import numpy as np try: import pymc as pm except: pass from ._base_components import BaseComponents from ..tools.enthalpy import get_RH_from_Tdb_and_Hr from ..tools.enthalpy import get_Dew_from_HumRatio class WheelS2(BaseComponents): def __init__(self): super().__init__() @classmethod def model( cls, TinP,HinP,FP, TinR,HinR,FR, engine : str, param : dict, ): FUNC = cls.get_func_by_engine(engine) EXP = FUNC['EXP'] RinP = get_RH_from_Tdb_and_Hr(TinP,HinP,engine) beta_Q1 = param['beta_Q1'] beta_H1 = param['beta_H1'] beta_H2 = param['beta_H2'] beta_H3 = param['beta_H3'] beta_H4 = param['beta_H4'] # 转轮的温度 T_avg = TinR * (1 - beta_H4) + TinP * beta_H4 # 出风露点（除湿量） ## 处理侧 Hdiff_mu = beta_H1 * RinP ** beta_H2 * EXP(-beta_H3 / T_avg) / 1000 # kg水蒸气/kg干空气 HoutP_mu = HinP - Hdiff_mu DoutP_mu = get_Dew_from_HumRatio(HoutP_mu,engine) ## 再生侧 HoutR_mu = HinR + Hdiff_mu * (FP / FR) DoutR_mu = get_Dew_from_HumRatio(HoutR_mu,engine) # 出风温度 # 处理侧 Q_latent = Hdiff_mu * cls.CONSTANT['h_ads'] # Kj/kg 潜热 Q_sensible = beta_Q1 * (TinR - TinP) # Kj/kg 显热（影响升焓的部分） Q = (Q_latent + Q_sensible) * FP # Kj ToutP_mu = TinP + Q / (FP * cls.CONSTANT['c_p_air']) # 再生侧 ToutR_mu = TinR - Q / (FR * cls.CONSTANT['c_p_air']) return { 'ToutP':ToutP_mu,'HoutP':HoutP_mu,'DoutP':DoutP_mu, 'ToutR':ToutR_mu,'HoutR':HoutR_mu,'DoutR':DoutR_mu, } @classmethod def prior(cls,name): param = { 'beta_Q1': pm.HalfNormal(f'{name}_beta_Q1',sigma=10), 'beta_H1': pm.HalfNormal(f'{name}_beta_H1',sigma=10), 'beta_H2': pm.HalfNormal(f'{name}_beta_H2',sigma=10), 'beta_H3': pm.HalfNormal(f'{name}_beta_H3',sigma=10), 'beta_H4': pm.Uniform(f'{name}_beta_H4',lower=0,upper=1), } return param class WheelS3(BaseComponents): def __init__(self): super().__init__() @classmethod def model( cls, TinP,HinP,FP, TinR,HinR,FR, TinC,HinC,FC, engine : str, param : dict, ): FUNC = cls.get_func_by_engine(engine) EXP = FUNC['EXP'] beta_P1 = param['beta_P1'] beta_P2 = param['beta_P2'] beta_P3 = param['beta_P3'] beta_P4 = param['beta_P4'] beta_P5 = param['beta_P5'] beta_C1 = param['beta_C1'] beta_C2 = param['beta_C2'] beta_C3 = param['beta_C3'] beta_C4 = param['beta_C4'] RinP = get_RH_from_Tdb_and_Hr(TinP,HinP,engine) RinC = get_RH_from_Tdb_and_Hr(TinC,HinC,engine) # 处理侧 HdiffP = (beta_P1 * RinP**beta_P4 * HinP * TinR * EXP(-beta_P5 * FP) + beta_P2)/1000 WdiffP = HdiffP * FP HoutP = HinP - HdiffP DoutP = get_Dew_from_HumRatio(HoutP,engine) Q_lat_P = WdiffP * cls.CONSTANT['h_ads'] Q_sen_P = beta_P3 * (TinR - TinP) * FP #TODO TdiffP = (Q_lat_P + Q_sen_P) / (FP * cls.CONSTANT['c_p_air']) ToutP = TinP + TdiffP # 冷却侧 TdiffC = beta_C1 * EXP(-beta_C2 * EXP(-beta_C3 * (TinR - TinC))) * EXP(-beta_C4 * FC) ToutC = TinC + TdiffC HdiffC = (beta_P1 * RinC**beta_P4 * HinC * TinR * EXP(-beta_P5 * FC) + beta_P2)/1000 WdiffC = HdiffC * FC HoutC = HinC - HdiffC DoutC = get_Dew_from_HumRatio(HoutC,engine) Q_total_C = TdiffC * FC * cls.CONSTANT['c_p_air'] # 再生侧 WdiffR = WdiffP + WdiffC HoutR = (HinR * FR + WdiffR) / FR DoutR = get_Dew_from_HumRatio(HoutR,engine) Q_total_R = Q_lat_P + Q_sen_P + Q_total_C TdiffR = Q_total_R / (FR * cls.CONSTANT['c_p_air']) ToutR = TinR - TdiffR return { 'ToutP':ToutP,'HoutP':HoutP,'DoutP':DoutP,'FP':FP, 'ToutR':ToutR,'HoutR':HoutR,'DoutR':DoutR,'FR':FR, 'ToutC':ToutC,'HoutC':HoutC,'DoutC':DoutC,'FC':FC, } @classmethod def prior(cls,name): param = { 'beta_P1': pm.TruncatedNormal(f'{name}_beta_P1',mu=5,sigma=10,initval=5,lower=0), 