第3回「次世代エネルギー物質科学の基盤構築」講演会
工学研究科未来工学研究センター研究課題
「革新的低炭素化技術に関する物質科学研究」 第1回講演会
下記のとおり長崎大学第2期中期目標・中期計画重点研究課題 第3回「次世代エネルギー物質科学の基盤構築」講演会を開催致します。万障お繰り合わせの上,ご参加下さい。
工学研究科物質科学部門 森口 勇
時間 | 講演内容 | 講演者 |
---|---|---|
15:00- 16:00 |
「Multiscale Modeling of Chemical Transport」 | University of California Professor Dr. D. M. Tartakovsky |
【Abstract】
- 「Multiscale Modeling of Chemical Transport」
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We present computational techniques for multi-scale modeling of reactive transport. We focus on two ubiquitous challenges: quantifying the effects of crowded environments on heterogeneous chemical reactions and dealing with finite numbers of reacting molecules. Both phenomena often defy continuum representations and might require discreet (pore-scale or particle-based) simulations.
The first challenge is typical of reactive transport in porous media ( e.g., membranes, porous silicon, biological cells) is a complex nonlinear phenomenon that involves both homogeneous (bio-)chemical reactions between species dissolved in a fluid and heterogeneous reactions that occur on liquid-solid interfaces. We establish sufficient conditions under which macroscopic reaction-diffusion equations (RDEs) provide an adequate averaged description of pore-scale processes. These conditions are represented by a phase diagram in a two-dimensional space, which is spanned by Damkohler number and a scale-separation parameter. This phase diagram shows that highly localized phenomena in porous media, including precipitation on (and/or dissolution of) a porous matrix, do not lend themselves to macroscopic (upscaled) descriptions.
The second challenge is posed by chemical reactions involving a small number of molecules. The local numbers of these molecules vary in space and time, and exhibit random fluctuations that can only be captured with stochastic simulations. We present a novel stochastic operator-splitting algorithm to model such reaction-diffusion phenomena. The reaction and diffusion steps employ stochastic simulation algorithms and Brownian dynamics, respectively. Through theoretical analysis, we have developed an algorithm to identify if the system is reaction-controlled, diffusion-controlled or is in an intermediate regime. The time-step size is chosen accordingly at each step of the simulation. We will present several examples to demonstrate the accuracy and robustness of the proposed algorithm.