Understanding Reactor Flow Patterns

Understanding Reactor Flow Patterns As discussed above, a RTD obtained using a nonreactive tracer may not uniquely represent the flow behavior within a reactor. For diagnostic and simulation purposes, however, tracer results may be explained by combining the expected tracer responses of ideal reactors combined in series, in parallel, or both, to provide an RTD that matches the observed reactor response. The most commonly used ideal models for matching an actual RTD are PRF and CSTR models. Figure 19-9 illustrates the responses of CSTRs and PFRs to impulse or step inputs of tracers. 

Several sophisticated techniques and data analysis methodologies have been developed to measure the RTD of industrial reactors (see, for example, Shinnar, 1987). Various different types of models have been developed to interpret RTD data and to use it further to predict the influence of non-ideal behavior on reactor performance (Wen and Fan, 1975). Most of these models use ideal reactors as the building blocks (except the axial dispersion model). Combinations of these ideal reactors with or without by-pass and recycle are used to simulate observed RTD data. To select an appropriate model for a reactor, the actual flow pattern and its dependence on reactor hardware and operating protocol must be known. In the absence of detailed quantitative models to predict the flow patterns, selection of a model is often carried out based on a qualitative understanding of flow patterns and an analysis of observed RTD data. It must be remembered that more than one model may fit the observed RTD data. A general philosophy is to select the simplest model which adequately represents the physical phenomena occurring in the actual reactor. 

This chapter deals with basic fundamentals of novel reactor technology and some of green reactor design softwares and their applications. Basic understanding of flow pattern in stirred-tank reactor by computational fluid dynamics and simulation of CSTR model by using ASPEN Plus were mainly presented in this chapter. 

The fluid flow and tnrbulence in many plant reactors is more complex than in vessels modeled by academics. CFD is useful for understanding the flow patterns in such reactors however, at the time of writing CFD still does a poor job of predicting the local turbulence quantities vital to micromixing and mesomixing analysis. This is another area where greater understanding is needed. 

Suppose now that a pilot-plant or full-scale reactor has been built and operated. How can its performance be used to confirm the kinetic and transport models and to improve future designs Reactor analysis begins with an operating reactor and seeks to understand several interrelated aspects of actual performance kinetics, flow patterns, mixing, mass transfer, and heat transfer. This chapter is concerned with the analysis of flow and mixing processes and their interactions with kinetics. It uses residence time theory as the major tool for the analysis. 

The chemical engineer almost never encounters a single reaction in an ideal single-phase isothermal reactor. Real reactors are extremely complex with multiple reactions, multiple phases, and intricate flow patterns within the reactor and in inlet and outlet streams. An engineer needs enough information from this course to understand the basic concepts of reactions, flow, and heat management and how these interact so that she or he can begin to assemble simple analytical or intuitive models of the process. 

Like CVD units, plasma etching and deposition systems are simply chemical reactors. Therefore, flow rates and flow patterns of reactant vapors, along with substrate or film temperature, must be precisely controlled to achieve uniform etching and deposition. The prediction of etch and deposition rates and uniformity require a detailed understanding of thermodynamics, kinetics, fluid flow, and mass-transport phenomena for the appropriate reactions and reactor designs. 

Numerous studies on the kinetics and mechanisms of CVD reactions have been made. These studies provide useful information such as activation energy and limiting steps of deposition reactions which are important for the understanding of deposition processes. The main problem in the CVD kinetics studies is the complexity of the deposition process. The difficulty arises not only from the various steps of the CVD process but also from the temperature and concentration gradient, geometric effects, and gas flow patterns in the reaction zones. Exact kinetic analysis is therefore usually not possible as the kinetic data are reactor dependent. There are several possible rate-limiting factors but mass transport and surface kinetics control are the most... 

