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2ª aula. Evolution Equation . The Finite Volume Method . . Objective of the lecture. The Students “ mise à zero” as francophone say. To show that the conservation principle can be written on: Words (is a concept) Integral equation form, Differential form (can have analytical solution),

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2 aula

2ª aula


TheFinite Volume Method.

objective of the lecture
Objective of the lecture
  • The Students “mise à zero” as francophone say.
  • To show that the conservation principle can be written on:
    • Words (is a concept)
    • Integral equation form,
    • Differential form (can have analytical solution),
    • Algebraic form (used by mathematical models).
  • To recall methods to solve advection. Temporal discretisation, stability and numerical diffusion.
  • To tell about the need for initial and boundary conditions and about the difficulties to get them.
the integral equation
The Integral Equation
  • Accumulation Rate:
  • Fluxes:
    • Advective: (Why the sign “-”)?
    • Diffusive:
differential evolution equation
Differential Evolution Equation


The rate of accumulation is “minus” the divergence of the fluxes + (Souces-Sinks)

finite volume
Finite Volume

The Finite (Control) Volume :

1) isolates a portion of the space,

2) systematises budgets’ computation across its faces,

3) Computes the rate of accumulation,

4) Permits the computation of a property rate of change.

finite volume in a 1d case
Finite Volume in a 1D case

In 1D case properties can change along one direction only.

shrinking the volume to zero
Shrinkingthe volume to zero

Knowing that:

And assuming that the volume is a parallelepiped that doesn’t change in time:

That is the 1D advection-diffusion equation for one property. In a 3D case, for a generic property “k” one would get:

That represents the conservation principle in one point

explicit central differences
Explicit Central Differences


understanding the central differences
Understandingthe Central Differences
  • Why are CD instable without diffusion?
    • Resp: They violate the transportive property of advection. The computing point learns about the downstream property value through advection, which is physically impossible.
    • Why can bestablewithdiffusion
      • Resp: Because diffusion transports information in any direction. If the diffusive transport is stronger than advective, the process becomes physically correct.
more questions
More Questions
  • Can explicit central differrences be used on advection is dominant?
    • Resp: No. In that case difusion transports upstream much less than advection transport downstream (Grid Reynolds number is large).
  • If diffusion is dominant is better to use centra differences or upwind?
    • Central differences are better they have second order accuracy and introduce less numerical diffusion.
  • What about an implicit algorithm? Would it be stable without diffusion?
    • Resp: Yes. In implicit algorithms fluxes are computed using the new concentrations. If Advection would generate negative concentrations the leaving flux would become positive. Thos means that it is impossible to generate negative concentrations.
  • Even in upwind?
    • Resp: In upwind case the concentration can become negative only if we remove from a volume more than its content. But since what is leaving the volume is computed at the end of the time step negative values can not be generated.
other methods for advection
Othermethods for advection
  • Upwind: Assumes that the concentration at the face is equal to the upstream concentration.
  • Central Differences: Assume the average between both sides.
  • What if a 2nd order polynom was considered (using 3 points)? One would get the QUICK: (Quadratic Upstream Interpolation for Convective Kinematics):
  • It has 3rd order accuracy. It has increased stability problems next to boundaries.
  • What is the best method?
initial and boundary conditions




  • Initialconditions are lessimportant in dissipativesystems (highsinks).
  • Boundaryconditions are lessimportantwhenSourcesand/orsinks are important?
boundary conditions
  • Diffusion:
    • Requires the knowledge of concentrations outside the domain. If not known zero gradient is usually the best option
  • Advection
    • When the flow enters the domain carries information from outside that must be known.
how to know the external boundary condition
How to know the external boundary condition?
  • Gradients can be considered null if sources and sinks are important.
  • Otherwise nested models are required!
  • The finite control volume helps us to think about fluxes. That is usually good..
  • Explicit methods get instable when the amount removed from a volume is higher than the volume contained inside.
  • Central differences assume linear concentration evolution between adjacent finite volumes. They cannot respect the transportive property of advection.
  • The QUICK method assume a quadratic evolution between adjacent centres. Requires three points and consequently cannot be used next to boundaries. It does not respect completely the transportive property and can generate instabilities. It is better if combined with upwind.
  • The finite volume method puts into evidence the advantage of combining methods for advection.
  • Initial and boundary conditions choice determine the quality of the results.