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80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
def r_value_per_mm_to_u_value(depth_mm: int, r_value_per_mm: float):
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"""
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Converts R-value per mm to U-value in W/m²K.
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Parameters
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----------
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depth_mm : int
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Depth of the material in mm.
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r_value_per_mm : float
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R-value per mm.
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Returns
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-------
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float
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U-value in W/m²K.
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"""
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return 1 / (depth_mm * r_value_per_mm)
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def calculate_u_value_uplift(u_value, insulation_u_value):
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"""
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Calculates the U-value uplift (improvement) when applying internal wall insulation to a wall.
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:param u_value: Float, Starting U-value of the wall (without insulation) in W/m²K.
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:param insulation_u_value: Float, U-value of the internal wall insulation in W/m²K.
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Returns:
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float: U-value uplift (improvement) achieved by applying internal wall insulation in W/m²K.
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Raises:
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ZeroDivisionError: If either u_value or iwi_u_value is zero.
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Notes:
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This function assumes 100% coverage of the internal wall insulation and does not account for other factors
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such as thermal bridging or the specific configuration of the wall.
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"""
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inverse_u_value = 1 / u_value
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inverse_insulation_u_value = 1 / insulation_u_value
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inverse_u_total = inverse_u_value + inverse_insulation_u_value
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new_u_value = 1 / inverse_u_total
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u_value_uplift = u_value - new_u_value
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return u_value_uplift, new_u_value
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def is_diminishing_returns(recommendations, new_u_value, lowest_selected_u_value, diminishing_returns_u_value):
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"""
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What are defines diminishing returns?
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1) The new u value is lower than the lowest selected u value
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2) The new u value is below the diminishing returns threshold
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3) We already have some recommendations so there is no need to
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insert another recommendation in
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"""
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# if we don't have anything selected, lowest_selected_u_value will be missing
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if lowest_selected_u_value is None:
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if recommendations:
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raise ValueError("Recommendations should be empty - investigate")
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# This means that nothing has been selected yet
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# the new u value is less than the threshold, however this MIGHT be the only
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# solution and so we consider it
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return False
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# We should already have recommendations
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if not recommendations:
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raise ValueError("Recommendations should not be empty - investigate")
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# We already have a solution that is suitable so we want to make sure that
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# any new solutin actually has a higher u-value as it will either be
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# 1) cheaper
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# 2) thinner with a more efficient material
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is_diminishing = (new_u_value < diminishing_returns_u_value) and (
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new_u_value < lowest_selected_u_value
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)
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return is_diminishing
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