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Chemical reaction processes kinetic model

Thus there are enough uncertainties in the kinetics in most chemical reaction processes that we almost always need to resort to a simplified model from which we can estimate performance. Then, from more refined data and pilot plant experiments, we begin to refine the design of the process to specify the details of the equipment needed. [Pg.181]

The properties of wood(7,14) were used to analyze time scales of physical and chemical processes during wood pyrolysis as done in Russel, et al (15) for coal. Even at combustion level heat fluxes, intraparticle heat transfer is one to two orders of magnitude slower than mass transfer (volatiles outflow) or chemical reaction. A mathematical model reflecting these facts is briefly presented here and detailed elsewhere(16). It predicts volatiles release rate and composition as a function of particle physical properties, and simulates the experiments described herein in order to determine adequate kinetic models for individual product formation rates. [Pg.460]

Similar in spirit, but aimed at a very different community, is the work at Leeds, carried out jointly between the research groups of Peter Dew in computing and Mike Pilling in chemistry. One important focus here is on distributing the computational task of modelling chemical reaction processes in reaction kinetics, combustion, and... [Pg.158]

Quantum chemistry provides data that improves understanding of chemical kinetics. The data is further used as input for parameterizing transport and deposition models or chemical reaction schemes in models of various other atmospheric processes. As documented in many of the articles in this special edition, theoretical techniques are tested through comparison to laboratory measurements and atmospheric observations, and then further applied towards predicting mechanisms and reaction rates which are currently unknown. [Pg.6]

Several types of models are commonly used to describe the dispersion of atmospheric contaminants. Among these are the box, plume, and puff models. None are suitable, however, for describing the coupled transport and reaction phenomena that characterize atmospheres in which chemical reaction processes are important. Simulation models that have been proposed for the prediction of concentrations of photochemically formed pollutants in an urban airshed are reviewed here. The development of a generalized kinetic mechanism for photochemical smog suitable for inclusion in an urban airshed model, the treatment of emissions from automobiles, aircraft, power plants, and distributed sources, and the treatment of temporal and spatial variations of primary meteorological parameters are also discussed. [Pg.58]

Chemical reaction processes account for the production of a variety of contaminant species in the atmosphere. Each of the basic airshed models above includes reaction phenomena in the conservative equations. The reaction term, denoted by R accounts for the rate of production of species i by chemical reaction and depends generally on the concentrations of each N species. The conservation equations are thus coupled through the Ri terms, the functional form of each term being determined through the specification of a particular kinetic mechanism for the atmospheric reactions. [Pg.75]

There will be instances where the use of an airshed model will be limited to the prediction of concentrations of inert species. However, when chemical reaction processes are important, it is essential to include an adequate description of these phenomena in the model. Here we outline the requirements that an appropriate kinetic mechanism must meet, survey pertinent model development efforts, and present an example of a mechanism that possesses many of the attributes that a suitable model must display. [Pg.75]

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. [Pg.33]

The outlooks for the development of new fundamental concepts or for a general chemical engineering approach to catalytic processes will be summarized. RC takes place in numerous reactions. Many aspects are influenced by consideration of the RC concept activity and selectivity, catalyst formulation and "architecture", ageing processes, kinetic modelling, and process operation. [Pg.203]

The recent research focus of CVD B4C is to reveal the deposition mechanism under different deposition conditions and establish the relationship between deposition parameter and deposition mechanism, for which thermodynamic, mass transfer and kinetic modeling attempts have been studied by several research groups". The CVD B4C from BCI3/CH4/H2 precursor is a very complex chemical reaction process, and the B4C can be deposited by different mechanisms. Some reasonable deposition mechanisms have been established, such as Thomas S. Moss et al, and Mustafa Karaman et al, their experiments were performed under a small variation of deposition parameters and thus all of the B4C deposits had similar microstriicture and phase composition, which probably suggest the B4C coatings were deposited by a single mechanism. [Pg.379]

