Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top

2017 | Book

Basic Models of Computational Mass Transfer Read chapter Read first chapter

Introduction to Computational Mass Transfer

With Applications to Chemical Engineering

Authors: Kuo-Tsung Yu, Xigang Yuan

Publisher: Springer Singapore

Book Series : Heat and Mass Transfer

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Login to get access
insite
SEARCH

About this book

This book offers an easy-to-understand introduction to the computational mass transfer (CMT) method. On the basis of the contents of the first edition, this new edition is characterized by the following additional materials. It describes the successful application of this method to the simulation of the mass transfer process in a fluidized bed, as well as recent investigations and computing methods for predictions for the multi-component mass transfer process. It also demonstrates the general issues concerning computational methods for simulating the mass transfer of the rising bubble process. This new edition has been reorganized by moving the preparatory materials for Computational Fluid Dynamics (CFD) and Computational Heat Transfer into appendices, additions of new chapters, and including three new appendices on, respectively, generalized representation of the two-equation model for the CMT, derivation of the equilibrium distribution function in the lattice-Boltzmann method, and derivation of the Navier-Stokes equation using the lattice-Boltzmann model. This book is a valuable resource for researchers and graduate students in the fields of computational methodologies for the numerical simulation of fluid dynamics, mass and/or heat transfer involved in separation processes (distillation, absorption, extraction, adsorption etc.), chemical/biochemical reactions, and other related processes.

