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implementing u-value population wip
This commit is contained in:
Khalim Conn-Kowlessar
parent
f86a466f3d
commit
aa3b1e172d
3 changed files with 301 additions and 7 deletions
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@ -77,6 +77,239 @@ def app():
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if len(descriptions) != len(set(descriptions)):
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raise ValueError("Duplicated descriptions found, check me")
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# Finally, we attach u-values to the descriptions for walls, roofs and floors
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wall_types = [
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"Stone: granite or whinstone as built",
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"Stone: sandstone or limestone as built",
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"Solid brick as built",
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"Stone/solid brick with 50 mm external or internal insulation",
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"Stone/solid brick with 100 mm external or internal insulation",
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"Stone/solid brick with 150 mm external or internal insulation",
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"Stone/solid brick with 200 mm external or internal insulation",
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"Cob as built",
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"Cob with 50 mm external or internal insulation",
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"Cob with 100 mm external or internal insulation",
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"Cob with 150 mm external or internal insulation",
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"Cob with 200 mm external or internal insulation",
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"Cavity as built",
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"Unfilled cavity with 50 mm external or internal insulation",
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"Unfilled cavity with 100 mm external or internal insulation",
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"Unfilled cavity with 150 mm external or internal insulation",
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"Unfilled cavity with 200 mm external or internal insulation",
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"Filled cavity",
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"Filled cavity with 50 mm external or internal insulation",
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"Filled cavity with 100 mm external or internal insulation",
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"Filled cavity with 150 mm external or internal insulation",
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"Filled cavity with 200 mm external or internal insulation",
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"Timber frame as built",
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"Timber frame with internal insulation",
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"System build as built",
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"System build with 50 mm external or internal insulation",
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"System build with 100 mm external or internal insulation",
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"System build with 150 mm external or internal insulation",
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"System build with 200 mm external or internal insulation",
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]
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u_values = [
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["a", "a", "a", "a", "1.7b", "1.0", "0.6", "0.60", "0.45", "0.35", "0.30", "0.28"],
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["a", "a", "a", "a", "1.7b", "1.0", "0.6", "0.60", "0.45", "0.35", "0.30", "0.28"],
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["1.7", "1.7", "1.7", "1.7", "1.7", "1.0", "0.60", "0.60", "0.45", "0.35", "0.30", "0.28"],
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["0.55", "0.55", "0.55", "0.55", "0.55", "0.45", "0.35", "0.35", "0.30", "0.25", "0.21", "0.21"],
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["0.32", "0.32", "0.32", "0.32", "0.32", "0.28", "0.24", "0.24", "0.21", "0.19", "0.17", "0.16"],
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["0.23", "0.23", "0.23", "0.23", "0.23", "0.21", "0.18", "0.18", "0.17", "0.15", "0.14", "0.14"],
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["0.18", "0.18", "0.18", "0.18", "0.18", "0.17", "0.15", "0.15", "0.14", "0.13", "0.12", "0.12"],
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["0.80", "0.80", "0.80", "0.80", "0.80", "0.80", "0.60", "0.60", "0.45", "0.35", "0.30", "0.28"],
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["0.40", "0.40", "0.40", "0.40", "0.40", "0.40", "0.35", "0.35", "0.30", "0.25", "0.21", "0.21"],
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["0.26", "0.26", "0.26", "0.26", "0.26", "0.26", "0.24", "0.24", "0.21", "0.19", "0.17", "0.16"],
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["0.20", "0.20", "0.20", "0.20", "0.20", "0.20", "0.18", "0.18", "0.17", "0.15", "0.14", "0.14"],
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["0.16", "0.16", "0.16", "0.16", "0.16", "0.16", "0.15", "0.15", "0.14", "0.13", "0.12", "0.12"],
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["1.5", "1.5", "1.5", "1.5", "1.5", "1.0", "0.60", "0.60", "0.45", "0.35", "0.30", "0.28"],
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["0.53", "0.53", "0.53", "0.53", "0.53", "0.45", "0.35", "0.35", "0.30", "0.25", "0.21", "0.21"],
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["0.32", "0.32", "0.32", "0.32", "0.32", "0.30", "0.24", "0.24", "0.21", "0.19", "0.17", "0.16"],
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["0.23", "0.23", "0.23", "0.23", "0.23", "0.21", "0.18", "0.18", "0.17", "0.15", "0.14", "0.14"],
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["0.18", "0.18", "0.18", "0.18", "0.18", "0.17", "0.15", "0.15", "0.14", "0.13", "0.12", "0.12"],
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["0.7", "0.7", "0.7", "0.7", "0.7", "0.40", "0.35", "0.35", "0.45", "0.35", "0.30", "0.28"],
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["0.37", "0.37", "0.37", "0.37", "0.37", "0.27", "0.25", "0.25", "0.25", "0.25", "0.21", "0.21"],
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["0.25", "0.25", "0.25", "0.25", "0.25", "0.20", "0.19", "0.19", "0.19", "0.19", "0.17", "0.16"],
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["0.19", "0.19", "0.19", "0.19", "0.19", "0.16", "0.15", "0.15", "0.15", "0.15", "0.14", "0.14"],
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["0.16", "0.16", "0.16", "0.16", "0.16", "0.13", "0.13", "0.13", "0.13", "0.13", "0.12", "0.12"],
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["2.5", "1.9", "1.9", "1.0", "0.80", "0.45", "0.40", "0.40", "0.40", "0.35", "0.30", "0.28"],
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["0.60", "0.55", "0.55", "0.40", "0.40", "0.40", "0.40", "0.40", "0.40", "0.35", "0.30", "0.28"],
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["2.0", "2.0", "2.0", "2.0", "1.7", "1.0", "0.60", "0.60", "0.45", "0.35", "0.30", "0.28"],
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["0.60", "0.60", "0.60", "0.60", "0.55", "0.45", "0.35", "0.35", "0.30", "0.25", "0.21", "0.21"],
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["0.35", "0.35", "0.35", "0.35", "0.35", "0.32", "0.24", "0.24", "0.21", "0.19", "0.17", "0.16"],
