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Broer–Kaup equations; Burgers' equation; Euler equations; Fokker–Planck equation; Hamilton–Jacobi equation, Hamilton–Jacobi–Bellman equation; Heat equation; Laplace's equation
Please introduce links to this page from ; try the Find link tool for suggestions. ( November 2016 ) The mathematical analysis of partial differential equations uses analytical techniques to study partial differential equations .
Name Dim Equation Applications Landau–Lifshitz model: 1+n = + Magnetic field in solids Lin–Tsien equation: 1+2 + = Liouville equation: any + = Liouville–Bratu–Gelfand equation
PDE-constrained optimization; Perfectly matched layer; Perron method; Petrov–Galerkin method; Phase space method; Poincaré–Lelong equation; Poisson's equation; Population balance equation; Porous medium equation; Potential theory; Primitive equations; Proper orthogonal decomposition; Pseudo-differential operator; Pseudoanalytic function
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FEATool Multiphysics is a fully integrated physics and PDE simulation environment where the modeling process is subdivided into six steps; preprocessing (CAD and geometry modeling), mesh and grid generation, physics and PDE specification, boundary condition specification, solution, and postprocessing and visualization.
In mathematics, a partial differential equation (PDE) is an equation which involves a multivariable function and one or more of its partial derivatives.. The function is often thought of as an "unknown" that solves the equation, similar to how x is thought of as an unknown number solving, e.g., an algebraic equation like x 2 − 3x + 2 = 0.
The Kolmogorov backward equation (KBE) (diffusion) and its adjoint sometimes known as the Kolmogorov forward equation (diffusion) are partial differential equations (PDE) that arise in the theory of continuous-time continuous-state Markov processes. Both were published by Andrey Kolmogorov in 1931. [1]