Merge branch 'main' into pfas

QSD-Group · May 12, 2024 · 9949eca · 9949eca
2 parents 47432c4 + ea32b82
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diff --git a/.github/workflows/build-coverage.yml b/.github/workflows/build-coverage.yml
@@ -19,9 +19,9 @@ jobs:
         python-version: ["3.9", "3.10"]
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
@@ -36,7 +36,9 @@ jobs:
       run: |
         pytest --cov=./ --cov-report=xml
     - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v3
+      uses: codecov/codecov-action@v4
+      env:
+        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
       with:
         directory: ./coverage/reports/
         env_vars: OS,PYTHON

diff --git a/.github/workflows/build-only.yml b/.github/workflows/build-only.yml
@@ -19,7 +19,7 @@ jobs:
         python-version: ["3.9", "3.10"]
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v4
       with:

diff --git a/docs/source/Systems.rst b/docs/source/Systems.rst
@@ -15,7 +15,7 @@ When publishing the paper that introduces QSDsan (`Li and Zhang`_ et al., 2022),
 
 Water Resource Recovery Facilities
 ----------------------------------
-Work is underway to model the 25 distinct Water Resource Recovery Facility (WRRF) configurations identified as “typical” across North America (`Tarallo <https://doi.org/10.2166/9781780407685>`_ et al., 2015; Zhang et al., *In Prep*, 2023).
+Work is underway to model the 25 distinct Water Resource Recovery Facility (WRRF) configurations identified as “typical” across North America (`Tarallo <https://doi.org/10.2166/9781780407685>`_ et al., 2015; Zhang et al., *In Prep*, 2024).
 
 .. figure:: images/wrrf_configs.png
 
@@ -58,14 +58,19 @@ A variety of other sanitation and resource recovery systems have been developed
 
 #. Hydrothermal systems for fuel and fertilizer production from wet organic wastes
 
-    * Manuscript: Feng et al., Characterizing the Opportunity Space for Sustainable Hydrothermal Valorization of Wet Organic Wastes, Submitted.
+    * Publication: `Feng <https://pubs.acs.org/doi/10.1021/acs.est.3c07394>`_ et al., 2024.
     * `htl EXPOsan module <https://github.com/QSD-Group/EXPOsan/tree/main/exposan/htl>`_
 
-#. Modular encapsulated two-stage anaerobic biological system
+#. Modular encapsulated two-stage anaerobic biological (METAB) system
 
     * Manuscript: Zhang et al., Sustainable design of a modular anaerobic system for distributed energy recovery from industrial wastewaters, In Prep.
     * `metab EXPOsan module <https://github.com/QSD-Group/EXPOsan/tree/main/exposan/metab>`_
 
+#. EcoRecover system: microalgae-based tertiary P recovery process
+
+    * Manuscript: Kim et al., Development and validation of a Phototrophic-Mixotrophic Process Model (PM2) and a process simulator for microalgae-based wastewater treatment, In Prep.
+    * `pm2_ecorecover EXPOsan module <https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_ecorecover>`_
+
 
 **Notes:**
     - "Under NDA" indicates that the system is under non-disclosure agreement with the technology design team and unfortunately we are not able to share the codes in full at this stage. The source link code will lead to a private repository that only individuals who have signed the NDA can access.

diff --git a/docs/source/api/Process.rst b/docs/source/api/Process.rst
@@ -16,4 +16,25 @@ CompiledProcesses
 -----------------
 
 .. autoclass:: qsdsan.CompiledProcesses
+   :members:
+
+
+DynamicParameter
+----------------
+
+.. autoclass:: qsdsan.DynamicParameter
+   :members:
+
+
+Kinetics
+--------
+
+.. autoclass:: qsdsan.Kinetics
+   :members:
+
+
+MultiKinetics
+-------------
+
+.. autoclass:: qsdsan.MultiKinetics
    :members:
diff --git a/docs/source/api/_index.rst b/docs/source/api/_index.rst
@@ -3,7 +3,7 @@
 API
 ===
 