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["0.25", "0.25", "0.25", "0.25", "0.25", "0.21", "0.18", "0.18", "0.17", "0.15", "0.14", "0.14"],
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["0.18", "0.18", "0.18", "0.18", "0.18", "0.17", "0.15", "0.15", "0.14", "0.13", "0.12", "0.12"],
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]
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age_bands = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L"]
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wall_uvalues = []
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for i, wall_type in enumerate(wall_types):
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row = {"Wall_type": wall_type}
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for j, age_band in enumerate(age_bands):
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row[age_band] = u_values[i][j]
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wall_uvalues.append(row)
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parkhome_wall_uvalues = [
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{"Wall_type": "Park home as built", "F": "1.7", "G": "1.2", "I": "0.7", "K": "0.6"},
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{"Wall_type": "Park home with additional insulation", }
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]
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wall_uvalues.extend(parkhome_wall_uvalues)
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wall_uvalues_df = pd.DataFrame(wall_uvalues)
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# This maps the descriptions in the EPC data to the descriptions in the table
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epc_wall_description_map = {
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############################
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# Cavity wall mappings
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############################
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"Cavity wall, as built, partial insulation": "Filled cavity",
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"Cavity wall, filled cavity": "Filled cavity",
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"Cavity wall, as built, no insulation": "Cavity as built",
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"Cavity wall, as built, insulated": "Unfilled cavity with 100 mm external or internal insulation",
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"Cavity wall, with external insulation": "Unfilled cavity with 100 mm external or internal insulation",
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"Cavity wall,": "Cavity as built", # General case of cavity wall without further details
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"Cavity wall, filled cavity and external insulation":
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"Filled cavity with 100 mm external or internal insulation",
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"Cavity wall, filled cavity and internal insulation":
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"Filled cavity with 100 mm external or internal insulation",
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"Cavity wall, with internal insulation": "Unfilled cavity with 100 mm external or internal insulation",
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############################
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# Solid brick wall mappings
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############################
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"Solid brick, as built, no insulation": "Solid brick as built",
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"Solid brick, with internal insulation": "Stone/solid brick with 100 mm external or internal insulation",
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"Solid brick, as built, insulated": "Stone/solid brick with 100 mm external or internal insulation",
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"Solid brick, with external insulation": "Stone/solid brick with 100 mm external or internal insulation",
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"Solid brick, as built, partial insulation": "Stone/solid brick with 50 mm external or internal insulation",
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############################
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# Timber frame wall mappings
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############################
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# These mappings are perhaps the most dubious due to the lack of timber options in the RdSAP table
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"Timber frame, as built, insulated": "Timber frame with internal insulation",
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"Timber frame, with additional insulation": "Timber frame with internal insulation",
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"Timber frame, as built, partial insulation": "Timber frame as built",
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"Timber frame, as built, no insulation": "Timber frame as built",
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"Timber frame, with external insulation": "Timber frame with internal insulation",
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############################
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# Sandstone/limestones wall mappings
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############################
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"Sandstone or limestone, as built, no insulation": "Stone: sandstone or limestone as built",
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"Sandstone or limestone, with internal insulation":
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"Stone/solid brick with 100 mm external or internal insulation",
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"Sandstone or limestone, as built, partial insulation": "Stone/solid brick with 50 mm external or internal "
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"insulation",
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"Sandstone, as built, no insulation": "Stone: sandstone or limestone as built",
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"Sandstone or limestone, as built, insulated": "Stone/solid brick with 100 mm external or internal"
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"insulation",
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"Sandstone, as built, insulated": "Stone/solid brick with 100 mm external or internal insulation",
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"Sandstone, with internal insulation": "Stone/solid brick with 100 mm external or internal insulation",
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"Sandstone or limestone, with external insulation": "Stone/solid brick with 100 mm external or internal "
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"insulation",
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"Sandstone, with external insulation": "Stone/solid brick with 100 mm external or internal insulation",
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"Sandstone, as built, partial insulation": "Stone/solid brick with 50 mm external or internal insulation",
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############################
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# Granite/whinstone wall mappings
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############################
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"Granite or whinstone, as built, no insulation": "Stone: granite or whinstone as built",
