results

Organize simulation results.

class results.SimulationResults(simu_parameters)

Bases: object

Organize composition variables from a simulation.

Variables:

• saved_steps (list) – Steps for which simulation results are stored in resdict.

• saved_times (1D array) – Times in h (rounded) that correspond to the saved steps.

• comps (list of str) – System constituents, with ‘Va’ first and dependent constituent last.

• inds (list of str) – Independent constituents, with ‘Va’ first.

• V_partial (dict) – Partial molar volumes.

• title (str) – Default plot title.

• results (dict) – Simulation results stored as UnitResult instances.

__init__(simu_parameters)

Class constructor.

Parameters:

• resdict (dict) – Simulation results (dict).

• simu_parameters (dict) – Simulation parameters, see class attributes.

add_results(resdict)

Populate results dictionary.

Generate UnitResult instances and set up their plots.StaticProfile attribute.

result(step_index=-1, th=None)

Access results at required step index or nearest to asked time.

Parameters:

• step_index (int) – Index of required time step in saved_steps/saved_times.

• th (float) – Required time in hour.

Returns:

Simulation results.

Return type:

UnitResult

Raises:

Exception – If the user specifies both step_index and th. If step_index is not an integer or is out of range.

plot(varname='x', step_index=-1, th=None, **kwargs)

Plot profile of variable varname at required time.

Select results at time step with result() (see doc of result() for handling of step_index and th). Then call UnitResult.plot().

Parameters:

• varname (str) – Name of variable to be plotted.

• step_index (int) – Index of required time step in saved_steps/saved_times.

• th (float) – Required time in hour.

Returns:

fig, ax

Return type:

matplotlib figure and axis

plot_quartet(step_index=-1, th=None, **kwargs)

Plot 2x2 subplots with profiles of simulation results.

Select results at time step with result() (see doc of result() for handling of step_index and th). Then call UnitResult.plot_quartet().

Parameters:

• step_index (int) – Index of required time step in saved_steps/saved_times.

• th (float) – Required time in hour.

Returns:

fig, axes, lines

Return type:

matplotlib figure, axes and lines

interactive_plot(variable='x')

Interactive plot (call plots.InteractivePlot).

add_mass_balance()

Add mass balance.

For each time step in steps, integrate concentrations and volume along profile, and compute difference with initial values.

Variables:

• N : amount of vacancies and atom species

• Np : amount of pores

• NW : amount of vacancies annihilated due to volume variation since initial step.

• Nv : amount of vacancies in simulation box, in solution and in pores, plus amount annihilated due to volume variations.

Type of operation:

• INx : integral amount in mol/m2

• dINx : difference with initial value, mol/m2

• rdINx : relative difference with initial value

plot_mass_balance()

Call plots.plot_mass_balance().

class results.UnitResult(result, V_partial)

Bases: object

Gather composition variables from one time step of a simulation.

Most attributes below are available in three versions: * x_mid: variable x evaluated on mid points * x_nod: variable x evaluated on nodes * x: shorthand for x_nod

Variables:

• z_nod (1D array) – Node positions.

• z_mid (1D array) – Midpoint positions.

• c (dict of 1D arrays) – System concentrations.

• V (1D array) – Average molar volume of system.

• y (dict of 1D arrays) – Metal site fractions.

• yVa_eq (1D array) – Equilibrium vacancy site fraction.

• dyVa (1D array) – Difference between actual and equilibrium vacancy fraction.

• ryVa (1D array) – Relative difference between actual and eq. vacancy fraction.

• x (dict of 1D arrays) – Metal atom fractions.

• Vm (1D array) – Average molar volume of metal.

• mu (dict of 1D arrays) – Chemical potentials.

• Jlat (dict of 1D arrays) – Fluxes in lattice-fixed frame.

• v (1D array) – Velocity field of lattice relative to laboratory frame.

• Jref (dict of 1D arrays) – Fluxes in laboratory frame.

• alpha_dislo (1D array) – Lattice sink rate due to dislocations.

• alpha_pores (1D array) – Lattice sink rate due to pore growth.

• alpha (1D array) – Total lattice sink rate.

• L (2D array) – Onsager coefficients.

• fm (1D array) – Metal volume fraction.

• fp (1D array) – Pore volume fraction.

• gamma_V (1D array) – Relative volume variation rate due to molar volume variations.

• gamma_N (1D array) – Relative volume variation rate due to variations in the number of lattice sites.

• gamma_p (1D array) – Relative volume variation rate due to pore growth.

• gamma (1D array) – Total relative volume variation.

• deformation (1D array) – Relative length variation.

• static_prof (plots.StaticProfile) – Configure and plot static profiles.

__init__(result, V_partial)

Class constructor.

Parameters:

• comps (list of str) – System constituents, list with ‘Va’ first and dependent constituent last.

• result (dict) – Simulation results at one time step.

• V_partial (dict) – Partial molar volumes.

to_nod(vec)

Interpolate vector on nodes.

make_nod_attributes()

Make attributes on nodes.

For every variable x in the list, create attribute x_nod by interpolating x_mid on nodes.

make_shorthands()

Make attribute shorthands.

For every variable x in the list, create attribute with shorthand x and assign existing x_nod value.

compute_Vm(V_partial, x_mid, y_mid)

Compute average molar volume of the metal phase.

compute_L_nod(L_mid)

Interpolate Onsager coefficients on nodes.

plot(varname='x', title=None, **kwargs)

Plot profile of variable varname.

Call plots.StaticProfile.single(). See list of variable names in class documentation.

plot_quartet(**kwargs)

Plot 2x2 grid plot with profiles of simulation results.

Call plots.StaticProfile.quartet(). Plot x, yVa, Jlat, fp.