Menu
Home Explore People Places Arts History Plants & Animals Science Life & Culture Technology
On this page
Upwind differencing scheme for convection

The upwind differencing scheme is a method used in numerical methods in computational fluid dynamics for convectiondiffusion problems. This scheme is specific for Peclet number greater than 2 or less than −2

We don't have any images related to Upwind differencing scheme for convection yet.
We don't have any YouTube videos related to Upwind differencing scheme for convection yet.
We don't have any PDF documents related to Upwind differencing scheme for convection yet.
We don't have any Books related to Upwind differencing scheme for convection yet.
We don't have any archived web articles related to Upwind differencing scheme for convection yet.

Description

By taking into account the direction of the flow, the upwind differencing scheme overcomes that inability of the central differencing scheme. This scheme is developed for strong convective flows with suppressed diffusion effects. Also known as ‘Donor Cell’ Differencing Scheme, the convected value of property ϕ {\displaystyle \phi } at the cell face is adopted from the upstream node.

It can be described by Steady convection-diffusion partial Differential Equation:1: 103 2[circular reference] ∂ ∂ t ( ρ ϕ ) + ∇ ⋅ ( ρ u ϕ ) = ∇ ⋅ ( Γ ∇ ϕ ) + S ϕ {\displaystyle {\frac {\partial }{\partial t}}(\rho \phi )+\nabla \cdot (\rho \mathbf {u} \phi )\,=\nabla \cdot (\Gamma \nabla \phi )+S_{\phi }}

Continuity equation: ( ρ u A ) e − ( ρ u A ) w = 0 {\displaystyle \left(\rho uA\right)_{e}-\left(\rho uA\right)_{w}=0\,} 3: 104 4[circular reference]

where ρ {\displaystyle \rho } is density, Γ {\displaystyle \Gamma } is the diffusion coefficient, u {\displaystyle \mathbf {u} } is the velocity vector, ϕ {\displaystyle \phi } is the property to be computed, S ϕ {\displaystyle S_{\phi }} is the source term, and the subscripts e {\displaystyle e} and w {\displaystyle w} refer to the "east" and "west" faces of the cell (see Fig. 1 below).

After discretization, applying continuity equation, and taking source term equals to zero we get5[circular reference]

Central difference discretized equation6: 105 

F e ϕ e − F w ϕ w = D e ( ϕ E − ϕ P ) − D w ( ϕ P − ϕ W ) {\displaystyle F_{e}\phi _{e}-F_{w}\phi _{w}\,=D_{e}(\phi _{E}-\phi _{P})-D_{w}(\phi _{P}-\phi _{W})} 1
F e − F w = 0 {\displaystyle F_{e}-F_{w}\,=0} 2

Lower case denotes the face and upper case denotes node; E {\displaystyle E} , W {\displaystyle W} , and P {\displaystyle P} refer to the "East," "West," and "Central" cell. (again, see Fig. 1 below).

Defining variable F as convection mass flux and variable D as diffusion conductance F = ρ u A {\displaystyle F\,=\rho uA} and D = Γ A δ x {\displaystyle D\,={\frac {\Gamma A}{\delta x}}}

Peclet number (Pe) is a non-dimensional parameter determining the comparative strengths of convection and diffusion

Peclet number: P e = F D = ρ u Γ / δ x {\displaystyle Pe\,={\frac {F}{D}}\,={\frac {\rho u}{\Gamma /\delta x}}}

For a Peclet number of lower value (|Pe| < 2), diffusion is dominant and for this the central difference scheme is used. For other values of the Peclet number, the upwind scheme is used for convection-dominated flows with Peclet number (|Pe| > 2).

For positive flow direction

u w > 0 u e > 0 {\displaystyle {\begin{aligned}u_{w}>0\\u_{e}>0\end{aligned}}} Corresponding upwind scheme equation:7: 115 

F e ϕ P − F w ϕ W = D e ( ϕ E − ϕ P ) − D w ( ϕ P − ϕ W ) {\displaystyle F_{e}\phi _{P}-F_{w}\phi _{W}\,=D_{e}(\phi _{E}-\phi _{P})-D_{w}(\phi _{P}-\phi _{W})} 3

Due to strong convection and suppressed diffusion8: 115  ϕ e = ϕ P ϕ w = ϕ W {\displaystyle {\begin{aligned}\phi _{e}\,=\phi _{P}\\\phi _{w}\,=\phi _{W}\end{aligned}}}

