RLumModel is the definition by +Bailey (2001) and so the values of +B (in Pagonis et al. (2009)) +are A in the notation above.

+

As a next step it is possible to set own starting-parameters, also +called state parameters. In the case of Pagonis +et al. (2009) they submitted initial concentrations of electrons +and holes. This can be done via:

-own_state_parameters <- c(0, 0, 0, 9.4e15)
-

Here the first entry is the first electron trap, the second entry the second electron trap, the third entry the hole center and the fourth entry the luminescence center responsible for the RF signal. The vector own_state_parameters needs as much entries as energy levels used in the model.

-
-
-

-Running the simulation with RLumModel

-

When all parameters are set, the simulation can be started. The main function in RLumModel is model_LuminescenceSignals() and the usage with own parameter sets is described below. For a general overview for creating a sequence, running RLumModel with stored models etc. the user is referred to Friedrich, Kreutzer, and Schmidt (2016) and to the vignette RLumModel - Getting started with RLumModel.

-

For simulating the results of Pagonis et al. (2009) the follwing sequence is needed.

+own_state_parameters <- c(0, 0, 0, 9.4e15)
+

Here the first entry is the first electron trap, the second entry the +second electron trap, the third entry the hole center and the fourth +entry the luminescence center responsible for the RF signal. The vector +own_state_parameters needs as much entries as energy levels +used in the model.

+
+
+

Running the simulation with RLumModel +

+

When all parameters are set, the simulation can be started. The main +function in RLumModel is model_LuminescenceSignals() and +the usage with own parameter sets is described below. For a general +overview for creating a sequence, running RLumModel with stored models +etc. the user is referred to Friedrich, Kreutzer, +and Schmidt (2016) and to the vignette RLumModel - +Getting started with RLumModel.

+

For simulating the results of Pagonis et al. +(2009) the follwing sequence is needed.

-sequence <- list(RF = c(20, 0.1, 0.1))
-

This sequence describes a radiofluorescence simulation at 20 °C with a dose of 0.1 Gy and a dose rate of 0.1 Gy/s, so the stimulation time is 1s.

-

The parameters own_parameters and own_state_parameters in model_LuminescenceSignals() are prepared for using own created parameter sets. Parameter model = "customized" is necessary to not load stored parameters.

+sequence <- list(RF = c(20, 0.1, 0.1))
+

This sequence describes a radiofluorescence simulation at 20 °C with +a dose of 0.1 Gy and a dose rate of 0.1 Gy/s, so the stimulation time is +1s.

+

The parameters own_parameters and +own_state_parameters in +model_LuminescenceSignals() are prepared for using own +created parameter sets. Parameter model = "customized" is +necessary to not load stored parameters.

 RF_Pagonis2009 <- model_LuminescenceSignals(
   model = "customized", 
@@ -199,31 +274,44 @@ 

 RF signal for 0.1 Gy/s
-

As in the original publication, initially the RF signal increases and is followed by an approximately linear region until the stimulation ends. Figure 5 in Pagonis et al. (2009) shows the concentration of the luminescence center m1 for the stimulation time of 1s. With RLumModel this can be plotted very fast with the following command (for a detailed description see vignette RLumModel - Getting started with RLumModel

+

As in the original publication, initially the RF signal increases and +is followed by an approximately linear region until the stimulation +ends. Figure 5 in Pagonis et al. (2009) +shows the concentration of the luminescence center m1 for the +stimulation time of 1s. With RLumModel this can be plotted very fast +with the following command (for a detailed description see vignette RLumModel - +Getting started with RLumModel

-concentration_m1 <- Luminescence::get_RLum(
+concentration_m1 <- Luminescence::get_RLum(
   RF_Pagonis2009,
-  recordType = c("conc. level 4"))
+  recordType = c("conc. level 4"))
   
-Luminescence::plot_RLum(
+Luminescence::plot_RLum(
   concentration_m1, 
-  ylim = c(9.2e15, 9.6e15))
+ ylim = c(9.2e15, 9.6e15))
Concentration of m1 during RF

Concentration of m1 during RF

-
-

-Re-calculate the original results

-

Reproducing Figure 3 and Figure 6 in Pagonis et al. (2009) a loop over different dose rates is necessary. The following code lines are able to run the model for five different dose rates from 0.1 to 0.5 Gy/s and plot all contained RF curves and the initial RF signal. For a more detailed descripton of the loop and the single commands therein the user is referred to Friedrich, Kreutzer, and Schmidt (2016) and the vignette RLumModel - Getting started with RLumModel.

+
+

Re-calculate the original results +

+

Reproducing Figure 3 and Figure 6 in Pagonis +et al. (2009) a loop over different dose rates is necessary. The +following code lines are able to run the model for five different dose +rates from 0.1 to 0.5 Gy/s and plot all contained RF curves and the +initial RF signal. For a more detailed descripton of the loop and the +single commands therein the user is referred to Friedrich, Kreutzer, and Schmidt (2016) and the +vignette RLumModel - +Getting started with RLumModel.

-dose.rate <- seq(from = 0.1, to = 0.5, by = 0.1)
+dose.rate <- seq(from = 0.1, to = 0.5, by = 0.1)
 
-model.output <- lapply(dose.rate, function(x) {
+model.output <- lapply(dose.rate, function(x) {
     
-    sequence <- list(RF = c(20, x, x))
+    sequence <- list(RF = c(20, x, x))
     
     RF_data <- model_LuminescenceSignals(
       model = "customized", 
@@ -235,17 +323,17 @@ 

     )
     
     ## "RF$" for exact matching RF and not (RF)
-    return(get_RLum(RF_data, recordType = "RF$", drop = FALSE))
+    return(get_RLum(RF_data, recordType = "RF$", drop = FALSE))
     
   })
 
-model.output.merged <- merge_RLum(model.output)
+model.output.merged <- merge_RLum(model.output)
 
-plot_RLum(
+plot_RLum(
  object = model.output.merged,
  xlab = "Stimulation time [s]",
  ylab = "RF signal [a.u.]",
- legend.text = paste(dose.rate, "Gy/s"),
+ legend.text = paste(dose.rate, "Gy/s"),
  legend.pos = "outside",
  combine = TRUE)
@@ -253,13 +341,14 @@

RF signals for different dose rates

-

The following code calcultes the initial RF signal for the five different dose rates.

+

The following code calcultes the initial RF signal for the five +different dose rates.

-dose.rate <- seq(from = 0.1, to = 0.5, by = 0.1)
+dose.rate <- seq(from = 0.1, to = 0.5, by = 0.1)
 
-model.output <- vapply(X = dose.rate, FUN = function(x) {
+model.output <- vapply(X = dose.rate, FUN = function(x) {
     
-    sequence <- list(RF = c(20, x, x))
+    sequence <- list(RF = c(20, x, x))
     
     temp <- model_LuminescenceSignals(
       model = "customized", 
@@ -271,39 +360,52 @@ 

     )
     
     ## "RF$" for exact matching RF and not (RF)
-    RF_curve <- get_RLum(temp, recordType = "RF$")
+    RF_curve <- get_RLum(temp, recordType = "RF$")
     
-    return(max(get_RLum(RF_curve)[2,2]))
+    return(max(get_RLum(RF_curve)[2,2]))
     
   }, FUN.VALUE = 1)
Initial RF signal for different dose rates with parameters of Lawless 2009

-Initial RF signal for different dose rates with parameters of Lawless 2009 +Initial RF signal for different dose rates with parameters of Lawless +2009

-

The results show that ‘RLumModel’ is able to simulate the same results as published in Pagonis et al. (2009) with only little effort. All these examples can be modified to own needs, e.g. own sequences or own parameters.

-
-
-
-

-Lawless 2009

-

Lawless, Chen, and Pagonis (2009) investigateted the sublinear dose dependence of TL and OSL. They published a set of model parameters to simulate the behaviour of the quartz luminescence system during different dose rates. In contrast to the example above, this simulation has no state parameters and so they were not definded.

-
-

-Set parameters and recalculate the results

-

All used parameters are defined in the named list own_parameters. K=0 was chosen, because no thermal quenching was simulated. Note: In the “Bailey 2001” notation B has the same meaning as Am in Lawless, Chen, and Pagonis (2009) (for details see example in chapter 2.1.1).

+

The results show that ‘RLumModel’ is able to simulate the same +results as published in Pagonis et al. +(2009) with only little effort. All these examples can be +modified to own needs, e.g. own sequences or own parameters.

+
+
+
+

Lawless 2009 +

+

Lawless, Chen, and Pagonis (2009) +investigateted the sublinear dose dependence of TL and OSL. They +published a set of model parameters to simulate the behaviour of the +quartz luminescence system during different dose rates. In contrast to +the example above, this simulation has no state parameters and so they +were not definded.

+
+

Set parameters and recalculate the results +

+

All used parameters are defined in the named list +own_parameters. K=0 was chosen, because no +thermal quenching was simulated. Note: In the “Bailey 2001” notation +B has the same meaning as Am in Lawless, Chen, and Pagonis (2009) (for details +see example in chapter 2.1.1).

-own_parameters <- list(
-  N = c(1e14, 1e15),
-  E = c(0, 0),
-  s = c(0, 0),
-  A = c(1e-13, 1e-14),
-  B = c(0, 1e-7),
+own_parameters <- list(
+  N = c(1e14, 1e15),
+  E = c(0, 0),
+  s = c(0, 0),
+  A = c(1e-13, 1e-14),
+  B = c(0, 1e-7),
   K = 0,
   model = "customized",
   R = 1e8)
 
-sequence <- list(RF = c(20, 100, 1))
+sequence <- list(RF = c(20, 100, 1))
 
 RF_Lawless_2009 <- model_LuminescenceSignals(
   model = "customized", 
@@ -312,10 +414,14 @@ 

   verbose = FALSE,
   plot = FALSE)
 
-concentration_n <- Luminescence::get_RLum(
+concentration_n <- Luminescence::get_RLum(
   RF_Lawless_2009, 
-    recordType = c("conc. level 1"))
-

This code leads to the following results and shows the same as plotted in Lawless, Chen, and Pagonis (2009), Fig. 2 (plot commands not shown here). More details to the equations mentioned in the legend are available in the original publication.

+ recordType = c("conc. level 1"))
+

This code leads to the following results and shows the same as +plotted in Lawless, Chen, and Pagonis +(2009), Fig. 2 (plot commands not shown here). More details to +the equations mentioned in the legend are available in the original +publication.

Concentration of Level 1 with numerical and analytical solutions

Concentration of Level 1 with numerical and analytical solutions @@ -323,34 +429,45 @@

-
-

-Chen 2013

-

Chen and Pagonis (2013) published a numerical model to investigate the quasi-equilibrium assumptions in TL. For the description of the system a OTOR model was used.

-
-

-Set parameters

-

This model is the first in this vignette which did not start its simulation at 20 °C. For this cases, model_LuminescenceSignals() offers a parameter called own_start_temperature. This parameter offers maximal flexibility for the user to set the initial temperature of the simulation. The parameter takes effect when model = "customized" is used, see example below.

