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  2. Crank–Nicolson method - Wikipedia

    en.wikipedia.org/wiki/Crank–Nicolson_method

    The Crank–Nicolson stencil for a 1D problem. The Crank–Nicolson method is based on the trapezoidal rule, giving second-order convergence in time.For linear equations, the trapezoidal rule is equivalent to the implicit midpoint method [citation needed] —the simplest example of a Gauss–Legendre implicit Runge–Kutta method—which also has the property of being a geometric integrator.

  3. Finite volume method for two dimensional diffusion problem

    en.wikipedia.org/wiki/Finite_volume_method_for...

    The methods used for solving two dimensional Diffusion problems are similar to those used for one dimensional problems. The general equation for steady diffusion can be easily derived from the general transport equation for property Φ by deleting transient and convective terms [1]

  4. Finite volume method for one-dimensional steady state diffusion

    en.wikipedia.org/wiki/Finite_volume_method_for...

    Discretized equation must be set up at each of the nodal points in order to solve the problem. The resulting system of linear algebraic equations Linear equation can then be solved to obtain at the nodal points. The matrix of higher order can be solved in MATLAB. This method can also be applied to a 2D situation.

  5. Numerical solution of the convection–diffusion equation

    en.wikipedia.org/wiki/Numerical_solution_of_the...

    The unsteady convection–diffusion problem is considered, at first the known temperature T is expanded into a Taylor series with respect to time taking into account its three components. Next, using the convection diffusion equation an equation is obtained from the differentiation of this equation.

  6. Numerical diffusion - Wikipedia

    en.wikipedia.org/wiki/Numerical_diffusion

    Numerical diffusion is a difficulty with computer simulations of continua (such as fluids) wherein the simulated medium exhibits a higher diffusivity than the true medium. . This phenomenon can be particularly egregious when the system should not be diffusive at all, for example an ideal fluid acquiring some spurious viscosity in a numerical mo

  7. Lax–Friedrichs method - Wikipedia

    en.wikipedia.org/wiki/Lax–Friedrichs_method

    One can view the Lax–Friedrichs method as an alternative to Godunov's scheme, where one avoids solving a Riemann problem at each cell interface, at the expense of adding artificial viscosity. Illustration for a Linear Problem

  8. Convection–diffusion equation - Wikipedia

    en.wikipedia.org/wiki/Convection–diffusion...

    The convection–diffusion equation can be derived in a straightforward way [4] from the continuity equation, which states that the rate of change for a scalar quantity in a differential control volume is given by flow and diffusion into and out of that part of the system along with any generation or consumption inside the control volume: + =, where j is the total flux and R is a net ...

  9. Upwind scheme - Wikipedia

    en.wikipedia.org/wiki/Upwind_scheme

    In computational physics, the term advection scheme refers to a class of numerical discretization methods for solving hyperbolic partial differential equations. In the so-called upwind schemes typically, the so-called upstream variables are used to calculate the derivatives in a flow field. That is, derivatives are estimated using a set of data ...