ME/AE 339 Computational Fluid Dynamics K. M. Isaac Topic2_PDE

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ME/AE 339 Computational Fluid Dynamics K. M. Isaac Topic2_PDE 11/28/2018 topic2_PDE

Partial Differential Equations (PDE) (CLW: 7.1, 7.3, 7.4) Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Partial Differential Equations (PDE) (CLW: 7.1, 7.3, 7.4) PDE’s can be linear or nonlinear Order : Determined by the order of the highest derivative. Linear, 2nd order PDE’s are classified as the elliptic, hyperbolic Parabolic type. Example: 11/28/2018 topic2_PDE

u is the dependent variable and x, y, z are the independent variables. Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Coefficients May be +1, -1 or zero. u is the dependent variable and x, y, z are the independent variables. Note that we do not have any cross-derivative terms. Classification: Elliptic: are non-zero and have the same sign, then PDE is of the elliptic type. 11/28/2018 topic2_PDE

are non-zero and of mixed sign, the PDE is hyperbolic Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Hyperbolic: are non-zero and of mixed sign, the PDE is hyperbolic Parabolic: If one of A1, A2, A3, say A2 is zero and the rest are of the same sign, and if B2 is non-zero, the PDE is parabolic. Since Ai, Bi, C and D may be functions of x, y and z, the classification may depend on position in space. In many CFD problems, one of the independent variables will be time and the rest will be space coordinates such as x, y, z or or transformed variables such as x, h, z. 11/28/2018 topic2_PDE

Two-Dimensional Examples Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Two-Dimensional Examples Elliptic Hyperbolic Parabolic 11/28/2018 topic2_PDE

Numerical solution of PDE requires a finite number of points to Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Numerical solution of PDE requires a finite number of points to Descretize the equations. Examples: See Figure in the next slide. 11/28/2018 topic2_PDE

Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR 11/28/2018 topic2_PDE

between nodes along x, y, t coordinate directions. Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Solution requires initial and boundary conditions depending on the Problem. Indices i, j, n can be used to label the nodes in x, y, t directions(see fig.) If the origin has i=0, j=0 and n = 0, then the node i, j, n has coordinates where are the uniform intervals between nodes along x, y, t coordinate directions. Let be the exact solution of the PDE and be the approximations to be determined at each grid point. 11/28/2018 topic2_PDE

The derivatives of the original PDE are approximated using the symbol Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR The derivatives of the original PDE are approximated using the symbol and the discretization intervals The procedure leads to a set of algebraic equations of which are then solved. Fine grids can be used to obtain solutions that are close to Examples of PDE’s common in engineering 1.Unsteady heat conduction equation 1D form: 11/28/2018 topic2_PDE

T - temperature k - thermal conductivity r - density Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR T - temperature k - thermal conductivity r - density cp - specific heat If k is a constant, the equation becomes Where is the thermal diffusivity. 11/28/2018 topic2_PDE

, Let In CFD , normalization of variables are often used to improve Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR In CFD , normalization of variables are often used to improve the solution (for proper scaling of the variables). Let , for heat conduction in a rod of length L. Figure. The PDE then becomes It is also possible to non-dimensionalize the dependent variable T. 11/28/2018 topic2_PDE

Taylor series is as follows. (1) Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Taylor’s Expansion. Let Taylor series is as follows. (1) (2) Where 11/28/2018 topic2_PDE

The higher order derivatives in Eq.(2) can be determined by Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR The higher order derivatives in Eq.(2) can be determined by Differentiating Eq.(1) by chain rule. i. e., Example 1 : f(x,y) is a function of x alone. 11/28/2018 topic2_PDE

Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR 11/28/2018 topic2_PDE

The function at the neighboring point (x = x0+h) becomes Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR The function at the neighboring point (x = x0+h) becomes Example 2: f(x,y) is a function of y alone. 11/28/2018 topic2_PDE

Similarly Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Similarly 11/28/2018 topic2_PDE

Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR 11/28/2018 topic2_PDE

Taylor series can also be used for non-linear higher order equations. Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Taylor series can also be used for non-linear higher order equations. Example: 11/28/2018 topic2_PDE

Consider the initial conditions Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Consider the initial conditions At 11/28/2018 topic2_PDE

Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR 11/28/2018 topic2_PDE

Since Taylor series gives Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Since Taylor series gives For k = 0, y1 becomes Letting h=0.1, we get 11/28/2018 topic2_PDE

by differentiating the expression for Computational Fluid Dynamics (AE/ME 339) K. M. Isaac PDE MAEEM Dept., UMR Calculation of y2 Need Calculate by differentiating the expression for w.r.t. h. etc. can now be calculated as before and can be obtained. 11/28/2018 topic2_PDE

Program Completed University of Missouri-Rolla Copyright 2002 Curators of University of Missouri 11/28/2018 topic2_PDE