Rearranging equation (3) gives [ ( D w + F w ) + D e + ( F e − F w ) ] ϕ P = ( D w + F w ) ϕ W + D e ϕ E ) {\displaystyle [(D_{w}+F_{w})+D_{e}+(F_{e}-F_{w})]\phi _{P}\,=(D_{w}+F_{w})\phi _{W}+D_{e}\phi _{E})}

Identifying coefficients, a P = [ ( D w + F w ) + D e + ( F e − F w ) ] a W = ( D w + F w ) a E = D e {\displaystyle {\begin{aligned}a_{P}&=[(D_{w}+F_{w})+D_{e}+(F_{e}-F_{w})]\\a_{W}&=(D_{w}+F_{w})\\a_{E}&=D_{e}\end{aligned}}}

For negative flow direction u w < 0 u e < 0 {\displaystyle {\begin{aligned}u_{w}<0\\u_{e}<0\end{aligned}}}

Corresponding upwind scheme equation:9: 115 

F e ϕ E − F w ϕ P = D e ( ϕ E − ϕ P ) − D w ( ϕ P − ϕ W ) {\displaystyle F_{e}\phi _{E}-F_{w}\phi _{P}\,=D_{e}(\phi _{E}-\phi _{P})-D_{w}(\phi _{P}-\phi _{W})} 4

ϕ w = ϕ P ϕ e = ϕ E {\displaystyle {\begin{aligned}\phi _{w}=\phi _{P}\\\phi _{e}=\phi _{E}\end{aligned}}}

Rearranging equation (4) gives [ ( D e − F e ) + D w + ( F e − F w ) ] ϕ P = D w ϕ W + ( D e − F e ) ϕ E {\displaystyle [(D_{e}-F_{e})+D_{w}+(F_{e}-F_{w})]\phi _{P}=D_{w}\phi _{W}+(D_{e}-F_{e})\phi _{E}}

Identifying coefficients, a W = D w a E = D e − F e {\displaystyle {\begin{aligned}a_{W}&=D_{w}\\a_{E}&=D_{e}-F_{e}\end{aligned}}}

We can generalize coefficients as10: 116  a W = D w + max ( F w , 0 ) a E = D e + max ( 0 , − F e ) {\displaystyle {\begin{aligned}a_{W}&=D_{w}+\max(F_{w},0)\\a_{E}&=D_{e}+\max(0,-F_{e})\end{aligned}}}

Use

Solution in the central difference scheme fails to converge for Peclet number greater than 2 which can be overcome by using an upwind scheme to give a reasonable result.11: Fig. 5.5, 5.13  Therefore the upwind differencing scheme is applicable for Pe > 2 for positive flow and Pe < −2 for negative flow. For other values of Pe, this scheme doesn’t give effective solution.

Assessment

Conservativeness12: 118(5.6.1.1) 

The upwind differencing scheme formulation is conservative.

Boundedness13: 118 (5.6.1.2) 

As the coefficients of the discretised equation are always positive hence satisfying the requirements for boundedness and also the coefficient matrix is diagonally dominant therefore no irregularities occur in the solution.

Transportiveness14: 118. (5.6.1.3) 

Transportiveness is built into the formulation as the scheme already accounts for the flow direction.

Accuracy

Based on the backward differencing formula, the accuracy is only first order on the basis of the Taylor series truncation error. It gives error when flow is not aligned with grid lines. Distribution of transported properties become marked giving diffusion-like appearance, called as the false diffusion. Refinement of grid serves in overcoming the issue of false diffusion. With decrease in the grid size, false diffusion decrease thus increasing the accuracy.

See also

References

  1. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  2. Central differencing scheme#Steady-state convection diffusion equation /wiki/Central_differencing_scheme#Steady-state_convection_diffusion_equation

  3. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  4. Central differencing scheme#Formulation of Steady state convection diffusion equation /wiki/Central_differencing_scheme#Formulation_of_Steady_state_convection_diffusion_equation

  5. Central differencing scheme#Formulation of Steady state convection diffusion equation /wiki/Central_differencing_scheme#Formulation_of_Steady_state_convection_diffusion_equation

  6. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  7. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  8. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  9. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  10. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  11. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  12. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  13. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3

  14. Versteeg, H. K.; Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: the Finite Volume Method (2nd ed.). Harlow, England: Pearson Education Ltd. ISBN 978-0-13-127498-3. OCLC 76821177. 978-0-13-127498-3