'beta_P2': pm.TruncatedNormal(f'{name}_beta_P2',mu=0.5,sigma=1,initval=0.02,lower=0), 'beta_P3': pm.TruncatedNormal(f'{name}_beta_P3',mu=1,sigma=2,initval=1.5,lower=0), 'beta_P4': pm.TruncatedNormal(f'{name}_beta_P4',mu=1,sigma=0.3,initval=1,lower=0), 'beta_P5': pm.TruncatedNormal(f'{name}_beta_P5',mu=5,sigma=2,initval=5,lower=0), 'beta_C1': pm.TruncatedNormal(f'{name}_beta_C1',mu=60,sigma=10,initval=60,lower=10), 'beta_C2': pm.TruncatedNormal(f'{name}_beta_C2',mu=30,sigma=10,initval=30,lower=1), 'beta_C3': pm.TruncatedNormal(f'{name}_beta_C3',mu=0.05,sigma=0.1,initval=0.05,lower=0), 'beta_C4': pm.TruncatedNormal(f'{name}_beta_C4',mu=1,sigma=1,initval=1,lower=0), } return param # class WheelS3(BaseComponents): # # 需要校准的输出 ToutP DoutP ToutR/ToutC # def __init__(self): # super().__init__() # @classmethod # def model( # cls, # TinP,HinP,FP, # TinR,HinR,FR, # TinC,HinC,FC, # engine : str, # param : dict, # ): # FUNC = cls.get_func_by_engine(engine) # EXP = FUNC['EXP'] # RinP = get_RH_from_Tdb_and_Hr(TinP,HinP,engine) # RinC = get_RH_from_Tdb_and_Hr(TinC,HinC,engine) # beta_Q1 = param['beta_Q1'] # beta_Q2 = param['beta_Q2'] # # beta_Q3 = param['beta_Q3'] # beta_H1 = param['beta_H1'] # beta_H2 = param['beta_H2'] # beta_H3 = param['beta_H3'] # beta_H4 = param['beta_H4'] # beta_H5 = param['beta_H5'] # # 转轮的温度 # T_avg = TinR * beta_H4 + TinC * (1 - beta_H4) # # 除湿量 # ## 处理侧 # H_diff_P = beta_H1 * RinP ** beta_H2 * EXP(-beta_H3 / T_avg) # 描述吸附 kg水蒸气/kg干空气 # W_diff_P = H_diff_P * FP # kg水蒸气 # HoutP = HinP - H_diff_P # # 冷却测 # # !转轮的处理侧和冷却侧都在除湿，由于冷却侧出来的空气的温度非常高，所以湿度很难测准 # # !因此冷却侧的除湿量需要假定，这里假定和处理侧参数一致 # H_diff_C = beta_H1 * RinC ** beta_H2 * EXP(-beta_H3 / T_avg) * beta_H5 # W_diff_C = H_diff_C * FC # HoutC = HinC - H_diff_C # ## 再生侧 # HoutR = (HinR * FR + W_diff_P + W_diff_C) / FR # kg水蒸气/kg干空气 # # 露点 # DoutP = get_Dew_from_HumRatio(HoutP,engine) # DoutC = get_Dew_from_HumRatio(HoutC,engine) # DoutR = get_Dew_from_HumRatio(HoutR,engine) # # 热量 # Q_lat_C = W_diff_C * cls.CONSTANT['h_ads'] # Kj 冷却侧潜热 # Q_lat_P = W_diff_P * cls.CONSTANT['h_ads'] # Kj 处理侧潜热 # Q_lat_total = Q_lat_C + Q_lat_P # Kj 总潜热 # Q_sen_C = beta_Q1 * (TinR - TinC) # Kj 冷却侧显热 # # Q_sen_P = beta_Q1 * (TinR - beta_Q2 * (TinR - TinC) - TinP) # Kj 处理侧显热 # Q_sen_P = beta_Q1 * (TinR - TinP) * beta_Q2 # Q_sen_Total = Q_sen_C + Q_sen_P # Kj 总显热 # # 温度变化 # ToutP = TinP + (Q_lat_P + Q_sen_P) / (FP * cls.CONSTANT['c_p_air']) # ToutC = TinC + (Q_lat_C + Q_sen_C) / (FC * cls.CONSTANT['c_p_air']) # ToutR = TinR - (Q_lat_total + Q_sen_Total) / (FR * cls.CONSTANT['c_p_air']) # return { # 'ToutP':ToutP,'HoutP':HoutP,'DoutP':DoutP, # 'ToutR':ToutR,'HoutR':HoutR,'DoutR':DoutR, # 'ToutC':ToutC,'HoutC':HoutC,'DoutC':DoutC, # } # @classmethod # def prior(cls,name): # param = { # 'beta_Q1': pm.HalfNormal(f'{name}_beta_Q1',sigma=1,initval=1), # 'beta_Q2': pm.HalfNormal(f'{name}_beta_Q2',sigma=0.1,initval=0.01), # 'beta_H1': pm.HalfNormal(f'{name}_beta_H1',sigma=1,initval=0.01), # 'beta_H2': pm.HalfNormal(f'{name}_beta_H2',sigma=1,initval=0.01), # 'beta_H3': pm.HalfNormal(f'{name}_beta_H3',sigma=20,initval=100), # 'beta_H4': pm.Uniform(f'{name}_beta_H4',lower=0,upper=1,initval=0.7), # # 'beta_H5': pm.TruncatedNormal(f'{name}_beta_H5',mu=5,sigma=2,lower=1,initval=5), # 'beta_H5':pm.HalfNormal(f'{name}_beta_H5',sigma=1,initval=0.01) # } # return param