+
+

Chen 2013 +

+

Chen and Pagonis (2013) published a +numerical model to investigate the quasi-equilibrium assumptions in TL. +For the description of the system a OTOR model was used.

+
+

Set parameters +

+

This model is the first in this vignette which did not start its +simulation at 20 °C. For this cases, +model_LuminescenceSignals() offers a parameter called +own_start_temperature. This parameter offers maximal +flexibility for the user to set the initial temperature of the +simulation. The parameter takes effect when +model = "customized" is used, see example below.

-own_parameters <- list(
-  N = c(1e9, 0),
-  E = c(0.4, 0),
-  s = c(1e11, 0),
-  A = c(1e-9,0),
-  B = c(0, 1e-10),
+own_parameters <- list(
+  N = c(1e9, 0),
+  E = c(0.4, 0),
+  s = c(1e11, 0),
+  A = c(1e-9,0),
+  B = c(0, 1e-10),
   K = 0,
   model = "customized")
 
-own_state_parameters <- c(1e8, 1e8)
+own_state_parameters <- c(1e8, 1e8)
 
 own_start_temperature <- -220
 
-sequence <- list(TL = c(-220, 130, 1))
-
-
-

-Re-calculate the original results

-

Here the parameter own_start_temperature from the function model_LuminescenceSignals() is used to set the beginning of the measurement to -220°C. It is important, that ‘RLumModel’ always uses temperatures in °C.

+sequence <- list(TL = c(-220, 130, 1))
+
+
+

Re-calculate the original results +

+

Here the parameter own_start_temperature from the +function model_LuminescenceSignals() is used to set the +beginning of the measurement to -220°C. It is important, that +‘RLumModel’ always uses temperatures in °C.

 TL_Chen2013 <- model_LuminescenceSignals(
   model = "customized", 
@@ -364,7 +481,9 @@ 

 TL with parameter sets of Chen 2013
-

With this result it is possible to plot the concentration of every single energy level, leading to the following plot (see also Fig. 6 in Chen and Pagonis (2013))

+

With this result it is possible to plot the concentration of every +single energy level, leading to the following plot (see also Fig. 6 in +Chen and Pagonis (2013))

Concentrations of different energy levels

Concentrations of different energy levels @@ -373,35 +492,55 @@

-
-

-Summary

-

This vignette showed the potential of the R package ‘RLumModel’ to use own parameter sets simulating quartz luminescence behaviour. Quartz as well as Al2O3 luminescence phenomena can be numerically described and graphically plotted.

+
+

Summary +

+

This vignette showed the potential of the R package ‘RLumModel’ to +use own parameter sets simulating quartz luminescence behaviour. Quartz +as well as Al2O3 luminescence phenomena can be +numerically described and graphically plotted.

-
-

-References

+
+

References +

-Bailey, R M. 2001. “Towards a General Kinetic Model for Optically and Thermally Stimulated Luminescence of Quartz.” Radiation Measurements 33: 17–45. +Bailey, R M. 2001. “Towards a General Kinetic Model for Optically +and Thermally Stimulated Luminescence of Quartz.” Radiation +Measurements 33: 17–45.
-Chen, R, and V Pagonis. 2013. “On the quasi-equilibrium assumptions in the theory of thermoluminescence (TL).” Journal of Luminescence 143: 734–40. +Chen, R, and V Pagonis. 2013. “On the +quasi-equilibrium assumptions in the theory of thermoluminescence +(TL).” Journal of Luminescence 143: 734–40.
-Eddelbuettel, Dirk. 2013. Seamless R and C++ integration with Rcpp. Springer. +Eddelbuettel, Dirk. 2013. Seamless R and C++ +integration with Rcpp. Springer.
-Friedrich, Johannes, Sebastian Kreutzer, and Christoph Schmidt. 2016. “Solving ordinary differential equations to understand luminescence: ’RLumModel’, an advanced research tool for simulating luminescence in quartz using R .” Quaternary Geochronology 35: 88–100. +Friedrich, Johannes, Sebastian Kreutzer, and Christoph Schmidt. 2016. +“Solving ordinary differential equations to +understand luminescence: ’RLumModel’, an advanced research tool for +simulating luminescence in quartz using R .” +Quaternary Geochronology 35: 88–100.
-Lawless, J L, R Chen, and V Pagonis. 2009. “Sublinear Dose Dependence of Thermoluminescence and Optically Stimulated Luminescence Prior to the Approach to Saturation Level.” Radiation Measurements 44 (5): 606–10. +Lawless, J L, R Chen, and V Pagonis. 2009. “Sublinear Dose +Dependence of Thermoluminescence and Optically Stimulated Luminescence +Prior to the Approach to Saturation Level.” Radiation +Measurements 44 (5): 606–10.
-Pagonis, V, J L Lawless, R Chen, and C Andersen. 2009. “Radioluminescence in Al\({_2}\)O\({_3}\):C – Analytical and Numerical Simulation Results.” Journal of Physics D: Applied Physics 42 (17): 175107. +Pagonis, V, J L Lawless, R Chen, and C Andersen. 2009. +“Radioluminescence in Al\({_2}\)O\({_3}\):C – Analytical and Numerical +Simulation Results.” Journal of Physics D: Applied +Physics 42 (17): 175107.
-Wintle, AG. 1975. “Thermal Quenching of Thermoluminescence in Quartz.” Geophysical Journal International 41 (1): 107–13. +Wintle, AG. 1975. “Thermal Quenching of +Thermoluminescence in Quartz.” Geophysical Journal +International 41 (1): 107–13.
@@ -418,11 +557,15 @@

-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+

+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown +2.0.2.

@@ -431,5 +574,7 @@

+ + diff --git a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/Different Dose-rates Pagonis 2009-1.png b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/Different Dose-rates Pagonis 2009-1.png index 91dc904..d8705f0 100644 Binary files a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/Different Dose-rates Pagonis 2009-1.png and b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/Different Dose-rates Pagonis 2009-1.png differ diff --git a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/solve Chen 2013-1.png b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/solve Chen 2013-1.png index 49aa01d..a5371f8 100644 Binary files a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/solve Chen 2013-1.png and b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/solve Chen 2013-1.png differ diff --git a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-4-1.png b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-4-1.png index 007fbe8..c1821ad 100644 Binary files a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-4-1.png and b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-4-1.png differ diff --git a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-5-1.png b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-5-1.png index 942d435..4997716 100644 Binary files a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-5-1.png and b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-5-1.png differ diff --git a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-7-1.png b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-7-1.png index 2b596ad..cc645ed 100644 Binary files a/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-7-1.png and b/docs/articles/RLumModel_-_Using_own_parameter_sets_files/figure-html/unnamed-chunk-7-1.png differ diff --git a/docs/articles/index.html b/docs/articles/index.html index 99f4acd..317707c 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -1,76 +1,18 @@ - - - - - - - -Articles • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Articles • RLumModel - - - - - - + + - - -
-
- -
- -
+

Articles

@@ -154,35 +87,35 @@

Articles

All vignettes

-
-
RLumModel - Getting started with RLumModel
-
-
RLumModel - Simulating luminescence in Al<sub>2</sub>O<sub>3</sub>
-
-
RLumModel - Using own parameter sets
-
-
-
+
RLumModel - Getting started with RLumModel
+
+
RLumModel - Models and parameters
+
+
RLumModel - Simulating luminescence in Al<sub>2</sub>O<sub>3</sub>
+
+
RLumModel - Using own parameter sets
+
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/authors.html b/docs/authors.html index 86f545e..f5898a6 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -1,76 +1,18 @@ - - - - - - - -Authors • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Authors and Citation • RLumModel - - - - - - - - + + - -
-
-
- -
+
-
-

Authors

+
+
+

Authors

+
+ + +
  • +

    Johannes Friedrich. Author, translator, maintainer. +

    +
    • +
  • +

    Sebastian Kreutzer. Author, thesis advisor. +

    +
    • +
  • +

    Christoph Schmidt. Author, thesis advisor. +

    +
    • +
+
+
+

Citation

+ Source: DESCRIPTION +
-
    -
  • -

    Johannes Friedrich. Author, translator, maintainer. -

    -
    • -
  • -

    Sebastian Kreutzer. Author, thesis advisor. -

    -
    • -
  • -

    Christoph Schmidt. Author, thesis advisor. -

    -
    • -
+ +

Friedrich J, Kreutzer S, Schmidt C (2022). +RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. +R package version 0.2.10, https://CRAN.R-project.org/package=RLumModel. +

+ 
@Manual{,
+  title = {RLumModel: Solving Ordinary Differential Equations to Understand Luminescence},
+  author = {Johannes Friedrich and Sebastian Kreutzer and Christoph Schmidt},
+  year = {2022},
+  note = {R package version 0.2.10},
+  url = {https://CRAN.R-project.org/package=RLumModel},
+}
@@ -171,22 +124,22 @@

Authors

-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/index.html b/docs/index.html index c10ef25..8a435b1 100644 --- a/docs/index.html +++ b/docs/index.html @@ -25,6 +25,8 @@ + +
-
-

-RLumModel +
+

RLumModel +

-

The R package ‘RLumModel’ by Johannes Friedrich (University of Bayreuth, Germany), Sebastian Kreutzer (IRAMAT-CRP2A, Université Bordeaux Montaigne, France) and Christoph Schmidt (University of Bayreuth, Germany) provides a collection of various R functions modelling luminescence signals in quartz and Al2O3, based on energy-band models.

-

For an introduction and further details, visit the RLumModel homepage.

-
-

-Installation

-
-

-Install the package

-

To install the stable version from CRAN, simply run the following from an R console:

+

The R package 'RLumModel' by Johannes +Friedrich (University of Bayreuth, Germany), Sebastian Kreutzer +(Geography & Earth Sciences, Aberystwyth University, United Kingdom) +and Christoph Schmidt (University of Lausanne, Switzerland) provides a +collection of various R functions modelling luminescence signals in +quartz and Al2O3, based on energy-band models.

+

For an introduction and further details, visit the RLumModel homepage.

+
+

Installation +

+
+

Install the package +

+

To install the stable version from CRAN, simply run the following +from an R console:

-install.packages("RLumModel")
-

To install the latest development builds directly from GitHub, run

+install.packages("RLumModel")
+

To install the latest development builds directly from GitHub, +run

-if(!require("devtools"))
-  install.packages("devtools")
-devtools::install_github("R-Lum/RLumModel@master")
-

To install a developer build other than ‘master’, replace the term ‘master’ in the codeline by the name of the wanted developer build.

-
-
-

-Requirements

-

Depending on your OS please download and install one of the following:

+if(!require("devtools")) + install.packages("devtools") +devtools::install_github("R-Lum/RLumModel@master")
+

To install a developer build other than ‘master’, replace the term +‘master’ in the codeline by the name of the wanted developer build.

