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.

This book presents a new computational methodology called Computational Mass Transfer (CMT). It offers an approach to rigorously simulating the mass, heat and momentum transfer under turbulent flow conditions with the help of two newly published models, namely the C’2—εC’ model and the Reynolds mass flux model, especially with regard to predictions of concentration, temperature and velocity distributions in chemical and related processes. The book will also allow readers to understand the interfacial phenomena accompanying the mass transfer process and methods for modeling the interfacial effect, such as the influences of Marangoni convection and Rayleigh convection. The CMT methodology is demonstrated by means of its applications to typical separation and chemical reaction processes and equipment, including distillation, absorption, adsorption and chemical reactors. Professor Kuo-Tsong Yu is a Member of the Chinese Academy of Sciences. Dr. Xigang Yuan is a Professor at the School of Chemical Engineering and Technology, Tianjin University, China.

Computational methods have risen as a powerful technique for exploring the system phenomena and solving real-life problems. Currently, there are two principle computational approaches for system analysis: continuous and discrete. In the continuous approach, the governing equations can be obtained by applying the fundamental laws, such as conservation of mass, momentum, and energy over an infinitesimal control volume. On the other hand, the discrete approach concentrates on mimicking the molecular movement within the system. Both approaches have pros and cons, and continuous development and improvement in the existing computational methods are ongoing. Advanced Computational Techniques for Heat and Mass Transfer in Food Processing provides, in a single source, information on the use of methods based on numerical and computational analysis as applied in food science and technology. It explores the use of various numerical/computational techniques for the simulation of fluid flow and heat and mass transfer within food products. Key Features: Explores various numerical techniques used for modeling and validation Describes the knowhow of numerical and computational techniques for food process operations Covers a detailed numerical or computational approach of the principles of heat and mass transfer in the food processing operation Discusses the detailed computational simulation procedure of the food operation Recent years have witnessed a rapid development in the field of computational techniques owing to its abundant benefit to the food processing industry. The relevance of advanced computational methods has helped in understanding the fundamental physics of thermal and hydrodynamic behavior that can provide benefits to the food processing industry in numerous applications. As a single information source for those interested in the use of methods based on numerical and computational analysis as applied in food science and technology, this book will ably serve any food academician or researcher in learning the advanced numerical techniques exploring fluid flow, crystallization, and other food processing operations.

This book focuses on heat and mass transfer, fluid flow, chemical reaction, and other related processes that occur in engineering equipment, the natural environment, and living organisms. Using simple algebra and elementary calculus, the author develops numerical methods for predicting these processes mainly based on physical considerations. Through this approach, readers will develop a deeper understanding of the underlying physical aspects of heat transfer and fluid flow as well as improve their ability to analyze and interpret computed results.

Introduction to Computational Fluid Dynamics is a textbook for advanced undergraduate and first year graduate students in mechanical, aerospace and chemical engineering. The book emphasizes understanding CFD through physical principles and examples. The author follows a consistent philosophy of control volume formulation of the fundamental laws of fluid motion and energy transfer, and introduces a novel notion of 'smoothing pressure correction' for solution of flow equations on collocated grids within the framework of the well-known SIMPLE algorithm. The subject matter is developed by considering pure conduction/diffusion, convective transport in 2-dimensional boundary layers and in fully elliptic flow situations and phase-change problems in succession. The book includes chapters on discretization of equations for transport of mass, momentum and energy on Cartesian, structured curvilinear and unstructured meshes, solution of discretised equations, numerical grid generation and convergence enhancement. Practising engineers will find this particularly useful for reference and for continuing education.