This is a mathematical expression for the steady-state mass balance of component i at the boundary of the control volume (i.e., the catalytic surface) which states that the net rate of mass transfer away from the catalytic surface via diffusion (i.e., in the direction of n) is balanced by the net rate of production of component i due to multiple heterogeneous surface-catalyzed chemical reactions. The kinetic rate laws are typically written in terms of Hougen-Watson models based on Langmuir-Hinshelwood mechanisms. Hence, iR ,Hw is the Hougen-Watson rate law for the jth chemical reaction on the catalytic surface. Examples of Hougen-Watson models are discussed in Chapter 14. Both rate processes in the boundary conditions represent surface-related phenomena with units of moles per area per time. The dimensional scaling factor for diffusion in the boundary conditions is... [Pg.450]

Process models for RD have to take into account both the chemical and the physical side of the process. Two basic types of model are used stage models, which are based on the idea of the equilibrium stage with phase equilibrium between the outlet streams, and rate-based models, which explicitly take into account heat and mass transfer. Similarly to the physical side of RD, the chemical reaction is either modeled using the assumption of chemical equilibrium or reaction kinetics are taken into account. Note that a kinetic model, either for physical transport processes or for chemical reactions, always includes an equilibrium model. The equilibrium model is the stationary solution of the kinetic model, for which all derivatives with respect to time become zero. Hence, whatever model type is used, it has to be based on a sound knowledge of the chemical and phase equilibrium, which is supplied by thermodynamic methods. Starting from there, kinetic effects can be included. [Pg.66]

Quasi-kinetic models deal with processes that are controlled by mass transfer rates rather than by chemical reaction rates. These models assume nearly instantaneous attainment of equilibrium within the region of interest, so changes in the species distribution are controlled by the rate of transfer of substances into or out of that region. These models are constrained by continuity equations making them similar to the chemical reactors models in Chapter 4. [Pg.156]

Both deterministic and stochastic models can be defined to describe the kinetics of chemical reactions macroscopically. (Microscopic models are out of the scope of this book.) The usual deterministic model is a subclass of systems of polynomial differential equations. Qualitative dynamic behaviour of the model can be analysed knowing the structure of the reaction network. Exotic phenomena such as oscillatory, multistationary and chaotic behaviour in chemical systems have been studied very extensively in the last fifteen years. These studies certainly have modified the attitude of chemists, and exotic begins to become common . Stochastic models describe both internal and external fluctuations. In general, they are a subclass of Markovian jump processes. Two main areas are particularly emphasised, which prove the importance of stochastic aspects. First, kinetic information may be extracted from noise measurements based upon the fluctuation-dissipation theorem of chemical kinetics second, noise may change the qualitative behaviour of systems, particularly in the vicinity of instability points. [Pg.273]

In the sections that follow, we will delve deeply into the atomistic world of reaction kinetics and learn how to predict the rates of a number of fairly simple zero, first, and second-order reaction processes. While this chapter will focus mostly on simple gas-phase chemical reaction processes, the principles learned here will apply just as well to the solid-state materials kinetic examples that we will confront later in the textbook. This is because bond-breaking and bond-forming processes are remarkably similar at the atomistic level whether they happen between molecules in the gas phase or between atoms in a solid. Thus, most reaction processes can be described using a common set of approaches. Toward the end of the chapter, in preparation for later solid-state applications of reaction kinetic principles, we will examine how reaction rates can be affected by a catalyst or a surface, and we will learn how to model several gas-solid surface reaction processes relevant to materials science and engineering. [Pg.50]

Dispersion is measured by the conceptually simple and practically useful dispersion coefficient, D, (D = CJC, where is the concentration of the analyte in the sample as the point of introduction (i.e., before the dispersion process begins) and C is the concentration of the analyte at the detection point) (McKelvie, 2008). Although this definition of dispersion does not take into consideration chemical reactions, the kinetic implications of chemical reactions were included in theoretical models developed in the 1980s (Kolev, 2008). Critical issues related to the description of mass transfer in FIA have been reviewed (Kolev, 2008 Inon and Tudino, 2008 Ruzicka, 2014). [Pg.37]

