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We discuss a class of particle methods for diffusion problems with small diffusivity, in which diffusion is modeled by random walk update of the particle positions; each particle carries a point-value of the problem's initial data; and the numerical solution is obtained as a discrete convolution of the particle data with an approximate δ-function.
The difficulties related to numerical fluxes of DG methods for diffusion problems have been a major issue of investigation in the literature.
Since spatial simulations are mainly dominated by diffusion, the largest gain in efficiency may come with implementing approximate methods for diffusion.
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We developed a new monotone finite volume method for diffusion equations.
A new geometrical method for diffusion estimation in binary liquids is derived and validated.
An interpolation method for diffusion in anisotropic discontinuous media based on convex combinations and physical relationships is presented.
This paper discusses issues encountered by the hyperbolic method for diffusion (Nishikawa, 2007) [1] in dimensional heat conduction problems, and proposes a practical resolution.
Following the direct discontinuous Galerkin (DDG) method introduced by Liu and Yan [H. Liu, J. Yan, The direct discontinuous Galerkin (DDG) method for diffusion with interface corrections, Commun. Comput. Phys.
Therefore, more research on the information diffusion patterns and mechanisms is needed, as well as proper modeling and analysis methods for information diffusion in financial networks.
In the literature, there are many methods for predicting diffusion coefficients of gases in hydrocarbon systems.
Specifically, this paper investigates alternative methods for integrating diffusion as well as extending the model to nonhydrostatic flow.
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