Table of Contents

Frontmatter
Chapter 1. Basic Models of Computational Mass Transfer
Abstract
The computational mass transfer (CMT) aims to find the concentration profile in a process equipment, which is the most important basis for evaluating the process efficiency, as well as, the effectiveness of an existing mass transfer equipment. This chapter is dedicated to the description of the fundamentals and the recently published models of CMT for obtaining simultaneously the concentration, velocity and temperature distributions. The challenge is the closure of the differential species conservation equation for the mass transfer in turbulent flow. Two models are presented. The first is a two-equation model termed as \(\overline{{c^{\prime 2} }} - \varepsilon_{{c^{\prime}}}\) model, which is based on the Boussinesq postulate by introducing an isotropic turbulent mass transfer diffusivity. The other is the Reynolds mass flux model, in which the variable covariant term in the equation is modeled and computed directly, and so it is anisotropic and rigorous. Both methods are proved to be validated by comparing with experimental data.
Kuo-Tsung Yu, Xigang Yuan
Chapter 2. Application of Computational Mass Transfer (I) Distillation Process
Abstract
In this chapter, the application of computational mass transfer (CMT) method in the forms of two-equation model and Rayleigh mass flux model as developed in previous chapters to the simulation of distillation process is described for tray column and packed column. The simulation of tray column includes the individual tray efficiency and the outlet composition of each tray of an industrial scale column. Methods for estimating various source terms in the model equations are presented and discussed for the implementation of the CMT method. The simulated results are presented and compared with published experimental data. The superiority of using standard Reynolds mass flux model is shown in the detailed prediction of circulating flow contours in the segmental area of the tray. In addition, the capability of using CMT method to predict the tray efficiency with different tray structures for assessment is illustrated. The prediction of tray efficiency for multicomponent system and the bizarre phenomena is also described. For the packed column, both CMT models are used for the simulation of an industrial scale column with success in predicting the axial concentrations and HETP. The influence of fluctuating mass flux is discussed.
Kuo-Tsung Yu, Xigang Yuan
Chapter 3. Application of Computational Mass Transfer (II) Chemical Absorption Process
Abstract
In this chapter, the two CMT models, i.e., \(\overline{{c^{{{\prime }2}} }} \text{ - }\varepsilon_{{c^{{\prime }} }}\) model and Reynolds mass flux model (in standard, hybrid, and algebraic forms) are used for simulating the chemical absorption of CO2 in packed column by using MEA, AMP, and NaOH separately and their simulated results are closely checked with the experimental data. It is noted that the radial distribution of \(D_{t}\) is similar to \(\alpha_{t}\) but quite different from \(\mu_{t}\). It means that the conventional assumption on the analogy between the momentum transfer and the mass transfer in turbulent fluids is unjustified and thus the use of CMT method for simulation is necessary. In the analysis of the simulation results, some transport phenomena are interpreted in terms of the co-action or counter-action of the turbulent mass flux diffusion.
Kuo-Tsung Yu, Xigang Yuan
Chapter 4. Application of Computational Mass Transfer (III)—Adsorption Process
Abstract
In this chapter, adsorption process is simulated using computational mass transfer (CMT) models as presented in Chap. 3. As the adsorption process is unsteady and accompanied with heat effect, the time parameter and the energy equation as presented in Chap. 2 are involved in the model equations. The simulated concentration profile of the column at different times enables to show the progress of adsorption along the column as an indication of the process dynamics. The simulated breakthrough curve and regeneration curve for adsorption and desorption by the two CMT models, i.e., the \(\overline{{c^{{{\prime }2}} }} - \varepsilon_{{c^{{\prime }} }}\) model and the Reynolds mass flux model, are well checked with the experimental data. Some issues that may cause discrepancies are discussed.
Kuo-Tsung Yu, Xigang Yuan
Chapter 5. Application of Computational Mass Transfer (IV) Fixed-Bed Catalytic Reaction
Abstract
In this chapter, an exothermic catalytic reaction process is simulated using computational mass transfer (CMT) models as presented in Chap. 1. The difference between the simulation in this chapter from those in Chaps. 2–4 is that chemical reaction is involved. The source term S n in the species conservation equation represents not only the mass transferred from one phase to the other, but also the mass created or depleted by a chemical reaction. Thus the application of the CMT model is extended to simulating the chemical reactor. The simulation is carried out on a wall-cooled catalytic reactor for the synthesis of vinyl acetate from acetic acid and acetylene using both \(\overline{{c^{{{\prime }2}} }} - \varepsilon_{{c^{\prime}}}\) model and Reynolds mass flux model. The simulated axial concentration and temperature distributions are in agreement with the experimental measurement. As the distribution of \(\mu_{\text{t}}\) shows dissimilarity with D t and \(\alpha_{\text{t}}\), the \(Sc_{\text{t}}\) or \(\Pr_{\text{t}}\) are thus varying throughout the reactor. The anisotropic axial and radial turbulent mass transfer diffusivity are predicted where the wavy shape of axial diffusivity D t,x along the radial direction indicates the important influence of catalysis porosity distribution on the performance of a reactor.
Kuo-Tsung Yu, Xigang Yuan
Chapter 6. Application of Computational Mass Transfer (V) Fluidized Chemical Process
Abstract
In this chapter, the CMT models developed in Chap. 1 are implemented for the simulation of concentration, velocity, and temperature distributions in gas-solid particle fluidized processes. A \(c^{{{\prime 2}}} - \varepsilon_{{c^{{\prime }} }}\) two-equation model is developed and applied to the removal of CO2 in flue gas by K2CO3 particle in a bubbling fluidized bed; while a Reynolds mass flux model is used for the process of decomposition of ozone in riser and downer of a circulating fluidized bed (CFB). The simulation results are validated with experimental data. Anisotropic feature of the eddy diffusivity in the fluidized process is discussed.
Kuo-Tsung Yu, Xigang Yuan
Chapter 7. Mass Transfer in Multicomponent Systems
Abstract
Theoretical basis and empirical correlations applicable in the computational mass transfer model for binary and multicomponent mass transfer are discussed in this chapter. The description of multicomponent mass transfer is best by applying the Maxwell–Stefan equation is shown to be the best way of description of multicomponent mass transfer. Generalized Fick’s law for multicomponent mass transfer, related parameters’ estimation models, and thermodynamic models are also discussed in this chapter.
Kuo-Tsung Yu, Xigang Yuan
Chapter 8. Micro Behaviors Around Rising Bubbles
Abstract
Velocity and concentration distribution near the interface of moving bubble in liquid are investigated experimentally and numerically. The tangential and nominal velocity distributions of liquid in the vicinity of the interface are measured by a Laser Doppler anemometer. Then a numerical model for predicting the liquid velocity distribution around a bubble is developed and the results are compared with some other models by checking with the experimental data from a Particle Imaging Velocimeter (PIV). The species concentration distribution of liquid near the interface is measured by using holographic interferometer. It is shown in the experiment that the concentration at distance about 10−2 mm from the interface is far from the thermodynamic equilibrium value, and some insight in understanding the interfacial mass transfer is discussed.
Kuo-Tsung Yu, Xigang Yuan
Chapter 9. Simulation of Interfacial Effect on Mass Transfer
Abstract
The mass transferred from one phase to the adjacent phase must diffuse through the interface and subsequently may produce interfacial effect. In this chapter, two kinds of important interfacial effects are introduced and discussed: Marangoni effect and Rayleigh effect. The theoretical background and method of computation are described including origin of interfacial convection, mathematical expression, observation, theoretical analysis (interface instability, on-set condition), experimental and theoretical study on enhancement factor of mass transfer. The details of interfacial effects are simulated by using CMT differential equations.
Kuo-Tsung Yu, Xigang Yuan
Chapter 10. Simulation of Interfacial Behaviors by the Lattice-Boltzmann Method
Abstract
In this chapter, the mesoscale computational methodology, lattice-Boltzmann Method (LBM) is introduced for the simulation of the interfacial Marangoni and Rayleigh effects as described and discussed in Chap. 8. The fundamentals of LBM are briefly introduced and discussed. By the simulation using the LBM, some mechanisms and phenomena of the interfacial effect are studied, including the patterns of the interfacial disturbance for inducing the interfacial convections, conditions of initiating interfacial instability and interfacial convection as well as the effect on interfacial mass transfer.
Kuo-Tsung Yu, Xigang Yuan
Metadata
Title
Introduction to Computational Mass Transfer
Authors
Kuo-Tsung Yu
Xigang Yuan
Copyright Year
2017
Publisher
Springer Singapore
Electronic ISBN
978-981-10-2498-6
Print ISBN
978-981-10-2497-9
DOI
https://doi.org/10.1007/978-981-10-2498-6