Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Random walk algorithms for solving nonlinear chemotaxis problems. / Sabelfeld, Karl K.; Bukhasheev, Oleg.
в: Monte Carlo Methods and Applications, Том 30, № 3, 03.08.2024, стр. 235-248.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Random walk algorithms for solving nonlinear chemotaxis problems
AU - Sabelfeld, Karl K.
AU - Bukhasheev, Oleg
PY - 2024/8/3
Y1 - 2024/8/3
N2 - Random walk based stochastic simulation methods for solving a nonlinear system of coupled transient diffusion and drift-diffusion equations governing a two-component chemotaxis process are developed. The nonlinear system is solved by linearization, the system is evolved in time, by small time steps, where on each step a linear system of equations is solved by using the solution from the previous time step. Three different stochastic algorithms are suggested, (1) the global random walk on grid (GRWG), (2) a randomized vector algorithm (RVA) based on a special transformation of the original matrix to a stochastic matrix, and (3) a stochastic projection algorithm (SPA). To get high precision results, these methods are combined with an iterative refinement method.
AB - Random walk based stochastic simulation methods for solving a nonlinear system of coupled transient diffusion and drift-diffusion equations governing a two-component chemotaxis process are developed. The nonlinear system is solved by linearization, the system is evolved in time, by small time steps, where on each step a linear system of equations is solved by using the solution from the previous time step. Three different stochastic algorithms are suggested, (1) the global random walk on grid (GRWG), (2) a randomized vector algorithm (RVA) based on a special transformation of the original matrix to a stochastic matrix, and (3) a stochastic projection algorithm (SPA). To get high precision results, these methods are combined with an iterative refinement method.
KW - Chemotaxis process
KW - Keller–Segel equation
KW - global random walk on grid
KW - randomized vector linear solver
KW - stochastic projection method
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85200321019&origin=inward&txGid=429bf044df98d2c1beb2d619f7948c9
UR - https://www.mendeley.com/catalogue/b67f3e9f-271d-3af3-a918-888154098954/
U2 - 10.1515/mcma-2024-2008
DO - 10.1515/mcma-2024-2008
M3 - Article
VL - 30
SP - 235
EP - 248
JO - Monte Carlo Methods and Applications
JF - Monte Carlo Methods and Applications
SN - 0929-9629
IS - 3
ER -
ID: 60848767