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BioSTEAMDevelopmentGroup · Nov 17, 2024 · 48c0c0a · 48c0c0a
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diff --git a/biosteam/_system.py b/biosteam/_system.py
@@ -211,11 +211,7 @@ def solve_energy_departures(self):
         departures = solve(A, np.array(b).T).T
         try:
             for obj, departure in zip(objs, departures): 
-                try:
-                    obj._update_energy_variable(departure)
-                except:
-                    print(repr(obj))
-                    breakpoint()
+                obj._update_energy_variable(departure)
         except AttributeError as e:
             if obj._update_energy_variable:
                 raise e
@@ -2425,12 +2421,9 @@ def run_phenomena(self):
                 conf.solve_nonlinearities()
                 conf.solve_energy_departures()
                 conf.solve_material_flows()
-                print('GOOD!')
-            # except (NotImplementedError, UnboundLocalError, TypeError, AttributeError, KeyError) as error:
-            #     raise error
+            except (NotImplementedError, UnboundLocalError, TypeError, KeyError) as error:
+                raise error
             except:
-                print('FAILED X')
-                # del self._stage_configuration
                 for i in path: i.run()
 
     def _solve(self):

diff --git a/biosteam/evaluation/_model.py b/biosteam/evaluation/_model.py
@@ -201,32 +201,28 @@ def parameters_from_df(self, df_or_filename, namespace=None):
         
         Parameters
         ----------
-        df_or_filename : pandas.DataFrame or file path to a spreadsheet of the following format:
-                         Column titles (these must be included, but others may be added for convenience):
-                            'Parameter name': String
-                                Name of the parameter.
-                            'Element': String, optional
-                            'Kind': String, optional
-                            'Units': String, optional
-                            'Baseline': float or int
-                                The baseline value of the parameter.
-                            'Shape': String, one of ['Uniform', 'Triangular']
-                                The shape of the parameter distribution.
-                            'Lower': float or int
-                                The lower value defining the shape of the parameter distribution.
-                            'Midpoint': float or int
-                                The midpoint value defining the shape of a 'Triangular' parameter distribution.
-                            'Upper': float or int
-                                The upper value defining the shape of the parameter distribution.
-                            'Load statement': String
-                                A statement executed to load the value of the parameter. The value is stored in 
-                                the variable x. A namespace defined in the namespace during EasyInputModel 
-                                initialization may be accessed. 
-                                E.g., to load a value into an example distillation unit D101's light key recovery, 
-                                ensure 'D101' is a key pointing to the D101 unit object in namespace, then 
-                                simply include the load statement: 'D101.Lr = x'. New lines in the statement
-                                may be represented by '\n' or ';'.
-        
+        df_or_filename : pandas.DataFrame or file path to a spreadsheet with the following column titles.
+                         
+            * 'Parameter name' [String] Name of the parameter.
+            
+            * 'Element' [String] 
+                        
+            * 'Kind' [String] 
+                        
+            * 'Units' [String] 
+                        
+            * 'Baseline' [float] The baseline value of the parameter.
+                        
+            * 'Shape' {'Uniform', 'Triangular'} The shape of the parameter distribution.
+                        
+            * 'Lower' [float] The lower value defining the shape of the parameter distribution.
+                        
+            * 'Midpoint' [float] The midpoint value defining the shape of a 'Triangular' parameter distribution.
+                        
+            * 'Upper' [float] The upper value defining the shape of the parameter distribution.
+                        
+            * 'Load statement' [String] A statement executed to load the value of the parameter. 
+            
         namespace : dict, optional
             Dictionary used to update the namespace accessed when executing
             statements to load values into model parameters. Defaults to the
@@ -327,7 +323,7 @@ def parameter(self, setter=None, element=None, kind=None, name=None,
         Define and register parameter.
         
         Parameters
-        ----------    
+        ---------*    
         setter : function
                  Should set parameter in the element.
         element : Unit or :class:`~thermosteam.Stream`

diff --git a/biosteam/units/stage.py b/biosteam/units/stage.py
@@ -1551,7 +1551,6 @@ def _update_nonlinearities(self):
         if self._has_vle:
             for i in self.stages: i._update_nonlinearities()
         elif self._has_lle:
-            # pass
             self.update_lle_variables()
 
     def _update_aggretated_nonlinearities(self):

diff --git a/docs/index.rst b/docs/index.rst
@@ -144,47 +144,55 @@ tools for sustainability assessments. Here is a short list of related publicatio
 
 * **Software tools**:
 
