Computational design parameters

Effect of Uncertainties in Thermal Design Parameters. The parameters that are used ia the basic siting calculations of a heat exchanger iaclude heat-transfer coefficients tube dimensions, eg, tube diameter and wall thickness and physical properties, eg, thermal conductivity, density, viscosity, and specific heat. Nominal or mean values of these parameters are used ia the basic siting calculations. In reaUty, there are uncertainties ia these nominal values. For example, heat-transfer correlations from which one computes convective heat-transfer coefficients have data spreads around the mean values. Because heat-transfer tubes caimot be produced ia precise dimensions, tube wall thickness varies over a range of the mean value. In addition, the thermal conductivity of tube wall material cannot be measured exactiy, a dding to the uncertainty ia the design and performance calculations. 

Classes II and III include all tests in which the specified gas and/or the specified operating conditions cannot be met. Class II and Class III basically differ only in method of analysis of data and computation of results. The Class II test may use perfect gas laws in the calculation, while Class III must use the more complex real gas equations. An example of a Class II test might be a suction throttled air compressor. An example of a Class III test might be a CO2 loop test of a hydrocarbon compressor. Table 10-4 shows code allowable departure from specified design parameters for Class II and Class III tests. 

A number of areas in which plastics are used in electrical and electronic design have been covered there are many more. Examples include fiber optics, computer hardware and software, radomes for radar transmitters, sound transmitters, and appliances. Reviewed were the basic use and behavior for plastics as an insulator or as a dielectric material and applying design parameters. The effect of field intensity, frequency, environmental effects, temperature, and time were reviewed as part of the design process. Several special applications for plastics based on intrinsic properties of plastics materials were also reviewed. 

After perusal of these process options, the engineer asks the computer to select five designs for further study, and the oomputer produces a paper copy of the flowsheet and design parameters... 

Based on a detailed mathematical model, one can make computer simulations of the behaviour of various reactor types. Optimization of operating conditions and design parameters can be done for each reactor type. Downstream equipment should also be taken into account since the cost of product isolation and purification can heavily influence the final choice of all equipment items. A proper combination of investment and operating costs is used as the... 

The idea of a root locus plot is simple—if we have a computer. We pick one design parameter, say, the proportional gain Kc, and write a small program to calculate the roots of the characteristic polynomial for each chosen value of as in 0, 1, 2, 3,., 100,..., etc. The results (the values of the roots) can be tabulated or better yet, plotted on the complex plane. Even though the idea of plotting a root locus sounds so simple, it is one of the most powerful techniques in controller design and analysis when there is no time delay. 

The intelligent computer software CyclePad is a very effective tool in design cycles. Any complicated gas cycle can be easily designed and analyzed using CyclePad. Optimization of design parameters of the cycle is demonstrated by the following examples. 

Burrell, G.R. Key Design Parameters of a Computer Production Control System. paper prevented at 22nd Annual Technical Meeting of the Pet.. Sac. of CTM. Banff, Alta.. June 2-4,1971,... 

Extraction DCs values have been shown to be affected most strongly by the potassium concentration in the feed, temperature variation, nitrate concentration, and hydroxide concentration [41,49-51,53,54], Flowsheet design parameters include O/A ratios, number of extraction stages, and possibly temperature control, and the computer model developed for CSSX extraction behavior [53,54] may be employed to estimate the values of DCs for various waste compositions at 25 °C. The model remains to be expanded to cover expected changes in some compositional variables (especially high K+ concentrations), temperature, and concentrations of solvent components. 

Effective system design depends on the proper application of the principles of thermodynamics, kinetics, and transport phenomena. Reliable design data are invariably obtained empirically because ab initio computation of design parameters, such as kinetic quantities, are not sufficiently reliable for engineering purposes. 

For better model discrimination and/or parameter estimation, sequential methods for computer designed plans of experiments have been proposed [52], They take advantage of the information obtained from the previous experiments and plan the new experiments in the region of independent variables where the maximum difference of the dependent variable can be expected. 

No formal optimization of the parameters was attempted. Instead, individual feed, operating, and design parameters were perturbed around a standard set to assess their influence on the computed performance parameters. 

Cybulski et al. [39] have studied the performance of a commercial-scale monolith reactor for liquid-phase methanol synthesis by computer simulations. The authors developed a mathematical model of the monolith reactor and investigated the influence of several design parameters for the actual process. Optimal process conditions were derived for the three-phase methanol synthesis. The optimum catalyst thickness for the monolith was found to be of the same order as the particle size for negligible intraparticle diffusion (50-75 p.m). Recirculation of the solvent with decompression was shown to result in higher CO conversion. It was concluded that the performance of a monolith reactor is fully commensurable with slurry columns, autoclaves, and trickle-bed reactors. 

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