Batch reactor simulation

The component mass balance, when coupled with the heat balance equation and temperature dependence of the kinetic rate coefficient, via the Arrhenius relation, provide the dynamic model for the system. Batch reactor simulation examples are provided by BATCHD, COMPREAC, BATCOM, CASTOR, HYDROL and RELUY. 

Figure 4.2 Matlab program for batch reactor simulation.

The hquid-phase chlorination of benzene is an ideal example of a set of sequential reactions with varying rates from the single-chlorinated molecule to the completely chlorinated molecule containing six chlorines. Classical papers have modeled the chlorination of benzene through the dichlorobenzenes (14,15). A reactor system may be simulated with the relative rate equations and flow equation. The batch reactor gives the minimum ratio of... 

Simulation of complex chemical reactions in a batch reactor... 

Simulation of a nonisothermal batch reactor Temperature versus... 

Figure 6-5b Temperature versus time in an adiabatic batch reactor. Fig ure 6-5. Simulation of a non-isothermal batch reactor.

Simulation of a batch reactor for the hydrolysis of acetylated castor oil... 

To run the residence time distribution experiments under conditions which would simulate the conditions occurring during chemical reaction, solutions of 15 weight percent and 30 percent polystyrene in benzene as well as pure benzene were used as the fluid medium. The polystyrene used in the RTD experiment was prepared in a batch reactor and had a number average degree of polymerization of 320 and a polydispersity index, DI, of 1.17. 

For purposes of simulation and illustration we have chosen a batch reactor, solution polymerization of methylmethacrylate (MMA). Kinetic data were taken from Schmidt and Ray (1981) and thermodynamic data from Bywater (1955). We do not here consider the influence of diffusion control on the termination or other rate processes because such effects may be small when in a solution which is siifHciently dilute or when the polymer is of low molecular weight. 

This paper presents the physical mechanism and the structure of a comprehensive dynamic Emulsion Polymerization Model (EPM). EPM combines the theory of coagulative nucleation of homogeneously nucleated precursors with detailed species material and energy balances to calculate the time evolution of the concentration, size, and colloidal characteristics of latex particles, the monomer conversions, the copolymer composition, and molecular weight in an emulsion system. The capabilities of EPM are demonstrated by comparisons of its predictions with experimental data from the literature covering styrene and styrene/methyl methacrylate polymerizations. EPM can successfully simulate continuous and batch reactors over a wide range of initiator and added surfactant concentrations. 

In this work, a comprehensive kinetic model, suitable for simulation of inilticomponent aiulsion polymerization reactors, is presented A well-mixed, isothermal, batch reactor is considered with illustrative purposes. Typical model outputs are PSD, monomer conversion, multivariate distritution of the i lymer particles in terms of numtoer and type of contained active Chains, and pwlymer ccmposition. Model predictions are compared with experimental data for the ternary system acrylonitrile-styrene-methyl methacrylate. 

In order to illustrate how the mode of operation can positively modify selectivity for a large reactor of poor heat-transfer characteristics, simulations of the reactions specified in Example 5.3.1.4 carried out in a semibatch reactor were performed. The reaction data and process conditions are essentially the same as those for the batch reactor, except that the initial concentration of A was decreased to cao = 0.46 mol litre, and the remaining amount of A is dosed (1) either for the whole reaction time of 1.5 h with a rate of 0.1 mol m s", or (2) starting after 0.5 h with a rate of 0.15 mol m " s". It is assumed that the volume of the reaction mixture and its physical properties do not change during dosing. The results of these simulations are shown in Fig. 5.3-15. The results of calculation for reactors of both types are summarized in Table 5.3-3. 

Two simple forms of a batch reactor temperature control are possible, in which the reactor is either heated by a controlled supply of steam to the heating jacket, or cooled by a controlled flow of coolant (Fig. 3.18) Other control schemes would be to regulate the reactor flow rate or feed concentration, in order to maintain a given reaction rate (see simulation example SEMIEX). 

