4 add validation based on optihorst

CHANGELOG.md

@@ -1,4 +1,15 @@
 - v0.1.0:
    - First implementation based on prior work
 - v0.1.1:
-  - Move plot_cycle function
+  - Move plot_cycle function
+- v0.2.0:
+  - Add LMTD MovingBoundary heat exchangers 
+  - Add VDI atlas methods for plate heat exchanger 
+  - Add scaling factor to TenCoefficientCompressor
+  - Add extrapolation option to TenCoefficientCompressor
+  - Improve warnings and parameters in TenCoefficientCompressor (eta_mech, T_sc)
+  - Add T_con_out as possible Input
+  - Automation is now with multiprocessing
+  - SDF saving is optional in automation
+  - Improve nominal design util
+  - Improve C10 regression generation, add .csv support for TenCoefficientCompressor

docs/jupyter_notebooks/e6_simple_heat_pump.ipynb

@@ -44,14 +44,14 @@
         {
             "cell_type": "markdown",
             "metadata": {},
-            "source": "As in the other example, we can specify save-paths,\nsolver settings and inputs to vary:\n"
+            "source": "As in the other example, we can specify save-paths,\nsolver settings and inputs to vary:\nNote that T_con can either be inlet or outlet, depending on the setting\nof `use_condenser_inlet`. Per default, we simulate the inlet, T_con_in\n"
         },
         {
             "cell_type": "code",
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "save_path = r\"D:\\00_temp\\simple_heat_pump\"\nT_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]\nT_con_in_ar = [30 + 273.15, 50 + 273.15, 70 + 273.15]\nn_ar = [0.3, 0.7, 1]\n"
+            "source": "save_path = r\"D:\\00_temp\\simple_heat_pump\"\nT_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]\nT_con_ar = [30 + 273.15, 50 + 273.15, 70 + 273.15]\nn_ar = [0.3, 0.7, 1]\n"
         },
         {
             "cell_type": "markdown",
@@ -63,7 +63,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "import logging\nlogging.basicConfig(level=\"INFO\")\n\nfrom vclibpy import utils\nsave_path_sdf, save_path_csv = utils.full_factorial_map_generation(\n    heat_pump=heat_pump,\n    save_path=save_path,\n    T_con_in_ar=T_con_in_ar,\n    T_eva_in_ar=T_eva_in_ar,\n    n_ar=n_ar,\n    use_multiprocessing=False,\n    save_plots=True,\n    m_flow_con=0.2,\n    m_flow_eva=0.9,\n    dT_eva_superheating=5,\n    dT_con_subcooling=0,\n)\n"
+            "source": "import logging\nlogging.basicConfig(level=\"INFO\")\n\nfrom vclibpy import utils\nsave_path_sdf, save_path_csv = utils.full_factorial_map_generation(\n    heat_pump=heat_pump,\n    save_path=save_path,\n    T_con_ar=T_con_ar,\n    T_eva_in_ar=T_eva_in_ar,\n    n_ar=n_ar,\n    use_condenser_inlet=use_condenser_inlet,\n    use_multiprocessing=False,\n    save_plots=True,\n    m_flow_con=0.2,\n    m_flow_eva=0.9,\n    dT_eva_superheating=5,\n    dT_con_subcooling=0,\n)\n"
         },
         {
             "cell_type": "markdown",
@@ -99,19 +99,19 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "import matplotlib.pyplot as plt\nx_name = \"n in - (Relative compressor speed)\"\ny_name = \"COP in - (Coefficient of performance)\"\nplt.scatter(df[x_name], df[y_name])\nplt.ylabel(y_name)\nplt.xlabel(x_name)\nplt.show()\n"
+            "source": "import matplotlib.pyplot as plt\nx_name = \"n in - (Relative compressor speed)\"\ny_name = \"COP in - (Coefficient of performance)\"\nplt.scatter(df[x_name], df[y_name], s=20)\nplt.ylabel(y_name)\nplt.xlabel(x_name)\nplt.show()\n"
         },
         {
             "cell_type": "markdown",
             "metadata": {},
-            "source": "Looking at the results, we see that a higher frequency often leads to lower COP values.\nHowever, other inputs (temperatures) have a greater impact on the COP.\nWe can also use existing 3D-plotting scripts in vclibpy to analyze the\ndependencies. For this, we need the .sdf file. In the sdf, the field names are without\nthe unit and description, as those are accessible in the file-format in other columns.\n"
+            "source": "Looking at the results, we see that a higher frequency often leads to lower COP values.\nHowever, other inputs (temperatures) have a greater impact on the COP.\nWe can also use existing 3D-plotting scripts in vclibpy to analyze the\ndependencies. For this, we need the .sdf file. In the sdf, the field names are without\nthe unit and description, as those are accessible in the file-format in other columns.\nDepending on whether we varied the inlet or outlet, we have to specify the correct name.\n"
         },
         {
             "cell_type": "code",
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "from vclibpy.utils.plotting import plot_sdf_map\nplot_sdf_map(\n    filepath_sdf=save_path_sdf,\n    nd_data=\"COP\",\n    first_dimension=\"T_eva_in\",\n    second_dimension=\"T_con_in\",\n    fluids=[\"Propane\"],\n    flowsheets=[\"Standard\"]\n)\n"
+            "source": "from vclibpy.utils.plotting import plot_sdf_map\nplot_sdf_map(\n    filepath_sdf=save_path_sdf,\n    nd_data=\"COP\",\n    first_dimension=\"T_eva_in\",\n    second_dimension=\"T_con_in\" if use_condenser_inlet else \"T_con_out\",\n    fluids=[\"Propane\"],\n    flowsheets=[\"Standard\"]\n)\n"
         }
     ],
     "metadata": {