+
+
+

Requirements +

+

Depending on your OS please download and install one of the +following:

  • -Windows: Rtools (provided by CRAN)
    • +Windows: Rtools +(provided by CRAN)
  • -macOS: Xcode (provided by Apple)
    • +macOS: Xcode (provided by +Apple)
  • -Linux: gcc often comes pre-installed in most distributions. Should gcc be not available, however, we kindly refer to the exhaustive collection of installation guides depending on the Linux distribution.
    • +Linux: gcc often comes +pre-installed in most distributions. Should gcc be not available, however, we kindly +refer to the exhaustive collection of installation guides depending on +the Linux distribution.
-
-

-Using RLumModel

-
-

-Simple Example

+
+

Using RLumModel +

+
+

Simple Example +

 model <- "Bailey2001"
 
-sequence <- list(
-    IRR = c(20, 10, 1),
-    TL = c(20, 500, 5))
+sequence <- list(
+    IRR = c(20, 10, 1),
+    TL = c(20, 500, 5))
     
 model.output <- model_LuminescenceSignals(
     model = model,
@@ -160,24 +176,52 @@
-
-

-Note

+
+

Note +

The package comes without any guarantee!

-

Please further note that this version is a development version and may change day by day. For stable branches please visit the package on CRAN.

+

Please further note that this version is a development version and +may change day by day. For stable branches please visit the package on +CRAN.

-
-

-License

-

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

-

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

+
+

License +

+

This program is free software: you can redistribute it and/or modify +it under the terms of the GNU General Public License as published by the +Free Software Foundation, either version 3 of the License, or any later +version.

+

This program is distributed in the hope that it will be useful, but +WITHOUT ANY WARRANTY; without even the implied warranty of +MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +General Public License for more details.

+
+
+

+ Funding +

+

The development of +RLumModel benefited from the support by various funding bodies:

+
    +

  • The initial work by Johannes Friedrich, Sebastian Kreutzer and +Christoph Schmidt was supported by the DFG (2015–2018, SCHM 3051/4-1, +“Modelling quartz luminescence signal dynamics relevant for dating and +dosimetry”, SCHM 3051/4-1)

    • +

  • The work of Sebastian Kreutzer as package author was supported by +LabEx LaScArBx (ANR - +n. ANR-10-LABX-52) between 2017 and 2019.

    • +

  • From 2020, Sebastian Kreutzer received funding from the European +Union’s Horizon 2020 research and innovation programme under the Marie +Skłodowska-Curie grant agreement No 844457 (project: CREDit).

    • +
- @@ -185,55 +229,67 @@

-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+

+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

+

Site built with pkgdown +2.0.2.

@@ -242,5 +298,7 @@

Dev status

+ + diff --git a/docs/news/index.html b/docs/news/index.html index ba5a6b6..0870619 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -1,76 +1,18 @@ - - - - - - - -Changelog • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Changelog • RLumModel - - - - - - + + - - -
-
- -
- -
+

Changelog

- Source: NEWS.md + Source: NEWS.md
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/pkgdown.css b/docs/pkgdown.css index 1273238..80ea5b8 100644 --- a/docs/pkgdown.css +++ b/docs/pkgdown.css @@ -56,8 +56,10 @@ img.icon { float: right; } -img { +/* Ensure in-page images don't run outside their container */ +.contents img { max-width: 100%; + height: auto; } /* Fix bug in bootstrap (only seen in firefox) */ @@ -78,11 +80,10 @@ dd { /* Section anchors ---------------------------------*/ a.anchor { - margin-left: -30px; - display:inline-block; - width: 30px; - height: 30px; - visibility: hidden; + display: none; + margin-left: 5px; + width: 20px; + height: 20px; background-image: url(./link.svg); background-repeat: no-repeat; @@ -90,17 +91,15 @@ a.anchor { background-position: center center; } -.hasAnchor:hover a.anchor { - visibility: visible; -} - -@media (max-width: 767px) { - .hasAnchor:hover a.anchor { - visibility: hidden; - } +h1:hover .anchor, +h2:hover .anchor, +h3:hover .anchor, +h4:hover .anchor, +h5:hover .anchor, +h6:hover .anchor { + display: inline-block; } - /* Fixes for fixed navbar --------------------------*/ .contents h1, .contents h2, .contents h3, .contents h4 { @@ -264,31 +263,26 @@ table { /* Syntax highlighting ---------------------------------------------------- */ -pre { - word-wrap: normal; - word-break: normal; - border: 1px solid #eee; -} - -pre, code { +pre, code, pre code { background-color: #f8f8f8; color: #333; } +pre, pre code { + white-space: pre-wrap; + word-break: break-all; + overflow-wrap: break-word; +} -pre code { - overflow: auto; - word-wrap: normal; - white-space: pre; +pre { + border: 1px solid #eee; } -pre .img { +pre .img, pre .r-plt { margin: 5px 0; } -pre .img img { +pre .img img, pre .r-plt img { background-color: #fff; - display: block; - height: auto; } code a, pre a { @@ -305,9 +299,8 @@ a.sourceLine:hover { .kw {color: #264D66;} /* keyword */ .co {color: #888888;} /* comment */ -.message { color: black; font-weight: bolder;} -.error { color: orange; font-weight: bolder;} -.warning { color: #6A0366; font-weight: bolder;} +.error {font-weight: bolder;} +.warning {font-weight: bolder;} /* Clipboard --------------------------*/ @@ -365,3 +358,27 @@ mark { content: ""; } } + +/* Section anchors --------------------------------- + Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71 +*/ + +div.csl-bib-body { } +div.csl-entry { + clear: both; +} +.hanging-indent div.csl-entry { + margin-left:2em; + text-indent:-2em; +} +div.csl-left-margin { + min-width:2em; + float:left; +} +div.csl-right-inline { + margin-left:2em; + padding-left:1em; +} +div.csl-indent { + margin-left: 2em; +} diff --git a/docs/pkgdown.js b/docs/pkgdown.js index 7e7048f..6f0eee4 100644 --- a/docs/pkgdown.js +++ b/docs/pkgdown.js @@ -80,7 +80,7 @@ $(document).ready(function() { var copyButton = ""; - $(".examples, div.sourceCode").addClass("hasCopyButton"); + $("div.sourceCode").addClass("hasCopyButton"); // Insert copy buttons: $(copyButton).prependTo(".hasCopyButton"); @@ -91,7 +91,7 @@ // Initialize clipboard: var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', { text: function(trigger) { - return trigger.parentNode.textContent; + return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, ""); } }); diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index d9df16f..2754a30 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -1,11 +1,12 @@ -pandoc: '2.16' -pkgdown: 1.6.1 +pandoc: 2.17.1.1 +pkgdown: 2.0.2 pkgdown_sha: ~ articles: RLumModel_-_Getting_started_with_RLumModel: RLumModel_-_Getting_started_with_RLumModel.html + RLumModel_-_Models_and_parameters: RLumModel_-_Models_and_parameters.html RLumModel_-_Simulating_luminescence_in_Al2O3: RLumModel_-_Simulating_luminescence_in_Al2O3.html RLumModel_-_Using_own_parameter_sets: RLumModel_-_Using_own_parameter_sets.html -last_built: 2021-11-08T19:31Z +last_built: 2022-02-20T21:37Z urls: reference: https://github.com/R-Lum/RLumModel/reference article: https://github.com/R-Lum/RLumModel/articles diff --git a/docs/reference/ExampleData.ModelOutput-1.png b/docs/reference/ExampleData.ModelOutput-1.png index 6e0894a..ec84a30 100644 Binary files a/docs/reference/ExampleData.ModelOutput-1.png and b/docs/reference/ExampleData.ModelOutput-1.png differ diff --git a/docs/reference/ExampleData.ModelOutput-2.png b/docs/reference/ExampleData.ModelOutput-2.png index 9642f64..8ed1638 100644 Binary files a/docs/reference/ExampleData.ModelOutput-2.png and b/docs/reference/ExampleData.ModelOutput-2.png differ diff --git a/docs/reference/ExampleData.ModelOutput-3.png b/docs/reference/ExampleData.ModelOutput-3.png index 3397581..7d655a6 100644 Binary files a/docs/reference/ExampleData.ModelOutput-3.png and b/docs/reference/ExampleData.ModelOutput-3.png differ diff --git a/docs/reference/ExampleData.ModelOutput.html b/docs/reference/ExampleData.ModelOutput.html index 4627354..c82d9af 100644 --- a/docs/reference/ExampleData.ModelOutput.html +++ b/docs/reference/ExampleData.ModelOutput.html @@ -1,77 +1,18 @@ - - - - - - - -Example data (TL curve) simulated with parameter set from Pagonis 2007 — ExampleData.ModelOutput • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Example data (TL curve) simulated with parameter set from Pagonis 2007 — ExampleData.ModelOutput • RLumModel - - - - - - + + - - -
-
- -
- -
+

Example data (TL curve) simulated with parameter set from Pagonis 2007

- Source: R/RLumModel-package.R + Source: R/RLumModel-package.R
@@ -158,71 +90,76 @@

Example data (TL curve) simulated with parameter set from Pagonis 2007

- -

Format

- +
+

Format

A RLum.Analysis object containing one TL curve as RLum.Data.Curve.

-

Source

- +
+
+

Source

model_LuminescenceSignals()

-

Note

- +
+
+

Note

This example has only one record (TL). The used sequence was sequence <- list(IRR = c(temp = 20, dose = 10, DoseRate = 1), TL = c(temp_begin = 20, temp_end = 400, heating_rate = 5))

-

Function version

- +
+
+

Function version

0.1.1

-

References

- +
+
+

References

Pagonis, V., Chen, R., Wintle, A.G., 2007: Modelling thermal transfer in optically stimulated luminescence of quartz. Journal of Physics D: Applied Physics 40, 998-1006.

-

Author

- +
+
+

Author

Johannes Friedrich, University of Bayreuth (Germany)

+
-

Examples

- 

-data("ExampleData.ModelOutput", envir = environment())
-
-TL_curve <- get_RLum(model.output, recordType = "TL$", drop = FALSE)
-
-##plot TL curve
-plot_RLum(TL_curve)
-
-
-TL_concentrations <- get_RLum(model.output, recordType = "(TL)", drop = FALSE)
-plot_RLum(TL_concentrations)
-
-
-
-
-
+
+

Examples

+ 

+data("ExampleData.ModelOutput", envir = environment())
+
+TL_curve <- get_RLum(model.output, recordType = "TL$", drop = FALSE)
+
+##plot TL curve
+plot_RLum(TL_curve)
+
+
+TL_concentrations <- get_RLum(model.output, recordType = "(TL)", drop = FALSE)
+plot_RLum(TL_concentrations)
+
+
+
+
+
+
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/reference/RLumModel-package.html b/docs/reference/RLumModel-package.html index 6d1d79c..1071f19 100644 --- a/docs/reference/RLumModel-package.html +++ b/docs/reference/RLumModel-package.html @@ -1,77 +1,18 @@ - - - - - - - -Solving Ordinary Differential Equations to Understand Luminescence — RLumModel-package • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Solving Ordinary Differential Equations to Understand Luminescence — RLumModel-package • RLumModel - - - - - - - - + + -
-
- -
- -
+

Solving Ordinary Differential Equations to Understand Luminescence

- Source: R/RLumModel-package.R + Source: R/RLumModel-package.R
-


+


- -

Details

- +
+

Details

A collection of function to simulate luminescence signals in the mineral quartz based on published models.

