A function within CityBEM_workflow is designed to handle user inputs related to the SRA model. If preferred, CityBEM can also read radiation data generated by SRA. Additionally, it's important to note that while the hub uses surface IDs, CityBEM operates on a triangular basis. Therefore, a file named buildingSurfaceId is generated, which maps each triangle to its corresponding surface by assigning surface numbers to each triangle in sequence. This enables CityBEM to accurately link each triangle to its associated surface.

hub/exports/formats/stl.py

@@ -69,11 +69,16 @@ class Stl:
     stl_name = f'{self._city.name}.stl'
     stl_file_path = (Path(self._path).resolve() / stl_name).resolve()
     with open(stl_file_path, 'w', encoding='utf-8') as stl:
+      with open(stl_file_path.parent/'buildingSurfaceId.txt', 'w') as textfile:
         for building in self._city.buildings:
           stl.write(f"solid building{building.name}\n")
+          # write the building id in the buildingSurfaceId.txt file
+          textfile.write(building.name + " ")
           for surface in building.surfaces:
+            surfaceID=surface.id
             vertices = []
-          normal = self._to_normal_vertex_stl(surface.perimeter_polygon.coordinates) #the normal vector should be calculated for every surface
+            normal = self._to_normal_vertex_stl(
+              surface.perimeter_polygon.coordinates)  # the normal vector should be calculated for every surface
             for coordinate in surface.perimeter_polygon.coordinates:
               vertex = self._to_vertex_stl(coordinate)
               if vertex not in vertices:
@@ -97,10 +102,14 @@ class Stl:
 
             # write the facets (triangles) in the stl file
             for triangle in triangles:
-            stl.write(f"facet normal {normal[0]} {normal[2]} {normal[1]}\n") #following the idea that y axis is the height
+              #write the id of the surface (the triangles that belong to one surface should have similar id). Note that surface id is number like 2,3,4,
+              textfile.write(surfaceID + " ")
+              stl.write(
+                f"facet normal {normal[0]} {normal[2]} {normal[1]}\n")  # following the idea that y axis is the height
               stl.write("  outer loop\n")
               for vertex in triangle:
                 stl.write(f"    vertex {vertex[0]} {vertex[1]} {vertex[2]}\n")
               stl.write("  endloop\n")
               stl.write("endfacet\n")
+          textfile.write("\n") # End the line after all surface IDs are written for a given building
           stl.write(f"endsolid building{building.name}\n")

main.py

@@ -17,7 +17,10 @@ import subprocess
 # Specify the GeoJSON file path
 # geojson_file = process_geojson(a=-73.5681295982132, b=45.49218262677643, c=-73.5681295982132, d=45.51218262677643,
 #                                e=-73.5881295982132, f=45.49218262677643,g=-73.5881295982132, h=45.51218262677643)
-geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
+geojson_file = process_geojson(x=-73.57711768607801, y=45.495098237967, diff=0.0001)
+#-73.63805499801724; 45.415970792153075
+#x=-73.5681295982132, y=45.49218262677643
+
 
 file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
 # Specify the output path for the PDF file
@@ -35,13 +38,12 @@ city = GeometryFactory('geojson',
 ConstructionFactory('nrcan', city).enrich()
 UsageFactory('nrcan', city).enrich()
 WeatherFactory('epw', city).enrich()
-
 ExportsFactory('stl', city, output_path/'CityBEM_input_output').export()
-
-#ExportsFactory('sra', city, tmp_folder).export()
-#sra_path = (tmp_folder / f'{city.name}_sra.xml').resolve()
+ExportsFactory('sra', city, tmp_folder).export()
+sra_path = (tmp_folder / f'{city.name}_sra.xml').resolve()
 #subprocess.run(['sra', str(sra_path)])
 #ResultFactory('sra', city, tmp_folder).enrich()
-CityBEM_workflow(city) #run the city using a fast City-Building Energy Model, CityBEM
+
+CityBEM_workflow(city,SRA_radiation_status=True, SRA_path=tmp_folder) #run the city using a fast City-Building Energy Model, CityBEM
 #energy_plus_workflow(city)
 print ("test done")

out_files/CityBEM_input_output/SRA_settings.txt

@@ -0,0 +1,3 @@
+cityName: Montreal
+SRA_radiation_status: True
+SRA_path: C:\Users\User\PycharmProjects\CityBEM-CityLayers-SaeedRayegan\tmp

out_files/CityBEM_input_output/buildingSurfaceId.txt

@@ -0,0 +1 @@
+177628 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 

scripts/CityBEM_run.py

@@ -11,12 +11,15 @@ from hub.imports.weather.epw_weather_parameters import EpwWeatherParameters
 sys.path.append('./')
 
 
-def CityBEM_workflow(city):
+def CityBEM_workflow(city, SRA_radiation_status=False, SRA_path=None):
   """
      Main function to run the CityBEM under the CityLayer's hub.
 
      :Note: City object contains necessary attributes for the CityBEM workflow.
      The first final version is created at 10/07/2024
+     Note:CityBEM includes a built-in function to calculate solar radiation on building facades.
+     However, SRA can account for shading effects from nearby buildings, both direct and diffuse. If the user opts to use SRA, CityBEM will read the radiation data generated by SRA.
+
      """
   #general output path for the CityLayer's hub
   out_path = Path(__file__).parent.parent / 'out_files'
@@ -31,7 +34,8 @@ def CityBEM_workflow(city):
   #load the geojson file (for now this is necessary, later, it should be removed to extract building usage type code, center lat and lon). Later, these should be added to the building class
   with open(file_path, 'r') as f:
     geojson_data = json.load(f)
-
+  #city name
+  cityName = city.name
   #call functions to provide inputs for CityBEM and finally run CityBEM
   export_geometry(city, CityBEM_path)
   export_building_info(city, CityBEM_path,geojson_data)
@@ -39,6 +43,7 @@ def CityBEM_workflow(city):
   export_comprehensive_building_data(city, CityBEM_path)
   export_indoor_temperature_setpoint_data(city, CityBEM_path)
   export_internal_heat_gain_data(city, CityBEM_path)
+  write_user_setting_for_SRA_radiation_data(CityBEM_path,cityName, SRA_radiation_status, SRA_path)
   run_CityBEM(CityBEM_path)
 def export_geometry(city, CityBEM_path):
   """
@@ -371,6 +376,13 @@ def export_internal_heat_gain_data(city, CityBEM_path):
             # write the values to the text file for this building
             textfile.write(values_str + '\n')
     print("Internal heat gains for every building is successfully exported into a text file named Input_internal_heat_gain_CityLayer.txt")
+def write_user_setting_for_SRA_radiation_data(CityBEM_path,cityName, SRA_radiation_status, SRA_path):
+    # Open the file in write mode and write the settings
+    with open(CityBEM_path / 'SRA_settings.txt', 'w') as textfile:
+        textfile.write(f"cityName: {cityName}\n")
+        textfile.write(f"SRA_radiation_status: {SRA_radiation_status}\n")
+        textfile.write(f"SRA_path: {SRA_path}\n")
+
 def run_CityBEM(CityBEM_path):
     """
         Run the CityBEM executable after all inputs are processed.