docs/jupyter_notebooks/e7_vapor_injection.ipynb

@@ -63,7 +63,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "save_path = r\"D:\\00_temp\\vapor_injection\"\nT_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]\nT_con_in_ar = [30 + 273.15, 50 + 273.15, 60 + 273.15]\nn_ar = [0.3, 0.7, 1]\n"
+            "source": "save_path = r\"D:\\00_temp\\vapor_injection\"\nT_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]\nT_con_ar = [30 + 273.15, 50 + 273.15, 60 + 273.15]\nn_ar = [0.3, 0.7, 1]\n"
         },
         {
             "cell_type": "markdown",
@@ -75,7 +75,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "import logging\nlogging.basicConfig(level=\"INFO\")\n\nfrom vclibpy import utils\nutils.full_factorial_map_generation(\n    heat_pump=heat_pump,\n    save_path=save_path,\n    T_con_in_ar=T_con_in_ar,\n    T_eva_in_ar=T_eva_in_ar,\n    n_ar=n_ar,\n    use_multiprocessing=False,\n    save_plots=True,\n    m_flow_con=0.2,\n    m_flow_eva=0.9,\n    dT_eva_superheating=5,\n    dT_con_subcooling=0,\n)\n"
+            "source": "import logging\nlogging.basicConfig(level=\"INFO\")\n\nfrom vclibpy import utils\nutils.full_factorial_map_generation(\n    heat_pump=heat_pump,\n    save_path=save_path,\n    T_con_ar=T_con_ar,\n    T_eva_in_ar=T_eva_in_ar,\n    n_ar=n_ar,\n    use_condenser_inlet=True,\n    use_multiprocessing=False,\n    save_plots=True,\n    m_flow_con=0.2,\n    m_flow_eva=0.9,\n    dT_eva_superheating=5,\n    dT_con_subcooling=0,\n)\n"
         },
         {
             "cell_type": "markdown",
@@ -123,7 +123,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "heat_pump = VaporInjectionEconomizer(\n    evaporator=evaporator,\n    condenser=condenser,\n    fluid=\"Propane\",\n    economizer=economizer,\n    high_pressure_compressor=high_pressure_compressor,\n    low_pressure_compressor=low_pressure_compressor,\n    high_pressure_valve=high_pressure_valve,\n    low_pressure_valve=low_pressure_valve\n)\nutils.full_factorial_map_generation(\n    heat_pump=heat_pump,\n    save_path=r\"D:\\00_temp\\vapor_injection_economizer\",\n    T_con_in_ar=T_con_in_ar,\n    T_eva_in_ar=T_eva_in_ar,\n    n_ar=n_ar,\n    use_multiprocessing=False,\n    save_plots=True,\n    m_flow_con=0.2,\n    m_flow_eva=0.9,\n    dT_eva_superheating=5,\n    dT_con_subcooling=0,\n)\n"
+            "source": "heat_pump = VaporInjectionEconomizer(\n    evaporator=evaporator,\n    condenser=condenser,\n    fluid=\"Propane\",\n    economizer=economizer,\n    high_pressure_compressor=high_pressure_compressor,\n    low_pressure_compressor=low_pressure_compressor,\n    high_pressure_valve=high_pressure_valve,\n    low_pressure_valve=low_pressure_valve\n)\nutils.full_factorial_map_generation(\n    heat_pump=heat_pump,\n    save_path=r\"D:\\00_temp\\vapor_injection_economizer\",\n    T_con_ar=T_con_ar,\n    T_eva_in_ar=T_eva_in_ar,\n    n_ar=n_ar,\n    use_multiprocessing=False,\n    save_plots=True,\n    m_flow_con=0.2,\n    m_flow_eva=0.9,\n    dT_eva_superheating=5,\n    dT_con_subcooling=0,\n)\n"
         }
     ],
     "metadata": {