Authors

- - - - -
Johannes FriedrichUniversity of Bayreuth, Germany
Sebastian KreutzerGeography & Earth Sciences, Aberystwyth University, United Kingdom
Christoph SchmidtUniversity of Bayreuth, Germany
- - -

Supervisor

-

Christoph Schmidt, University of Bayreuth, Germany
+
Johannes FriedrichUniversity of Bayreuth, Germany
Sebastian KreutzerGeography & Earth Sciences, Aberystwyth University, United Kingdom
Christoph SchmidtUniversity of Bayreuth, Germany

Supervisor

+

Christoph Schmidt, University of Bayreuth, Germany
Sebastian Kreutzer,Geography & Earth Sciences, Aberystwyth University, United Kingdom #' -Project source code repository

    -

  • https://github.com/R-Lum/RLumModel

    • -
- -

Related package projects

    -

  • http://r-luminescence.de

    • +Project source code repository

    • https://github.com/R-Lum/RLumModel

      • +

    Related package projects

    • http://r-luminescence.de

    • https://CRAN.r-project.org/package=Luminescence

    • https://CRAN.r-project.org/package=RLumShiny

      • -
    - -

    Package maintainer

    +

Package maintainer

Johannes Friedrich, University of Bayreuth, Germany -
johannes.friedrich@posteo.de

+
johannes.friedrich@posteo.de

Acknowledgement

The work of Johannes Friedrich is gratefully supported by the DFG in framework of the project 'Modelling quartz luminescence signal dynamics relevant for dating and dosimetry' (SCHM 305114-1).

+
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png index 17a3580..68c3e0e 100644 Binary files a/docs/reference/Rplot001.png and b/docs/reference/Rplot001.png differ diff --git a/docs/reference/Rplot002.png b/docs/reference/Rplot002.png index 5677422..14d80e6 100644 Binary files a/docs/reference/Rplot002.png and b/docs/reference/Rplot002.png differ diff --git a/docs/reference/Rplot003.png b/docs/reference/Rplot003.png index c04c375..2da2f96 100644 Binary files a/docs/reference/Rplot003.png and b/docs/reference/Rplot003.png differ diff --git a/docs/reference/Rplot004.png b/docs/reference/Rplot004.png index eb7fb5a..e9435f6 100644 Binary files a/docs/reference/Rplot004.png and b/docs/reference/Rplot004.png differ diff --git a/docs/reference/Rplot005.png b/docs/reference/Rplot005.png index d4ebc80..fff91ad 100644 Binary files a/docs/reference/Rplot005.png and b/docs/reference/Rplot005.png differ diff --git a/docs/reference/Rplot006.png b/docs/reference/Rplot006.png index ee3ec12..c0deb01 100644 Binary files a/docs/reference/Rplot006.png and b/docs/reference/Rplot006.png differ diff --git a/docs/reference/dot-set_pars.html b/docs/reference/dot-set_pars.html index 5058054..493572c 100644 --- a/docs/reference/dot-set_pars.html +++ b/docs/reference/dot-set_pars.html @@ -1,78 +1,19 @@ - - - - - - - -Set parameters for Different Quartz Luminescence Models — .set_pars • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Set parameters for Different Quartz Luminescence Models — .set_pars • RLumModel - - - - - - - - + + -
-
- -
- -
+

Set parameters for Different Quartz Luminescence Models

- Source: R/set_pars.R + Source: R/set_pars.R
@@ -159,25 +91,25 @@

Set parameters for Different Quartz Luminescence Models

calculation of the ODEs.

- 
.set_pars(model)
+
+ 
.set_pars(model)
+
-

Arguments

- - - - - - -
model

character (required): set model to be used. +

+

Arguments

+
model
+

character (required): set model to be used. Available models are: "Bailey2001", "Bailey2002", "Bailey2004", "Pagonis2007", -"Pagonis2008"

- -

Value

- -

This function returns a list with all necessary parameters for -the used model.

-

Details

- +"Pagonis2008", "Friedrich2017", "Friedrich2018", "Peng2022". If model is indeed missing, +the list of allowed keywords is returned.

+
+
+

Value

+

This function returns a list with all necessary parameters for +the used model. Returns vector of allowed keywords if model is missing.

+
+
+

Details

The common model parameters are:

N: concentrations of electron/hole traps in cm^(-3) E: depth of the electron/hole trap in eV @@ -185,13 +117,14 @@

Details A: conduction band to electron/hole trap transition probability in s^(-1) B: valence band to hole trap transition probability in s^(-1) Th: photo-ionisation cross-section in s^(-1) -E_th: `thermal assistance' energy in eV +E_th: thermal assistance energy in (eV) n: concentrations of electron/hole traps after sample history in cm^(-3)

-

Note

- +
+
+

Note

n are the saved concentrations of the last step of the sample history of the used model. They will be loaded, if simulate_sample_history = FALSE in -model_LuminescenceSignals is chosen.

+model_LuminescenceSignals is chosen.

The order of the energy-band-levels is sometimes in an different order than in the original model. This was necessary, because in the simulations the luminescence centre always has to be the last entry in every parameter. @@ -199,63 +132,69 @@

Note

When a user wants to create his/her own parameter sets he/she only has to take care that the luminescence centre is the last entry in every vector and that the first entries are the electron traps and the last entries the hole centres.

-

Function version

- +
+
+

Function version

0.1.3

-

How to cite

- -

Friedrich, J., 2021. .set_pars(): Set parameters for Different Quartz Luminescence Models. Function version 0.1.3. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2021. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.9. https://CRAN.R-project.org/package=RLumModel

-

References

- +
+
+

How to cite

+

Friedrich, J., 2022. .set_pars(): Set parameters for Different Quartz Luminescence Models. Function version 0.1.3. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2022. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.10. https://CRAN.R-project.org/package=RLumModel

+
+
+

References

Bailey, R.M., 2001. Towards a general kinetic model for optically and thermally stimulated luminescence of quartz. Radiation Measurements 33, 17-45.

Bailey, R.M., 2002. Simulations of variability in the luminescence characteristics of natural quartz and its implications for estimates of absorbed dose. Radiation Protection Dosimetry 100, 33-38.

Bailey, R.M., 2004. Paper I-simulation of dose absorption in quartz over geological timescales -and it simplications for the precision and accuracy of optical dating. +and its implications for the precision and accuracy of optical dating. Radiation Measurements 38, 299-310.

Friedrich, J., Pagonis, V., Chen, R., Kreutzer, S., Schmidt, C., 2017: Quartz radiofluorescence: a modelling approach. Journal of Luminescence 186, 318-325.

-

Pagonis, V., Chen, R., Wintle, A.G., 2007: Modelling thermal transfer in optically +

Pagonis, V., Chen, R., Wintle, A.G., 2007. Modelling thermal transfer in optically stimulated luminescence of quartz. Journal of Physics D: Applied Physics 40, 998-1006.

Pagonis, V., Wintle, A.G., Chen, R., Wang, X.L., 2008. A theoretical model for a new dating protocol for quartz based on thermally transferred OSL (TT-OSL). Radiation Measurements 43, 704-708.

-

Author

- +

Peng, J., Wang, X., Adamiec, G., 2022. The build-up of the laboratory-generated dose-response curve and underestimation of equivalent dose for quartz OSL in the high dose region: A critical modelling study. Quaternary Geochronology 67, 101231.

+
+
+

Author

Johannes Friedrich, University of Bayreuth (Germany),

+
-

Examples

- 

-pars <- .set_pars("Bailey2001")
-
-
+
+

Examples

+ 

+pars <- .set_pars("Bailey2001")
+
+
+
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/reference/index.html b/docs/reference/index.html index a46f030..ec1e9fb 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -1,76 +1,18 @@ - - - - - - - -Function reference • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Function reference • RLumModel - - - - - - - - + + -
-
- -
- -
+

Reference

- - - - - - - - - - - + +
-

All functions

+ - - - - - - - - - - - - - - - - - - - - - - - -
+

All functions

+

ExampleData.ModelOutput

Example data (TL curve) simulated with parameter set from Pagonis 2007

+

RLumModel-package

Solving Ordinary Differential Equations to Understand Luminescence

+

.set_pars()

Set parameters for Different Quartz Luminescence Models

+

model_LuminescenceSignals()

Model Luminescence Signals

+

read_SEQ2R()

Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz luminescence

- +
+

trace_ParameterStateEvolution()

+

Trace parameter state evolution

+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/reference/model_LuminescenceSignals-1.png b/docs/reference/model_LuminescenceSignals-1.png index 5f751af..3170e07 100644 Binary files a/docs/reference/model_LuminescenceSignals-1.png and b/docs/reference/model_LuminescenceSignals-1.png differ diff --git a/docs/reference/model_LuminescenceSignals-2.png b/docs/reference/model_LuminescenceSignals-2.png index cce3d35..a7aea85 100644 Binary files a/docs/reference/model_LuminescenceSignals-2.png and b/docs/reference/model_LuminescenceSignals-2.png differ diff --git a/docs/reference/model_LuminescenceSignals-3.png b/docs/reference/model_LuminescenceSignals-3.png index 17fe435..4101f81 100644 Binary files a/docs/reference/model_LuminescenceSignals-3.png and b/docs/reference/model_LuminescenceSignals-3.png differ diff --git a/docs/reference/model_LuminescenceSignals-4.png b/docs/reference/model_LuminescenceSignals-4.png index d5cb818..d070cd5 100644 Binary files a/docs/reference/model_LuminescenceSignals-4.png and b/docs/reference/model_LuminescenceSignals-4.png differ diff --git a/docs/reference/model_LuminescenceSignals-5.png b/docs/reference/model_LuminescenceSignals-5.png index 63ced09..b2de60c 100644 Binary files a/docs/reference/model_LuminescenceSignals-5.png and b/docs/reference/model_LuminescenceSignals-5.png differ diff --git a/docs/reference/model_LuminescenceSignals-6.png b/docs/reference/model_LuminescenceSignals-6.png index 5e5d504..f749ea5 100644 Binary files a/docs/reference/model_LuminescenceSignals-6.png and b/docs/reference/model_LuminescenceSignals-6.png differ diff --git a/docs/reference/model_LuminescenceSignals.html b/docs/reference/model_LuminescenceSignals.html index d22a1d3..117c913 100644 --- a/docs/reference/model_LuminescenceSignals.html +++ b/docs/reference/model_LuminescenceSignals.html @@ -1,83 +1,23 @@ - - - - - - - -Model Luminescence Signals — model_LuminescenceSignals • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Model Luminescence Signals — model_LuminescenceSignals • RLumModel - - - - - - - - - - - - - - + + - - - -
-
- -
- -
+

Model Luminescence Signals

- Source: R/model_LuminescenceSignals.R + Source: R/model_LuminescenceSignals.R

This function models luminescence signals for quartz based on published physical models. It is possible to simulate TL, (CW-) OSL, RF measurements in a arbitrary sequence. This -sequence is definded as a list of certain abrivations. Furthermore it is possible to -load a sequence direct from the Riso Sequence Editor. -The output is an RLum.Analysisobject and so the plots are done -by the plot_RLum.Analysis function. If a SAR sequence is simulated the plot output can be disabled and SAR analyse functions +sequence is defined as a list of certain aberrations. Furthermore it is possible to +load a sequence direct from the Risø Sequence Editor. The output is an Luminescence::RLum.Analysis object and so the plots are done by the Luminescence::plot_RLum.Analysis function. +If a SAR sequence is simulated the plot output can be disabled and SAR analyse functions can be used.