Over the last years it has become clear that the dynamics of most biological phenomena can be studied via the techniques of either nonlinear dynamics or stochastic processes. In either case, the biological system is usually visualized as a set of interdependent chemical reactions and the model equations are derived out of this picture. Deterministic, nonlinear dynamic models rely on chemical kinetics, while stochastic models are developed from the chemical master equation. Recent publications have demonstrated that deterministic models are nothing but an average description of the behavior of unicellular stochastic models. In that sense, the most detailed modeling approach is that of stochastic processes. However, both the deterministic and the stochastic approaches are complementary. The vast amount of available techniques to analytically explore the behavior of deterministic, nonlinear dynamical models is almost completely inexistent for their stochastic counterparts. On the other hand, the only way to investigate biochemical noise is via stochastic processes. [Pg.134]

As reactants transfonn to products in a chemical reaction, reactant bonds are broken and refomied for the products. Different theoretical models are used to describe this process ranging from time-dependent classical or quantum dynamics [1,2], in which the motions of individual atoms are propagated, to models based on the postidates of statistical mechanics [3], The validity of the latter models depends on whether statistical mechanical treatments represent the actual nature of the atomic motions during the chemical reaction. Such a statistical mechanical description has been widely used in imimolecular kinetics [4] and appears to be an accurate model for many reactions. It is particularly instructive to discuss statistical models for unimolecular reactions, since the model may be fomuilated at the elementary microcanonical level and then averaged to obtain the canonical model. [Pg.1006]

Model Reactions. Independent measurements of interfacial areas are difficult to obtain in Hquid—gas, Hquid—Hquid, and Hquid—soHd—gas systems. Correlations developed from studies of nonreacting systems maybe satisfactory. Comparisons of reaction rates in reactors of known small interfacial areas, such as falling-film reactors, with the reaction rates in reactors of large but undefined areas can provide an effective measure of such surface areas. Another method is substitution of a model reaction whose kinetics are well estabUshed and where the physical and chemical properties of reactants are similar and limiting mechanisms are comparable. The main advantage of employing a model reaction is the use of easily processed reactants, less severe operating conditions, and simpler equipment. [Pg.516]

Dente and Ranzi (in Albright et al., eds.. Pyrolysis Theory and Industrial Practice, Academic Press, 1983, pp. 133-175) Mathematical modehng of hydrocarbon pyrolysis reactions Shah and Sharma (in Carberry and Varma, eds.. Chemical Reaction and Reaction Engineering Handbook, Dekker, 1987, pp. 713-721) Hydroxylamine phosphate manufacture in a slurry reactor Some aspects of a kinetic model of methanol synthesis are described in the first example, which is followed by a second example that describes coping with the multiphcity of reactants and reactions of some petroleum conversion processes. Then two somewhat simph-fied industrial examples are worked out in detail mild thermal cracking and production of styrene. Even these calculations are impractical without a computer. The basic data and mathematics and some of the results are presented. [Pg.2079]

This involves knowledge of chemistry, by the factors distinguishing the micro-kinetics of chemical reactions and macro-kinetics used to describe the physical transport phenomena. The complexity of the chemical system and insufficient knowledge of the details requires that reactions are lumped, and kinetics expressed with the aid of empirical rate constants. Physical effects in chemical reactors are difficult to eliminate from the chemical rate processes. Non-uniformities in the velocity, and temperature profiles, with interphase, intraparticle heat, and mass transfer tend to distort the kinetic data. These make the analyses and scale-up of a reactor more difficult. Reaction rate data obtained from laboratory studies without a proper account of the physical effects can produce erroneous rate expressions. Here, chemical reactor flow models using matliematical expressions show how physical... [Pg.1116]

Mukherjee studied the gas phase equilibria and the kinetics of the possible chemical reactions in the pack-chromising of iron by the iodide process. One conclusion was that iodine-etching of the iron preceded chromis-ing also, not unexpectedly, the initial rate of chromising was controlled by transport of chromium iodide. Neiri and Vandenbulcke calculated, for the Al-Ni-Cr-Fe system, the partial pressures of chlorides and mixed chlorides in equilibrium with various alloys and phases, and so developed for pack aluminising a model of gaseous transport, solid-state transport, and equilibria at interfaces. [Pg.414]


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