-The UML below shows the structure and core Python classes implemented in ``QSDsan``. Each class is represented by a box containing the class name (bold, top part of the box) with select data (middle part of the box) and method (end with parentheses, bottom part of the box) attributes. The ``Component`` and ``WasteStream`` classes in blue are inherited from the ``Chemical`` and ``Stream`` classes in `Thermosteam <https://github.com/BioSTEAMDevelopmentGroup/thermosteam>`_ with the addition of wastewater-related attributes. The `Process` class in red enables dynamic simulation of Component objects’ transformation during kinetic processes (e.g., degradation of substrates). The ``SanUnit``, ``System``, ``TEA``, and ``Model`` classes in yellow are inherited from `BioSTEAM <https://github.com/BioSTEAMDevelopmentGroup/biosteam>`_ with added capacities for dynamic simulation and handling of construction inventories. Green boxes including ``mpactItem``, ``ImpactIndicator``, and ``LCA`` are implemented in ``QSDsan`` to enable LCA functionalities. 
+The UML below shows the structure and core Python classes implemented in ``QSDsan``. Each class is represented by a box containing the class name (bold, top part of the box) with select data (middle part of the box) and method (end with parentheses, bottom part of the box) attributes. The ``Component`` and ``WasteStream`` classes in blue are inherited from the ``Chemical`` and ``Stream`` classes in `Thermosteam <https://github.com/BioSTEAMDevelopmentGroup/thermosteam>`_ with the addition of wastewater-related attributes. The `Process` class in red enables dynamic simulation of Component objects’ transformation during kinetic processes (e.g., degradation of substrates). The ``SanUnit``, ``System``, ``TEA``, and ``Model`` classes in yellow are inherited from `BioSTEAM <https://github.com/BioSTEAMDevelopmentGroup/biosteam>`_ with added capacities for dynamic simulation and handling of construction inventories. Green boxes including ``ImpactItem``, ``ImpactIndicator``, and ``LCA`` are implemented in ``QSDsan`` to enable LCA functionalities. 
 
 .. figure:: https://lucid.app/publicSegments/view/c8de361f-7292-47e3-8870-d6f668691728/image.png
    :width: 100%

diff --git a/docs/source/api/processes/PM2.rst b/docs/source/api/processes/PM2.rst
@@ -0,0 +1,4 @@
+Phototrophic Mixotrophic Process Model (PM2)
+============================================
+.. autoclass:: qsdsan.processes.PM2
+   :members:
diff --git a/docs/source/api/processes/_index.rst b/docs/source/api/processes/_index.rst
@@ -15,6 +15,10 @@ List of Biological Kinetic Models
 +----------+------------------+-----------------------------+
 | ASM2d    | `asm`_ & `bsm1`_ | `Henze`_ et al., 2006       |
 +----------+------------------+-----------------------------+
+| PM2      | `pm2_ecorecover`_| N/A                         |
+|          | & `pm2_batch`_   |				    |
++----------+------------------+-----------------------------+
+
 
 
 List of Other Kinetic Modules
@@ -38,6 +42,8 @@ List of Other Kinetic Modules
 .. _asm: https://github.com/QSD-Group/EXPOsan/tree/main/exposan/asm
 .. _bsm1: https://github.com/QSD-Group/EXPOsan/tree/main/exposan/bsm1
 .. _bwaise: https://github.com/QSD-Group/EXPOsan/tree/main/exposan/bwaise
+.. _pm2_batch: https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_batch
+.. _pm2_ecorecover: https://github.com/QSD-Group/EXPOsan/tree/main/exposan/pm2_ecorecover
 
