Concept

Upwinding — where it appears

Differencing a convection term in the direction the flow comes from, which is central differencing at a larger diffusion and produces an M-matrix. It buys an unconditionally non-oscillatory answer at the price of solving a problem with more diffusion than the one posed, and the price is a modelling error rather than a rounding one.

Named by 4 essays across 2 fields — each of them below, with the objects they name alongside it.

Péclet 100centred nodal edge at 1,0008.9upwind nodal edge at 1,0006.8upwind weighted edge at 1,000-0.45110¹10²10³-202468largest cell over smallestright edge of the numerical rangecentred, nodalupwind, nodalcentred, weightedupwind, weightedabove the dashed line the certificate is goneupwinding lowers the line and does not cross it

The smaller cell downstream

Nodal values on a convection–diffusion mesh graded towards its outflow layer put the numerical range in the right half plane, and Galerkin reduced models then fail. A code that grades towards the layer usually also upwinds, and upwinding adds diffusion. It does not give the certificate back: at Péclet 100 and a grading of a thousand the range's edge falls from 8.94 to 6.78 and stays positive, and 18 reduced models fail where 23 did. Each row of the upwind stencil's symmetric part sums to half the difference between the inverse widths of the cell after the node and the cell before it, so wherever the cells shrink downstream the dissipation upwinding adds is outweighed by the coupling to the smaller cell next door.

reduction · Reduced stability
05101520253035404510⁻¹⁷10⁻¹⁴10⁻¹¹10⁻⁸10⁻⁵10⁻²angle between the flow and the grid (degrees)worst nodal errortunedcentralupwindexact, and then nottuned, on the axis2.4·10⁻¹⁷tuned, five degrees off0.0079tuned at 45°0.066upwind at 45°0.0019fifteen orders of magnitude for five degreesand the worst of the three by forty-five

Exact along one axis

The tuned diffusion makes the answer exact at every node, and in two dimensions it holds at exactly one flow angle. Five degrees off the grid the relative error goes from 1.2·10⁻¹⁴ to 6.9, and by twenty degrees the scheme is worse than the upwinding it was built to improve on.

iterative · Convection
worst nodal error, and nodes outside the interval the equation guarantees0°, streamline only2.39·10⁻¹⁷ · 0 outside0°, with crosswind5.25·10⁻¹⁷ · 0 outside15°, streamline only0.032 · 18 outside15°, with crosswind0.0145 · 9 outside30°, streamline only0.0571 · 50 outside30°, with crosswind0.0247 · 11 outside45°, streamline only0.0661 · 48 outside45°, with crosswind0.0281 · 0 outsidewhat the crosswind term buyserror ratio at 0°0.45error ratio at 15°2.2error ratio at 30°2.3error ratio at 45°2.3free where the scheme was exactand half the error everywhere else

The direction the diffusion does not go

Streamline diffusion adds τbbᵀ, a rank-one tensor that annihilates every direction across the flow. That is the design. The price is 18, 50 and 48 nodes where the computed solution leaves the interval the equation guarantees — and half a coefficient of crosswind diffusion halves the error at every angle while costing exactly nothing where the scheme was exact.

iterative · Convection
Péclet 100, ratio 1000centred edge8.9upwind edge6.8cell Péclet at upwind peak0.5800.20.40.60.81node position xweight of the edge eigenvectorcell Péclet onecentredupwindthirty interior nodes; the outflow layer is at x = 1where diffusion and convection meet

The edge sits where the cells meet the flow

On a convection–diffusion mesh graded towards its outflow, the nodal numerical range reaches into the right half plane, and Galerkin reduced models fail. The account was that the edge lives in the cells where diffusion and convection are comparable, and drawing the eigenvector that attains it says the account is right: on every operator whose mesh has a cell Péclet number above one, the eigenvector peaks where that number is between a half and one and a quarter, just downstream of where it crosses one, and the outflow layer's five smallest cells hold under four per cent of it. The other question has a short answer too. A one-sided stencil scaled by a cell width is dissipative in nodal coordinates only if its weights do not grow downstream, and a consistent one must grow there: the only dissipative weight is the constant one, which is wrong by up to four units of the derivative.

reduction · Reduced stability

Named alongside it

The objects these essays reach for when they reach for this one.

Convection diffusionPeclet numberArtificial diffusionBoundary layerGalerkin projectionGrid alignmentMass matrixNon-normalityNumerical rangeReduced stabilityStreamline diffusionAnisotropy

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