- 
model_LuminescenceSignals(
-  model,
-  sequence,
-  lab.dose_rate = 1,
-  simulate_sample_history = FALSE,
-  plot = TRUE,
-  verbose = TRUE,
-  show_structure = FALSE,
-  own_parameters = NULL,
-  own_state_parameters = NULL,
-  own_start_temperature = NULL,
-  ...
-)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
model

character (required): set model to be used. Available models are: -"Bailey2001", "Bailey2002", "Bailey2004", "Pagonis2007", "Pagonis2008", "Friedrich2017", "Friedrich2018" and for own models "customized" (or "customised"). -Note: When model = "customized" is set, the argument 'own_parameters' has to be set.

sequence

list (required): set sequence to model as list or as *.seq file from the -Riso sequence editor. To simulate SAR measurements there is an extra option to set the sequence list (cf. details).

lab.dose_rate

numeric (with default): laboratory dose rate in XXX -Gy/s for calculating seconds into Gray in the *.seq file.

simulate_sample_history

logical (with default): FALSE (with default): simulation begins at laboratory conditions, -TRUE: simulations begins at crystallization (all levels 0) process

plot

logical (with default): Enables or disables plot output

verbose

logical (with default): Verbose mode on/off

show_structure

logical (with default): Shows the structure of the result. -Recommended to show record.id to analyse concentrations.

own_parameters

list (with default): This argument allows the user to submit own parameter sets. The list -has to contain the following items:

    -

  • N: Concentration of electron- and hole traps [cm^(-3)]

    • -

  • E: Electron/Hole trap depth [eV

    • -

  • s: Frequency factor [s^(-1)]

    • -

  • A: Conduction band to electron trap and valence band to hole trap transition probability [s^(-1) * cm^(3)]. - CAUTION: Not every publication uses - the same definition of parameter A and B! See vignette "RLumModel - Usage with own parameter sets" for further details

    • -

  • B: Conduction band to hole centre transition probability [s^(-1) * cm^(3)].

    • -

  • Th: Photo-eviction constant or photoionisation cross section, respectively

    • -

  • E_th: Thermal assistence energy [eV]

    • -

  • k_B: Boltzman constant 8.617e-05 [eV/K]

    • -

  • W: activation energy 0.64 [eV] (for UV)

    • -

  • K: 2.8e7 (dimensionless constant)

    • -

  • model: "customized"

    • -

  • R (optional): Ionisation rate (pair production rate) equivalent to 1 Gy/s [s^(-1) * cm^(-3)]

    • -
+
+ 
model_LuminescenceSignals(
+  model,
+  sequence,
+  lab.dose_rate = 1,
+  simulate_sample_history = FALSE,
+  plot = TRUE,
+  verbose = TRUE,
+  show_structure = FALSE,
+  own_parameters = NULL,
+  own_state_parameters = NULL,
+  own_start_temperature = NULL,
+  ...
+)
+
-

For further details see Bailey 2001, Wintle 1975, vignette "RLumModel - Using own parameter sets" -and example 3.

own_state_parameters

numeric (with default): Some publications (e.g. Pagonis 2009) +

+

Arguments

+
model
+

character (required): set model to be used. Available models are: +"Bailey2001", "Bailey2002", "Bailey2004", "Pagonis2007", "Pagonis2008", "Friedrich2017", "Friedrich2018", "Peng2022" and for own models "customized" (or "customised"). +Note: When model = "customized"/"customised is set, the argument own_parameters has to be set.

+
sequence
+

list (required): set sequence to model as list or as *.seq file from the +Risø sequence editor. To simulate SAR measurements there is an extra option to set the sequence list (cf. details).

+
lab.dose_rate
+

numeric (with default): laboratory dose rate in XXX +Gy/s for calculating seconds into Gray in the *.seq file.

+
simulate_sample_history
+

logical (with default): FALSE (with default): +simulation begins at laboratory conditions, TRUE: simulations begins at crystallization process (all levels 0)

+
plot
+

logical (with default): Enables or disables plot output

+
verbose
+

logical (with default): Verbose mode on/off

+
show_structure
+

logical (with default): Shows the structure of the result. +Recommended to show record.id to analyse concentrations.

+
own_parameters
+

list (with default): This argument allows the user to submit own parameter sets. See details for more information.

+
own_state_parameters
+

numeric (with default): Some publications (e.g., Pagonis 2009) offer state parameters. With this argument the user can submit this state parameters. For further details -see vignette ""RLumModel - Using own parameter sets" and example 3.

own_start_temperature

numeric (with default): Parameter to control the start temperature (in deg. C) of -a simulation. This parameter takes effect only when 'model = "customized"' is choosen.

...

further arguments and graphical parameters passed to -plot.default. See details for further information.

- -

Value

- -

This function returns an RLum.Analysis object with all TL, (LM-) OSL and RF/RL steps -in the sequence. Every entry is an RLum.Data.Curve object and can be plotted, analysed etc. with +see vignette "RLumModel - Using own parameter sets" and example 3. The parameter also accepts an +Luminescence::RLum.Results object created by .set_pars as input.

+
own_start_temperature
+

numeric (with default): Parameter to control the start temperature (in ºC) of +a simulation. This parameter takes effect only when 'model = "customized"' is chosen.

+
...
+

further arguments and graphical parameters passed to +plot.default. See details for further information.

+
+
+

Value

+

This function returns an Luminescence::RLum.Analysis object with all TL, (LM-) OSL and RF/RL steps +in the sequence. Every entry is an Luminescence::RLum.Data.Curve object and can be plotted, analysed etc. with further RLum-functions.

-

Details

- -

Defining a sequence

- - - - - - - - - - - - -
ArgumentsDescriptionSub-arguments
TLthermally stimulated luminescence'temp begin' [\(^{\circ}\)C], 'temp end' [\(^{\circ}\)C], 'heating rate' [\(^{\circ}\)C/s]
OSLoptically stimulated luminescence'temp' [\(^{\circ}\)C], 'duration' [s], 'optical_power' [%]
ILLillumination'temp' [\(^{\circ}\)C], 'duration' [s], 'optical_power' [%]
LM_OSLlinear modulated OSL'temp' [\(^{\circ}\)C], 'duration' [s], optional: 'start_power' [%], 'end_power' [%]
RL/RFradioluminescence'temp' [\(^{\circ}\)C], 'dose' [Gy], 'dose_rate' [Gy/s]
RF_heatingRF during heating/cooling'temp begin' [\(^{\circ}\)C], 'temp end' [\(^{\circ}\)C], 'heating rate' [\(^{\circ}\)C/s], 'dose_rate' [Gy/s]
IRRirradiation'temp' [\(^{\circ}\)C], 'dose' [Gy], 'dose_rate' [Gy/s]
CHcutheat'temp' [\(^{\circ}\)C], optional: 'duration' [s], 'heating_rate' [\(^{\circ}\)C/s]
PHpreheat'temp' [\(^{\circ}\)C], 'duration' [s], optional: 'heating_rate' [\(^{\circ}\)C/s]
PAUSEpause'temp' [\(^{\circ}\)C], 'duration' [s]
- - -

Note: 100 % illumination power equates to 20 mW/cm^2

- -

Defining a SAR-sequence

- - - - - - - - - - - - - -
AbrivationDescriptionexamples
RegDoseDose points of the regenerative cycles [Gy]c(0, 80, 140, 260, 320, 0, 80)
TestDoseTest dose for the SAR cycles [Gy]50
PHTemperature of the preheat [\(^{\circ}\)C]240
CHTemperature of the cutheat [\(^{\circ}\)C]200
OSL_tempTemperature of OSL read out [\(^{\circ}\)C]125
OSL_durationDuration of OSL read out [s]default: 40
Irr_tempTemperature of irradiation [\(^{\circ}\)C]default: 20
PH_durationDuration of the preheat [s]default: 10
dose_rateDose rate of the laboratory irradiation source [Gy/s]default: 1
optical_powerPercentage of the full illumination power [%]default: 90
Irr_2recoverDose to be recovered in a dose-recovery-test [Gy]20
- - -

Function version

- -

0.1.5

-

How to cite

- -

Friedrich, J., Kreutzer, S., 2021. model_LuminescenceSignals(): Model Luminescence Signals. Function version 0.1.5. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2021. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.9. https://CRAN.R-project.org/package=RLumModel

-

References

- +
+
+

Details

+

Defining a sequence

+
ArgumentsDescriptionSub-arguments
TLthermally stimulated luminescence'temp begin' (ºC), 'temp end' (ºC), 'heating rate' (ºC/s)
OSLoptically stimulated luminescence'temp' (ºC), 'duration' (s), 'optical_power' (%)
ILLillumination'temp' (ºC), 'duration' (s), 'optical_power' (%)
LM_OSLlinear modulated OSL'temp' (ºC), 'duration' (s), optional: 'start_power' (%), 'end_power' (%)
RL/RFradioluminescence'temp' (ºC), 'dose' (Gy), 'dose_rate' (Gy/s)
RF_heatingRF during heating/cooling'temp begin' (ºC), 'temp end' (ºC), 'heating rate' (ºC/s], 'dose_rate' (Gy/s)
IRRirradiation'temp' (ºC), 'dose' (Gy), 'dose_rate' (Gy/s)
CHcutheat'temp' (ºC), optional: 'duration' (s), 'heating_rate' (ºC/s)
PHpreheat'temp' (ºC), 'duration' (s), optional: 'heating_rate' (ºC/s)
PAUSEpause'temp' (ºC), 'duration' (s)

Note: 100% illumination power equates to 20 mW/cm^2

+

Own parameters

+

The list has to contain the following items:

  • N: Concentration of electron- and hole traps (cm^(-3))

    • +

  • E: Electron/Hole trap depth (eV)

    • +

  • s: Frequency factor (s^(-1))

    • +

  • A: Conduction band to electron trap and valence band to hole trap transition probability (s^(-1) * cm^(3)). +CAUTION: Not every publication uses +the same definition of parameter A and B! See vignette "RLumModel - Usage with own parameter sets" for further details

    • +

  • B: Conduction band to hole centre transition probability (s^(-1) * cm^(3)).