 .. _Batstone: https://iwaponline.com/ebooks/book/152/Anaerobic-Digestion-Model-No-1-ADM1
 .. _EPA design manual: https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=3000464S.TXT
@@ -57,4 +63,5 @@ Links to docs
    ASM1
    ASM2d
    Decay
-   KineticReaction
+   KineticReaction
+   PM2
diff --git a/docs/source/api/sanunits/Reactor.rst b/docs/source/api/sanunits/Reactor.rst
@@ -0,0 +1,4 @@
+Reactor
+=======
+.. automodule:: qsdsan.sanunits._reactor
+    :members:
diff --git a/docs/source/api/sanunits/_index.csv b/docs/source/api/sanunits/_index.csv
@@ -3,7 +3,7 @@ ADMtoASM,Yes,Yes,Completed
 AnMBR (anaerobic membrane bioreactor),No,No,Completed
 ActivatedSludgeProcess,No,No,Completed
 AnaerobicBaffledReactor,No,No,Completed
-AnaerobicCSTR,Yes,No,Under development
+AnaerobicCSTR,Yes,No,Completed
 AnaerobicDigestion,No,No,Completed
 ASMtoADM,Yes,Yes,Completed
 BatchExperiment,Yes,Yes,Completed

diff --git a/docs/source/api/sanunits/_index.rst b/docs/source/api/sanunits/_index.rst
@@ -35,6 +35,7 @@ Individual Unit Operations
    combustion
    compressor
    CropApplication
+   distillation
    DynamicInfluent
    ElectrochemicalCell
    Excretion
@@ -50,6 +51,7 @@ Individual Unit Operations
    non_reactive
    PolishingFilter
    pumping
+   Reactor
    Screening
    Sedimentation
    SepticTank

diff --git a/docs/source/api/sanunits/distillation.rst b/docs/source/api/sanunits/distillation.rst
@@ -0,0 +1,4 @@
+Distillation
+============
+.. automodule:: qsdsan.sanunits._distillation
+    :members:
diff --git a/docs/source/api/utils/model_eval.rst b/docs/source/api/utils/model_eval.rst
@@ -32,6 +32,11 @@ DictAttrSetter
 .. autofunction:: qsdsan.utils.DictAttrSetter
 
 
+MethodSetter
+^^^^^^^^^^^^
+.. autofunction:: qsdsan.utils.MethodSetter
+
+
 Sample Manipulation
 -------------------
 

diff --git a/docs/source/images/wrrf_configs.png b/docs/source/images/wrrf_configs.png
diff --git a/qsdsan/_process.py b/qsdsan/_process.py
@@ -1191,8 +1191,12 @@ def stoichiometry(self):
         if isa(stoichio, list) and len(v_params) > 0:
             stoichio_vals = []
             for row in stoichio:
-                stoichio_vals.append([v.subs(v_params) if not isa(v, (float, int)) else v for v in row])
-            try: stoichio_vals = np.asarray(stoichio_vals, dtype=float)
+                # stoichio_vals.append([v.subs(v_params) if not isa(v, (float, int)) else v for v in row])
+                stoichio_vals.append([v.evalf(subs=v_params) if not isa(v, (float, int)) else v for v in row])
+            try: 
+                stoichio_vals = np.asarray(stoichio_vals, dtype=float)
+                #!!! round-off error
+                # stoichio_vals[np.abs(stoichio_vals) < 2.22044604925e-16] = 0.0
             except TypeError: pass
             return pd.DataFrame(stoichio_vals, index=self.IDs, columns=self._components.IDs)
         else: return pd.DataFrame(stoichio, index=self.IDs, columns=self._components.IDs)
@@ -1201,11 +1205,16 @@ def _lambdify_stoichio(self):
         dct = self._dyn_params
         dct_vals = self._parameters
         if dct:
-            sbs = [i.symbol for i in dct.values()]
-            lamb = lambdify(sbs, self._stoichiometry, 'numpy')
+            static_params = {k:v for k,v in dct_vals.items() if k not in dct}
+            stoichio = []
+            isa = isinstance
+            for row in self._stoichiometry:
+                stoichio.append([v.evalf(subs=static_params) if not isa(v, (float, int)) else v for v in row])
+            sbs = [symbols(i) for i in dct.keys()]
+            lamb = lambdify(sbs, stoichio, 'numpy')
             arr = np.empty((self.size, len(self._components)))
             def f():
-                v = [v for k,v in dct_vals.items() if k in dct.keys()]
+                v = [dct_vals[k] for k in dct.keys()]
                 arr[:,:] = lamb(*v)
                 return arr
             self.__dict__['_stoichio_lambdified'] = f

