Remove Units from Report Strings

watertap/unit_models/MD/membrane_distillation_base.py

@@ -696,7 +696,7 @@ def _get_performance_contents(self, time_point=0):
         if hasattr(self, "width"):
             var_dict["Membrane Width"] = self.width
 
-        expr_dict["Average Solute Flux (LMH)"] = self.flux_mass_avg[time_point] * 1000
+        expr_dict["Average Solute Flux"] = self.flux_mass_avg[time_point] * 1000
         expr_dict["Thermal efficiency (%)"] = self.thermal_efficiency[time_point] * 100
         expr_dict["Effectiveness (%)"] = self.effectiveness[time_point] * 100
 

watertap/unit_models/coag_floc_model.py

@@ -1280,9 +1280,9 @@ def _get_performance_contents(self, time_point=0):
         t = time_point
         return {
             "vars": {
-                "Total Power Usage  (kW)": self.total_power[t],
-                "Rapid Mixing Power (kW)": self.rapid_mixing_power[t],
-                "Flocc Mixing Power (kW)": self.flocculation_power[t],
+                "Total Power Usage": self.total_power[t],
+                "Rapid Mixing Power": self.rapid_mixing_power[t],
+                "Flocc Mixing Power": self.flocculation_power[t],
             },
             "exprs": {},
             "params": {},

watertap/unit_models/crystallizer.py

@@ -769,22 +769,20 @@ def _get_stream_table_contents(self, time_point=0):
 
     def _get_performance_contents(self, time_point=0):
         var_dict = {}
-        var_dict["Operating Temperature (K)"] = self.temperature_operating
-        var_dict["Operating Pressure (Pa)"] = self.pressure_operating
-        var_dict["Magma density of solution (Kg/m**3)"] = self.dens_mass_magma
-        var_dict["Slurry density (Kg/m3)"] = self.dens_mass_slurry
+        var_dict["Operating Temperature"] = self.temperature_operating
+        var_dict["Operating Pressure"] = self.pressure_operating
+        var_dict["Magma density of solution"] = self.dens_mass_magma
+        var_dict["Slurry density"] = self.dens_mass_slurry
         var_dict["Heat requirement"] = self.work_mechanical[time_point]
-        var_dict["Crystallizer diameter (m)"] = self.diameter_crystallizer
-        var_dict["Magma circulation flow rate (m**3/s)"] = (
-            self.magma_circulation_flow_vol
-        )
+        var_dict["Crystallizer diameter"] = self.diameter_crystallizer
+        var_dict["Magma circulation flow rate"] = self.magma_circulation_flow_vol
         var_dict["Vol. frac. of solids in suspension, 1-E"] = (
             self.product_volumetric_solids_fraction
         )
         var_dict["Residence time"] = self.t_res
-        var_dict["Crystallizer minimum active volume (m**3)"] = self.volume_suspension
-        var_dict["Suspension height in crystallizer (m)"] = self.height_slurry
-        var_dict["Crystallizer height (m)"] = self.height_crystallizer
+        var_dict["Crystallizer minimum active volume"] = self.volume_suspension
+        var_dict["Suspension height in crystallizer"] = self.height_slurry
+        var_dict["Crystallizer height"] = self.height_crystallizer
 
         for j in self.config.property_package.solute_set:
             yield_mem_name = f"{j} yield (fraction)"

watertap/unit_models/electrodialysis_0D.py

@@ -2508,10 +2508,8 @@ def _get_stream_table_contents(self, time_point=0):
     def _get_performance_contents(self, time_point=0):
         return {
             "vars": {
-                "Total electrical power consumption(Watt)": self.power_electrical[
-                    time_point
-                ],
-                "Specific electrical power consumption (kW*h/m**3)": self.specific_power_electrical[
+                "Total electrical power consumption": self.power_electrical[time_point],
+                "Specific electrical power consumption": self.specific_power_electrical[
                     time_point
                 ],
                 "Current efficiency for deionzation": self.current_efficiency[