docs/source/examples/e6_simple_heat_pump.md

@@ -71,11 +71,13 @@ heat_pump = StandardCycle(
 
 As in the other example, we can specify save-paths,
 solver settings and inputs to vary:
+Note that T_con can either be inlet or outlet, depending on the setting
+of `use_condenser_inlet`. Per default, we simulate the inlet, T_con_in
 
 ```python
 save_path = r"D:\00_temp\simple_heat_pump"
 T_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]
-T_con_in_ar = [30 + 273.15, 50 + 273.15, 70 + 273.15]
+T_con_ar = [30 + 273.15, 50 + 273.15, 70 + 273.15]
 n_ar = [0.3, 0.7, 1]
 ```
 
@@ -92,9 +94,10 @@ from vclibpy import utils
 save_path_sdf, save_path_csv = utils.full_factorial_map_generation(
     heat_pump=heat_pump,
     save_path=save_path,
-    T_con_in_ar=T_con_in_ar,
+    T_con_ar=T_con_ar,
     T_eva_in_ar=T_eva_in_ar,
     n_ar=n_ar,
+    use_condenser_inlet=use_condenser_inlet,
     use_multiprocessing=False,
     save_plots=True,
     m_flow_con=0.2,
@@ -127,7 +130,7 @@ You have to know the names, which are the column headers.
 import matplotlib.pyplot as plt
 x_name = "n in - (Relative compressor speed)"
 y_name = "COP in - (Coefficient of performance)"
-plt.scatter(df[x_name], df[y_name])
+plt.scatter(df[x_name], df[y_name], s=20)
 plt.ylabel(y_name)
 plt.xlabel(x_name)
 plt.show()
@@ -138,14 +141,15 @@ However, other inputs (temperatures) have a greater impact on the COP.
 We can also use existing 3D-plotting scripts in vclibpy to analyze the
 dependencies. For this, we need the .sdf file. In the sdf, the field names are without
 the unit and description, as those are accessible in the file-format in other columns.
+Depending on whether we varied the inlet or outlet, we have to specify the correct name.
 
 ```python
 from vclibpy.utils.plotting import plot_sdf_map
 plot_sdf_map(
     filepath_sdf=save_path_sdf,
     nd_data="COP",
     first_dimension="T_eva_in",
-    second_dimension="T_con_in",
+    second_dimension="T_con_in" if use_condenser_inlet else "T_con_out",
     fluids=["Propane"],
     flowsheets=["Standard"]
 )

docs/source/examples/e7_vapor_injection.md

@@ -85,7 +85,7 @@ solver settings and inputs to vary:
 ```python
 save_path = r"D:\00_temp\vapor_injection"
 T_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]
-T_con_in_ar = [30 + 273.15, 50 + 273.15, 60 + 273.15]
+T_con_ar = [30 + 273.15, 50 + 273.15, 60 + 273.15]
 n_ar = [0.3, 0.7, 1]
 ```
 
@@ -102,9 +102,10 @@ from vclibpy import utils
 utils.full_factorial_map_generation(
     heat_pump=heat_pump,
     save_path=save_path,
-    T_con_in_ar=T_con_in_ar,
+    T_con_ar=T_con_ar,
     T_eva_in_ar=T_eva_in_ar,
     n_ar=n_ar,
+    use_condenser_inlet=True,
     use_multiprocessing=False,
     save_plots=True,
     m_flow_con=0.2,
@@ -161,7 +162,7 @@ heat_pump = VaporInjectionEconomizer(
 utils.full_factorial_map_generation(
     heat_pump=heat_pump,
     save_path=r"D:\00_temp\vapor_injection_economizer",
-    T_con_in_ar=T_con_in_ar,
+    T_con_ar=T_con_ar,
     T_eva_in_ar=T_eva_in_ar,
     n_ar=n_ar,
     use_multiprocessing=False,

examples/e6_simple_heat_pump.py

@@ -1,6 +1,6 @@
 # # Example for a heat pump with a standard cycle
 
-def main():
+def main(use_condenser_inlet: bool = True):
     # Let's start the complete cycle simulation with the
     # most basic flowsheet, the standard-cycle. As all flowsheets
     # contain a condenser and an evaporator, we defined a common BaseCycle
@@ -61,9 +61,11 @@ def main():
     )
     # As in the other example, we can specify save-paths,
     # solver settings and inputs to vary:
+    # Note that T_con can either be inlet or outlet, depending on the setting
