Experimental methods in chemical engineering: Computational fluid dynamics/finite volume method—CFD/FVM

计算流体力学 湍流 有限体积法 流体力学 流量(数学) 压缩性 计算机科学 机械 物理
作者
Laurens Van Hoecke,Dieter Boeye,Arturo González‐Quiroga,Gregory S. Patience,Patrice Perreault
出处
期刊:Canadian Journal of Chemical Engineering [Wiley]
卷期号:101 (2): 545-561 被引量:15
标识
DOI:10.1002/cjce.24571
摘要

Abstract Computational fluid dynamics (CFD) applies numerical methods to solve transport phenomena problems. These include, for example, problems related to fluid flow comprising the Navier–Stokes transport equations for either compressible or incompressible fluids, together with turbulence models and continuity equations for single and multi‐component (reacting and inert) systems. The design space is first segmented into discrete volume elements (meshing). The finite volume method, the subject of this article, discretizes the equations in time and space to produce a set of non‐linear algebraic expressions that are assigned to each volume element—cell. The system of equations is solved iteratively with algorithms like the semi‐implicit method for pressure‐linked equations (SIMPLE) and the pressure implicit splitting of operators (PISO). CFD is especially useful for testing multiple design elements because it is often faster and cheaper than experiments. The downside is that this numerical method is based on models that require validation to check their accuracy. According to a bibliometric analysis, the broad research domains in chemical engineering include: (1) dynamics and CFD‐DEM, (2) fluid flow, heat transfer, and turbulence, (3) mass transfer and combustion, (4) ventilation and the environment, and (5) design and optimization. Here, we review the basic theoretical concepts of CFD and illustrate how to set up a problem in the open‐source software OpenFOAM to isomerize n ‐butane to i ‐butane in a notched reactor under turbulent conditions. We simulated the problem with 1000, 4000, and 16 000 cells. According to the Richardson extrapolation, the simulation underestimates the adiabatic temperature rise by 7% with 16 000 cells.
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