watertap/unit_models/electrodialysis_1D.py

@@ -2863,17 +2863,17 @@ def _get_performance_contents(self, time_point=0):
 
         return {
             "vars": {
-                "Total electrical power consumption(Watt)": self.diluate.power_electrical_x[
+                "Total electrical power consumption": self.diluate.power_electrical_x[
                     time_point, self.diluate.length_domain.last()
                 ],
-                "Specific electrical power consumption, ED stack (kW*h/m**3)": self.specific_power_electrical[
+                "Specific electrical power consumption, ED stack": self.specific_power_electrical[
                     time_point
                 ],
                 "Water recovery by mass": self.recovery_mass_H2O[time_point],
-                "Channel inlet velocity, diluate (m/s)": self.velocity_diluate[
+                "Channel inlet velocity, diluate": self.velocity_diluate[
                     time_point, self.diluate.length_domain.first()
                 ],
-                "Channel inlet velocity, concentrate (m/s)": self.velocity_concentrate[
+                "Channel inlet velocity, concentrate": self.velocity_concentrate[
                     time_point, self.diluate.length_domain.first()
                 ],
             },

watertap/unit_models/ion_exchange_0D.py

@@ -1450,7 +1450,7 @@ def _get_performance_contents(self, time_point=0):
         var_dict["Bed Depth"] = self.bed_depth
         var_dict["Col. Height to Diam. Ratio"] = self.col_height_to_diam_ratio
         var_dict["Bed Porosity"] = self.bed_porosity
-        var_dict["Service Flow Rate [BV/hr]"] = self.service_flow_rate
+        var_dict["Service Flow Rate"] = self.service_flow_rate
         var_dict["Bed Velocity"] = self.vel_bed
         var_dict["Resin Particle Diameter"] = self.resin_diam
         var_dict["Resin Bulk Density"] = self.resin_bulk_dens
@@ -1460,8 +1460,8 @@ def _get_performance_contents(self, time_point=0):
         var_dict["Peclet Number (bed)"] = self.N_Pe_bed
         var_dict["Peclet Number (particle)"] = self.N_Pe_particle
         if self.config.isotherm == IsothermType.langmuir:
-            var_dict["Total Resin Capacity [eq/L]"] = self.resin_max_capacity
-            var_dict["Usable Resin Capacity [eq/L]"] = self.resin_eq_capacity
+            var_dict["Total Resin Capacity"] = self.resin_max_capacity
+            var_dict["Usable Resin Capacity"] = self.resin_eq_capacity
             var_dict["Number Transfer Units"] = self.num_transfer_units
             var_dict["Total Mass Removed [equivalents]"] = self.mass_removed[target_ion]
             var_dict["Dimensionless Time"] = self.dimensionless_time

watertap/unit_models/nanofiltration_DSPMDE_0D.py

@@ -1579,9 +1579,7 @@
             time_point
         ].flow_vol_phase["Liq"]
 
-        expr_dict["Average Volumetric Flux (LMH)"] = (
-            self.flux_vol_water_avg[time_point] * 3.6e6
-        )
+        expr_dict["Average Volumetric Flux"] = self.flux_vol_water_avg[time_point]
         for j in self.config.property_package.component_list:
             expr_dict[f"Average Mole FLux of {j} "] = self.flux_mol_phase_comp_avg[
                 time_point, "Liq", j
@@ -1682,13 +1680,13 @@
             if self.feed_side.properties_in[time_point].is_property_constructed(
                 "pressure_osm_phase"
             ):
-                var_dict[f"Osmotic Pressure @ Bulk Feed, Inlet (Pa)"] = (
+                var_dict[f"Osmotic Pressure @ Bulk Feed, Inlet"] = (
                     self.feed_side.properties_in[time_point].pressure_osm_phase["Liq"]
                 )
             if self.feed_side.properties_out[time_point].is_property_constructed(
                 "pressure_osm_phase"
             ):
-                var_dict[f"Osmotic Pressure @ Bulk Feed, Outlet (Pa)"] = (
+                var_dict[f"Osmotic Pressure @ Bulk Feed, Outlet"] = (
                     self.feed_side.properties_out[time_point].pressure_osm_phase["Liq"]
                 )
 
