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MATLAB program reactions

When the equilibrium constants for the reactions (A) and (B) are expressed in terms of the partial pressure of the various species (in atm), the equilibrium constants for these reactions have the values KpA = 0.046 and KpB = 0.034. Determine the number of independent reactions, and then determine the equilibrium composition of the mixture, making use of a simple MATLAB program that you develop for this purpose. [Pg.131]

The reaction is exothermic. For (3 = 1.2 the exothermicity factor, and 7 the dimensionless activities factor, find the range of a, the dimensionless preexponential factor, that gives multiplicity of steady states using a suitable MATLAB program with Kc = 0, the dimensionless heat transfer coefficient of the cooling jacket. Choose a value of a in the multiplicity region and obtain the multiple steady-state dimensionless temperatures and concentrations. [Pg.132]

Let us investigate how MATLAB handles boundary value problems such as (5.24) with the boundary conditions (5.25) and (5.26) for first- and second-order reactions. The MATLAB program linquadbvp.m has been designed for this purpose. [Pg.273]

In this section we have presented and solved the BVPs associated with the diffusion and reaction that take place in the pores of a porous catalyst pellet. The results were expressed graphically in terms of the effectiveness factor rj versus the Thiele modulus d> for two cases One with negligible external mass and heat transfer resistances, i.e., when Sh and Nu —> oo, and another with finite Sh and Nu values. This problem is very important in the design of fixed-bed catalytic reactors. The sample results presented here have shown that for exothermal reactions multiple steady states may occur over a range of Thiele moduli d>. Efficient numerical techniques have been presented as MATLAB programs that solve singular two-point boundary value problems. [Pg.323]

Several important types of reactions are considered in the following sections. The equations describing each of these systems are developed. The steady-state design of CSTRs with these reactions are discussed, using Matlab programs for hypothetical chemical examples and the commercial software Aspen Plus for a real chemical example. [Pg.31]

The reactions considered in previous sections have involved hypothetical components A, B, C, and I) for which arbitrary physical properties and kinetics could be selected to illustrate various phenomena. Simple Matlab programs can be easily generated for these systems. [Pg.72]

The reaction is actually a third-order reaction with value of /c = 1 x 10. Note Refer MATLAB program diff anal kinet.m... [Pg.34]

Figure 12.4 shows the experimental versus simulated data obtained from the MATLAB program during reaction at 50°C. It is observed that the simulated curves adequately fit with the experimental data. An increasing trend in the rate of methyl ester formation with reaction temperature found in Figure 12.5 confirms that the reaction is favoured at higher temperatures, in line with those reported in the literature (Noureddini and Zhu, 1997 Kusdiana and Saka, 2001 Zhou et al, 2003 Schumacher, 2005 Vicente et al, 2005, 2006 Issariyakul and Dalai, 2010). [Pg.232]

Table 12.5 shows the rate constants calculated using the MATLAB program. It is observed that the values of reverse rate constants k2 are not zero, which indicates that the reaction step of TAG to DAG is reversible. The exceptionally low values of... [Pg.232]

The holistic thermodynamic approach based on material (charge, concentration and electron) balances is a firm and valuable tool for a choice of the best a priori conditions of chemical analyses performed in electrolytic systems. Such an approach has been already presented in a series of papers issued in recent years, see [1-4] and references cited therein. In this communication, the approach will be exemplified with electrolytic systems, with special emphasis put on the complex systems where all particular types (acid-base, redox, complexation and precipitation) of chemical equilibria occur in parallel and/or sequentially. All attainable physicochemical knowledge can be involved in calculations and none simplifying assumptions are needed. All analytical prescriptions can be followed. The approach enables all possible (from thermodynamic viewpoint) reactions to be included and all effects resulting from activation barrier(s) and incomplete set of equilibrium data presumed can be tested. The problems involved are presented on some examples of analytical systems considered lately, concerning potentiometric titrations in complex titrand + titrant systems. All calculations were done with use of iterative computer programs MATLAB and DELPHI. [Pg.28]

Note that the above program works for both endothermic reactions (/ < 0) and exothermic reactions (/ > 0) and that only exothermic reactions can have multiple steady states. The built-in MATLAB root finder fzero finds the roots of a function / from a starting guess a if we call fzero( /,a,.. . ), i.e., if we attach the function handle to / and follow this with the appropriate list of parameters in MATLAB. [Pg.73]

