Main Manuscript for Morphology-driven energy vulnerabilities in urban building stocks: Quantifying climate adaptation mismatches across 12,000 buildings
- @ashrae_template_parser.py: Parses ASHRAE templates for internal loads, schedules, materials, and constructions to be used in EnergyPlus models.
- @clustering.py: Performs various clustering analyses (DBSCAN, K-Means, etc.) on building data to group similar building segments.
- @cp_shp.py: Calculates wind pressure coefficients (Cp) for building facades based on shapefile data and surrounding context.
- @EP_model.py: Creates and simulates EnergyPlus building models, including geometry, airflow networks, and energy consumption.
- @Eppy_shp_cpcalc_split_sort.py: Processes shapefiles to calculate Cp values, reorganizes the data, and creates EnergyPlus models for individual buildings.
- @leeward.py: Calculates wind pressure coefficients for the leeward side of buildings.
- @main.py: The main script that orchestrates the entire workflow from preprocessing to simulation and analysis.
- @preprocessing.py: Preprocesses shapefiles by standardizing column names, projecting to UTM, and regularizing geometries.
- @regularize.py: Regularizes building footprint geometries to minimum bounding rectangles.
- @result_viz.py: Visualizes the simulation results, such as energy consumption and cluster assignments, in 3D.
- @solar_potential.py: Calculates the solar potential for building facades by performing ray-tracing analysis.
- @windward.py: Calculates wind pressure coefficients for the windward side of buildings.
- @plots/EUIs_combined.py: Generates visualizations for Energy Use Intensity (EUI) distributions across multiple cities.
- @plots/validation.py: Creates validation plots comparing predicted and actual EUI values.