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Chapter 8 Configuring Fluidity - The Applied Modelling and ...

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28 Numerical discretisation<br />

where we have substituted c = �<br />

j ϕjcj. From this it is readily seen that we have in fact obtained a<br />

matrix equation of the following form<br />

where M, A <strong>and</strong> K are the following matrices<br />

�<br />

Mij =<br />

3.2.1.3 Advective stabilisation for CG<br />

Ω<br />

M dc<br />

+ A(u)c + Kc = 0, (3.8)<br />

dt<br />

�<br />

�<br />

ϕiϕj, Aij = − ∇ϕi · uϕj, Kij = ∇ϕi · µ · ∇ϕj. (3.9)<br />

Ω<br />

Ω<br />

It is well known that a continuous Galerkin discretisation of an advection-diffusion equation for an<br />

advection dominated flow can suffer from over- <strong>and</strong> under-shoot errors. Furthermore, these overshoot<br />

errors are not localised: they can propagate throughout the simulation domain <strong>and</strong> pollute the<br />

global solution [Hughes, 1987]. Consider a simple 1D linear steady-state advection-diffusion problem<br />

for a single scalar c:<br />

or equivalently in weak form:<br />

�<br />

Ω<br />

u ∂c<br />

∂x − κ ∂2c = f(x), (3.10)<br />

∂x2 ϕ(u ∂c<br />

∂x<br />

∂c<br />

+ κ∂ϕ − f(x)) = 0, (3.11)<br />

∂x ∂x<br />

where we have integrated by parts <strong>and</strong> applied the natural Neumann boundary condition ∂c/∂x =<br />

0 on ∂Ω. Discretising (3.11) with a continuous Galerkin method leads to truncation errors in the<br />

advection term equivalent to a negative diffusivity term of magnitude [Donea <strong>and</strong> Huerta, 2003]:<br />

where:<br />

<strong>and</strong>:<br />

ξ =<br />

is a grid Péclet number, with grid spacing h.<br />

¯κ = ξκPe, (3.12)<br />

1 1<br />

− , (3.13)<br />

tanh(Pe) Pe<br />

Pe = uh<br />

, (3.14)<br />

2κ<br />

This implicit negative diffusivity becomes equal to the explicit diffusivity at a Péclet greater than one,<br />

<strong>and</strong> hence instability occurs for Pe � 1. In order to achieve a stable discretisation using a continuous<br />

Galerkin method one is therefore required either to increase the model resolution so as to reduce the<br />

grid Péclet number, or to apply advective stabilisation methods.<br />

Balancing diffusion A simple way to stabilise the system is to add an extra diffusivity of equal<br />

magnitude to that introduced by the discretisation of the advection term, but of opposite sign. This<br />

method is referred to as balancing diffusion. Note, however, that for two or more dimensions, we<br />

require this balancing diffusion to apply in the along-stream direction only [Brooks <strong>and</strong> Hughes,<br />

1982, Donea <strong>and</strong> Huerta, 2003]. For this reason this method is also referred to as streamline-upwind<br />

stabilisation. <strong>The</strong> multidimensional weak-form equation:<br />

�<br />

ϕ(u · ∇c + κ∇ϕ∇c − f(x)) = 0, (3.15)<br />

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