-  - `BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. ACS Sustainable Chem. Eng. 2020 <https://doi.org/10.1021/acssuschemeng.9b07040>`_
+  #. `BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. ACS Sustainable Chem Eng 2020 <https://doi.org/10.1021/acssuschemeng.9b07040>`_
 
-  - `Thermosteam: BioSTEAM's Premier Thermodynamic Engine. Journal of Open Source Software. 2020 <doi.org/10.21105/joss.02814>`_
+  #. `Thermosteam: BioSTEAM's Premier Thermodynamic Engine. Journal of Open Source Software 2020 <doi.org/10.21105/joss.02814>`_
 
-  - `QSDsan: an integrated platform for quantitative sustainable design of sanitation and resource recovery systems. Environ. Sci.: Water Res. Technol. 2022 <https://doi.org/10.1039/D2EW00455K>`_
+  #. `QSDsan: an integrated platform for quantitative sustainable design of sanitation and resource recovery systems. Environ Sci: Water Res Technol 2022 <https://doi.org/10.1039/D2EW00455K>`_
 
 * **Social, economic, and policy studies**:
 
-  - `An agent-based modeling tool supporting bioenergy and bio-product community communication regarding cellulosic bioeconomy development. Renewable and Sustainable Energy Reviews 2022 <https://doi.org/10.1016/j.rser.2022.112745>`_
+  #. `An agent-based modeling tool supporting bioenergy and bio-product community communication regarding cellulosic bioeconomy development. Renewable and Sustainable Energy Reviews 2022 <https://doi.org/10.1016/j.rser.2022.112745>`_
 
-  - `Implications of Biorefinery Policy Incentives and Location-Specific Economic Parameters for the Financial Viability of Biofuels. Environ. Sci. Technol. 2023 <https://doi.org/10.1021/acs.est.2c07936>`_
+  #. `Implications of Biorefinery Policy Incentives and Location-Specific Economic Parameters for the Financial Viability of Biofuels. Environ Sci Technol 2023 <https://doi.org/10.1021/acs.est.2c07936>`_
 
 * **Bioproduct and biofuel studies**:
 
-  - `A Microbial Process for the Production of Benzyl Acetate. Nat Chem Eng 2024. <https://doi.org/10.1038/s44286-023-00022-0>`_
+  #. `Integration of plant and microbial oil processing at oilcane biorefineries for more sustainable biofuel production. GCB Bioenergy 2024 <https://doi.org/10.1111/gcbb.13183>`_
 
-  - `Characterizing the Opportunity Space for Sustainable Hydrothermal Valorization of Wet Organic Wastes. Environ. Sci. Technol. <https://doi.org/10.1021/acs.est.3c07394>`_
+  #. `Economic and Environmental Sustainability of Bio-Based HMF Production and Recovery from Lignocellulosic Biomass. Green Chem 2024 <https://doi.org/10.1039/D4GC04270K>`_
 
-  - `An End-to-End Pipeline for Succinic Acid Production at an Industrially Relevant Scale Using Issatchenkia Orientalis. Nat Commun. 2023. <https://doi.org/10.1038/s41467-023-41616-9>`_
+  #. `Comparative techno-economic and life cycle assessment of electrocatalytic processes for lignin valorization. Green Chem 2024 <https://doi.org/10.1039/D4GC01963F>`_
 
-  - `Metabolic engineering of Yarrowia lipolytica to produce 1,2-diacyl-3-acetyl triacylglycerol. Metabolic Engineering. 2023 <https://doi.org/10.1016/j.ymben.2023.01.003>`_
+  #. `The Economic and Environmental Case for Cattle Manure and Prairie Grass-Derived Sustainable Aviation Fuel. Energy Fuels 2024 <https://doi.org/10.1021/acs.energyfuels.4c02929>`_
 
-  - `Economic and Environmental Sustainability of Vegetative Oil Extraction Strategies at Integrated Oilcane and Oil-sorghum Biorefineries. ACS Sustainable Chem. Eng. 2022 <https://doi.org/10.1021/acssuschemeng.2c04204>`_
+  #. `A Microbial Process for the Production of Benzyl Acetate. Nat Chem Eng 2024. <https://doi.org/10.1038/s44286-023-00022-0>`_
 
-  - `Adsorptive separation and recovery of triacetic acid lactone from fermentation broth. Biofuels Bioprod Bioref 2022 <https://doi.org/10.1002/bbb.2427>`_
+  #. `Characterizing the Opportunity Space for Sustainable Hydrothermal Valorization of Wet Organic Wastes. Environ Sci Technol <https://doi.org/10.1021/acs.est.3c07394>`_
 
