From b746ac84346d72f38670717817de72be0b4e0848 Mon Sep 17 00:00:00 2001 From: u0169319 Date: Tue, 3 Dec 2024 13:44:24 +0100 Subject: [PATCH] Starting last part of validation process and restructure --- .../Sandbox/Sandbox.py | 8 +- .../Three_buildings/Auditorium/auditorium.py | 262 +- .../Auditorium/auditorium_naomi.py | 89 + .../Auditorium/auditorium_switched.csv | 8761 +++++++++++++++++ .../Auditorium/switch_columns.py | 19 + .../Office/office_switched.csv | 8761 +++++++++++++++++ .../Three_buildings/Office/switch_columns.py | 19 + .../Swimming pool/swimming_pool.py | 2 +- .../Swimming pool/swimmingpool_switched.csv | 8761 +++++++++++++++++ .../Swimming pool/switch_columns.py | 20 + 10 files changed, 26510 insertions(+), 192 deletions(-) create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_naomi.py create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_switched.csv create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/switch_columns.py create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/office_switched.csv create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/switch_columns.py create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimmingpool_switched.csv create mode 100644 GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/switch_columns.py diff --git a/GHEtool/Validation/short_term_effects_validation/Sandbox/Sandbox.py b/GHEtool/Validation/short_term_effects_validation/Sandbox/Sandbox.py index 0946a0ab..c2773be0 100644 --- a/GHEtool/Validation/short_term_effects_validation/Sandbox/Sandbox.py +++ b/GHEtool/Validation/short_term_effects_validation/Sandbox/Sandbox.py @@ -130,7 +130,7 @@ def Sandbox(): fig = plt.figure() ax = fig.add_subplot(111) # set axes labelsv - ax.set_xlabel(r"Time (year)") + ax.set_xlabel(r"Time (hours)") ax.set_ylabel(r"Temperature ($^\circ C$)") ax.yaxis.label.set_color(plt.rcParams["axes.labelcolor"]) ax.xaxis.label.set_color(plt.rcParams["axes.labelcolor"]) @@ -140,7 +140,7 @@ def Sandbox(): ax.step(time_array, df_mod_Tb[:8760], "g-", where="post", lw=1, label="Tb mod") ax.step(time_array, Tf_L4[:8760], "b-", where="post", lw=1, label="Tf L4") ax.step(time_array, Tf_L4_ste[:8760], "b-", linestyle="dashed", where="post", lw=1, label="Tf incl. ste") - ax.step(time_array, Tf_mod, "g-", where="post", lw=1, label="Tf mod dynamic") + ax.step(time_array, Tf_mod, "m-", where="post", lw=1, label="Tf mod dynamic") ax.step(time_array, Tf_exp, "r-", where="post", lw=1, label="Tf experimental") ax.set_xticks(range(0, 52 + 1, 5)) @@ -154,13 +154,13 @@ def Sandbox(): plt.figure("PVT versus PV") nb_subplots = 2 ax1 = plt.subplot(nb_subplots, 1, 1) - ax1.plot(time_array, DTf_mod_a, label='mod dyn', color='g') + ax1.plot(time_array, DTf_mod_a, label='mod dyn', color='m') ax1.plot(time_array, DTf_L4_a, label='L4', color='b') ax1.plot(time_array, DTf_L4_ste_a, label='L4 ste', color= "b", linestyle="dashed",) ax1.legend() ax1.grid() ax2 = plt.subplot(nb_subplots, 1, 2, sharex=ax1) - ax2.plot(time_array, DTf_mod_r, label='mod dyn', color='g') + ax2.plot(time_array, DTf_mod_r, label='mod dyn', color='m') ax2.plot(time_array, DTf_L4_r, label='L4', color='b') ax2.plot(time_array, DTf_L4_ste_r, label='L4 ste', color= "b", linestyle="dashed",) ax2.legend() diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium.py b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium.py index 1bad3ae5..4f101ae0 100644 --- a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium.py +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium.py @@ -24,194 +24,82 @@ from GHEtool import * +plot_load = True def Auditorium(): - ## To do: - # check load (ground) ghetool is same as input