None of the above studies, however, deals with the detailed hydrodynamics in a membrane reactor. It can be appreciated that detailed information on the hydrodynamics in a membrane enhances the understanding and prediction of the separation as well as reaction performances in a membrane reactor. All the reactor models presented in Chapter 10 assume very simple flow patterns in both the tube and annular regions. In almost all cases either plug flow or perfect mixing is used to represent the hydrodynamics in each reactor zone. No studies have yet been published linking detailed hydrodynamics inside a membrane reactor to reactor models. With the advent of CFD, this more complete rigorous description of a membrane reactor should become feasible in the near future. 

In the next layer of subjects we list the engineering sciences which are needed in various ways for understanding and further developing the core engineering subjects thermodynamics, chemical kinetics, electrochemical phenomena, and transport phenomena. These engineering sciences, which are themselves interrelated, form the basis for the analytical and numerical description of the chemical reactor and its peripheral equipment. For example, the subject of transport phenomena can be used to analyze difiiision-controlled reactions, separation schemes, transient processes in reactors, thermal processes, flow patterns in reacting systems, corrosion, difiusion in porous media, and other problems connected with reactor engineering. 

The velocity and hold-up distribution of the solid phase in a liquid-solid riser has been studied with radioactive particle tracking and computed tomography (CT).[ 1 The goal of this research was the development of an understanding of the variables affecting the performance of liquid-solid risers, and of fundamentally-based scale-up rules. An improved PEPT system has recently been developed, capable of continuously following the 3D trajectory of a radiotracer particle (as small as 500/um) moving at 0.1 ms with a resolution of 5 mm. The system has been used to measure in situ flow patterns of solids in a gas-solids Interconnected Fluidised Bed reactor. 

In this chapter, fluid-fluid flow patterns and mass transfer in microstructured devices are discussed. The first part is a brief discussion of conventionai fluid-fluid reactors with their advantages and disadvantages. Further, the ciassi-flcation of fluid-fluid microstructured reactors is presented. In order to obtain generic understanding of hydrodynamics, mass transfer, and chemical reaction, dimensionless parameters and design criteria are proposed. The conventional mass transfer models such as penetration and film theory as well as empirical correlations are then discussed. Finally, literature data on mass transfer efficiency at different flow regimes and proposed empirical correlations as well as important hydrodynamic design parameters are presented. 

A perennial problem in multiphase reactors is scale-up, that is, how to achieve the desired results in a large-scale reactor based on the observations made in the laboratory unit, which remains elusive due to complexities associated with transport-kinetic coupling [14]. The success of scale-up of trickle-bed reactors is based on the ability to understand and quantify the transport-kinetic interactions at the particle scale level (or single eddy scale), the interphase transport at the particle and reactor scales, and the flow pattern of each phase and phase contacting pattern and their changes with the changes in reactor scale and operating conditions [1]. 

The US DOE had a major effort to understand the many variables affecting the performance of a bubble column reactor. Dudukovic and Toseland [75] outlined the cooperative study by Air Products and Chemicals (APC), Ohio State University (OSU), Sandia National Laboratory (SNL), and Washington University in St. Louis (WU). The efforts of this group have developed valuable unique experimental techniques for the measurement of gas holdup, velocity, and eddy diffusivities in bubble columns. They have obtained data that allows improved insight in churn-turbulent flow and have assessed the impact of various effects (internals, solid concentration, high gas velocity, pressure, etc.). General ideal flow pattern-based models do not reflect bubble column reality to date the models are based on a combination where some parameters are evaluated from first principles and some from the database. 

Several reactors deviate from the ideal flow patterns presented in the previous chapters. This is why it is important to understand the meaning of residence time distribution (RTD) in the system under consideration. In this chapter, a basic characterization of RTDs will be presented. It is relevant, however, to emphasize that in studies of purely physical systems, such as different kinds of mixing chambers, knowledge of the RTD of the system can be considerably beneficial. Before the actual, detailed treatment of the problem, we will briefly define the concepts of residence time and RTDs. 

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