scholarly journals Parallel calculation of the stationary diffusion equation

2020 ◽  
Vol 1689 ◽  
pp. 012074
Author(s):  
E O Soldatov ◽  
Yu N Volkov ◽  
M N Zizin
2017 ◽  
Vol 22 (11) ◽  
pp. 0-0 ◽  
Author(s):  
Vo Anh Khoa ◽  
◽  
Thi Kim Thoa Thieu ◽  
Ekeoma Rowland Ijioma ◽  
◽  
...  

2021 ◽  
Vol 247 ◽  
pp. 14005
Author(s):  
B. Ganapol ◽  
P. Tsvetkov

In many nuclear reactor physics texts (excluding Elmer Lewis’s recent text however), “Chapter 5” is dedicated to diffusion theory; hence, the title of this submission. Here, we will investigate analytical solutions to the most basic form of the monoenergetic 1D stationary diffusion equation. The intuitive approach taken radically departs from the usual method of solving the diffusion equation. In particular, we consider a general setting such that the method accommodates all solutions to the monoenergetic diffusion equations in 1D plane and curvilinear geometries. This is not your father’s diffusion theory and, for this reason, we anticipate it will eventually become the classroom standard.


Author(s):  
U. Dobramysl ◽  
D. Holcman

We develop a computational approach to locate the source of a steady-state gradient of diffusing particles from the fluxes through narrow windows distributed either on the boundary of a three-dimensional half-space or on a sphere. This approach is based on solving the mixed boundary stationary diffusion equation with Neumann–Green’s function. The method of matched asymptotic expansions enables the computation of the probability fluxes. To explore the range of validity of this expansion, we develop a fast analytical-Brownian numerical scheme. This scheme accelerates the simulation time by avoiding the explicit computation of Brownian trajectories in the infinite domain. The results obtained from our derived analytical formulae and the fast numerical simulation scheme agree on a large range of parameters. Using the analytical representation of the particle fluxes, we show how to reconstruct the location of the point source. Furthermore, we investigate the uncertainty in the source reconstruction due to additive fluctuations present in the fluxes. We also study the influence of various window configurations: clustered versus uniform distributions on recovering the source position. Finally, we discuss possible applications for cell navigation in biology.


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