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"Granite or whinstone, with internal insulation": "Stone/solid brick with 100 mm external or internal "
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"insulation",
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"Granite or whinstone, as built, partial insulation": "Stone/solid brick with 50 mm external or internal "
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"insulation",
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"Granite or whinstone, as built, insulated": "Stone/solid brick with 100 mm external or internal "
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"insulation",
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"Granite or whinstone, with external insulation": "Stone/solid brick with 100 mm external or internal "
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"insulation",
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############################
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# System built wall mappings
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############################
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"System built, as built, no insulation": "System build as built",
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"System built, as built, partial insulation": "System build with 50 mm external or internal insulation",
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"System built, with internal insulation": "System build with 100 mm external or internal insulation",
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"System built, with external insulation": "System build with 100 mm external or internal insulation",
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"System built, as built, insulated": "System build with 100 mm external or internal insulation",
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############################
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# Cob wall mappings
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############################
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"Cob, as built": "Cob as built",
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"Cob, with external insulation": "Cob with 100 mm external or internal insulation",
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"Cob, with internal insulation": "Cob with 100 mm external or internal insulation",
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############################
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# Park home mappings
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############################
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"Park home wall, as built": "Park home as built",
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"Park home wall, with external insulation": "Park home with additional insulation",
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"Park home wall, with internal insulation": "Park home with additional insulation",
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}
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from recommendations.rdsap_tables import default_wall_thickness
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def apply_formula_s_5_1_1(is_granite_or_whinstone, is_sandstone_or_limestone, age_band):
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"""
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As the u-value table in https://bregroup.com/wp-content/uploads/2019/09/RdSAP_2012_9.94-20-09-2019.pdf
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on page 19, certain u-values as indicated by an "a", should be populated using a formula as defined in section
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S.5.1.1
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:param wall_type:
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:return:
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"""
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stone_wall_thickness = [x for x in default_wall_thickness if x["type"] == "stone"][0]
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thickness = stone_wall_thickness["J_K_L"] if age_band in ["J", "L", "L"] else stone_wall_thickness[age_band]
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if is_granite_or_whinstone:
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return 3.3 - 0.002 * thickness
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if is_sandstone_or_limestone:
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return 3 - 0.002 * thickness
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for wall in cleaned_data["walls-description"]:
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if wall["thermal_transmittance"]:
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continue
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description = wall["clean_description"]
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# Remove (assumed)
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description = description.replace("(assumed)", "").rstrip()
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mapped_description = epc_wall_description_map[description]
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# Get the u-value
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for ab in age_bands:
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mapped_value = wall_uvalues_df[wall_uvalues_df["Wall_type"] == mapped_description][ab].values[0]
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if mapped_value == "a":
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# The rdSap documentation indicateswe should use a formula to calculate the u-value
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uvalue = float(
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apply_formula_s_5_1_1(
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is_granite_or_whinstone=wall["is_granite_or_whinstone"],
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is_sandstone_or_limestone=wall["is_sandstone_or_limestone"],
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age_band=ab
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)
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)
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elif "b" in mapped_value:
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potential_uvalue = float(mapped_value.replace("b", ""))
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formula_uvalue = float(apply_formula_s_5_1_1(
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is_granite_or_whinstone=wall["is_granite_or_whinstone"],
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is_sandstone_or_limestone=wall["is_sandstone_or_limestone"],
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age_band=ab
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))
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uvalue = min(potential_uvalue, formula_uvalue)
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else:
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uvalue = float(mapped_value)
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df = pd.DataFrame(cleaned_data["walls-description"])
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df = df[pd.isnull(df["thermal_transmittance"])]
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df["clean_description"].values
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# We store a singular file however we could store the data under the following file path:
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# cleaned_epc_data/{component}/{original_description}/cleaned.bson