In this chapter the simulation examples are described. As seen from the Table of Contents, the examples are organised according to twelve application areas Batch Reactors, Continuous Tank Reactors, Tubular Reactors, Semi-Continuous Reactors, Mixing Models, Tank Flow Examples, Process Control, Mass Transfer Processes, Distillation Processes, Heat Transfer, and Dynamic Numerical Examples. There are aspects of some examples which relate them to more than one application area, which is usually apparent from the titles of the examples. Within each section, the examples are listed in order of their degree of difficulty. 

A simulation model needs to be developed for each reactor compartment within each time interval. An ideal-batch reactor has neither inflow nor outflow of reactants or products while the reaction is carried out. Assuming the reaction mixture is perfectly mixed within each reactor compartment, there is no variation in the rate of reaction throughout the reactor volume. The design equation for a batch reactor in differential form is from Chapter 5 ... 

Thus, the design of a batch reactor can be based on the optimization of a temporal superstructure. Given a simulation model with a mathematical formulation, the next step is to determine the optimal values for the control variables of a batch reaction system. 

Sandhya S, Padmavathy S, Swaminathan K et al (2005) Microaetophilic-aerobic sequential batch reactor for treatment of azo dyes containing simulated wastewater. Process Biochem 40 885-890... 

Some typical results from their simulations are presented in Fig. 16 in which the yield XQ of the product Q from the slow reaction of a set of two competitive reactions in a fed batch reactor has been plotted vs. impeller speed for two micromixing models, viz. their own CSV model and Bourne s EDD model their simulation results are compared with experimental data from Bourne and Yu (1991). For the cases shown, the CSV model may perform better than Bourne s EDD model, in particular when A is fed near to the impeller where mixing is most intense. 

Fig. 16. The yield Xg of the product Q of the slower reaction of a set of two competitive parallel reactions in a fed batch reactor plotted vs. impeller speed (in /s). The experimental data are due to Bourne and Yu (1991) the crosses refer to feeding reactant A at the top of the vessel, while the diamonds refer to feeding more closely to the impeller. The various types of lines refer to simulations as specified in the legend. Reproduced with permission from R. A. Bakker (1996).

The above simulations as to the occurrence of hot spots once more illustrate the power and promises of LES over RANS-type simulations. The hot spots can never be found by means of a RANS-type of simulation. The same technique was used by Van Vliet et al. (2006) to study the influence of the injector geometry and inlet temperature on product quality and process efficiency in the LDPE reactor. On the contrary, the RANS-based simulations due to R. A. Bakker and Van den Akker (1994, 1996) were pretty much suited to arrive at yield predictions for a fed batch reactor as a whole. 

The RC1 is designed to simulate closely the operation of large scale batch and semi-batch reactor systems. The RC1 equipment consists of the reaction vessel, overhead condenser for reflux/distillation operations, receiver, metering pumps, and a heat transfer fluid heating/cooling circulating unit. Me-... 

The RC1 is an automated laboratory batch/semi-batch reactor for calorimetric studies which has proven precision. The calorimetric principle used and the physical design of the system are sound. The application of the RC1 extends from process safety assessments including calorimetric measurements, to chemical research, to process development, and to optimization. The ability of the RC1 to generate accurate and reproducible data under simulated plant scale operating conditions may result in considerably reduced testing time and fewer small scale pilot plant runs. 

Extensive numerical simulations were performed for the basic system when operated as a fed-batch reactor. The sets of basic values used for the parameters... 

In Section 4.1.4.1 results of numerical simulations were presented for the case when the basic system is operated as a fed-batch reactor. In this section, results of the numerical simulations are presented for the case when the basic system is operated in continuous reactors. The results were obtained for several reactor types. In terms of compartmental analysis (see Section 4.1.3.2) these types are determined by the number of compartments (n) considered to make up the reactor (see Figure 4.3). Three cases are presented here n = ... 

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