+    # of `use_condenser_inlet`. Per default, we simulate the inlet, T_con_in
     save_path = r"D:\00_temp\simple_heat_pump"
     T_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]
-    T_con_in_ar = [30 + 273.15, 50 + 273.15, 70 + 273.15]
+    T_con_ar = [30 + 273.15, 50 + 273.15, 70 + 273.15]
     n_ar = [0.3, 0.7, 1]
 
     # Now, we can generate the full-factorial performance map
@@ -77,9 +79,10 @@ def main():
     save_path_sdf, save_path_csv = utils.full_factorial_map_generation(
         heat_pump=heat_pump,
         save_path=save_path,
-        T_con_in_ar=T_con_in_ar,
+        T_con_ar=T_con_ar,
         T_eva_in_ar=T_eva_in_ar,
         n_ar=n_ar,
+        use_condenser_inlet=use_condenser_inlet,
         use_multiprocessing=False,
         save_plots=True,
         m_flow_con=0.2,
@@ -101,7 +104,7 @@ def main():
     import matplotlib.pyplot as plt
     x_name = "n in - (Relative compressor speed)"
     y_name = "COP in - (Coefficient of performance)"
-    plt.scatter(df[x_name], df[y_name])
+    plt.scatter(df[x_name], df[y_name], s=20)
     plt.ylabel(y_name)
     plt.xlabel(x_name)
     plt.show()
@@ -110,16 +113,17 @@ def main():
     # We can also use existing 3D-plotting scripts in vclibpy to analyze the
     # dependencies. For this, we need the .sdf file. In the sdf, the field names are without
     # the unit and description, as those are accessible in the file-format in other columns.
+    # Depending on whether we varied the inlet or outlet, we have to specify the correct name.
     from vclibpy.utils.plotting import plot_sdf_map
     plot_sdf_map(
         filepath_sdf=save_path_sdf,
         nd_data="COP",
         first_dimension="T_eva_in",
-        second_dimension="T_con_in",
+        second_dimension="T_con_in" if use_condenser_inlet else "T_con_out",
         fluids=["Propane"],
         flowsheets=["Standard"]
     )
 
 
 if __name__ == "__main__":
-    main()
+    main(use_condenser_inlet=False)

examples/e7_vapor_injection.py

@@ -69,7 +69,7 @@ def main():
     # solver settings and inputs to vary:
     save_path = r"D:\00_temp\vapor_injection"
     T_eva_in_ar = [-10 + 273.15, 273.15, 10 + 273.15]
-    T_con_in_ar = [30 + 273.15, 50 + 273.15, 60 + 273.15]
+    T_con_ar = [30 + 273.15, 50 + 273.15, 60 + 273.15]
     n_ar = [0.3, 0.7, 1]
 
     # Now, we can generate the full-factorial performance map
@@ -83,9 +83,10 @@ def main():
     utils.full_factorial_map_generation(
         heat_pump=heat_pump,
         save_path=save_path,
-        T_con_in_ar=T_con_in_ar,
+        T_con_ar=T_con_ar,
         T_eva_in_ar=T_eva_in_ar,
         n_ar=n_ar,
+        use_condenser_inlet=True,
         use_multiprocessing=False,
         save_plots=True,
         m_flow_con=0.2,
@@ -127,7 +128,7 @@ def main():
     utils.full_factorial_map_generation(
         heat_pump=heat_pump,
         save_path=r"D:\00_temp\vapor_injection_economizer",
-        T_con_in_ar=T_con_in_ar,
+        T_con_ar=T_con_ar,
         T_eva_in_ar=T_eva_in_ar,
         n_ar=n_ar,
         use_multiprocessing=False,

requirements.txt

@@ -1,4 +1,4 @@
-numpy>=1.20.0
+numpy<=2.0
 matplotlib>=3.3.4
 coolprop>=6.4.1
 sdf>=0.3.5

tests/test_examples.py

@@ -13,12 +13,12 @@ class TestExamples(unittest.TestCase):
     def setUp(self) -> None:
         self.timeout = 100  # Seconds which the script is allowed to run
 
-    def _run_example(self, example, timeout=None):
+    def _run_example(self, example, timeout=None, **kwargs):
         ex_py = pathlib.Path(__file__).absolute().parents[1].joinpath("examples", example)
         sys.path.insert(0, str(ex_py.parent))