diff --git a/qsdsan/processes/_adm1.py b/qsdsan/processes/_adm1.py
@@ -569,9 +569,12 @@ def __new__(cls, components=None, path=None, N_xc=2.686e-3, N_I=4.286e-3, N_aa=7
                 **kwargs):
 
         cmps = _load_components(components)
-        cmps.X_c.i_N = N_xc * N_mw
-        cmps.X_I.i_N = cmps.S_I.i_N = N_I * N_mw
-        cmps.S_aa.i_N = cmps.X_pr.i_N = N_aa * N_mw
+        cmps.X_c.i_N = round(N_xc * N_mw, 4)
+        cmps.X_I.i_N = cmps.S_I.i_N = round(N_I * N_mw, 4)
+        cmps.S_aa.i_N = cmps.X_pr.i_N = round(N_aa * N_mw, 4)
+        # cmps.X_c.i_N = N_xc * N_mw
+        # cmps.X_I.i_N = cmps.S_I.i_N = N_I * N_mw
+        # cmps.S_aa.i_N = cmps.X_pr.i_N = N_aa * N_mw
 
         if not path: path = _path
         self = Processes.load_from_file(path,
@@ -591,11 +594,11 @@ def __new__(cls, components=None, path=None, N_xc=2.686e-3, N_I=4.286e-3, N_aa=7
         self.extend(gas_transfer)
         self.compile(to_class=cls)
 
-        stoichio_vals = (f_ch_xc, f_pr_xc, f_li_xc, f_xI_xc, 1-f_ch_xc-f_pr_xc-f_li_xc-f_xI_xc,
-                         f_fa_li, f_bu_su, f_pro_su, f_ac_su, 1-f_bu_su-f_pro_su-f_ac_su,
-                         f_va_aa, f_bu_aa, f_pro_aa, f_ac_aa, 1-f_va_aa-f_bu_aa-f_pro_aa-f_ac_aa,
-                         f_ac_fa, 1-f_ac_fa, f_pro_va, f_ac_va, 1-f_pro_va-f_ac_va,
-                         f_ac_bu, 1-f_ac_bu, f_ac_pro, 1-f_ac_pro,
+        stoichio_vals = (f_ch_xc, f_pr_xc, f_li_xc, f_xI_xc, 1.0-f_ch_xc-f_pr_xc-f_li_xc-f_xI_xc,
+                         f_fa_li, f_bu_su, f_pro_su, f_ac_su, 1.0-f_bu_su-f_pro_su-f_ac_su,
+                         f_va_aa, f_bu_aa, f_pro_aa, f_ac_aa, 1.0-f_va_aa-f_bu_aa-f_pro_aa-f_ac_aa,
+                         f_ac_fa, 1.0-f_ac_fa, f_pro_va, f_ac_va, 1.0-f_pro_va-f_ac_va,
+                         f_ac_bu, 1.0-f_ac_bu, f_ac_pro, 1.0-f_ac_pro,
                          Y_su, Y_aa, Y_fa, Y_c4, Y_pro, Y_ac, Y_h2)
         pH_LLs = np.array([pH_limits_aa[0]]*6 + [pH_limits_ac[0], pH_limits_h2[0]])
         pH_ULs = np.array([pH_limits_aa[1]]*6 + [pH_limits_ac[1], pH_limits_h2[1]])

diff --git a/qsdsan/sanunits/_anaerobic_reactor.py b/qsdsan/sanunits/_anaerobic_reactor.py
@@ -444,6 +444,7 @@ def _init_state(self):
 
     def _update_state(self):
         y = self._state
+        y[-1] = sum(ws.state[-1] for ws in self.ins)
         f_rtn = self._f_retain
         i_mass = self.components.i_mass
         chem_MW = self.components.chem_MW
@@ -473,7 +474,7 @@ def _update_state(self):
         gas.state[:n_cmps] = gas.state[:n_cmps] * chem_MW / i_mass * 1e3 # i.e., M biogas to mg (measured_unit) / L
 