to modelica - # put same pipe and grout vol. heat cap in modelica - # size this model with modelica (based on average fluid temp) - - num_pipes = [1, 2] - gradients = [0, 1, 2] - - plot_load = False - - for pipes in num_pipes: - for grad in gradients: - - # Rb calculated by tool - # initiate ground, fluid and pipe data - ground_data = GroundTemperatureGradient(k_s=3, T_g=10, volumetric_heat_capacity= 2.4 * 10**6, gradient=grad) - fluid_data = FluidData(0.2, 0.568, 998, 4180, 1e-3) - pipe_data = MultipleUTube(1, 0.015, 0.02, 0.4, 0.05, pipes) - - # initiate borefield - borefield = Borefield() - - # set ground data in borefield - borefield.set_ground_parameters(ground_data) - borefield.set_fluid_parameters(fluid_data) - borefield.set_pipe_parameters(pipe_data) - borefield.create_rectangular_borefield(5, 4, 6, 6, 100, 4, 0.075) - #borefield.set_Rb(0.12) - - # set temperature bounds - borefield.set_max_avg_fluid_temperature(17) - borefield.set_min_avg_fluid_temperature(3) - - # load the hourly profile - load = HourlyGeothermalLoad(simulation_period=20) - load.load_hourly_profile(os.path.join(os.path.dirname(__file__), 'auditorium.csv'), header=True, separator=";", - decimal_seperator=".", col_extraction=1, - col_injection=0) - borefield.load = load - - SEER = 20 - SCOP = 4 - - # load hourly heating and cooling load and convert it to geothermal loads - primary_geothermal_load = HourlyGeothermalLoad(simulation_period=load.simulation_period) - primary_geothermal_load.set_hourly_injection_load(load.hourly_injection_load.copy() * (1 + 1 / SEER)) - primary_geothermal_load.set_hourly_extraction_load(load.hourly_extraction_load.copy() * (1 - 1 / SCOP)) - # set geothermal load - borefield.load = primary_geothermal_load - - if plot_load: - #Plotting Load - heating = load.hourly_extraction_load.copy() * (1 + 1 / SCOP) - cooling = load.hourly_injection_load.copy() * (1 + 1 / SEER) - t = [i for i in range(8760)] - fig = plt.subplots(figsize =(12, 8)) - plt.plot(t, heating, color ='orange', lw=2, label ='Heating') - plt.plot(t, cooling, color ='b', lw=2, label ='Cooling') - plt.xlabel('Time [h]', fontsize = 18) - plt.ylabel('Load [kW]', fontsize = 18) - plt.legend(fontsize = 16) - plt.title('Profile 1: Yearly geothermal load profile auditorium building', fontsize = 22) - plt.show() - - - options = {'nSegments': 12, - 'disp': False, - 'profiles': True, - 'method': 'equivalent' - } - - borefield.set_options_gfunction_calculation(options) - - # according to L4 - L4_start = time.time() - depth_L4 = borefield.size(100, L4_sizing=True) - Rb_L4 = borefield.Rb - L4_stop = time.time() - Tf_L4 = borefield.results.peak_injection - Tb_L4 = borefield.results.Tb - - # initiate borefield - borefield = Borefield() - - # set ground data in borefield - borefield.set_ground_parameters(ground_data) - borefield.set_fluid_parameters(fluid_data) - borefield.set_pipe_parameters(pipe_data) - borefield.create_rectangular_borefield(5, 4, 6, 6, 100, 4, 0.075) - #borefield.set_Rb(0.12) - # set temperature bounds - borefield.set_max_avg_fluid_temperature(17) - borefield.set_min_avg_fluid_temperature(3) - - # load the hourly profile - borefield.load = primary_geothermal_load - # Addidional input data needed for short-term model - rho_cp_grout = 3800000.0 - rho_cp_pipe = 2150000.0 - - # Sample dictionary with short-term effect parameters - short_term_effects_parameters = { - 'rho_cp_grout': rho_cp_grout, - 'rho_cp_pipe': rho_cp_pipe, - } - - options = {'nSegments': 12, - 'disp': False, - 'profiles': True, - 'method': 'equivalent', - 'cylindrical_correction': True, - 'short_term_effects': True, - 'ground_data': ground_data, - 'fluid_data': fluid_data, - 