Adding VariableResidualNorm postprocessor #8518
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I would like to have a vector postprocessor that runs on non linear and gathers residual norms. Seems more useful for convergence studies. |
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For doing convergence studies, it is useful to be able to plot the residual norm of variables of the interest. MOOSE computes these values, but we want to be able to store them as postprocessor values, so we can plot them easily without postprocessing the console output. Closes idaholab#7206
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permcody
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Feb 13, 2017
| input = 'variable_residual.i' | ||
| csvdiff = 'variable_residual_out.csv' | ||
| max_threads = 1 | ||
| max_parallel = 1 |
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Why the restrictions? I know it's a small test but it should still run in parallel right?
| VariableResidual::execute() | ||
| { | ||
| NonlinearSystemBase & nl = _fe_problem.getNonlinearSystemBase(); | ||
| _var_residual = nl.system().calculate_norm(nl.RHS(), _var.number(), DISCRETE_L2); |
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Any desire to support more than L2? We could make an enum if there might be and default it to L2.
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I think L2 for residual is all we need. If somebody wanted something like H1, we would need a gradient of the residual and I do not think we can compute that...
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| # this is large on purpose so we don't reduce the variable residual to machine zero | ||
| # and so that we can compare to larger numbers. This also means this test can run only | ||
| # in serial, since parallel runs yield different convergence history. |
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Ah! Here's the reason it's restricted
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For doing convergence studies, it is useful to be able to plot the
residual norm of variables of the interest. MOOSE computes these
values, but we want to be able to store them as postprocessor values, so
we can plot them easily without postprocessing the console output.
Closes #7206