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  2. Finite difference coefficient - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_coefficient

    Backward finite difference [ edit ] To get the coefficients of the backward approximations from those of the forward ones, give all odd derivatives listed in the table in the previous section the opposite sign, whereas for even derivatives the signs stay the same.

  3. Finite difference - Wikipedia

    en.wikipedia.org/wiki/Finite_difference

    In an analogous way, one can obtain finite difference approximations to higher order derivatives and differential operators. For example, by using the above central difference formula for f ′(x + ⁠ h / 2 ⁠) and f ′(x − ⁠ h / 2 ⁠) and applying a central difference formula for the derivative of f ′ at x, we obtain the central difference approximation of the second derivative of f:

  4. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    The method is based on finite differences where the differentiation operators exhibit summation-by-parts properties. Typically, these operators consist of differentiation matrices with central difference stencils in the interior with carefully chosen one-sided boundary stencils designed to mimic integration-by-parts in the discrete setting.

  5. Difference quotient - Wikipedia

    en.wikipedia.org/wiki/Difference_quotient

    The difference between two points, themselves, is known as their Delta (ΔP), as is the difference in their function result, the particular notation being determined by the direction of formation: Forward difference: ΔF(P) = F(P + ΔP) − F(P); Central difference: δF(P) = F(P + ⁠ 1 / 2 ⁠ ΔP) − F(P − ⁠ 1 / 2 ⁠ ΔP);

  6. MacCormack method - Wikipedia

    en.wikipedia.org/wiki/MacCormack_method

    The order of differencing can be reversed for the time step (i.e., forward/backward followed by backward/forward). For nonlinear equations, this procedure provides the best results. For linear equations, the MacCormack scheme is equivalent to the Lax–Wendroff method. [4]

  7. FTCS scheme - Wikipedia

    en.wikipedia.org/wiki/FTCS_scheme

    In numerical analysis, the FTCS (forward time-centered space) method is a finite difference method used for numerically solving the heat equation and similar parabolic partial differential equations. [1] It is a first-order method in time, explicit in time, and is conditionally stable when applied to the heat equation.

  8. Explicit and implicit methods - Wikipedia

    en.wikipedia.org/wiki/Explicit_and_implicit_methods

    Forward-Backward Euler method The result of applying both the Forward Euler method and the Forward-Backward Euler method for = and =. In order to apply the IMEX-scheme, consider a slightly different differential equation:

  9. Discretization of Navier–Stokes equations - Wikipedia

    en.wikipedia.org/wiki/Discretization_of_Navier...

    The goal at this point is to determine expressions for the face-values for u, v, and P and to approximate the derivatives using finite difference approximations. For this example we will use backward difference for the time derivative and central difference for the spatial derivatives.