    • +

  • Th: Photo-eviction constant or photoionisation cross section, respectively

    • +

  • E_th: Thermal assistence energy (eV)

    • +

  • k_B: Boltzman constant 8.617e-05 (eV/K)

    • +

  • W: activation energy 0.64 (eV) (for UV)

    • +

  • K: 2.8e7 (dimensionless constant)

    • +

  • model: "customized"

    • +

  • R (optional): Ionisation rate (pair production rate) equivalent to 1 Gy/s (s^(-1)) * cm^(-3))

    • +

For further details see Bailey 2001, Wintle 1975, vignette "RLumModel - Using own parameter sets" +and example 3.

+

Defining a SAR-sequence

+
AbrivationDescriptionexamples
RegDoseDose points of the regenerative cycles (Gy)c(0, 80, 140, 260, 320, 0, 80)
TestDoseTest dose for the SAR cycles (Gy)50
PHTemperature of the preheat (ºC)240
CHTemperature of the cutheat (ºC)200
OSL_tempTemperature of OSL read out (ºC)125
OSL_durationDuration of OSL read out (s)default: 40
Irr_tempTemperature of irradiation (ºC)default: 20
PH_durationDuration of the preheat (s)default: 10
dose_rateDose rate of the laboratory irradiation source (Gy/s)default: 1
optical_powerPercentage of the full illumination power (%)default: 90
Irr_2recoverDose to be recovered in a dose-recovery-test (Gy)20
+
+

Function version

+

0.1.6

+
+
+

How to cite

+

Friedrich, J., Kreutzer, S., 2022. model_LuminescenceSignals(): Model Luminescence Signals. Function version 0.1.6. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2022. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.10. https://CRAN.R-project.org/package=RLumModel

+
+
+

References

Bailey, R.M., 2001. Towards a general kinetic model for optically and thermally stimulated luminescence of quartz. Radiation Measurements 33, 17-45.

Bailey, R.M., 2002. Simulations of variability in the luminescence characteristics of natural @@ -328,343 +207,348 @@

R

Pagonis, V., Wintle, A.G., Chen, R., Wang, X.L., 2008. A theoretical model for a new dating protocol for quartz based on thermally transferred OSL (TT-OSL). Radiation Measurements 43, 704-708.

-

Pagonis, V., Lawless, J., Chen, R., Anderson, C., 2009. Radioluminescence in Al2O3:C - analytical and numerical +

Pagonis, V., Lawless, J., Chen, R., Anderson, C., 2009. Radioluminescence in Al2O3:C - analytical and numerical simulation results. Journal of Physics D: Applied Physics 42, 175107 (9pp).

+

Peng, J., Wang, X., Adamiec, G., 2022. The build-up of the laboratory-generated dose-response curve and +underestimation of equivalent dose for quartz OSL in the high dose region: A critical modelling study. +Quaternary Geochronology 67, 101231.

Soetaert, K., Cash, J., Mazzia, F., 2012. Solving differential equations in R. Springer Science & Business Media.

Wintle, A., 1975. Thermal Quenching of Thermoluminescence in Quartz. Geophysical Journal International 41, 107-113.

-

See also

- -

plot, RLum, -read_SEQ2R

-

Author

- +
+
+

See also

+

plot, Luminescence::RLum, +read_SEQ2R

+
+
+

Author

Johannes Friedrich, University of Bayreuth (Germany), -Sebastian Kreutzer, IRAMAT-CRP2A, Universite Bordeaux Montaigne (France)

+Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom)

+
-

Examples

- 

-
-##================================================================##
-## Example 1: Simulate Bailey2001
-## (cf. Bailey, 2001, Fig. 1)
-##================================================================##
-
-##set sequence with the following steps
-## (1) Irradiation at 20 deg. C with a dose of 10 Gy and a dose rate of 1 Gy/s
-## (2) TL from 20-400 deg. C with a rate of 5 K/s
-
-sequence <-
-  list(
-    IRR = c(20, 10, 1),
-    TL = c(20, 400, 5)
-  )
-
-##model sequence
-model.output <- model_LuminescenceSignals(
-  sequence = sequence,
-  model = "Bailey2001"
-)
-#> 
-#> [.translate_Sequence()] 
-#> 	>> Simulate sequence 
-#> 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================================================| 100%
-
-
-##get all TL concentrations
-
-TL_conc <- get_RLum(model.output, recordType = "(TL)", drop = FALSE)
-
-plot_RLum(TL_conc)
-
-
-
-##plot 110 deg. C trap concentration
-
-TL_110 <- get_RLum(TL_conc, recordType = "conc. level 1") 
-plot_RLum(TL_110)
-
-
-##============================================================================##
-## Example 2: compare different optical powers of stimulation light
-##============================================================================##
-
-# call function "model_LuminescenceSignals", model = "Bailey2004"
-# and simulate_sample_history = FALSE (default),
-# because the sample history is not part of the sequence
-# the optical_power of the LED is varied and then compared.
-
-optical_power <- seq(from = 0,to = 100,by = 20)
-
-model.output <- lapply(optical_power, function(x){
-
- sequence <- list(IRR = c(20, 50, 1),
-                  PH = c(220, 10, 5),
-                  OSL = c(125, 50, x)
-                  )
-
- data <- model_LuminescenceSignals(
-           sequence = sequence,
-           model = "Bailey2004",
-           plot = FALSE,
-           verbose = FALSE
-           )
-
- return(get_RLum(data, recordType = "OSL$", drop = FALSE))
-})
-
-##combine output curves
-model.output.merged <- merge_RLum(model.output)
-
-##plot
-plot_RLum(
- object = model.output.merged,
- xlab = "Illumination time [s]",
- ylab = "OSL signal [a.u.]",
- main = "OSL signal dependency on optical power of stimulation light",
- legend.text = paste("Optical power density", 20*optical_power/100, "mW/cm^2"),
- combine = TRUE)
-
- 
-##============================================================================##
-## Example 3: Usage of own parameter sets (Pagonis 2009)
-##============================================================================##
-
-own_parameters <- list(
-  N = c(2e15, 2e15, 1e17, 2.4e16),
-  E = c(0, 0, 0, 0),
-  s = c(0, 0, 0, 0),
-  A = c(2e-8, 2e-9, 4e-9, 1e-8),
-  B = c(0, 0, 5e-11, 4e-8),
-  Th = c(0, 0),
-  E_th = c(0, 0),
-  k_B = 8.617e-5,
-  W = 0.64,
-  K = 2.8e7,
-  model = "customized",
-  R = 1.7e15
- )
- ## Note: In Pagonis 2009 is B the valence band to hole centre probability, 
- ## but in Bailey 2001 this is A_j. So the values of B (in Pagonis 2009)
- ## are A in the notation above. Also notice that the first two entries in N, A and 
- ## B belong to the electron traps and the last two entries to the hole centres.
- 
- own_state_parameters <- c(0, 0, 0, 9.4e15)
- 
- ## calculate Fig. 3 in Pagonis 2009. Note: The labels for the dose rate in the original 
- ## publication are not correct.
- ## For a dose rate of 0.1 Gy/s belongs a RF signal to ~ 1.5e14 (see Fig. 6).
- 
- sequence <- list(RF = c(20, 0.1, 0.1))
- 
- model_LuminescenceSignals(
-   model = "customized", 
-   sequence = sequence, 
-   own_parameters = own_parameters, 
-   own_state_parameters = own_state_parameters)
-#> 
-#> [.translate_Sequence()] 
-#> 	>> Simulate sequence 
-#> 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
-
-#> 
-#>  [RLum.Analysis-class]
-#> 	 originator: model_LuminescenceSignals()()
-#> 	 protocol: customized
-#> 	 additional info elements:  3
-#> 	 number of records: 7
-#> 	 .. : RLum.Data.Curve : 7
-#> 	 .. .. : #1 RF | #2 conc. level 1 (RF) | #3 conc. level 2 (RF) | #4 conc. level 3 (RF) | #5 conc. level 4 (RF) | #6 conc. n_c (RF) | #7 conc. n_v (RF)
- 
- 
- 
- 
-if (FALSE) {  
-##============================================================================##
-## Example 4: Simulate Thermal-Activation-Characteristics (TAC)
-##============================================================================##
- 
- ##set temperature
- act.temp <- seq(from = 80, to = 600, by = 20)
- 
- ##loop over temperature
- model.output <- vapply(X = act.temp, FUN = function(x) {
- 
- ##set sequence, note: sequence includes sample history
-   sequence <- list(
-     IRR = c(20, 1, 1e-11),
-     IRR = c(20, 10, 1),
-     PH = c(x, 1),
-     IRR = c(20, 0.1, 1),
-     TL = c(20, 150, 5)
- )
- ##run simulation
-   temp <- model_LuminescenceSignals(
-     sequence = sequence,
-     model = "Pagonis2007",
-     simulate_sample_history = TRUE,
-     plot = FALSE,
-     verbose = FALSE
-   )
-     ## "TL$" for exact matching TL and not (TL)
-   TL_curve <- get_RLum(temp, recordType = "TL$")
-   ##return max value in TL curve
-   return(max(get_RLum(TL_curve)[,2]))
- }, FUN.VALUE = 1)
- 
- ##plot resutls
- plot(
-   act.temp[-(1:3)],
-   model.output[-(1:3)],
-   type = "b",
-   xlab = "Temperature [\u00B0C]",
-   ylab = "TL [a.u.]"
- )
-
-##============================================================================##
-## Example 5: Simulate SAR sequence
-##============================================================================##
-
-##set SAR sequence with the following steps
-## (1) RegDose: set regenerative dose [Gy] as vector
-## (2) TestDose: set test dose [Gy]
-## (3) PH: set preheat temperature in deg. C
-## (4) CH: Set cutheat temperature in deg. C
-## (5) OSL_temp: set OSL reading temperature in deg. C
-## (6) OSL_duration: set OSL reading duration in s
-
-sequence <- list(
- RegDose = c(0,10,20,50,90,0,10),
- TestDose = 5,
- PH = 240,
- CH = 200,
- OSL_temp = 125,
- OSL_duration = 70)
-
-# call function "model_LuminescenceSignals", set sequence = sequence,
-# model = "Pagonis2007" (palaeodose = 20 Gy) and simulate_sample_history = FALSE (default),
-# because the sample history is not part of the sequence
-
- model.output <- model_LuminescenceSignals(
-   sequence = sequence,
-   model = "Pagonis2007",
-   plot = FALSE
- )
-
-# in environment is a new object "model.output" with the results of
-# every step of the given sequence.
-# Plots are done at OSL and TL steps and the growth curve
-
-# call "analyse_SAR.CWOSL" from RLum package
- results <- analyse_SAR.CWOSL(model.output,
-                            signal.integral.min = 1,
-                            signal.integral.max = 15,
-                            background.integral.min = 601,
-                            background.integral.max = 701,
-                            fit.method = "EXP",
-                            dose.points = c(0,10,20,50,90,0,10))
-
-
-##============================================================================##
-## Example 6: generate sequence from *.seq file and run SAR simulation
-##============================================================================##
-
-# load example *.SEQ file and construct a sequence.
-# call function "model_LuminescenceSignals", load created sequence for sequence,
-# set model = "Bailey2002" (palaeodose = 10 Gy)
-# and simulate_sample_history = FALSE (default),
-# because the sample history is not part of the sequence
-
-path <- system.file("extdata", "example_SAR_cycle.SEQ", package="RLumModel")
-
-sequence <- read_SEQ2R(file = path)
-
-model.output <- model_LuminescenceSignals(
-  sequence = sequence,
-  model = "Bailey2001",
-  plot = FALSE
-)
-
-
-## call RLum package function "analyse_SAR.CWOSL" to analyse the simulated SAR cycle
-
-results <- analyse_SAR.CWOSL(model.output,
-                             signal.integral.min = 1,
-                             signal.integral.max = 10,
-                             background.integral.min = 301,
-                             background.integral.max = 401,
-                             dose.points = c(0,8,14,26,32,0,8),
-                             fit.method = "EXP")
-
-print(get_RLum(results))
-
-
-##============================================================================##
-## Example 7: Simulate sequence at laboratory without sample history
-##============================================================================##
-
-##set sequence with the following steps
-## (1) Irraditation at 20 deg. C with a dose of 100 Gy and a dose rate of 1 Gy/s
-## (2) Preheat to 200 deg. C and hold for 10 s
-## (3) LM-OSL at 125 deg. C. for 100 s
-## (4) Cutheat at 200 dec. C.
-## (5) Irraditation at 20 deg. C with a dose of 10 Gy and a dose rate of 1 Gy/s
-## (6) Pause at 200 de. C. for 100 s
-## (7) OSL at 125 deg. C for 100 s with 90 % optical power
-## (8) Pause at 200 deg. C for 100 s
-## (9) TL from 20-400 deg. C with a heat rate of 5 K/s
-## (10) Radiofluorescence at 20 deg. C with a dose of 200 Gy and a dose rate of 0.01 Gy/s
-
-sequence <-
- list(
-   IRR = c(20, 100, 1),
-   PH = c(200, 10),
-   LM_OSL = c(125, 100),
-   CH = c(200),
-   IRR = c(20, 10, 1),
-   PAUSE = c(200, 100),
-   OSL = c(125, 100, 90),
-   PAUSE = c(200, 100),
-   TL = c(20, 400, 5),
-   RF = c(20, 200, 0.01)
-)
-
-# call function "model_LuminescenceSignals", set sequence = sequence,
-# model = "Pagonis2008" (palaeodose = 200 Gy) and simulate_sample_history = FALSE (default),
-# because the sample history is not part of the sequence
-
-model.output <- model_LuminescenceSignals(
-   sequence = sequence,
-   model = "Pagonis2008"
-   )
-
-}
-
+
+

Examples

+ 

+##================================================================##
+## Example 1: Simulate Bailey2001
+## (cf. Bailey, 2001, Fig. 1)
+##================================================================##
+
+##set sequence with the following steps
+## (1) Irradiation at 20 deg. C with a dose of 10 Gy and a dose rate of 1 Gy/s
+## (2) TL from 20-400 deg. C with a rate of 5 K/s
+
+sequence <-
+  list(
+    IRR = c(20, 10, 1),
+    TL = c(20, 400, 5)
+  )
+
+##model sequence
+model.output <- model_LuminescenceSignals(
+  sequence = sequence,
+  model = "Bailey2001"
+)
+#> 
+#> [.translate_Sequence()] 
+#> 	>> Simulate sequence 
+#> 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |======================================================================| 100%
+
+
+##get all TL concentrations
+
+TL_conc <- get_RLum(model.output, recordType = "(TL)", drop = FALSE)
+
+plot_RLum(TL_conc)
+
+
+
+##plot 110 deg. C trap concentration
+
+TL_110 <- get_RLum(TL_conc, recordType = "conc. level 1")
+plot_RLum(TL_110)
+
+
+##============================================================================##
+## Example 2: compare different optical powers of stimulation light
+##============================================================================##
+
+# call function "model_LuminescenceSignals", model = "Bailey2004"
+# and simulate_sample_history = FALSE (default),
+# because the sample history is not part of the sequence
+# the optical_power of the LED is varied and then compared.
+
+optical_power <- seq(from = 0,to = 100,by = 20)
+
+model.output <- lapply(optical_power, function(x){
+
+ sequence <- list(IRR = c(20, 50, 1),
+                  PH = c(220, 10, 5),
+                  OSL = c(125, 50, x)
+                  )
+
+ data <- model_LuminescenceSignals(
+           sequence = sequence,
+           model = "Bailey2004",
+           plot = FALSE,
+           verbose = FALSE
+           )
+
+ return(get_RLum(data, recordType = "OSL$", drop = FALSE))
+})
+
+##combine output curves
+model.output.merged <- merge_RLum(model.output)
+
+##plot
+plot_RLum(
+ object = model.output.merged,
+ xlab = "Illumination time (s)",
+ ylab = "OSL signal (a.u.)",
+ main = "OSL signal dependency on optical power of stimulation light",
+ legend.text = paste("Optical power density", 20*optical_power/100, "mW/cm^2"),
+ combine = TRUE)
+
+
+##============================================================================##
+## Example 3: Usage of own parameter sets (Pagonis 2009)
+##============================================================================##
+
+own_parameters <- list(
+  N = c(2e15, 2e15, 1e17, 2.4e16),
+  E = c(0, 0, 0, 0),
+  s = c(0, 0, 0, 0),
+  A = c(2e-8, 2e-9, 4e-9, 1e-8),
+  B = c(0, 0, 5e-11, 4e-8),
+  Th = c(0, 0),
+  E_th = c(0, 0),
+  k_B = 8.617e-5,
+  W = 0.64,
+  K = 2.8e7,
+  model = "customized",
+  R = 1.7e15
+ )
+ ## Note: In Pagonis 2009 is B the valence band to hole centre probability,
+ ## but in Bailey 2001 this is A_j. So the values of B (in Pagonis 2009)
+ ## are A in the notation above. Also notice that the first two entries in N, A and
+ ## B belong to the electron traps and the last two entries to the hole centres.
+
+ own_state_parameters <- c(0, 0, 0, 9.4e15)
+
+ ## calculate Fig. 3 in Pagonis 2009. Note: The labels for the dose rate in the original
+ ## publication are not correct.
+ ## For a dose rate of 0.1 Gy/s belongs a RF signal to ~ 1.5e14 (see Fig. 6).
+
+ sequence <- list(RF = c(20, 0.1, 0.1))
+
+ model_LuminescenceSignals(
+   model = "customized",
+   sequence = sequence,
+   own_parameters = own_parameters,
+   own_state_parameters = own_state_parameters)
+#> 
+#> [.translate_Sequence()] 
+#> 	>> Simulate sequence 
+#> 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
+
+#> 
+#>  [RLum.Analysis-class]
+#> 	 originator: model_LuminescenceSignals()
+#> 	 protocol: customized
+#> 	 additional info elements:  3
+#> 	 number of records: 7
+#> 	 .. : RLum.Data.Curve : 7
+#> 	 .. .. : #1 RF | #2 conc. level 1 (RF) | #3 conc. level 2 (RF) | #4 conc. level 3 (RF) | #5 conc. level 4 (RF) | #6 conc. n_c (RF) | #7 conc. n_v (RF)
+
+
+
+
+if (FALSE) {
+##============================================================================##
+## Example 4: Simulate Thermal-Activation-Characteristics (TAC)
+##============================================================================##
+
+ ##set temperature
+ act.temp <- seq(from = 80, to = 600, by = 20)
+
+ ##loop over temperature
+ model.output <- vapply(X = act.temp, FUN = function(x) {
+
+ ##set sequence, note: sequence includes sample history
+   sequence <- list(
+     IRR = c(20, 1, 1e-11),
+     IRR = c(20, 10, 1),
+     PH = c(x, 1),
+     IRR = c(20, 0.1, 1),
+     TL = c(20, 150, 5)
+ )
+ ##run simulation
+   temp <- model_LuminescenceSignals(
+     sequence = sequence,
+     model = "Pagonis2007",
+     simulate_sample_history = TRUE,
+     plot = FALSE,
+     verbose = FALSE
+   )
+     ## "TL$" for exact matching TL and not (TL)
+   TL_curve <- get_RLum(temp, recordType = "TL$")
+   ##return max value in TL curve
+   return(max(get_RLum(TL_curve)[,2]))
+ }, FUN.VALUE = 1)
+
+ ##plot resutls
+ plot(
+   act.temp[-(1:3)],
+   model.output[-(1:3)],
+   type = "b",
+   xlab = "Temperature [\u00B0C)",
+   ylab = "TL [a.u.]"
+ )
+
+##============================================================================##
+## Example 5: Simulate SAR sequence
+##============================================================================##
+
+##set SAR sequence with the following steps
+## (1) RegDose: set regenerative dose (Gy) as vector
+## (2) TestDose: set test dose (Gy)
+## (3) PH: set preheat temperature in deg. C
+## (4) CH: Set cutheat temperature in deg. C
+## (5) OSL_temp: set OSL reading temperature in deg. C
+## (6) OSL_duration: set OSL reading duration in s
+
+sequence <- list(
+ RegDose = c(0,10,20,50,90,0,10),
+ TestDose = 5,
+ PH = 240,
+ CH = 200,
+ OSL_temp = 125,
+ OSL_duration = 70)
+
+# call function "model_LuminescenceSignals", set sequence = sequence,
+# model = "Pagonis2007" (palaeodose = 20 Gy) and simulate_sample_history = FALSE (default),
+# because the sample history is not part of the sequence
+
+ model.output <- model_LuminescenceSignals(
+   sequence = sequence,
+   model = "Pagonis2007",
+   plot = FALSE
+ )
+
+# in environment is a new object "model.output" with the results of
+# every step of the given sequence.
+# Plots are done at OSL and TL steps and the growth curve
+
+# call "analyse_SAR.CWOSL" from RLum package
+ results <- analyse_SAR.CWOSL(model.output,
+                            signal.integral.min = 1,
+                            signal.integral.max = 15,
+                            background.integral.min = 601,
+                            background.integral.max = 701,
+                            fit.method = "EXP",
+                            dose.points = c(0,10,20,50,90,0,10))
+
+
+##============================================================================##
+## Example 6: generate sequence from *.seq file and run SAR simulation
+##============================================================================##
+
+# load example *.SEQ file and construct a sequence.
+# call function "model_LuminescenceSignals", load created sequence for sequence,
+# set model = "Bailey2002" (palaeodose = 10 Gy)
+# and simulate_sample_history = FALSE (default),
+# because the sample history is not part of the sequence
+
+path <- system.file("extdata", "example_SAR_cycle.SEQ", package="RLumModel")
+
+sequence <- read_SEQ2R(file = path)
+
+model.output <- model_LuminescenceSignals(
+  sequence = sequence,
+  model = "Bailey2001",
+  plot = FALSE
+)
+
+
+## call RLum package function "analyse_SAR.CWOSL" to analyse the simulated SAR cycle
+
+results <- analyse_SAR.CWOSL(model.output,
+                             signal.integral.min = 1,
+                             signal.integral.max = 10,
+                             background.integral.min = 301,
+                             background.integral.max = 401,
+                             dose.points = c(0,8,14,26,32,0,8),
+                             fit.method = "EXP")
+
+print(get_RLum(results))
+
+
+##============================================================================##
+## Example 7: Simulate sequence at laboratory without sample history
+##============================================================================##
+
+##set sequence with the following steps
+## (1) Irraditation at 20 deg. C with a dose of 100 Gy and a dose rate of 1 Gy/s
+## (2) Preheat to 200 deg. C and hold for 10 s
+## (3) LM-OSL at 125 deg. C. for 100 s
+## (4) Cutheat at 200 dec. C.
+## (5) Irraditation at 20 deg. C with a dose of 10 Gy and a dose rate of 1 Gy/s
+## (6) Pause at 200 de. C. for 100 s
+## (7) OSL at 125 deg. C for 100 s with 90 % optical power
+## (8) Pause at 200 deg. C for 100 s
+## (9) TL from 20-400 deg. C with a heat rate of 5 K/s
+## (10) Radiofluorescence at 20 deg. C with a dose of 200 Gy and a dose rate of 0.01 Gy/s
+
+sequence <-
+ list(
+   IRR = c(20, 100, 1),
+   PH = c(200, 10),
+   LM_OSL = c(125, 100),
+   CH = c(200),
+   IRR = c(20, 10, 1),
+   PAUSE = c(200, 100),
+   OSL = c(125, 100, 90),
+   PAUSE = c(200, 100),
+   TL = c(20, 400, 5),
+   RF = c(20, 200, 0.01)
+)
+
+# call function "model_LuminescenceSignals", set sequence = sequence,
+# model = "Pagonis2008" (palaeodose = 200 Gy) and simulate_sample_history = FALSE (default),
+# because the sample history is not part of the sequence
+
+model.output <- model_LuminescenceSignals(
+   sequence = sequence,
+   model = "Pagonis2008"
+   )
+
+}
+
+
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/reference/read_SEQ2R.html b/docs/reference/read_SEQ2R.html index dc483bf..b1dea98 100644 --- a/docs/reference/read_SEQ2R.html +++ b/docs/reference/read_SEQ2R.html @@ -1,78 +1,19 @@ - - - - - - - -Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz luminescence — read_SEQ2R • RLumModel - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz luminescence — read_SEQ2R • RLumModel - - - - - - + + - - -
-
- -
- -
+

Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz luminescence

- Source: R/read_SEQ2R.R + Source: R/read_SEQ2R.R
@@ -159,85 +91,86 @@

Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz lumine in the sequence editor.

- 
read_SEQ2R(file, lab.dose_rate = 1, txtProgressBar = TRUE)
- -

Arguments

- - - - - - - - - - - - - - -
file

character (required): a *.seq file created by the Risoe Sequence Editor

lab.dose_rate

character (with default): set the dose rate of the radiation source -in the laboratory Gy/s. Default: 1 Gy/s

txtProgressBar

logical (with default): enables or disables the txtProgressBar for a visuell -control of the progress. Default: txtProgressBar = TRUE

- -

Value

- -

This function returns a list with the parsed *.seq file and the required steps for -model_LuminescenceSignals.

-

Details

+
+ 
read_SEQ2R(file, lab.dose_rate = 1, txtProgressBar = TRUE)
+
+
+

Arguments

+
file
+

character (required): a *.seq file created by the Risoe Sequence Editor

+
lab.dose_rate
+

character (with default): set the dose rate of the radiation source +in the laboratory Gy/s. Default: 1 Gy/s

+
txtProgressBar
+

logical (with default): enables or disables the txtProgressBar for a visuell +control of the progress. Default: txtProgressBar = TRUE

+
+
+

Value

+

This function returns a list with the parsed *.seq file and the required steps for +model_LuminescenceSignals.

+
+
+

Details

Supported versions: Supppored and tested: version 4.36.

-

Function version

- +
+
+

Function version

0.1.0

-

How to cite

- -

Friedrich, J., 2021. read_SEQ2R(): Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz luminescence. Function version 0.1.0. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2021. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.9. https://CRAN.R-project.org/package=RLumModel

-

References

- +
+
+

How to cite

+

Friedrich, J., 2022. read_SEQ2R(): Parse a Risoe SEQ-file to a sequence neccessary for simulating quartz luminescence. Function version 0.1.0. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2022. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.10. https://CRAN.R-project.org/package=RLumModel

+
+
+

References

Riso: Sequence Editor User Manual. Available at: http://www.nutech.dtu.dk/english/-/media/Andre_Universitetsenheder/Nutech/Produkter SequenceEditor.ashx?la=da

-

See also

- -

model_LuminescenceSignals, readLines

-

Author

- +
+ +
+

Author

Johannes Friedrich, University of Bayreuth (Germany),

+
-

Examples

- 
##search "example_SAR_cycle.SEQ" in "extdata" in package "RLumModel"
-path <- system.file("extdata", "example_SAR_cycle.SEQ", package="RLumModel")
-
-sequence <- read_SEQ2R(file = path, txtProgressBar = FALSE)
-
-
+
+

Examples

+ 
##search "example_SAR_cycle.SEQ" in "extdata" in package "RLumModel"
+path <- system.file("extdata", "example_SAR_cycle.SEQ", package="RLumModel")
+
+sequence <- read_SEQ2R(file = path, txtProgressBar = FALSE)
+
+
+
+
-
-
-

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph Schmidt.

+
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

-

Site built with pkgdown 1.6.1.

+

Site built with pkgdown +2.0.2.

-
-
+
- - + + diff --git a/docs/reference/trace_ParameterStateEvolution-1.png b/docs/reference/trace_ParameterStateEvolution-1.png new file mode 100644 index 0000000..dfb4ede Binary files /dev/null and b/docs/reference/trace_ParameterStateEvolution-1.png differ diff --git a/docs/reference/trace_ParameterStateEvolution.html b/docs/reference/trace_ParameterStateEvolution.html new file mode 100644 index 0000000..f0b6d54 --- /dev/null +++ b/docs/reference/trace_ParameterStateEvolution.html @@ -0,0 +1,187 @@ + +Trace parameter state evolution — trace_ParameterStateEvolution • RLumModel + + +
+
+ + + +
+
+
+

Trace parameter state evolution

+ Source: R/trace_ParameterStateEvolution.R + +
+ +
+

Traces the evolution of the concentrations in the different +levels over different simulation steps. For instance, a sequence consisting +of one TL and one OSL step has two iterations. For each step the end concentration +is extracted. This way, the evolution of the system can be traced throughout +a sequence.

+
+ +
+ 
trace_ParameterStateEvolution(object, step = NULL, plot = TRUE, ...)
+
+ +
+

Arguments

+
object
+

Luminescence::RLum.Analysis (required): input object +created by the function model_LuminescenceSignals. The input can be a list of such +objects

+
step
+

character (optional): filter the input object to pick particular +steps, the input is passed to Luminescence::get_RLum

+
plot
+

logical (with default): enables/disables plot output

+
...
+

optional arguments to be passed to control the plot output. Supported +are xlim, xlab, ylab, log, col, type, bg, main, norm (TRUE/FALSE), +grid (TRUE/FALSE), step_names (TRUE/FALSE) +Where meaningful, parameters can be provided as vectors. Vectors short than the number of plots are recycled.

+
+
+

Value

+

Returns a plot and list with matrix objects of the parameter evolution. If +object is a list the output is a nested list

+
+
+

Function version

+

0.1.0

+
+
+

Author

+

Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom)

+
+
+

How to cite

+

Kreutzer, S., 2022. trace_ParameterStateEvolution(): Trace parameter state evolution. Function version 0.1.0. In: Friedrich, J., Kreutzer, S., Schmidt, C., 2022. RLumModel: Solving Ordinary Differential Equations to Understand Luminescence. R package version 0.2.10. https://CRAN.R-project.org/package=RLumModel

+
+ +
+

Examples

+ 

+sequence <-
+list(
+IRR = c(20, 10, 1),
+TL = c(20, 400, 5),
+IRR = c(20, 10, 1),
+TL = c(20, 400, 5))
+
+##model sequence
+model.output <- model_LuminescenceSignals(
+ sequence = sequence,
+ verbose = FALSE,
+ plot = FALSE,
+ model = "Bailey2001")
+
+## trace
+trace_ParameterStateEvolution(model.output)
+
+
+
+
+
+ +
+ + +
+

Developed by Johannes Friedrich, Sebastian Kreutzer, Christoph +Schmidt.

+
+ +
+

Site built with pkgdown +2.0.2.

+
+ +
+ + + + + + + + diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 681ca3f..8ce2106 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -1,8 +1,38 @@ + + https://github.com/R-Lum/RLumModel/404.html + + + https://github.com/R-Lum/RLumModel/LICENSE-text.html + + + https://github.com/R-Lum/RLumModel/LICENSE.html + + + https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Getting_started_with_RLumModel.html + + + https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Models_and_parameters.html + + + https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Simulating_luminescence_in_Al2O3.html + + + https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Using_own_parameter_sets.html + + + https://github.com/R-Lum/RLumModel/articles/index.html + + + https://github.com/R-Lum/RLumModel/authors.html + https://github.com/R-Lum/RLumModel/index.html + + https://github.com/R-Lum/RLumModel/news/index.html + https://github.com/R-Lum/RLumModel/reference/ExampleData.ModelOutput.html @@ -13,18 +43,15 @@ https://github.com/R-Lum/RLumModel/reference/dot-set_pars.html - https://github.com/R-Lum/RLumModel/reference/model_LuminescenceSignals.html - - - https://github.com/R-Lum/RLumModel/reference/read_SEQ2R.html + https://github.com/R-Lum/RLumModel/reference/index.html - https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Getting_started_with_RLumModel.html + https://github.com/R-Lum/RLumModel/reference/model_LuminescenceSignals.html - https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Simulating_luminescence_in_Al2O3.html + https://github.com/R-Lum/RLumModel/reference/read_SEQ2R.html - https://github.com/R-Lum/RLumModel/articles/RLumModel_-_Using_own_parameter_sets.html + https://github.com/R-Lum/RLumModel/reference/trace_ParameterStateEvolution.html