Merge pull request #28 from zhieejhia93/compare-results-example

Demonstration on how to extract results from multiple runs and save in one CSV file
watts-dev · Mar 17, 2022 · 3f8b812 · 3f8b812
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diff --git a/examples/example1d_SAM_ParametricStudy/README.md b/examples/example1d_SAM_ParametricStudy/README.md
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+# Example1d - MOOSE/SAM Plugin
+
+## Purpose
+
+This example provides a demonstration on how to use WATTS to perform multiple runs and save selected outputs from all runs to a single '.csv' file for ease of comparison, post-processing, and visualization.
+
+## Code(s)
+
+- SAM
+
+## Keywords
+
+- Parametric study
+- Results extraction
+- Post-processing
+
+## File descriptions
+
+- [__example1d.py__](example1d.py): WATTS workflow for this example. This is the file to execute to run the problem described above.
+- [__sam_template__](sam_template): SAM templated input file.
+- [__results.csv__](results.csv): An example of CSV file that will be generated through running this example.
diff --git a/examples/example1d_SAM_ParametricStudy/example1d.py b/examples/example1d_SAM_ParametricStudy/example1d.py
@@ -0,0 +1,72 @@
+# SPDX-FileCopyrightText: 2022 UChicago Argonne, LLC
+# SPDX-License-Identifier: MIT
+
+"""
+This example demonstrates how to use WATTS to perform 
+multiple runs and extract selected results from the runs. 
+The demonstration includes an approach to save selected 
+results from different runs into a single CSV file for 
+ease of comparison, visualization, and post-processing.
+This demonstration uses SAM with a single PbCoreChannel
+with inlet and outlet boundary conditions. The input 
+power of the channel is varied. The simulation is run 
+as transient where the end time is varied to artificially
+create results of different lengths to show that the 
+output CSV file can accept columns of different lengths.
+"""
+
+from math import cos, pi
+import os
+import watts
+import pandas as pd
+from astropy.units import Quantity
+
+
+params = watts.Parameters()
+
+# Input parameters to template file
+
+params['He_inlet_temp'] = Quantity(600, "Celsius")  # 873.15 K
+params['He_outlet_temp'] = Quantity(850, "Celsius") # 1123.15 K
+params['He_cp'] = Quantity(4.9184126, "BTU/(kg*K)") # 5189.2 J/kg-K
+params['He_K'] =  0.32802   # W/m-K
+params['He_density'] = 3.8815   # kg/m3
+params['He_viscosity'] = 4.16e-5 # Pa.s
+params['He_Pressure'] = Quantity(1015.264164, "psi") # 7e6 Pa
+params['num_cool_pins'] = 1*6 + 2*6 + 6*2/2
+params['num_fuel_pins'] = 6 + 6 + 6 + 3*6 + 2*6/2 + 6/3
+params['Height_FC'] = Quantity(2000, "mm") # Automatically converts to 'm' for MOOSE and 'cm' for openmc
+params['Lattice_pitch'] = 2.0
+params['FuelPin_rad'] = 0.90 # cm
+params['cool_hole_rad'] = 0.60 # cm
+params['Coolant_channel_diam'] = (params['cool_hole_rad'] * 2)/100 # in m
+params['Graphite_thickness'] = (params['Lattice_pitch'] - params['FuelPin_rad'] - params['cool_hole_rad']) # cm
+
+params.show_summary(show_metadata=False, sort_by='key')
+
+# MOOSE Workflow
+moose_app_type = "SAM"
+app_dir = os.environ[moose_app_type.upper() + "_DIR"]
+
+power = [100_000, 250_000, 300_000, 400_000, 500_000] # Watts
+endtime = [50, 100, 100, 50, 50] # End time is varied to artificially create results of different lengths.
+results_dict = {} # Create empty dictionary
+for i in range(len(power)):
+    params['Tot_assembly_power'] = power[i]
+    params['endtime'] = endtime[i]
+
+    # Execute WATTS
+    moose_plugin = watts.PluginMOOSE(moose_app_type.lower() + '_template') # show all the output
+    moose_plugin.moose_exec = app_dir + "/" + moose_app_type.lower() + "-opt"
+    moose_result = moose_plugin(params)
+
+    # Add items to dictionary.
+    results_dict[f'time_{i+1}'] = moose_result.csv_data['time']
+    results_dict[f'max_Tcoolant_{i+1}'] = moose_result.csv_data['max_Tcoolant']
+    results_dict[f'max_Tw_{i+1}'] = moose_result.csv_data['max_Tw']
+
+# Store dictionary items as dataframe. Columns of unequal lengths are padded with NaN.
+df = pd.DataFrame({k: pd.Series(v) for k, v in results_dict.items()})
+
+# Sort column names alphabetically and save as CSV file
+df.sort_index(axis=1).to_csv('results.csv') 
diff --git a/examples/example1d_SAM_ParametricStudy/results.csv b/examples/example1d_SAM_ParametricStudy/results.csv
@@ -0,0 +1,17 @@
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