Statistical and probabilistic modeling of a cloud of particles coupled with a turbulent fluid

Ludovic Goudenège, Adam Larat, J. Llobell, M. Massot, David Mercier, O. Thomine, Aymeric Vi'e FR3487, Bacchus, Coffee, EM2C, Cealeti, Coria
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Abstract

This paper exposes a novel exploratory formalism, the end goal of which is the numerical simulation of the dynamics of a cloud of particles weakly or strongly coupled with a turbulent fluid. Given the large panel of expertise of the list of authors, the content of this paper scans a wide range of connex notions, from the physics of turbulence to the rigorous definition of stochastic processes. Our approach is to develop reduced-order models for the dynamics of both carrying and carried phases which remain consistant within this formalism, and to set up a numerical process to validate these models. The novelties of this paper lie in the gathering of a large panel of mathematical and physical definitions and results within a common framework and an agreed vocabulary (sections 1 and 2), and in some preliminary results and achievements within this context, section 3. While the first three sections have been simplified to the context of a gas field providing that the disperse phase only retrieves energy through drag, the fourth section opens this study to the more complex situation when the disperse phase interacts with the continuous phase as well, in an energy conservative manner. This will allow us to expose the perspectives of the project and to conclude.
与湍流耦合的粒子云的统计和概率建模
本文提出了一种新的探索性形式,其最终目标是对与湍流弱耦合或强耦合的粒子云的动力学进行数值模拟。鉴于作者名单上的大量专业知识,本文的内容扫描了广泛的连接概念,从湍流物理学到随机过程的严格定义。我们的方法是为在这种形式中保持一致的携带和携带阶段的动力学开发降阶模型,并建立一个数值过程来验证这些模型。本文的新颖之处在于在一个共同的框架和商定的词汇中收集了大量的数学和物理定义和结果(第1节和第2节),以及在此背景下的一些初步结果和成就(第3节)。前三个部分已经简化为气田的背景,即分散相仅通过阻力回收能量,而第四部分将本研究打开到更复杂的情况,即分散相也与连续相以能量保守的方式相互作用。这将使我们能够展示项目的观点并得出结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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