Process design model-based determination

In practical combustion systems, such as CO boilers, the flue gas experiences spatial and temporal variations. Constituent concentration, streamline residence time, and temperature are critical to determining an efficient process design. Computational fluid dynamics (CFD) modeling and chemical kinetic modeling are used to achieve accurate design assessments and NO, reduction predictions based on these parameters. The critical parameters affecting SNCR and eSNCR design are listed in Table 17.4. 

A model based on a modified mixing rule for the Peng-Robinson equation of state was able to reproduce quantitatively all features of the observed phase equilibrium behavior, with model parameters determined from binary data only. The use of such models may substantially facilitate the task of process design and optimization for separations that utilize supercritical fluids. 

The detailed course of a polymerization is determined by the nature of the particular reaction as well as by the characteristics of the reactor which is used. The design and control of the operation are greatly aided by mathematical modeling of the process. Such models may be based on empirical relations between the independent and dependent operating variables. This is not as satisfactory, however, as a model that is derived from accurate knowledge of the polymerization process and reactor operation, because only the latter tool permits extrapolation to reaction conditions that have not yet been tried. 

Similar to the design approaches employed in most water and wastewater treatment processes such as biological wastewater treatment, there are empirical (also called irrational) and model-based (rational) methodologies used for design of UV unit for aqueous-phase disinfection. The first one is based on empirical experience and has traditionally been used in the water industry, while the second one is based on a series of detailed mathematical analyses and experimental measurements and is still in the research phase. In the design, one will determine the requirement of UV lamps applied to the water based on the characteristics of water such as flow rate and the size of the disinfection unit. 

The value of the monomer partition coefBcient between the CO2 and the water phase indirectly determines the ratio between the effect of enhanced polymerization and the effect of extraction on the reduction of residual monomer. Depending on the process conditions, i.e. temperature, pressure, and the phase behavior of the system involved, this ratio between enhanced polymerization and extraction may vary for different latex systems. With respect to the PMMA latex, the high partition coefBcient m2 as shown in Section 14.4, causes extraction to be the predominant effect as compared to conversion of the monomer. Therefore, a preliminary process design has been developed based on C02-extraction. For this purpose, a mass transfer model has been set up to determine the rate-limiting step in the extraction process. In addition, a process flow diagram, including equipment sizing has been developed. Finally, an economic evaluation has been performed to study the viability of this technique for the removal of residual monomer from latex-products. 

Kinetic modeling of catalytic reaction systems plays a critical role in the design and optimization of chemical reactors and processes. The models that have been developed over the years have been the result of our understanding of the chemistry, available analytical capabilities, and the desired level of the results. Many of the earliest kinetic models were simply power-law models, i.e. empirical relationships between the measured partial pressures (or compositions) and the reaction rate. The earliest models were based solely on overall composition, conversion and yields since that was all that could be routinely determined. Despite their simplicity, power-law models are still used to model a number of industrial chemical processes. They capture the relevant information and can be used to predict daily operation and control of industrial reactors. 

The dynamic behaviour of batch process units changes with time and this makes their precision control difficult. The aim of this paper is to highlight that the slave process of batch process units can have a more complex dynamics than the master loop has, and very often this could be the reason for the non-satisfying control performance. Since the slave process is determined by the mechanical construction of the unit, the above mentioned problem can be effectively handled by a model-based controller designed using an appropriate nonlinear tendency model. The paper presents the structure of the tendency model of typical slave processes and presents a case study where real-time control results show that the proposed methodology gives superior control performance over the widely applied cascade PID control scheme. 

The reason for the non-satisfying control performance of batch process units very often is the slave process that can have a more complex dynamics than the master loop has. As the slave process is determined by the mechanical construction, it is straightforward to design a model-based controller based on a nonlinear tendency model of the slave process. It has been shown that the parameters of the model-based slave controller (namely the parameters of the tendency model) can be easily determined by simple process experiments, and the complexity of the controller is comparable to that of a well furnished PID controller. Real-time control results showed that the proposed controller effectively handles the constraints (no windup) and gives superior control performance. 

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