Finite volume method for one dimensional steady state diffusion

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Finite volume method in computational fluid dynamics is a discretization technique for partial differential equations that arise from physical conservation laws. These equations can be different in nature, e.g. elliptic, parabolic, or hyperbolic. First well-documented use was by Evans and Harlow (1957) at Los Alamos. The general equation for steady diffusion can be easily be derived from the general transport equation for property Φ by deleting transient and convective terms.[1]

General Transport equation can be define as

is density and is conservative form of all fluid flow,
is the Diffusion coefficient[2] and is the Source term.[3]
is Net rate of flow of out of fluid element(convection),
is Rate of increase of due to diffusion,
is Rate of increase of due to sources.

is Rate of increase of of fluid element(transient),

Conditions under which the transient and convective terms goes to zero:

For one-dimensional steady state diffusion, General Transport equation reduces to:


The following steps comprehend one dimensional steady state diffusion -

Grid Generation

  • Divide the domain in equal parts of small domain.
  • Place nodal points midway in between each small domain.
    Dividing small domains and assingning nodal points (Figure 1)
  • Create control volume using these nodal points.
Control volume and control volume & boundary faces (Figure 2)
  • Create control volume near the edge in such a way that the physical boundaries coincide with control volume boundaries.(Figure 1)
  • Assume a general nodal point 'P' for a general control volume.Adjacent nodal points in east and west are identified by E and W respectively.The west side face of the control volume is referred to by 'w' and east side control volume face by 'e'.(Figure 2)
Steady state one-dimensional diffusion (Figure 3)


Control volume width (Figure 4)
  • The crux of Finite volume method is to integrate governing equation all over control volume, known discretization.
  • Nodal points used to discretize equations.
  • At nodal point P control volume is defined as (Figure 3)


is Cross-sectional Area Cross section (geometry) of control volume face, is Volume,is average value of source S over control volume

  • In practical situation source term can be linearize

  • Merging above equations leads to

  • Re-arranging

  • Compare and identify above equation with


Solution of equations

  • Discretized equation must be set up at each of the nodal points in order to solve the problem.
  • The resulting system of linear algebraic equation Linear equation is then solved to obtain distribution of the property at the nodal points by any form of matrix solution technique.
  • The matrix of higher order [2] can be solved in MATLAB.


  • Patankar, Suhas V. (1980), Numerical Heat Transfer and Fluid Flow, Hemisphere.
  • Hirsch, C. (1990), Numerical Computation of Internal and External Flows, Volume 2: Computational Methods for Inviscid and Viscous Flows, Wiley.
  • Laney, Culbert B.(1998), Computational Gas Dynamics, Cambridge University Press.
  • LeVeque, Randall(1990), Numerical Methods for Conservation Laws, ETH Lectures in Mathematics Series, Birkhauser-Verlag.
  • Tannehill, John C., et al., (1997), Computational Fluid mechanics and Heat Transfer, 2nd Ed., Taylor and Francis.
  • Wesseling, Pieter(2001), Principles of Computational Fluid Dynamics, Springer-Verlag.
  • Carslaw, H. S. and Jager, J. C. (1959). Conduction of Heat in Solids. Oxford: Clarendon Press
  • Crank, J. (1956). The Mathematics of Diffusion. Oxford: Clarendon Press
  • Thambynayagam, R. K. M (2011). The Diffusion Handbook: Applied Solutions for Engineers: McGraw-Hill

External links

See also