Gradient discretisation method: Difference between revisions

Revision as of 07:51, 11 July 2018

Revision as of 17:55, 2 March 2019

Line 1:

<!-- {{more footnotes|date=March 2017}} answer and improvement completed by Cyclotourist -->

[[Image:Plaplacien4.svg|thumb|right|400px|Exact solution </br> <math>\overline{u}(x) = \frac 3 4 \big({0.5}^{4/3}- |x - 0.5|^{4/3}\big)</math> </br>

of the ''p''-Laplace problem <math>-( |\overline{u}'|^2 \overline{u}')'(x) = 1</math> on the ___domain [0,1] with <math>\overline{u}(0) = \overline{u}(1) = 0</math>

(black line) and approximate one (blue line) computed with the first degree discontinuous Galerkin method plugged into the GDM (uniform mesh with 6 elements).]]

{{Differential equations}}

In numerical mathematics, the '''gradient discretisation method''' ('''GDM''') is a framework which contains classical and recent numerical schemes for diffusion problems of various kinds: linear or non-linear, steady-state or time-dependent. The schemes may be conforming or non-conforming, and may rely on very general polygonal or polyhedral meshes (or may even be meshless).