-  - `Rewiring yeast metabolism for producing 2,3-butanediol and two downstream applications: Techno-economic analysis and life cycle assessment of methyl ethyl ketone (MEK) and agricultural biostimulant production. Chemical Engineering Journal 2022 <https://doi.org/10.1016/j.cej.2022.138886>`_
+  #. `An End-to-End Pipeline for Succinic Acid Production at an Industrially Relevant Scale Using Issatchenkia Orientalis. Nat Commun 2023 <https://doi.org/10.1038/s41467-023-41616-9>`_
 
-  - `Sustainable Production of Acrylic Acid via 3-Hydroxypropionic Acid from Lignocellulosic Biomass. ACS Sustainable Chem. Eng. 2021 <https://doi.org/10.1021/acssuschemeng.1c05441>`_
+  #. `Metabolic engineering of Yarrowia lipolytica to produce 1,2-diacyl-3-acetyl triacylglycerol. Metabolic Engineering 2023 <https://doi.org/10.1016/j.ymben.2023.01.003>`_
+
+  #. `Economic and Environmental Sustainability of Vegetative Oil Extraction Strategies at Integrated Oilcane and Oil-sorghum Biorefineries. ACS Sustainable Chem. Eng. 2022 <https://doi.org/10.1021/acssuschemeng.2c04204>`_
+
+  #. `Adsorptive separation and recovery of triacetic acid lactone from fermentation broth. Biofuels Bioprod Bioref 2022 <https://doi.org/10.1002/bbb.2427>`_
+
+  #. `Rewiring yeast metabolism for producing 2,3-butanediol and two downstream applications: Techno-economic analysis and life cycle assessment of methyl ethyl ketone (MEK) and agricultural biostimulant production. Chemical Engineering Journal 2022 <https://doi.org/10.1016/j.cej.2022.138886>`_
+
+  #. `Sustainable Production of Acrylic Acid via 3-Hydroxypropionic Acid from Lignocellulosic Biomass. ACS Sustainable Chem Eng 2021 <https://doi.org/10.1021/acssuschemeng.1c05441>`_
 
-  - `Renewable linear alpha-olefins by base-catalyzed dehydration of biologically-derived fatty alcohols. Green Chemistry 2021 <https://doi.org/10.1039/D1GC00243K>`_
+  #. `Renewable linear alpha-olefins by base-catalyzed dehydration of biologically-derived fatty alcohols. Green Chemistry 2021 <https://doi.org/10.1039/D1GC00243K>`_
 
-  - `Sustainable Lactic Acid Production from Lignocellulosic Biomass. ACS Sustainable Chem. Eng. 2021 <https://doi.org/10.1021/acssuschemeng.0c08055>`_
+  #. `Sustainable Lactic Acid Production from Lignocellulosic Biomass. ACS Sustainable Chem Eng 2021 <https://doi.org/10.1021/acssuschemeng.0c08055>`_
 
-  - `Techno-Economic Evaluation of Biorefineries Based on Low-Value Feedstocks Using the BioSTEAM Software: A Case Study for Animal Bedding. Processes 2020 <https://doi.org/10.3390/pr8080904>`_
+  #. `Techno-Economic Evaluation of Biorefineries Based on Low-Value Feedstocks Using the BioSTEAM Software: A Case Study for Animal Bedding. Processes 2020 <https://doi.org/10.3390/pr8080904>`_
 
 * **Plastics and recycling**:
 
-  - `Comparative Techno-Economic Analysis and Life Cycle Assessment of Producing High-Value Chemicals and Fuels from Waste Plastic via Conventional Pyrolysis and Thermal Oxo-Degradation. Energy Fuels. 2023 <https://doi.org/10.1021/acs.energyfuels.3c02321>`_
+  #. `Comparative Techno-Economic Analysis and Life Cycle Assessment of Producing High-Value Chemicals and Fuels from Waste Plastic via Conventional Pyrolysis and Thermal Oxo-Degradation. Energy Fuels 2023 <https://doi.org/10.1021/acs.energyfuels.3c02321>`_
 
-  - `High-purity polypropylene from disposable face masks via solvent-targeted recovery and precipitation. Green Chemistry. 2023 <https://doi.org/10.1039/D3GC00205E>`_
+  #. `High-purity polypropylene from disposable face masks via solvent-targeted recovery and precipitation. Green Chemistry 2023 <https://doi.org/10.1039/D3GC00205E>`_
 
 
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