Note that almost all calling sequences of MATLAB function m files start with the function s name, such as runsolveadiabxy above, followed by a list of parameters in parentheses (. .. ). Our particular call runsolveadiabxy(285,305,1,8.5) uses the interval limits 285 and 305 for a as its first two parameters, followed by the values of / and 7 for a specific chemical reaction. In our m files the list of possible parameters is always explained in the first comment lines of code. Often one or several of the parameters are optional. If they are not specified in the calling sequence, they are internally set to default values inside the program, such as n and anno are here. [Pg.75]

To solve equations of state, you must solve algebraic equations as described in this chapter. Later chapters cover other topics governed by algebraic equations, such as phase equilibrium, chemical reaction equilibrium, and processes with recycle streams. This chapter introduces the ideal gas equation of state, then describes how computer programs such as Excel , MATLAB , and Aspen Plus use modified equations of state to easily and accurately solve problems involving gaseous mixtures. [Pg.5]

The Matlab Simulink Model was designed to represent the model stmctuie and mass balance equations for SSF and is shown in Fig. 6. Shaded boxes represent the reaction rates, which have been lumped into subsystems. To solve the system of ordinary differential equations (ODEs) and to estimate unknown parameters in the reaction rate equations, the inter ce parameter estimation was used. This program allows the user to decide which parameters to estimate and which type of ODE solver and optimization technique to use. The user imports observed data as it relates to the input, output, or state data of the SimuUnk model. With the imported data as reference, the user can select options for the ODE solver (fixed step/variable step, stiff/non-stiff, tolerance, step size) as well options for the optimization technique (nonlinear least squares/simplex, maximum number of iterations, and tolerance). With the selected solver and optimization method, the unknown independent, dependent, and/or initial state parameters in the model are determined within set ranges. For this study, nonlinear least squares regression was used with Matlab ode45, which is a Rimge-Kutta [3, 4] formula for non-stiff systems. The steps of nonlinear least squares regression are as follows ... [Pg.385]

Most software package like Origin, SAS, MATLAB can perform kinetic analysis of reaction curve, but they are usually ineffective to implicit functions for kinetic analysis of reaction curve. For convenience and the use of some complicated methods for kinetic analysis of reaction curve in widow-aided mode, self-programming is still favourable. [Pg.177]

To summarize, we perform a singular value decomposition of the augmented formula matrix to obtain the matrices U, W, and V. With these, we use (11.2.10) to obtain a particular basis vector N for the range. From V, we form P and then use (11.2.7) to obtain all sets of stoichiometric coefficients Vy. Then we combine N and Vy into (11.2.5) to determine all sets of mole numbers that satisfy the elemental balances. Therefore, a singular value decomposition provides the number of independent reactions 91, all sets of 91 independent stoichiometric coefficients Vy, and all possible combinations of mole numbers N that satisfy the elemental balances. A computer program for performing the decomposition is contained in the book by Press et al. [9] routines for performing the decomposition are also available in MATLAB and in Mathematica . [Pg.503]

Zambon and Qielliah (2007) also elaborated a method for the explicit, iteration-free calculation of the QSS concentrations. The method is based on modifications to the original matrix-based methods of Chen (1988) and is implemented in the Matlab coding environment utilising its symbolic programming capabilities. The method was used to develop an 18-step scheme for ethylene/air combustion from a skeletal scheme containing 31 species and 128 reversible elementary reactions, i.e. a similar level of reduction to that achieved by Lu and Law (2006c). [Pg.242]

Each chapter contains examples that show in detail how a particular numerical method or programming methodology can be implemented in Excel and/or VBA (or MATLAB in Chapter 10). Most of the examples and problems presented in the text are related to chemical and biomolecular engineering and cover a broad range of application areas including thermodynamics, fluid flow, heat transfer, mass transfer, reaction kinetics, reactor design, process design, and process control. The chapters feature Did You Know" boxes, used to remind readers of Excel features. They also contain end-of-chapter exercises, with solutions provided. [Pg.227]

The experimental data of distillation curves of hydrocracked products obtained at the lowest LHSV (0.33 h ) at three reaction temperatures were used to determine the optimum set of parameters (5, a, Aq, a, and of the continuous kinetic model. Figure 11.6 shows the comparison between experimental and predicted distillation curves of the feedstock and the product hydrocracked at LHSV of 0.33 h" and 420°C. This plot is an example of the way the data are fed and reported by the MATLAB computer program as dimensionless curves. At 420°C, the optimum set of parameter values is a = 0.246, = 1.487, = 22.83, 8 = 1.67 x 10" , and... [Pg.426]


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