Chemical reactors optimal temperature

Variables It is possible to identify a large number of variables that influence the design and performance of a chemical reactor with heat transfer, from the vessel size and type catalyst distribution among the beds catalyst type, size, and porosity to the geometry of the heat-transfer surface, such as tube diameter, length, pitch, and so on. Experience has shown, however, that the reactor temperature, and often also the pressure, are the primary variables feed compositions and velocities are of secondary importance and the geometric characteristics of the catalyst and heat-exchange provisions are tertiary factors. Tertiary factors are usually set by standard plant practice. Many of the major optimization studies cited by Westerterp et al. (1984), for instance, are devoted to reactor temperature as a means of optimization. 

N. Aziz, M.A. Hussain, and I.M. Mujtaba. Performance of different types of controllers in tracking optimal temperature profiles in batch reactors. Computers and Chemical Engineering, 24 1069-1075, 2000. 

The many preexponential factors, activation energies and reaction order parameters required to describe the kinetics of chemical reactors must be determined, usually from laboratory, pilot plant, or plant experimental data. Ideally, the chemist or biologist has made extensive experiments in the laboratory at different temperatures, residence times and reactant concentrations. From these data, parameters can be estimated using a variety of mathematical methods. Some of these methods are quite simple. Others involve elegant statistical methods to attack this nonlinear optimization problem. A discussion of these methods is beyond the scope of this book. The reader is referred to the textbooks previously mentioned. 

We shall see later that the time of reaction here corresponds to the size of chemical reactor required, so what we have accomplished is minimization of the size and cost of the reactor system required to accomplish a specified conversion. Of course, such absolute optimal temperature schedules may not always be accomplished practically, but they can serve at least as indicators for desirable design policies. The general aspects of the solution to the optimal scheduling problem of Bilous and Amundson are shown in Figure 1.16. 

The two families of curves shown in Figure 10 constitute thermo-chemical rate-optimization constraints between reactor temperature, substrate concentration, and dilution rate. When any two of these three variables are fixed, each family specifies what value the third must have to maximize its rate. The separation of the two families means that both rates cannot be simultaneously maximized. As a result, an optimization strategy may be needed, such as operating at the optimum temperature of the process whose rate is most sensitive to temperature. 

Optimal periodic control involves a periodic process, which is characterized by a repetition of its state over a fixed time period. Examples from nature include the circadian rhythm of the core body temperature of mammals and the cycle of seasons. Man-made processes are run periodically by enforcing periodic control inputs such as periodic feed rate to a chemical reactor or cyclical injection of steam to heavy oil reservoirs inside the earth s crust. The motivation is to obtain performance that would be better than that imder optimal steady state conditions. 

To avoid mass and heat transfer resistances in practice, the characteristic transfer time should be roughly 1 order of magnitude smaller compared to the characteristic reaction time. As the mass and heat transfer performance in microstructured reactors (MSR) is up to 2 orders of magnitude higher compared to conventional tubular reactors, the reactor performance can be considerably increased leading to the desired intensification of the process. In addition, consecutive reactions can be efficiently suppressed because of a strict control of residence time and narrow residence time distribution (discussed in Chapter 3). Elimination of transport resistances allows the reaction to achieve its chemical potential in the optimal temperature and concentration window. Therefore, fast reactions carried out in MSR show higher product selectivity and yield. 

Various parameters must be considered when selecting a reactor for multiphase reactions, such as the number of phases involved, the differences in the physical properties of the participating phases, the post-reaction separation, the inherent reaction nature (stoichiometry of reactants, intrinsic reaction rate, isothermal/ adiabatic conditions, etc.), the residence time required and the mass and heat transfer characteristics of the reactor For a given reaction system, the first four aspects are usually controlled to only a limited extent, if at aH, while the remainder serve as design variables to optimize reactor performance. High rates of heat and mass transfer improve effective rates and selectivities and the elimination of transport resistances, in particular for the rapid catalytic reactions, enables the reaction to achieve its chemical potential in the optimal temperature and concentration window. Transport processes can be ameliorated by greater heat exchange or interfadal surface areas and short diffusion paths. These are easily attained in microstructured reactors. 

Mathematical theory and state-of-the-art numerical methods possess a great ability in computing optimal solutions for process control in chemical engineering which is until today not exhausted compared to other fields. The investigation of the optimal temperature control of a semi-batdi polymerization reactor being still a comparatively simple problem, might show some... 

Measurement techniques for the resolution of concentration and temperature profiles in chemical reactors with heterogeneously catalyzed gas-phase reactions are a very useful tool not only for a better understanding of the reaction sequence and derivation of reaction kinetics but also for the elucidation of the coupling between catalytic reaction kinetics and mass and heat transport. The combination of numerical simulations of the reactive flow in catalytic reactors incorporating microkinetic reaction schemes and those recently developed invasive and noninvasive in situ techniques can today support the optimization of reactor design and operating conditions in industrial applications. 

There are several principal sets of problem layouts in chemical reaction engineering the calculation of reactor performance, the sizing of a reactor, the optimization of a reactor, and the estimation of kinetic parameters from the experimental data. The primary problem is, however, a performance calculation that delivers the concentrations, molar amounts, temperature, and pressure in the reactor. Successful solutions of the remaining problems—sizing, optimization, and parameter estimation—require knowledge of performance calculations. The performance of a chemical reactor can be prognosticated by mass and energy balances, provided that the outlet conditions and the kinetic and thermodynamic parameters are known. 

Optimal reactor design is critical for the effectiveness and economic viability of AOPs. The WAO process poses significant challenges to chemical reactor engineering and design, due to the (i) multiphase nature of WAO reactions (ii) temperatures and pressures of the reaction and (iii) radical reaction mechanism. In multiphase reactors, complex relationships are present between parameters such as chemical kinetics, thermodynamics, interphase/intraphase intraparticle mass transport, flow patterns, and hydrodynamics influencing reactant mass transfer. Complex models of WAO are necessary to take into account the influence of catalyst wetting, the interface mass-transfer coefficients, the intraparticle effective diffusion coefficient, and the axial dispersion coefficient. " ... 

A batch chemical reactor is to be brought up to operating temperature with a dual-mode system. Full controller output supplies heat through a hot-water valve, while zero output opens a cold-mater valve fully at 50 percent output, both valves are closed. While full heating is applied, the temperature of the batch rises at, IT/min the time constant of the jacket is estimated at 3 min, and the total dead time of the system is 2 min. The normal load is equivalent to 30 percent, of controller output. Estimate the required values for the three adjustments in the optimal switching program. 

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