'pipe_data': pipe_data, - 'borefield': borefield, - 'short_term_effects_parameters': short_term_effects_parameters, - } - - borefield.set_options_gfunction_calculation(options) - - # according to L4 including short-term effects - L4_ste_start = time.time() - depth_L4_ste = borefield.size(100, L4_sizing=True) - Rb_L4_ste = borefield.Rb - L4_ste_stop = time.time() - Tf_L4_ste = borefield.results.peak_injection - Tb_L4_ste = borefield.results.Tb - - if pipes == 1: - print(f"Results for Single-U-tube boreholes and gradient equal to {grad} K/100m:") - else: - print(f"Results for Double-U-tube boreholes and gradient equal to {grad} K/100m:") - print( - f"The sizing according to L4 has a depth of {depth_L4:.2f}m (using dynamic Rb* of {Rb_L4:.3f})") - print( - f"The sizing according to L4 (including short-term effects) has a depth of {depth_L4_ste:.2f}m (using dynamic Rb* of {Rb_L4_ste:.3f})") - print( - f"Time needed for L4-sizing is {L4_stop-L4_start:.2f}s (using dynamic Rb*)") - print( - f"Time needed for L4-sizing including short-term effect is {L4_ste_stop-L4_ste_start:.2f}s (using dynamic Rb*)") - - - """ - # Load modelica data and experimental data for plotting - # import data - df_st = pd.read_csv(os.path.join(os.path.dirname(__file__), 'Modelica_Tf_static.csv'), header=0, decimal=".") - df_dyn = pd.read_csv(os.path.join(os.path.dirname(__file__), 'Modelica_Tf_dynamic.csv'), header=0, decimal=".") - - # set data - Tf_mod_st = np.array(df_st.iloc[:, 0]) - Tf_mod_dyn = np.array(df_dyn.iloc[:, 0]) - - ### Plotting figures - legend = True - # make a time array - time_array = borefield.load.time_L4 / 3600 - time_array = time_array[:8759] - print(time_array) - # plt.rc('figure') - # create new figure and axes if it not already exits otherwise clear it. - fig = plt.figure() - ax = fig.add_subplot(111) - # set axes labelsv - ax.set_xlabel(r"Time (year)") - ax.set_ylabel(r"Temperature ($^\circ C$)") - ax.yaxis.label.set_color(plt.rcParams["axes.labelcolor"]) - ax.xaxis.label.set_color(plt.rcParams["axes.labelcolor"]) - - # plot Temperatures - ax.step(time_array, Tb_L4[:8759], "k-", where="post", lw=1.5, label="Tb") - ax.step(time_array, Tb_L4_ste[:8759], "k-", where="post", lw=1.5, label="Tb incl. ste") - ax.step(time_array, Tf_L4[:8759], "b-", where="post", lw=1, label="Tf") - ax.step(time_array, Tf_L4_ste[:8759], "r-", where="post", lw=1, label="Tf incl. ste") - ax.step(time_array, Tf_mod_st[:8759], "c-", where="post", lw=1, label="Tf mod static") - ax.step(time_array, Tf_mod_dyn[:8759], "g-", where="post", lw=1, label="Tf mod dynamic") - ax.set_xticks(range(0, 52 + 1, 5)) - - # Plot legend - if legend: - ax.legend() - ax.set_xlim(left=0, right=52) - plt.show() - - """ - #plt.show() - + # Rb calculated by tool + # initiate ground, fluid and pipe data + ground_data = GroundTemperatureGradient(k_s=3, T_g=10, volumetric_heat_capacity= 2.4 * 10**6, gradient=2) + fluid_data = FluidData(0.2, 0.568, 998, 4180, 1e-3) + pipe_data = MultipleUTube(1, 0.015, 0.02, 0.4, 0.05, 1) + + # initiate borefield + borefield = Borefield() + + # set ground data in borefield + borefield.set_ground_parameters(ground_data) + borefield.set_fluid_parameters(fluid_data) + borefield.set_pipe_parameters(pipe_data) + borefield.create_rectangular_borefield(5, 4, 6, 6, 100, 4, 0.075) + #borefield.set_Rb(0.12) + + # set temperature bounds + borefield.set_max_avg_fluid_temperature(17) + borefield.set_min_avg_fluid_temperature(3) + + # load the hourly profile + load = HourlyGeothermalLoad(simulation_period=20) + load.load_hourly_profile(os.path.join(os.path.dirname(__file__), 'auditorium.csv'), header=True, separator=";", + decimal_seperator=".", col_extraction=1, + col_injection=0) + borefield.load = load + + SEER = 20 + SCOP = 4 + + # load hourly heating and cooling load and convert it to geothermal loads + primary_geothermal_load = HourlyGeothermalLoad(simulation_period=load.simulation_period) + primary_geothermal_load.set_hourly_injection_load(load.hourly_injection_load.copy() * (1 + 1 / SEER)) + primary_geothermal_load.set_hourly_extraction_load(load.hourly_extraction_load.copy() * (1 - 1 / SCOP)) + # set geothermal load + borefield.load = primary_geothermal_load + + if plot_load: + #Plotting Load + heating = load.hourly_extraction_load.copy() * (1 + 1 / SCOP) + cooling = load.hourly_injection_load.copy() * (1 + 1 / SEER) + t = [i for i in range(8760)] + fig = plt.subplots(figsize =(12, 8)) + plt.plot(t, heating, color ='orange', lw=2, label ='Heating') + plt.plot(t, cooling, color ='b', lw=2, label ='Cooling') + plt.xlabel('Time [h]', fontsize = 18) + plt.ylabel('Load [kW]', fontsize = 18) + plt.legend(fontsize = 16) + plt.title('Profile 1: Yearly geothermal load profile auditorium building', fontsize = 22) + plt.show() + + + options = {'nSegments': 12, + 'disp': False, + 'profiles': True, + 'method': 'equivalent' + } + + borefield.set_options_gfunction_calculation(options) + + # according to L4 + L4_start = time.time() + depth_L4 = borefield.size(100, L4_sizing=True) + borefield.print_temperature_profile(plot_hourly=True) + Rb_L4 = borefield.Rb + L4_stop = time.time() + Tf_L4 = borefield.results.peak_injection #you can use this for comparing different scenario's of fluid temperature on one plot + Tb_L4 = borefield.results.Tb + + print( + f"The sizing according to L4 has a depth of {depth_L4:.2f}m (using dynamic Rb* of {Rb_L4:.3f})") + print( + f"Time needed for L4-sizing is {L4_stop-L4_start:.2f}s (using dynamic Rb*)") + if __name__ == "__main__": # pragma: no cover Auditorium() diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_naomi.py b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_naomi.py new file mode 100644 index 00000000..f745a61f --- /dev/null +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_naomi.py @@ -0,0 +1,89 @@ +import os +import time + +import numpy as np +import pandas as pd + +import matplotlib.pyplot as plt + +from GHEtool import * + +plot_load = True + +def Auditorium(): + # Rb calculated by tool + # initiate ground, fluid and pipe data + ground_data = GroundTemperatureGradient(k_s=3, T_g=10, volumetric_heat_capacity= 2.4 * 10**6, gradient=2) + fluid_data = FluidData(0.2, 0.568, 998, 4180, 1e-3) + pipe_data = MultipleUTube(1, 0.015, 0.02, 0.4, 0.05, 1) + + # initiate borefield + borefield = Borefield() + + # set ground data in borefield + borefield.set_ground_parameters(ground_data) + borefield.set_fluid_parameters(fluid_data) + borefield.set_pipe_parameters(pipe_data) + borefield.create_rectangular_borefield(5, 4, 6, 6, 100, 4, 0.075) + #borefield.set_Rb(0.12) + + # set temperature bounds + borefield.set_max_avg_fluid_temperature(17) + borefield.set_min_avg_fluid_temperature(3) + + # load the hourly profile + load = HourlyGeothermalLoad(simulation_period=20) + load.load_hourly_profile(os.path.join(os.path.dirname(__file__), 'auditorium.csv'), header=True, separator=";", + decimal_seperator=".", col_extraction=1, + col_injection=0) + borefield.load = load + + SEER = 20 + SCOP = 4 + + # load hourly heating and cooling load and convert it to geothermal loads + primary_geothermal_load = HourlyGeothermalLoad(simulation_period=load.simulation_period) + primary_geothermal_load.set_hourly_injection_load(load.hourly_injection_load.copy() * (1 + 1 / SEER)) + primary_geothermal_load.set_hourly_extraction_load(load.hourly_extraction_load.copy() * (1 - 1 / SCOP)) + # set geothermal load + borefield.load = primary_geothermal_load + + if plot_load: + #Plotting Load + heating = load.hourly_extraction_load.copy() * (1 + 1 / SCOP) + cooling = load.hourly_injection_load.copy() * (1 + 1 / SEER) + t = [i for i in range(8760)] + fig = plt.subplots(figsize =(12, 8)) + plt.plot(t, heating, color ='orange', lw=2, label ='Heating') + plt.plot(t, cooling, color ='b', lw=2, label ='Cooling') + plt.xlabel('Time [h]', fontsize = 18) + plt.ylabel('Load [kW]', fontsize = 18) + plt.legend(fontsize = 16) + plt.title('Profile 1: Yearly geothermal load profile auditorium building', fontsize = 22) + plt.show() + + #options for g-function calculation, given to other package pygfunction (Massimo) + options = {'nSegments': 12, + 'disp': False, + 'profiles': True, + 'method': 'equivalent' + } + + borefield.set_options_gfunction_calculation(options) + + # according to L4 + L4_start = time.time() + depth_L4 = borefield.size(100, L4_sizing=True) + borefield.print_temperature_profile(plot_hourly=True) + Rb_L4 = borefield.Rb + L4_stop = time.time() + Tf_L4 = borefield.results.peak_injection #you can use this for comparing different scenario's of fluid temperature on one plot + Tb_L4 = borefield.results.Tb + + print( + f"The sizing according to L4 has a depth of {depth_L4:.2f}m (using dynamic Rb* of {Rb_L4:.3f})") + print( + f"Time needed for L4-sizing is {L4_stop-L4_start:.2f}s (using dynamic Rb*)") + +if __name__ == "__main__": # pragma: no cover + Auditorium() \ No newline at end of file diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_switched.csv b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_switched.csv new file mode 100644 index 00000000..37e7cf7b --- /dev/null +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/auditorium_switched.csv @@ -0,0 +1,8761 @@ +Heating,Cooling +9.241,0.0 +10.305,0.0 +11.171,0.0 +11.68,0.0 +11.907,0.0 +11.998,0.0 +11.893,0.0 +11.741,0.0 +31.481,0.0 +19.841,0.0 +21.697,0.0 +26.542,0.0 +20.843,0.0 +18.256,0.0 +17.67,0.0 +21.368,0.0 +20.542,0.0 +20.0,0.0 +0.787,0.0 +6.474,0.0 +8.876,0.0 +9.36,0.0 +9.497,0.0 +9.617,0.0 +9.816,0.0 +9.931,0.0 +9.962,0.0 +9.937,0.0 +9.752,0.0 +9.485,0.0 +9.255,0.0 +9.14,0.0 +29.885,0.0 +17.295,0.0 +14.762,0.0 +14.548,0.0 +12.946,0.0 +13.337,0.0 +11.763,0.0 +13.569,0.0 +13.853,0.0 +16.148,0.0 +0.0,0.0 +2.841,0.0 +5.185,0.0 +6.1,0.0 +6.433,0.0 +6.784,0.0 +7.183,0.0 +7.439,0.0 +7.593,0.0 +7.673,0.0 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new file mode 100644 index 00000000..8b8f6011 --- /dev/null +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Auditorium/switch_columns.py @@ -0,0 +1,19 @@ +import pandas as pd + +# Load the CSV file +input_file = r'GHEtool\Validation\short_term_effects_validation\Three_buildings\Auditorium\auditorium.csv' # Replace with your file path +output_file = 'auditorium_switched.csv' + +# Read the CSV file +df = pd.read_csv(input_file, sep=';') + +# Ensure there are exactly two columns +if len(df.columns) == 2: + # Swap the columns + df = df[df.columns[::-1]] + + # Save the modified CSV + df.to_csv(output_file, index=False) + print(f"Columns switched successfully! Saved as '{output_file}'.") +else: + print("Error: The CSV file does not have exactly two columns.") diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/office_switched.csv b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/office_switched.csv new file mode 100644 index 00000000..c658edc7 --- /dev/null +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/office_switched.csv @@ -0,0 +1,8761 @@ +Heating,Cooling +21.353,0.0 +30.121,0.0 +36.834,0.0 +41.075,0.0 +44.06,0.0 +45.663,0.0 +45.837,0.0 +193.703,0.0 +53.007,0.0 +29.305,0.0 +49.957,0.012 +50.584,0.512 +40.292,0.0 +39.883,0.0 +36.302,0.0 +39.433,0.0 +41.691,0.0 +38.878,0.0 +70.79,0.0 +1.419,0.0 +9.066,0.0 +25.504,0.0 +29.908,0.0 +31.846,0.0 +33.578,0.0 +34.676,0.0 +35.415,0.0 +35.769,0.0 +34.981,0.0 +33.613,0.0 +32.443,0.0 +32.038,0.0 +32.169,0.0 +30.091,0.0 +21.198,0.0 +12.703,0.0 +8.713,0.0 +10.509,0.0 +15.114,0.0 +19.052,0.0 +23.179,0.0 +26.504,0.0 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+170.795,0.0 +31.679,0.0 +16.2,0.0 +24.928,0.065 +22.91,0.69 +16.458,0.0 +15.059,0.0 +13.24,1.087 +14.039,5.718 +15.007,1.881 +14.374,0.0 +22.683,0.0 +0.288,0.0 +0.14,0.0 +0.582,0.0 +2.257,0.0 +10.093,0.0 diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/switch_columns.py b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/switch_columns.py new file mode 100644 index 00000000..92dc1b42 --- /dev/null +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Office/switch_columns.py @@ -0,0 +1,19 @@ +import pandas as pd + +# Load the CSV file +input_file = r'GHEtool\Validation\short_term_effects_validation\Three_buildings\Office\office.csv' # Replace with your file path +output_file = 'office_switched.csv' + +# Read the CSV file +df = pd.read_csv(input_file, sep=';') + +# Ensure there are exactly two columns +if len(df.columns) == 2: + # Swap the columns + df = df[df.columns[::-1]] + + # Save the modified CSV + df.to_csv(output_file, index=False) + print(f"Columns switched successfully! Saved as '{output_file}'.") +else: + print("Error: The CSV file does not have exactly two columns.") diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimming_pool.py b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimming_pool.py index 647f6045..436e1fa8 100644 --- a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimming_pool.py +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimming_pool.py @@ -33,7 +33,7 @@ def Swimming_pool(): # put same pipe and grout vol. heat cap in modelica # size this model with modelica (based on average fluid temp) - num_pipes = [1] + num_pipes = [2] gradients = [0, 1, 2] plot_load = False diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimmingpool_switched.csv b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/swimmingpool_switched.csv 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+346.5690255;0.0;147.6025491 +344.1260299;0.0;151.9073436 +356.2938903;0.0;156.2121381 +360.8428103;0.0;160.5169326 +365.3154311;0.0;160.5169326 +348.6161892;0.0;156.2121381 +359.9545932;0.0;151.9073436 +77.58885221;0.0;138.99296 diff --git a/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/switch_columns.py b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/switch_columns.py new file mode 100644 index 00000000..6b583f36 --- /dev/null +++ b/GHEtool/Validation/short_term_effects_validation/Three_buildings/Swimming pool/switch_columns.py @@ -0,0 +1,20 @@ +import pandas as pd + +# Load the CSV file +input_file = r'GHEtool\Validation\short_term_effects_validation\Three_buildings\Swimming pool\swimming_pool.csv' # Replace with your file path +output_file = 'swimmingpool_switched.csv' + +df = pd.read_csv(input_file, sep=';') + +# Ensure there are at least two columns +if len(df.columns) >= 2: + # Swap the first two columns while keeping others the same + cols = df.columns.tolist() + cols[0], cols[1] = cols[1], cols[0] # Swap the first two columns + df = df[cols] + + # Save the modified CSV with semicolon delimiter + df.to_csv(output_file, sep=';', index=False) + print(f"Columns switched successfully! Saved as '{output_file}'.") +else: + print("Error: The CSV file does not have at least two columns.")