     def _update_dstate(self):
-        self._tempstate = self.model.rate_function._params['root'].data.copy()
+        # self._tempstate = self.model.rate_function._params['root'].data.copy()
         dy = self._dstate
         f_rtn = self._f_retain
         n_cmps = len(self.components)
@@ -536,19 +537,23 @@ def _compile_ODE(self):
             gas_mass2mol_conversion = (cmps.i_mass / cmps.chem_MW)[self._gas_cmp_idx]
             hasexo = bool(len(self._exovars))
             f_exovars = self.eval_exo_dynamic_vars
-            # _rQ = self._rQ
             if self._fixed_P_gas:
                 f_qgas = self.f_q_gas_fixed_P_headspace
             else:
                 f_qgas = self.f_q_gas_var_P_headspace
+
+            if self.model._dyn_params:
+                def M_stoichio(state_arr):
+                    _f_param(state_arr)
+                    return self.model.stoichio_eval().T
+            else:
+                _M_stoichio = self.model.stoichio_eval().T
+                M_stoichio = lambda state_arr: _M_stoichio
             def dy_dt(t, QC_ins, QC, dQC_ins):
                 S_liq = QC[:n_cmps]
                 S_gas = QC[n_cmps: (n_cmps+n_gas)]
                 #!!! Volume change due to temperature difference accounted for 
                 # in _run and _init_state
-                # Q = QC[-1]
-                # S_in = QC_ins[0,:-1] * 1e-3  # mg/L to kg/m3
-                # Q_in = QC_ins[0,-1]
                 Q_ins = QC_ins[:, -1]
                 S_ins = QC_ins[:, :-1] * 1e-3  # mg/L to kg/m3
                 Q = sum(Q_ins)
@@ -557,15 +562,14 @@ def dy_dt(t, QC_ins, QC, dQC_ins):
                     QC = np.append(QC, exo_vars)
                     T = exo_vars[0]
                 else: T = self.T
-                _f_param(QC)
-                M_stoichio = _M_stoichio()
                 rhos =_f_rhos(QC)
                 _dstate[:n_cmps] = (Q_ins @ S_ins - Q*S_liq*(1-f_rtn))/V_liq \
-                    + np.dot(M_stoichio.T, rhos)
+                    + np.dot(M_stoichio(QC), rhos)
                 q_gas = f_qgas(rhos[-3:], S_gas, T)
                 _dstate[n_cmps: (n_cmps+n_gas)] = - q_gas*S_gas/V_gas \
                     + rhos[-3:] * V_liq/V_gas * gas_mass2mol_conversion
-                _dstate[-1] = dQC_ins[0,-1] #* _rQ
+                # _dstate[-1] = dQC_ins[0,-1]
+                _dstate[-1] = 0.
                 _update_dstate()
             self._ODE = dy_dt
 

diff --git a/qsdsan/sanunits/_membrane_bioreactor.py b/qsdsan/sanunits/_membrane_bioreactor.py
@@ -409,19 +409,18 @@ def _compute_mod_case_tank_N(self):
 
         mod_per_cas, cas_per_tank = N_mod_min, N_cas_min
 
-        J, J_max, N_train = self.J, self.J_max, self._N_train_min
-        while J > J_max:
+        J = self.J
+        while J > self.J_max:
             mod_per_cas += 1
             if mod_per_cas == N_mod_max + 1:
                 if cas_per_tank == N_cas_max + 1:
-                    N_train += 1
+                    self.N_train += 1
                     mod_per_cas, cas_per_tank = N_mod_min, N_cas_min
                 else:
                     cas_per_tank += 1
                     mod_per_cas = N_mod_min
 
-        self._N_train, self._mod_per_cas, self._cas_per_tank = \
-            N_train, mod_per_cas, cas_per_tank
+        self._mod_per_cas, self._cas_per_tank = mod_per_cas, cas_per_tank
 
 
     # Called by _run

diff --git a/qsdsan/sanunits/_polishing_filter.py b/qsdsan/sanunits/_polishing_filter.py
@@ -265,6 +265,7 @@ def _run(self):
             air_out.empty()
         else:
             biogas.empty()
+            air_out.empty()
             degassing(eff, air_out)
             degassing(waste, air_out)
             air_out.imol['N2'] += air_in.imol['N2']