Reactor-specific parameters

Earlier studies conqiaring feeding at the top or at the bottom of a gasifier have shown differences in the product distribution [11]. However, this reference makes a comparison between the feeder positions in different reactors, where other reactor-specific parameters also can influence the results, and does not include any measurements of the ammonia concentration. 

The operations of chemical reactors are expressed in terms of extensive, system-specific parameters (i.e., reactor volume, molar flow rates). In contrast, the common approach used in the design of most operations in chemical engineering is based on describing the operation in terms of dimensionless quantities. Dimensionless formulations provide an insight into file underlining phenomena that affect the operation, which are lost when file analysis is case specific. 

For a specific reactor design, parameter B is constant. Raw material costs increase faster than q when q/B >0.1. This is caused by increased feed rate W and increased unconverted Algol in the effluent. The variable production cost can also be expressed in terms of the annual Delos production q ... 

Determination of the loads through analysis of the reactor operating parameters combined with thermal hydraulics calculations for the specific thermal stratification and fluctuation areas. For this purpose, the recent R D progress made in the EFR (European Fast Reactor) project was used and transposed to a real installation. 

The choice and the design of a suitable reactor for gas-liquid reaction or absorption is very often a question of matching the chemical thermodynamics and the reaction kinetics with the capabilities of the proposed reactor. Specific interfacial area a, liquid holdup S or gas holdup a and mass transfer coefficients kLa and kQa are the most significant characteristics of a reactor. Some published values of the mass transfer parameters will be presented now. Our objective here is to help to answer the following questions ... 

The model of Reference (67) was later applied to evaluate the performance of an SCR catalyst with proprietary composition (124). Koebel and Elsener also compared, on a fully predictive basis, a similar model to experimental data of NO conversion and NH3 slip obtained on a diesel engine test stand (125). In this case, while the model was shown to describe qualitatively the performance of the SCR monolithic reactor, specifically with reference to the NO conversion versus NH3 slip relationship, an exact quantitative match was found impossible. According to the authors, the reasons for the discrepancies may include unaccovmted kinetic effects of the contaminants present in the diesel exhaust gases, vmcertainties due both to the extrapolation of the kinetic parameters and to the measurement of the intraporous diffusivities, and the excessive simplification involved in the assumption of a pure Langmuir isotherm for NH3 adsorption. 

The equilibrium concentration in the coolant after a longer time of steady-state operation of the plant is controlled by the production rate and the penetration rate, on the one hand, and by the removal rate on the other. For this reason it can vary considerably from plant to plant. In PWR plants, the equilibrium activity concentration in the primary coolant usually is within the range of 10 to 30 GBq/ Mg, in BWR plants it is considerably lower (about two orders of magnitude). In a PWR, the most important source is the generation from the B dissolved in the coolant in addition, in the case of insufficient LiOH isotopic purity the Li reaction may become important. In BWR plants which contain neither boron nor lithium in the coolant (with the possible exception of inadvertently introduced impurities), neutron capture in deuterium is usually the main somce. Due to the low base level of activity in the BWR reactor water, the penetration from fuel and control rods gains a greater significance, the extent of which depends on plant-specific parameters. 

The reactor unit is intended to generate steam of specific parameters. The reactor unit, shown in Fig. IV-7 and Fig. IV-8, includes ... 

SET and ASSIGN the only specific parameters-variables for kinetics model (kineticsl) in the sim reactor 2 process separately SET ko(j), Ea(j), gas constant, and RO and ASSIGN T. kineticsl is called using within reactorl. kineticsl DO. .. End. ... 

The structure itself was not fully consistent with typical or most significant NPP systems and the characteristics were of unequal detail, level or nature for different plant systems included in the database. Some items were specific for particular types of reactors, not applicable to other types, so some data fields had to be left blank. If a data field had been left blank, it was not clear why the data were missing (whether the characteristic was not applicable to the unit or the data provider failed to enter them). Some characteristics were of a questionnaire type suggesting yes/no answers. Such characteristics would provide only qualitative information on a particular system, equipment or practice used at the NPP, whereas no specific parameters of the equipment had been provided. 

Develop an unsteady-state model for a stirred batch reactor, using the nonlinear continuous reactor model presented in Example 4.8 as a starting point. For the parameter values given below, compare the dynamics of the linearized models of the batch reactor and the continuous reactor, specifically the time constants of the open-loop transfer function between c a and T c, the concentration of A, and the jacket temperature, respectively. Assume constant physical properties and the following data ... 

The parameter ranges covered in the spherical reactor calculations arc given in Table 10-2. Values used for and resonance escape probability are presently accepted values however, in a few cases they were varied in order to estimate how the results are affected by these changes. In the following sections the influence of specific parameters upon fuel cost is discussed. 

Among the most critical reactor-specific control parameters (see Figures 7.12 and 7.13) station control, power supply (generator), and gas control metrics are primary. 

A reactor performance monitoring program shall be established to optimize overall reactor performance as well as system and individual component performance and reliability. Specific parameters which are to be monitored through this program shall be identified. 

The designer usually wants to specify stream flow rates or parameters in the process, but these may not be directly accessible. For example, the desired separation may be known for a distiUation tower, but the simulation program requires the specification of the number of trays. It is left up to the designer to choose the number of trays that lead to the desired separation. In the example of the purge stream/ reactor impurity, a controller module may be used to adjust the purge rate to achieve the desired reactor impurity. This further complicates the iteration process. 

Type of Reactor The specific type of reac tor that is most compatible (or least incompatible) with the CTiosen combination of the preceding parameters seldom is clearly and unequivocally perceived without difficulty, if at all. In the end, however, that remains the objective. As is always true, the ultimate criteria are rehabihty and profitability. 

The second classification is the physical model. Examples are the rigorous modiiles found in chemical-process simulators. In sequential modular simulators, distillation and kinetic reactors are two important examples. Compared to relational models, physical models purport to represent the ac tual material, energy, equilibrium, and rate processes present in the unit. They rarely, however, include any equipment constraints as part of the model. Despite their complexity, adjustable parameters oearing some relation to theoiy (e.g., tray efficiency) are required such that the output is properly related to the input and specifications. These modds provide more accurate predictions of output based on input and specifications. However, the interactions between the model parameters and database parameters compromise the relationships between input and output. The nonlinearities of equipment performance are not included and, consequently, significant extrapolations result in large errors. Despite their greater complexity, they should be considered to be approximate as well. 

Parameter Estimation Relational and physical models require adjustable parameters to match the predicted output (e.g., distillate composition, tower profiles, and reactor conversions) to the operating specifications (e.g., distillation material and energy balance) and the unit input, feed compositions, conditions, and flows. The physical-model adjustable parameters bear a loose tie to theory with the limitations discussed in previous sections. The relational models have no tie to theory or the internal equipment processes. The purpose of this interpretation procedure is to develop estimates for these parameters. It is these parameters hnked with the model that provide a mathematical representation of the unit that can be used in fault detection, control, and design. 

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