zoomy_core.symsolver.discretization.reconstruction

`zoomy_core.symsolver.discretization.reconstruction`#

Face reconstruction of the solver templates: order 1 takes cell values of the reconstruction variables W(Q) to the faces, order 2 a limited LSQ gradient, and the inverse map recovers Q. Nothing is clipped: face positivity is the flux kernel’s, cell positivity MOOD’s.

Module Contents#

Functions#

`reconstruct`	Face traces `(QL, QR)` of order 1 (cell values) or 2 (limited LSQ gradient); `QR` on a boundary face is a placeholder for the BC value.
`maps`	`(W(Q), Q(W))` kernels, or `(None, None)` when `Q` itself is reconstructed.
`bed_rows`	`(bed, depth)` rows when the reconstruction is the pair (h, eta = b + h) with `bed=BedReconstruction.derived`, else None.
`limited`	Limiter factor per row and cell (the NSM’s limiter, per-row overrides, then ties), 1 where no row is limited.

Data#

LIMITERS

API#

zoomy_core.symsolver.discretization.reconstruction.LIMITERS#: None

zoomy_core.symsolver.discretization.reconstruction.reconstruct(nsm, Q, Qaux, p, time, order, demote, mesh)#

Face traces (QL, QR) of order 1 (cell values) or 2 (limited LSQ gradient); QR on a boundary face is a placeholder for the BC value.

Args

demote: False none, True all cells, or a cell mask; demoted cells are constant in W (MOOD).

References

van Leer 1979, https://doi.org/10.1016/0021-9991(79)90145-1
Mavriplis 2003, https://doi.org/10.2514/6.2003-3986

zoomy_core.symsolver.discretization.reconstruction.maps(nsm)#: (W(Q), Q(W)) kernels, or (None, None) when Q itself is reconstructed.

zoomy_core.symsolver.discretization.reconstruction.bed_rows(nsm)#

(bed, depth) rows when the reconstruction is the pair (h, eta = b + h) with bed=BedReconstruction.derived, else None.