add ui out put value test

idaes/models_extra/temperature_swing_adsorption/tests/test_fixed_bed_tsa0d_ui.py

@@ -1,12 +1,16 @@
 import pytest
 import logging
+import pandas as pd
 from pyomo.environ import check_optimal_termination
+from pyomo.environ import value
+from idaes.models_extra.temperature_swing_adsorption.util import tsa_summary
 from idaes.models_extra.temperature_swing_adsorption.fixed_bed_tsa0d_ui import (
     export_to_ui,
     build,
     initialize,
     solve,
 )
+from idaes.core.util.tables import stream_table_dataframe_to_string
 
 _log = logging.getLogger(__name__)
 
@@ -42,3 +46,65 @@ def test_default_build_options():
     for key, val in ui.fs_exp.build_options.items():
         assert default_build_options[key] == val.value
     assert True
+
+
+@pytest.mark.integration
+def test_ui_output():
+    """test ui data"""
+    # get model options from UI export to ui
+    ui_model_options = export_to_ui()
+    build_options = ui_model_options.fs_exp.build_options
+
+    # build and solve model
+    m = build(build_options=build_options)
+    initialize(m.fs)
+    solve(m.fs)
+
+    # base on UI output build data frame
+    var_dict = m.fs.tsa.get_var_dict()
+    ui_df = tsa_summary(m.fs.tsa)
+
+    # base on jupyter notebook example data, build data frame
+    jupyter_tsa_model_output_data = {
+        "Adsorption temperature [K]": 310.00,
+        "Desorption temperature [K]": 430.00,
+        "Heating temperature [K]": 440.00,
+        "Cooling temperature [K]": 300.00,
+        "Column diameter [m]": 0.030000,
+        "Column length [m]": 1.2000,
+        "Column volume [m3]": 0.00084823,
+        "CO2 mole fraction at feed [%]": 12.000,
+        "Feed flow rate [mol/s]": 0.0096000,
+        "Feed velocity [m/s]": 0.50008,
+        "Minimum fluidization velocity [m/s]": 1.5207,
+        "Time of heating step [h]": 0.37030,
+        "Time of cooling step [h]": 0.20826,
+        "Time of pressurization step [h]": 0.0051098,
+        "Time of adsorption step [h]": 0.25221,
+        "Cycle time [h]": 0.83588,
+        "Purity [-]": 0.90219,
+        "Recovery [-]": 0.89873,
+        "Productivity [kg CO2/ton/h]": 84.085,
+        "Specific energy [MJ/kg CO2]": 3.6532,
+        "Heat duty per bed [MW]": 5.1244e-05,
+        "Heat duty total [MW]": 0.00016646,
+        "Pressure drop [Pa]": 5263.6,
+        "Number of beds": 3.2484,
+        "CO2 captured in one cycle per bed [kg/cycle]": 0.042210,
+        "Cycles per year": 10480.0,
+        "Total CO2 captured per year [tonne/year]": 1.4369,
+        "Amount of flue gas processed per year [Gmol/year]": 0.00030275,
+        "Amount of flue gas processed per year (target) [Gmol/year]": 0.00030275,
+        "Amount of CO2 to atmosphere [mol/s]": 0.00011667,
+        "Concentration of CO2 emitted to atmosphere [ppm]": 13803.0,
+    }
+
+    # build jupyter notebook data frame
+    jupyter_df = pd.DataFrame.from_dict(
+        jupyter_tsa_model_output_data, orient="index", columns=["Value"]
+    )
+
+    # compare data frame string
+    jupyter_df_string = stream_table_dataframe_to_string(jupyter_df)
+    ui_df_string = stream_table_dataframe_to_string(ui_df)
+    assert jupyter_df_string == ui_df_string