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Add a dedicated linear WCNSFV page with links to the relevant sections in linearFV, NS and physics #31888
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Add a dedicated linear WCNSFV page with links to the relevant sections in linearFV, NS and physics #31888
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modules/navier_stokes/doc/content/modules/navier_stokes/linear_wcnsfv.md
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| # Weakly Compressible Navier Stokes using a Linear Finite Volume Implementation | ||
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| ## Equations | ||
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| The linear finite volume implementation of the weakly compressible Navier Stokes equations is used | ||
| to solve the following equations: | ||
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| - conservation of momentum | ||
| - pressure-correction (see [SIMPLE.md]) | ||
| - turbulence equations | ||
| - conservation of energy | ||
| - conservation of advected passive scalars | ||
| - conservation of an advected phase in a homogeneous mixture | ||
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| We refer the reader to the respective `Physics` pages, listed in [linear_wcnsfv.md#syntax], for the strong form of the equations. | ||
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| ## Solver algorithm(s) | ||
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| For steady state simulations, you may use the [SIMPLE.md] executioner which implements the SIMPLE algorithm [!citep](patankar1983calculation). | ||
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| For transient simulations, you may use the [PIMPLE.md] executioner which implements the PIMPLE algorithm [!citep](greenshieldsweller2022), which is a blend of PISO inner iterations and SIMPLE outer iterations. | ||
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| ## Discretization | ||
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| ### General | ||
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| We use a linearized cell-centered finite volume discretization. We have implemented orthogonal | ||
| gradient correction and skewness correction for face values and gradients, and thus can reach second-order accuracy in many cases. | ||
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| !alert note | ||
| Triangular and tetrahedral meshes currently only achieve first order spatial convergence rates at the moment. | ||
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| !alert note | ||
| This implementation does not form a Jacobian because it uses the SIMPLE/PIMPLE algorithm, which | ||
| solves segregated linear equations nested within a kind of fixed point iteration loop, rather than Newton. | ||
| Instead of forming a residual and Jacobian, this implementation forms a right hand side (RHS) and sparse coefficient matrix for direct use within linear system solvers. | ||
| Additional details about the linear finite volume discretization can be found on [this page](linear_fv_design.md). | ||
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| ### Advection term | ||
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| The advection term uses the Rhie Chow interpolation for computation of face velocities. Additional details may be found in the documentation | ||
| for the object handling the computation of the Rhie Chow velocities: the [RhieChowMassFlux.md]. | ||
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| ## Syntax id=syntax | ||
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| These equations can be created in MOOSE using the [LinearFVKernels](syntax/LinearFVKernels/index.md) and [LinearFVBCs](syntax/LinearFVBCs/index.md) | ||
| classes, or using the [Physics](syntax/Physics/index.md) classes. | ||
| For `LinearWCNSFV`, the relevant `Physics` classes are: | ||
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| - [WCNSLinearFVFlowPhysics.md] for the velocity-pressure coupling. | ||
| - [WCNSLinearFVFluidHeatTransferPhysics.md] for the fluid energy conservation equation. | ||
| - [WCNSLinearFVScalarTransportPhysics.md] for the advection of passive scalars. | ||
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| For `LinearWCNSFV2P`, the relevant `Physics` classes are: | ||
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| - [WCNSLinearFVTwoPhaseMixturePhysics.md] for a basic implementation of a mixture model. | ||
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| ## Validation | ||
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| The linear finite volume implementation is being verified and validated as part of the `OpenPronghorn` open-source software. | ||
| Please refer to [OpenPronghorn](https://mooseframework.inl.gov/open_pronghorn/) for this ongoing effort. | ||
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| ## Gallery | ||
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| !alert construction | ||
| The gallery has not been created for this finite volume implementation yet. | ||
| Please refer to [OpenPronghorn](https://mooseframework.inl.gov/open_pronghorn/) for example simulations. |
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it might be more accurate/clearer to introduce an additional column called "solver" and then discretization would remain just "FV" for the linear FV implementation and solver would be "SIMPLE/PIMPLE"
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linearFV is kind of different though, not just the solver? like the base classes for the variables are similar but different
like some items that are "discretization"-related such as "two term expansions" are decided in a different place (variables & kernels) in nonlinearFV and linearFV
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Those are implementation details that are not relevant to a user. Real differences are things like lagging certain quantities in order to keep them linear. I don't know if that is really a difference in the spatial discretization though. More like a state difference
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well we do lag a ton more in linearFV than in Newton. In fact we try not to lag anything in Newton
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but that's all tied to the solver / discretization in time rather than in space
the gradients are lagged in linearFV and not FV that's a space-time discretization that is different
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I know that. That's why I said
I wrote a very large share of the Newton code. I know how it works.
Agreed. That's why I said
If the spatial locations used to evaluate things like a Green-Gauss gradient or the non-orthogonal gradient are the same, then I believe the spatial discretization is the same. If the only difference is that you're indexing into different vectors (states), I don't think that equates to a difference in spatial discretization
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The iterative two term expansions are something that are unique to FV.
It is tied to not wanting to lag though
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@grmnptr any differences on that aspect?