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Book ChapterDOI

Packed Tubular Reactor Modeling and Catalyst Design using Computational Fluid Dynamics

TLDR
Computational fluid dynamics (CFD) is rapidly becoming a standard tool for the analysis of chemically reacting flows as discussed by the authors, and the application of CFD to the simulation of three-dimensional interstitial flow in packed tubes, with and without catalytic reaction.
Abstract
Computational fluid dynamics (CFD) is rapidly becoming a standard tool for the analysis of chemically reacting flows. For single-phase reactors, such as stirred tanks and “empty” tubes, it is already well-established. For multiphase reactors such as fixed beds, bubble columns, trickle beds and fluidized beds, its use is relatively new, and methods are still under development. The aim of this chapter is to present the application of CFD to the simulation of three-dimensional interstitial flow in packed tubes, with and without catalytic reaction. Although the use of CFD to simulate such geometrically complex flows is too expensive and impractical currently for routine design and control of fixed-bed reactors, the real contribution of CFD in this area is to provide a more fundamental understanding of the transport and reaction phenomena in such reactors. CFD can supply the detailed three-dimensional velocity, species and temperature fields that are needed to improve engineering approaches. In particular, this chapter considers the development of CFD methods for packed tube simulation by finite element or finite volume solution of the governing partial differential equations. It discusses specific implementation problems of special relevance to packed tubes, presents the validation by experiment of CFD results, and reviews recent advances in the field in transport and reaction. Extended discussion is given of two topics: heat transfer in packed tubes and the design of catalyst particles for steam reforming.

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Citations
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Journal ArticleDOI

A Coupled DEM and CFD Simulation of Flow Field and Pressure Drop in Fixed Bed Reactor with Randomly Packed Catalyst Particles

TL;DR: In this paper, the ability to predict void fraction and pressure drop in a packed bed would significantly improve reactor dif-ferentity and power saving in many commercial chemical processes.
Journal ArticleDOI

Systematic mesh development for 3D CFD simulation of fixed beds: Contact points study

TL;DR: Results for drag coefficient and heat flow for flow past sphere–sphere and wall-sphere contact points for CFD simulations of transport in fixed beds of spheres, focusing on higher flow rates typical of industrial steam reformers.
Journal ArticleDOI

Advances in fixed-bed reactor modeling using particle-resolved computational fluid dynamics (CFD)

TL;DR: In this paper, the latest advances are summarized in the field of modeling fixed-bed reactors with particle-resolved CFD, i.e. a geometric resolution of every pellet in the bed.
Journal ArticleDOI

Fixed bed catalytic reactor modelling—the radial heat transfer problem

TL;DR: An interpretation of the state-of-the-art in modelling radial heat transfer in fixed-bed catalytic reactors is presented in this article, where the persistence of the classical kr-hw model is discussed, problems with typical approaches to obtain and analyse experimental heat transfer data to get kr and hw are explained, current correlations for kr are evaluated and the contentious history of hw is elaborated.
Journal ArticleDOI

Local transport and reaction rates in a fixed bed reactor tube: Endothermic steam methane reforming

TL;DR: In this article, a 3D computational fluid dynamics (CFD) simulation of endothermic steam methane reforming in a random packed bed of 807 spherical catalyst particles at a tube-to-particle diameter ratio of N = 5.96 with constant wall heat flux is presented.
References
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Book

Numerical heat transfer and fluid flow

TL;DR: In this article, the authors focus on heat and mass transfer, fluid flow, chemical reaction, and other related processes that occur in engineering equipment, the natural environment, and living organisms.
Journal ArticleDOI

The numerical computation of turbulent flows

TL;DR: In this paper, the authors present a review of the applicability and applicability of numerical predictions of turbulent flow, and advocate that computational economy, range of applicability, and physical realism are best served by turbulence models in which the magnitudes of two turbulence quantities, the turbulence kinetic energy k and its dissipation rate ϵ, are calculated from transport equations solved simultaneously with those governing the mean flow behaviour.
Journal ArticleDOI

Lattice boltzmann method for fluid flows

TL;DR: An overview of the lattice Boltzmann method, a parallel and efficient algorithm for simulating single-phase and multiphase fluid flows and for incorporating additional physical complexities, is presented.
Book

Lectures in mathematical models of turbulence

TL;DR: In this article, a lecture in mathematical models of turbulence is presented. But it is based on a mathematical model of turbulence, not on a real world scenario, and it is not suitable for discussion.
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