@@ -1700,16 +1698,16 @@
                     io = "Outlet"
                     prop_feed = self.feed_side.properties_out[time_point]
 
-                var_dict[f"Osmotic Pressure @ Membrane Interface, {io} (Pa)"] = (
+                var_dict[f"Osmotic Pressure @ Membrane Interface, {io}"] = (
                     self.feed_side.properties_interface[
                         time_point, x
                     ].pressure_osm_phase["Liq"]
                 )
 
-                var_dict[f"Osmotic Pressure @ Permeate, {io} (Pa)"] = (
-                    self.permeate_side[time_point, x].pressure_osm_phase["Liq"]
-                )
-                expr_dict[f"Net Driving Pressure, {io} (Pa)"] = (
+                var_dict[f"Osmotic Pressure @ Permeate, {io}"] = self.permeate_side[
+                    time_point, x
+                ].pressure_osm_phase["Liq"]
+                expr_dict[f"Net Driving Pressure, {io}"] = (
                     prop_feed.pressure
                     - self.permeate_side[time_point, x].pressure
                     - (

watertap/unit_models/tests/test_electrodialysis_0D.py

@@ -256,10 +256,10 @@ def test_performance_contents(self, electrodialysis_cell1):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(3.06, rel=5e-3)
         assert value(
-            perform_dict["vars"]["Specific electrical power consumption (kW*h/m**3)"]
+            perform_dict["vars"]["Specific electrical power consumption"]
         ) == pytest.approx(0.202, rel=5e-3)
         assert value(
             perform_dict["vars"]["Current efficiency for deionzation"]
@@ -506,10 +506,10 @@ def test_performance_contents(self, electrodialysis_cell2):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(5.4, rel=5e-3)
         assert value(
-            perform_dict["vars"]["Specific electrical power consumption (kW*h/m**3)"]
+            perform_dict["vars"]["Specific electrical power consumption"]
         ) == pytest.approx(0.361, rel=5e-3)
         assert value(
             perform_dict["vars"]["Current efficiency for deionzation"]
@@ -735,10 +735,10 @@ def test_performance_contents(self, electrodialysis_cell3):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(5.41, rel=5e-3)
         assert value(
-            perform_dict["vars"]["Specific electrical power consumption (kW*h/m**3)"]
+            perform_dict["vars"]["Specific electrical power consumption"]
         ) == pytest.approx(0.361, rel=5e-3)
         assert value(
             perform_dict["vars"]["Current efficiency for deionzation"]
@@ -958,10 +958,10 @@ def test_performance_contents(self, EDcell):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(1.601, rel=5e-3)
         assert value(
-            perform_dict["vars"]["Specific electrical power consumption (kW*h/m**3)"]
+            perform_dict["vars"]["Specific electrical power consumption"]
         ) == pytest.approx(0.104, rel=5e-3)
         assert value(
             perform_dict["vars"]["Current efficiency for deionzation"]
@@ -1183,10 +1183,10 @@ def test_performance_contents(self, EDcell):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(1.4223, rel=5e-3)
         assert value(
-            perform_dict["vars"]["Specific electrical power consumption (kW*h/m**3)"]
+            perform_dict["vars"]["Specific electrical power consumption"]
         ) == pytest.approx(0.0921, rel=5e-3)
         assert value(
             perform_dict["vars"]["Current efficiency for deionzation"]
@@ -1408,10 +1408,10 @@ def test_performance_contents(self, EDcell):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(12.202, rel=5e-3)
         assert value(
-            perform_dict["vars"]["Specific electrical power consumption (kW*h/m**3)"]
+            perform_dict["vars"]["Specific electrical power consumption"]
         ) == pytest.approx(0.8157, rel=5e-3)
         assert value(
             perform_dict["vars"]["Current efficiency for deionzation"]