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# where component is one of the keys of cleaned_data. If we store it against the original data, this
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@ -66,11 +66,24 @@ class FloorRecommendations(Definitions):
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# Compute average room size based on total floor area and number of rooms
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avg_room_size = floor_area / num_rooms
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# Estimate total side length for square layout
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total_side_length = math.sqrt(avg_room_size * num_rooms)
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# Estimate the side length of a square room with the average room size
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avg_room_side_length = math.sqrt(avg_room_size)
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# Compute the perimeter
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perimeter = total_side_length * 4
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# Estimate total side length assuming rooms are lined up in a row
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total_side_length = avg_room_side_length * num_rooms
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# Assuming the house is a square (which is a very rough approximation), compute the perimeter
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perimeter = math.sqrt(total_side_length) * 4
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return perimeter
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@staticmethod
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def _estimate_perimeter_2_rooms(floor_area):
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# Assuming a square layout for the entire floor area to get a first-order approximation of the perimeter
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side_length = math.sqrt(floor_area)
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# Calculating the perimeter of the square layout
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perimeter = 4 * side_length
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return perimeter
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@ -126,7 +139,10 @@ class FloorRecommendations(Definitions):
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dg = defaults["w"] + defaults["lambda_g"] * (defaults["Rsi"] + defaults["Rse"])
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# P is the exposed perimeter, which we estimate as we not have this data
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p = self._estimate_perimeter(floor_area=floor_area, num_rooms=number_of_rooms)
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if number_of_rooms <= 2:
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p = self._estimate_perimeter_2_rooms(floor_area=floor_area)
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else:
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p = self._estimate_perimeter(floor_area=floor_area, num_rooms=number_of_rooms)
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b = 2 * floor_area / p
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u_g = 2 * defaults["lambda_g"] * math.log(math.pi * b / dg + 1) / (math.pi * b + dg)
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u_x = (2 * defaults["h"] * defaults["Uw"] / b) + (1450 * defaults["E"] * defaults["v"] * defaults["fw"] / b)
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@ -135,6 +151,49 @@ class FloorRecommendations(Definitions):
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return u
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def _estimate_solid_floor_u_value(self):
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"""
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1. dt =w + g × (Rsi + Rf + Rse)
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2. B = 2 × A/P
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3. if dt < B, U = 2 × g × ln( × B/dt + 1)/( × B + dt)
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4. if dt >= B, U = g / (0.457 × B + dt)
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:return:
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"""
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# TODO: complete
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insulation_thickness = 0
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age_band_letter = "E"
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wall_type = "cavity"
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floor_area = 37.26
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perimeter = 16.2
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# age_band_letter = [x for x in age_band_data if x[region] == age_band][0]["age_band"]
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defaults = {
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# We need width in meters
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"w": [x[age_band_letter] for x in default_wall_thickness if x["type"] == wall_type][0] / 1000,
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"lambda_g": 1.5,
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"Rsi": 0.17,
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"Rse": 0.04,
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"Rf": 0.001 * insulation_thickness / 0.035,
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"h": 0.3,
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"v": 5,
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"fw": 0.05,
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"E": 0.003,
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"Uw": 1.5,
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}
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dt = defaults["w"] + defaults["lambda_g"] * (defaults["Rsi"] + defaults["Rse"] + defaults["Rf"])
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# perimeter = self._estimate_perimeter(floor_area, number_of_rooms)
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B = 2 * floor_area / perimeter
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if dt < B:
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U = 2 * defaults["lambda_g"] * math.log(math.pi * B / dt + 1) / (math.pi * B + dt)
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else:
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print("implement me")
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def recommend(self):
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u_value = self.property.floor["thermal_transmittance"]
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is_suspended = self.property.floor["is_suspended"]
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@ -91,6 +91,8 @@ age_band_data = [
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},
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]
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# As defined in the rdsap documentation on page 9
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# https://bregroup.com/wp-content/uploads/2019/09/RdSAP_2012_9.94-20-09-2019.pdf
|
||||
default_wall_thickness = [
|
||||
{
|
||||
"type": "stone", "A": 500, "B": 500, "C": 500, "D": 500, "E": 450, "F": 420, "G": 420, "H": 420,
|
||||
|
|
@ -117,7 +119,7 @@ default_wall_thickness = [
|
|||
"I": 300, "J_K_L": 300
|
||||
},
|
||||
{
|
||||
"type": "park home", "A": None, "B": None, "C": None, "D": None, "E": None, "F": 50, "G": None,
|
||||
"H": None, "I": 50, "J_K_L": 100
|
||||
"type": "park home", "A": None, "B": None, "C": None, "D": None, "E": None, "F": 50, "G": 50,
|
||||
"H": None, "I": 75, "J_K_L": 100
|
||||
},
|
||||
]
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue