Modeling, Design, and Scale-up

Eulerian two-fluid model coupled with dispersed itequations was applied to predict gas-liquid two-phase flow in cyclohexane oxidation airlift loop reactor. Simulation results have presented typical hydrodynamic characteristics, distribution of liquid velocity and gas hold-up in the riser and downcomer were presented. The draft-tube geometry not only affects the magnitude of liquid superficial velocity and gas hold-up, but also the detailed liquid velocity and gas hold-up distribution in the reactor, the final construction of the reactor lies on the industrial technical requirement. The investigation indicates that CFD of airlift reactors can be used to model, design and scale up airlift loop reactors efficiently. 

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]. 

Rieckmann and Volker fitted their kinetic and mass transport data with simultaneous evaluation of experiments under different reaction conditions according to the multivariate regression technique [116], The multivariate regression enforces the identity of kinetics and diffusivities for all experiments included in the evaluation. With this constraint, model selection is facilitated and the evaluation results in one set of parameters which are valid for all of the conditions investigated. Therefore, kinetic and mass transfer data determined by multivariate regression should provide a more reliable data basis for design and scale-up. 

In complex systems such as three-phase reactors, the methods of mathematical modeling cannot provide the required information for process design and scale-up since it is practically impossible to take into account all existing phenomena and safely predict the influence of hydrodynamics, heat and mass transfer, or kinetics on each other (Datsevich and Muhkortov, 2004). Thus, models are almost always approximate in nature. They are based on a number of assumptions that cannot be met during scale-up. So, it is not surprising that industrial unit designers do not completely trust the results obtained from mathematical modeling. Thus, several systems cannot be fully modeled mathematically and other methods for scale-up are followed. 

A better approach would be to correlate the model parameters with several process variables before the model can be used to design and scale-up the column. 

The following example will show how design and scale-up data can be obtained by model measurements with the same material system in differently sized laboratory devices. 

For the economic analysis, the design and scale up of commercial reactor systems it becomes more important to use modem mathematical modelling tools and therefore it is necessary to get more insight into the macro kinetic aspect as well as the understanding of the behaviour of the phase equilibrium. As well for investigating the aspects of choosing the optimal catalyst it is necessary to have a suitable technology available. 

The use of models and model simulations are extremely useful in all design and scale-up considerations. Mathematical methods to solve model equations of any degree of complexity are available now, and fast numerical techniques have been developed. In addition, almost everywhere abundant computer facilities are at hand. Therefore, a reliable design and scale-up should use mathematical models formulated on the basis of first principles, even if these models are very sophisticated. Such models and simulations based on them present the most efficient and probably the cheapest way in today s design works. 

The reader will find here a complete mathematical development of the models of chromatography and other physical laws which direct the chemical engineer in the design and scale-up of chromatographic processes. For preparative chromatographic separations, our ultimate purpose is the optimization of the experimental conditions for maximum production rate, minimum solvent consumption, or minimum production cost, with or without constraints on the recovery yield. The considerable amormt of work done on this critical topic is presented in the... 

Mathematical modeling is an essential tool for design and scale-up. As emulsion polymerization involves a minimum of two phases, the kinetics is complex and makes it difficult to ... 

In recent years, there has been considerable effort to develop computational fluid dynamic (CFD) models to predict the hydrodynamics and performance of fluidized beds. While this approach will no doubt yield valuable tools in the future, CFD models are not yet at the point where they can be used with confidence for design and scale-up of fluidized bed processes. 

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