Fluid dynamics simulation selectivity

Software tools are applied in every step of process development. Tools for individual reactor simulations such as computational fluid dynamic simulations are not the topic in this chapter. These tools supply only numerical data for specific defined reactor geometry and defined specific process conditions. A change of parameter would demand a complete recalculation, which is often a very time-consuming process and not applicable to a parameter screening. Methods for reactor optimization by CFD are described in detail in the first volume of this series. Tools for process simulation allow the early selection of feasible process routes from a large... 

The effect of micromixing in the iodination reaction is smaller than that observed for the Friedel-Crafts alkylation using N-acyliminium ions. The smaller effect seems to be ascribed to the smaller rate of iodination, because computational fluid dynamics simulation indicated that the effect of the micromixing on the product selectivity of a competitive consecutive reaction increases with an increase in the reaction rate. Therefore, the electrochemically generated I seems to be less reactive than the N-acyliminium ions. 

For any even vaguely realistic atomically constituted membrane it is unlikely that any theory will become available in the near future which will properly or reasonably describe the dynamic properties of the membrane, the fluids near it, and their passage, or selective passage, through it. Nevertheless, one should continue trying with simple models and simple theories [39-43], which show the way forward and can, as usual, be tested by the virtually exact results of molecular dynamics simulation. 

Takeuchi et al. 7 reported a membrane reactor as a reaction system that provides higher productivity and lower separation cost in chemical reaction processes. In this paper, packed bed catalytic membrane reactor with palladium membrane for SMR reaction has been discussed. The numerical model consists of a full set of partial differential equations derived from conservation of mass, momentum, heat, and chemical species, respectively, with chemical kinetics and appropriate boundary conditions for the problem. The solution of this system was obtained by computational fluid dynamics (CFD). To perform CFD calculations, a commercial solver FLUENT has been used, and the selective permeation through the membrane has been modeled by user-defined functions. The CFD simulation results exhibited the flow distribution in the reactor by inserting a membrane protection tube, in addition to the temperature and concentration distribution in the axial and radial directions in the reactor, as reported in the membrane reactor numerical simulation. On the basis of the simulation results, effects of the flow distribution, concentration polarization, and mass transfer in the packed bed have been evaluated to design a membrane reactor system. 

It is important to know how mixing can influence the selectivity of chemical reactions, and computational fluid dynamics (CFD) simulations are quite helpful in providing a deeper insight into this issue. The calculations are based on a laminar flow model where mixing takes place only by molecular diffusion (Figure 6.9). Let us focus on the competitive... 

As a model system a cylindrical reactor of the length L = 60 mm and inner diameter di = 7 mm packed with 400 uniform, nonporous spherical particles of the diameter dp = 1.8 mm was studied. The geometrical dimensions, as well as the average porosity, e = 0.47, of the packed bed were adjusted to those used in Section 5.2. Spatial discretization with the resolution of 30 lattice constant per sphere diameter was performed resulting in the computational domain of dimension 1300 X 117 X 117 points. The selected results given below intend to illustrate substantial differences and characteristics in the fluid dynamics in a FBR (Frs/Fss = 00) and PBMR. All the simulations presented were carried out on a Hewlett Packard Superdome parallel computer (64 processors, 120GB RAM). Typical simulation times for the complete model were about 24h on this architecture. 

Until recently, reactor design, selection of suitable operating conditions, and scale up were performed using either rules of thumb [80] or different kinds of compartment models [36,81 -83].With the exponential increase in computing power, hard- and software tools became available to successfully implement simulation strategies based on integration of computational fluid dynamics (CFD) and structured biokinetics. 

The selected OLGA dynamic simulation results for the first CO2 pipeline packing routes (Route A) have been presented in this section in Figures 14 -20, respectively, for the following major categories of fluid flow parameters ... 

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