watertap/unit_models/tests/test_electrodialysis_1D.py

@@ -261,12 +261,10 @@ def test_performance_contents(self, electrodialysis_1d_cell1):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(3.0, rel=5e-3)
         assert value(
-            perform_dict["vars"][
-                "Specific electrical power consumption, ED stack (kW*h/m**3)"
-            ]
+            perform_dict["vars"]["Specific electrical power consumption, ED stack"]
         ) == pytest.approx(0.197, rel=5e-3)
         assert value(perform_dict["vars"]["Water recovery by mass"]) == pytest.approx(
             0.485, rel=5e-3
@@ -537,12 +535,10 @@ def test_performance_contents(self, electrodialysis_1d_cell2):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(5.83, rel=5e-3)
         assert value(
-            perform_dict["vars"][
-                "Specific electrical power consumption, ED stack (kW*h/m**3)"
-            ]
+            perform_dict["vars"]["Specific electrical power consumption, ED stack"]
         ) == pytest.approx(0.390, rel=5e-3)
         assert value(perform_dict["vars"]["Water recovery by mass"]) == pytest.approx(
             0.480, rel=5e-3
@@ -766,12 +762,10 @@ def test_performance_contents(self, electrodialysis_1d_cell3):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(5.837, rel=5e-3)
         assert value(
-            perform_dict["vars"][
-                "Specific electrical power consumption, ED stack (kW*h/m**3)"
-            ]
+            perform_dict["vars"]["Specific electrical power consumption, ED stack"]
         ) == pytest.approx(0.3896, rel=5e-3)
         assert value(perform_dict["vars"]["Water recovery by mass"]) == pytest.approx(
             0.480, rel=5e-3
@@ -995,12 +989,10 @@ def test_performance_contents(self, electrodialysis_1d_cell4):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(1.4735, rel=1e-3)
         assert value(
-            perform_dict["vars"][
-                "Specific electrical power consumption, ED stack (kW*h/m**3)"
-            ]
+            perform_dict["vars"]["Specific electrical power consumption, ED stack"]
         ) == pytest.approx(0.0955, rel=1e-3)
         assert value(perform_dict["vars"]["Water recovery by mass"]) == pytest.approx(
             0.4925, rel=1e-3
@@ -1209,12 +1201,10 @@ def test_performance_contents(self, electrodialysis_1d_cell5):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(1.3907, rel=1e-3)
         assert value(
-            perform_dict["vars"][
-                "Specific electrical power consumption, ED stack (kW*h/m**3)"
-            ]
+            perform_dict["vars"]["Specific electrical power consumption, ED stack"]
         ) == pytest.approx(0.0900, rel=1e-3)
         assert value(perform_dict["vars"]["Water recovery by mass"]) == pytest.approx(
             0.4928, rel=1e-3
@@ -1600,12 +1590,10 @@ def test_performance_contents(self, electrodialysis_1d_cell6):
         perform_dict = m.fs.unit._get_performance_contents()
         assert "vars" in perform_dict
         assert value(
-            perform_dict["vars"]["Total electrical power consumption(Watt)"]
+            perform_dict["vars"]["Total electrical power consumption"]
         ) == pytest.approx(12.904, rel=1e-3)
         assert value(
-            perform_dict["vars"][
-                "Specific electrical power consumption, ED stack (kW*h/m**3)"
-            ]
+            perform_dict["vars"]["Specific electrical power consumption, ED stack"]
         ) == pytest.approx(0.8627, rel=1e-3)
         assert value(perform_dict["vars"]["Water recovery by mass"]) == pytest.approx(
             0.4791, rel=1e-3