Computational flow modeling

Airlift loop reactor (ALR), basically a specially structured bubble column, has been widely used in chemical industry, biotechnology and environmental protection, due to its high efficiency in mixing, mass transfer, heat transfer etc [1]. In these processes, multiple reactions are commonly involved, in addition to their complicated aspects of mixing, mass transfer, and heat transfer. The interaction of all these obviously affects selectivity of the desired products [2]. It is, therefore, essential to develop efficient computational flow models to reveal more about such a complicated process and to facilitate design and scale up tasks of the reactor. However, in the past decades, most involved studies were usually carried out in air-water system and the assumed reactor constructions were oversimplified which kept itself far away from the real industrial conditions [3] [4]. 

Ranade, V. V., Computational Flow Modeling for Chemical Reactor Engineering, Volume 5 of Process Systems Engineering (G. Stephanopoulos and J. Perkins, Eds.), Academic Press, San Diego (CA, USA) (2002). 

Ranade, V. V., Computational Flow Modeling for Chemical Reactor Engineering . Academic Press, New York (2002). 

The theoretical and numerical basis of computational flow modeling (CFM) is described in detail in Part II. The three major tasks involved in CFD, namely, mathematical modeling of fluid flows, numerical solution of model equations and computer implementation of numerical techniques are discussed. The discussion on mathematical modeling of fluid flows has been divided into four chapters (2 to 5). Basic governing equations (of mass, momentum and energy), ways of analysis and possible simplifications of these equations are discussed in Chapter 2. Formulation of different boundary conditions (inlet, outlet, walls, periodic/cyclic and so on) is also discussed. Most of the discussion is restricted to the modeling of Newtonian fluids (fluids exhibiting the linear dependence between strain rate and stress). In most cases, industrial... 

The Epilogue recapitulates the lessons learnt from our experience of applying computational flow modeling while addressing practical reactor engineering... 

It is necessary to develop an appropriate methodology to harness the potential of CFD tools for engineering analysis and design despite some of the limitations. Computational flow modeling (CFM) includes such overall methodology and all the other activities required to use CFD to achieve the engineering objectives. 

The overall process of any computational flow-modeling project was discussed in Section 1.2 (see Fig. 1.11 for key steps). It will be instructive to re-examine such a process with the background of Chapters 2 to 7. The first step of any flow-modeling project is to identify key controlling processes and relate these controlling processes to underlying fluid dynamics. This analysis will allow one to formulate clear objectives for the flow-modeling exercise. It must be mentioned here that, usually, the potential... 

The basic elements of mapping a computational flow model on a computer are shown in Fig. 8.1. Some comments on developing a modeling approach were made in Chapter 1. Ways of devising a suitable modeling approach are discussed further in Chapter 9 with the help of practical examples. In this chapter, we essentially restrict the discussion to the basic elements which are necessary to generate simulated results from the flow model. 

Knowledge of underlying physics and its mathematical representation (Chapters 2 to 5), of numerical methods to solve such mathematical representations (Chapters 6 and 7) and of computational tools to implement these numerical methods (this chapter), equip the reader to harness the potential of computational flow modeling for reactor engineering. It is essential to develop an appropriate modeling approach to suit the reactor-engineering objectives at hand. Development of such approaches is discussed in Chapter 9 with the help of practical examples. 

These models require information about mean velocity and the turbulence field within the stirred vessels. Computational flow models can be developed to provide such fluid dynamic information required by the reactor models. Although in principle, it is possible to solve the population balance model equations within the CFM framework, a simplified compartment-mixing model may be adequate to simulate an industrial reactor. In this approach, a CFD model is developed to establish the relationship between reactor hardware and the resulting fluid dynamics. This information is used by a relatively simple, compartment-mixing model coupled with a population balance model (Vivaldo-Lima et al., 1998). The approach is shown schematically in Fig. 9.2. Detailed polymerization kinetics can be included. Vivaldo-Lima et a/. (1998) have successfully used such an approach to predict particle size distribution (PSD) of the product polymer. Their two-compartment model was able to capture the bi-modal behavior observed in the experimental PSD data. After adequate validation, such a computational model can be used to optimize reactor configuration and operation to enhance reactor performance. 

The development of oxychlorination technology in the late 1950s encouraged new growth in the vinyl chloride industry. Here, we will be considering an oxychlorination (OXY) reactor to illustrate the application of computational flow modeling to reactor engineering. 

---