Add batchwise pure class

openmc/deplete/abc.py

@@ -26,7 +26,7 @@
 from .pool import deplete
 from .transfer_rates import TransferRates
 from openmc import Material, Cell
-from .batchwise import (BatchwiseCellGeometrical, BatchwiseCellTemperature,
+from .batchwise import (BatchwisePure, BatchwiseCellGeometrical, BatchwiseCellTemperature,
     BatchwiseMaterialRefuel, BatchwiseMaterialDilute, BatchwiseMaterialAdd,
     BatchwiseSchemeStd, BatchwiseSchemeRefuel, BatchwiseSchemeFlex)
 
@@ -814,7 +814,7 @@ def integrate(self, final_step=True, output=True):
                             n, root = self._get_bos_from_batchwise(i, n)
                         else:
                             # Store root at previous timestep
-                            root = self.batchwise._get_cell_attrib()
+                            root = self.batchwise.get_root()
                     else:
                         root = None
                     n, res = self._get_bos_data_from_operator(i, source_rate, n)
@@ -884,7 +884,7 @@ def integrate_adaptive(self, material_id, nuclides, final_step=True,
         with change_directory(self.operator.output_dir):
             n = self.operator.initial_condition()
             t, self._i_res = self._get_start_data()
-            
+
             nuc_ids = [id for nuc,id in self.chain.nuclide_dict.items() if nuc in nuclides]
 
             dt = self.timesteps[0]
@@ -935,7 +935,7 @@ def integrate_adaptive(self, material_id, nuclides, final_step=True,
                 n = n_list.pop()
                 StepResult.save(self.operator, n_list, res_list, [t, t + dt],
                                 source_rate, self._i_res + i, proc_time, root)
-                
+
                 for rank in range(comm.size):
                     number_i = comm.bcast(self.operator.number, root=rank)
                     if material_id in number_i.materials:
@@ -947,7 +947,7 @@ def integrate_adaptive(self, material_id, nuclides, final_step=True,
                                            tol, err, rho1, rho2, f)
                 comm.barrier()
                 dt = comm.bcast(dt, root=rank_mat)
-                
+
                 t += dt
                 i += 1
             # Final simulation -- in the case that final_step is False, a zero
@@ -969,7 +969,7 @@ def integrate_adaptive(self, material_id, nuclides, final_step=True,
 
     def _adapt_timestep(self, n_pred, n_corr, mat_idx, nuc_ids, tol, err, rho1,
                         rho2, f ):
-                
+
         filt_pred = take(n_pred[mat_idx], nuc_ids)
         filt_corr = take(n_corr[mat_idx], nuc_ids)
 
@@ -1072,6 +1072,8 @@ def add_redox(self, mat, buffer, oxidation_states):
         self.transfer_rates.set_redox(mat, buffer, oxidation_states)
 
     def add_material(self, mat, value, mat_vector, timestep, quantity='grams'):
+        if self.batchwise is None:
+            self.batchwise = BatchwisePure(self.operator, self.operator.model)
         self.batchwise.add_material(mat, value, mat_vector, timestep,
                                     quantity)
 @add_params

openmc/deplete/batchwise.py

@@ -162,6 +162,11 @@ def target(self, value):
     def from_params(cls, obj, attr, operator, model, **kwargs):
         return cls(obj, attr, operator, model, **kwargs)
 
+    @abstractmethod
+    def get_root(self):
+        """
+        """
+
     @abstractmethod
     def _model_builder(self, param):
         """
@@ -619,6 +624,61 @@ def _add_material(self, x, mat, values):
                         x[mat_idx][nuc_idx] += val
         return x
 
+class BatchwisePure(Batchwise):
+    def __init__(self, operator, model, density_treatment='constant-volume',
+                 redox_vec=None):
+        super().__init__(operator, model, [0,1], [-100,100])
+        self.cell_materials = None
+
+    def get_root(self):
+        return np.nan
+
+    def search_for_keff(self, x, step_index):
+        """
+        Perform the criticality search on the parametric cell coefficient and
+        update materials accordingly.
+        The :meth:`openmc.search.search_for_keff` solution is then set as the
+        new cell attribute.
+        Parameters
+        ----------
+        x : list of numpy.ndarray
+            Total atoms concentrations
+        Returns
+        -------
+        x : list of numpy.ndarray
+            Updated total atoms concentrations
+        """
+        x = super()._update_materials(x, step_index)
+        # if at least one of the cell materials is depletable, calculate new
+        # volume and update x and number accordingly.
+        # Alternatively, if material has been edded x needs to be updated
+        # TODO: improve this
+        if self.cell_materials:
+            volumes = self._calculate_volumes()
+            x = super()._update_x_and_set_volumes(x, volumes)
+
+        return x, np.nan
+
+    def _model_builder(self, param):
+        """
+        Builds the parametric model to be passed to the
+        :meth:`openmc.search.search_for_keff` method.
+        Callable function which builds a model according to a passed
+        parameter. This function must return an openmc.model.Model object.
+        Parameters
+        ----------
+        param : parameter
+            model function variable
+        Returns
+        -------
+        _model :  openmc.model.Model
+            OpenMC parametric model
+        """
+
+    def update_from_restart(self, step_index, x, root):
+        """
+        """
+
 class BatchwiseCell(Batchwise):
     """Abstract class holding batch wise cell-based functions.
 
@@ -714,6 +774,9 @@ def _set_cell_attrib(self, val):
             cell coefficient to set
         """
 
+    def get_root(self):
+        return self._get_cell_attrib()
+
     def _get_cell(self, val):
         """Helper method for getting cell from cell instance or cell name or id.
         Parameters
@@ -1173,6 +1236,11 @@ def _model_builder(self, param):
             Openmc parametric model
         """
 
+    def get_root(self):
+        for mat in openmc.lib.materials.values():
+            if mat.id in [m.id for m in self.materials]:
+                return mat.get_density()
+
     def search_for_keff(self, x, step_index):
         """
         Perform the criticality search on parametric material variable.
@@ -1935,8 +2003,8 @@ def __init__(self, bw_list, n_timesteps, dilute_interval, restart_level,
             self.dilute_interval = dilute_interval
         self.interrupt = interrupt
 
-    def _get_cell_attrib(self):
-        return self.bw_geom._get_cell_attrib()
+    def get_root(self):
+        return self.bw_geom.get_root()
 
     def set_density_function(self, mats, density_func, oxidation_states):
         for bw in self.bw_list:
@@ -2046,8 +2114,8 @@ def __init__(self, bw_list, restart_level):
         else:
             self.restart_level = restart_level
 
-    def _get_cell_attrib(self):
-        return self.bw_geom._get_cell_attrib()
+    def get_root(self):
+        return self.bw_geom.get_root()
 
     def set_density_function(self, mats, density_func, oxidation_states):
         for bw in self.bw_list:
@@ -2176,8 +2244,8 @@ def __init__(self, bw_list, n_timesteps, nuclide, limit, flex_fraction, span,
         #
         self.converged_flex = False
 
-    def _get_cell_attrib(self):
-        return self.bw_geom_trans._get_cell_attrib()
+    def get_root(self):
+        return self.bw_geom_trans.get_root()
 
     def set_density_function(self, mats, density_func, oxidation_states):
         for bw in self.bw_list: