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International Journal for Multiscale Computational Engineering
Fator do impacto: 1.016 FI de cinco anos: 1.194 SJR: 0.554 SNIP: 0.82 CiteScore™: 2

ISSN Imprimir: 1543-1649
ISSN On-line: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.v4.i5-6.100
pages 755-770

Wavelet-based Spatiotemporal Multiscaling in Diffusion Problems with Chemically Reactive Boundary

George Frantziskonis
Department of Civil Engineering and Engineering Mechanics, and Department of Material Science and Engineering, University of Arizona, USA
Sudib Kumar Mishra
Sreekanth Pannala
Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Srdjan Simunovic
Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
C. Stuart Daw
Computer Science & Mathematics Division, Oak Ridge National Laboratory
Phani Nukala
Computer Science & Mathematics Division, Oak Ridge National Laboratory
Rodney O. Fox
Department of Chemical and Biological Engineering Iowa State University Ames, IA USA
Pierre A. Deymier
Department of Material Science and Engineering, University of Arizona, Tucson, Arizona 85721, USA

RESUMO

Chemically reacting flows over catalytic and noncatalytic surfaces are one of the elementary operations in chemical processing plants. The underlying physical phenomena span time and length scales over several orders of magnitude, which a robust and flexible modeling framework must efficiently account for. With this purpose as the eventual goal, we propose a wavelet-based multiscale numerical framework and demonstrate it on the coupling of two prototype methods for the problem of species generated on a chemically reactive boundary and diffusing through the bulk. The two methods consider different time and length scales. The first method in this coupling, termed "fine," models the chemical reactions on the reactive boundary stochastically by the kinetic Monte Carlo method and the diffusion in the medium deterministically using relatively small time increments and small spatial discretization mesh size. The second method, termed "coarse," models both the reaction and the diffusion deterministically and uses drastically larger time increments and spatial discretization size than the fine model. The two methods are coupled by forming a spatiotemporal compound wavelet matrix that combines information about the time and spatial scales contained in them.


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