4.6 Article

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

期刊

CHEMICAL ENGINEERING SCIENCE
卷 144, 期 -, 页码 165-175

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2016.01.037

关键词

Wavelet based transformation; Random surrogates; Kinetic Monte Carlo; Temporal upscaling; Multiscale modeling of catalysis

资金

  1. Laboratory Directed Research and Development Program of Oak Ridge National Laboratory

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We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which can be linked to the continuum scale simulation. We illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions. (C) 2016 Elsevier Ltd. All rights reserved.

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