         module = importlib.import_module(ex_py.stem)
         example_main = getattr(module, "main")
-        example_main()
+        example_main(**kwargs)
 
     def test_e1_refrigerant_data(self):
         self._run_example(example="e1_refrigerant_data.py")
@@ -38,6 +38,9 @@ def test_e5_expansion_valve(self):
     def test_e6_simple_heat_pump(self):
         self._run_example(example="e6_simple_heat_pump.py")
 
+    def test_e6_simple_heat_pump_outlet(self):
+        self._run_example(example="e6_simple_heat_pump.py", use_condenser_inlet=False)
+
     def test_e7_vapor_injection(self):
         self._run_example(example="e7_vapor_injection.py")
 

tests/test_regression.py

@@ -131,7 +131,7 @@ def _regression_of_examples(self, flowsheet, fluid):
 
         # Just for quick study: Specify concrete points:
         T_eva_in_ar = [-10 + 273.15, 273.15]
-        T_con_in_ar = [30 + 273.15, 70 + 273.15]
+        T_con_ar = [30 + 273.15, 70 + 273.15]
         n_ar = [0.3, 1]
 
         os.makedirs(self.working_dir, exist_ok=True)
@@ -146,7 +146,7 @@ def _regression_of_examples(self, flowsheet, fluid):
         _, path_csv = utils.full_factorial_map_generation(
             heat_pump=heat_pump,
             save_path=self.working_dir,
-            T_con_in_ar=T_con_in_ar,
+            T_con_ar=T_con_ar,
             T_eva_in_ar=T_eva_in_ar,
             n_ar=n_ar,
             use_multiprocessing=False,
@@ -155,6 +155,7 @@ def _regression_of_examples(self, flowsheet, fluid):
             m_flow_eva=0.9,
             dT_eva_superheating=5,
             dT_con_subcooling=0,
+            **kwargs
         )
         path_csv_regression = pathlib.Path(__file__).parent.joinpath(
             "regression_data", "reference_results", f"{flowsheet}_{fluid}.csv"
@@ -171,7 +172,7 @@ def test_vi_ps_propane(self):
         self._regression_of_examples("VaporInjectionPhaseSeparator", "Propane")
 
     def test_evi_propane(self):
-        self.skipTest("EVI works locally, only CI fails.")
+        #self.skipTest("EVI works locally, only CI fails.")
         self._regression_of_examples("VaporInjectionEconomizer", "Propane")
 
     @unittest.skip("not implemented")

vclibpy/__init__.py

@@ -4,4 +4,4 @@
 
 from vclibpy.datamodels import FlowsheetState, Inputs
 
-__version__ = "0.1.2"
+__version__ = "0.2.0"

vclibpy/components/compressors/compressor.py

@@ -127,7 +127,7 @@ def calc_state_outlet(self, p_outlet: float, inputs: Inputs, fs_state: Flowsheet
                 self.state_inlet.h + (state_outlet_isentropic.h - self.state_inlet.h) /
                 eta_is
         )
-        fs_state.set(name="eta_is", value=eta_is, unit="%", description="Isentropic efficiency")
+        fs_state.set(name="eta_is", value=eta_is, unit="-", description="Isentropic efficiency")
         self.state_outlet = self.med_prop.calc_state("PH", p_outlet, h_outlet)
 
     def calc_m_flow(self, inputs: Inputs, fs_state: FlowsheetState) -> float:
@@ -148,7 +148,7 @@ def calc_m_flow(self, inputs: Inputs, fs_state: FlowsheetState) -> float:
                 self.get_n_absolute(inputs.n)
         )
         self.m_flow = self.state_inlet.d * V_flow_ref
-        fs_state.set(name="lambda_h", value=lambda_h, unit="%", description="Volumetric efficiency")
+        fs_state.set(name="lambda_h", value=lambda_h, unit="-", description="Volumetric efficiency")
         fs_state.set(name="V_flow_ref", value=V_flow_ref, unit="m3/s", description="Refrigerant volume flow rate")
         fs_state.set(name="m_flow_ref", value=self.m_flow, unit="kg/s", description="Refrigerant mass flow rate")
         return self.m_flow