Simulating design calculation

Using the flowsheet simulators, design calculations are needed to estimate the reflux ratio and the theoretical tray requirements for the two towers in each of the sequences. In ASPEN PLUS, this is accomplished with the DSTWU subroutine, which is described in the module ASPEN — Separators Distillation FUG Shortcut Design on the multimedia CD-ROM. 

The considerable agreement is reached between the results of simulation design calculation and their actual operating parameters. It can be seen from Table 2.19 that under the same conditions the output of ammonia can increase up to 1,158.6 tons per day, if AllO is replaced by ZA-5 catalyst. The temperature of the whole reactor decreases, but that of outlet of the reactor rises. Thereinto, (1) the inlet temperature of the first bed decreases from 359°C to 325°C (2) temperature at the outlet of the reactor rises to 34.5°C which is still in the range of design values permitted (3) net ammonia value increases by 2.3%, and output of ammonia increases up to l,158.6t/d, or raises by 15.8%. 

The result of simulation design calculation shows that it is feasible to replace AllO by ZA-5 with high activity in the synthesis reactors used originally for AllO catalyst.However, it should be noted that ZA-5 is a new wiistite-based catalyst operating at low-temperatures. Its superiority can be better if it is used at low-temperatures. Therefore, it is not necessary to use it at high-temperatures at... 

Table 2.19 Results obtained by simulating design calculation...

Process calculations for traditional unit-operations equipment can be divided into two types design and performance. Sometimes the performance calculation is caHed a simulation (see Simulation and process design). The design calculation is used to roughly size or specify the equipment. EoUowing the... 

Hypercubes and other new computer architectures (e.g., systems based on simulations of neural networks) represent exciting new tools for chemical engineers. A wide variety of applications central to the concerns of chemical engineers (e.g., fluid dynamics and heat flow) have already been converted to run on these architectures. The new computer designs promise to move the field of chemical engineering substantially away from its dependence on simplified models toward computer simulations and calculations that more closely represent the incredible complexity of the real world. 

Using the digital simulation approach to steady-state design, the design calculation is shown to proceed naturally from the defining component balance and energy balance equations, giving a considerable simplification to conventional text book approaches. 

A number of design calculations require a knowledge of thermodynamic properties and phase equilibrium. In practice, the designer most often uses a commercial physical property or a simulation software package to access such data. However, the designer must understand the basis of the methods for thermodynamic properties and phase equilibrium, so that the most appropriate methods can be chosen and their limitations fully understood. 

In many respects, the solutions to equations 12.7.38 and 12.7.47 do not provide sufficient additional information to warrant their use in design calculations. It has been clearly demonstrated that for the fluid velocities used in industrial practice, the influence of axial dispersion of both heat and mass on the conversion achieved is negligible provided that the packing depth is in excess of 100 pellet diameters (109). Such shallow beds are only employed as the first stage of multibed adiabatic reactors. There is some question as to whether or not such short beds can be adequately described by an effective transport model. Thus for most preliminary design calculations, the simplified one-dimensional model discussed earlier is preferred. The discrepancies between model simulations and actual reactor behavior are not resolved by the inclusion of longitudinal dispersion terms. Their effects are small compared to the influence of radial gradients in temperature and composition. Consequently, for more accurate simulations, we employ a two-dimensional model (Section 12.7.2.2). 

Continuous binary distillation is illustrated by the simulation example CON-STILL. Here the dynamic simulation example is seen as a valuable adjunct to steady state design calculations, since with MADONNA the most important column design parameters (total column plate number, feed plate location and reflux ratio) come under the direct control of the simulator as facilitated by the use of sliders. Provided that sufficient simulation time is allowed for the column conditions to reach steady state, the resultant steady state profiles of composition versus plate number are easily obtained. In this way, the effects of changes in reflux ratio or choice of the optimum plate location on the resultant steady state profiles become almost immediately apparent. 

Our steadystate design calculations teU us nothing about what the dynamic response to the system will be. They teU us where we will start and where we will end up but not how we get there. This kind of information is what a study of the dynamics of the system will reveal. We will return to this system later in the book to derive a mathematical model of it and to determine its dynamic response quantitatively by simulation. 

In the same way that tests based on arbitrary conditions are deficient for design data purposes, so they may tend to lack in their direct relevance to service conditions and, hence, their value for predicting service performance. The two situations are not identical, in particular a test may simulate service use to enable predictions to be made but not yield data which can be used in design calculations. Not only for product proving but also for quality control, there is increasingly demand for tests which are better in this respect. A prime difficulty is that as effort is made to make the method reflect service so it tends to become more complicated and more expensive. There are many instances in specifications where a more relevant test exists but is not used because it is more time consuming or complex. 

In view of the large influence of interaction effects found by Toor and Burchard (1960) it is a little surprising that there have been so few design calculations reported in the literature. More experience with these models is required before definitive conclusions can be made regarding the use of complicated efficiency models in sophisticated distillation codes. The whole issue of multicomponent mass transfer models in distillation column simulation is taken up again in Chapter 14. 

In considering very many condenser simulations (not just those reviewed here) we have yet to find an application where the differences between any of the multicomponent film models that account for interaction effects (Krishna-Standart, 1976 Toor-Stewart-Prober, 1964 Krishna, 1979a-d Taylor-Smith, 1982) are significant. There is also very little difference between the turbulent eddy diffusivity model and the film models that use the Chilton-Colburn analogy (Taylor et al., 1986). This result is important because it indicates that the Chilton-Colburn analogy, widely used in design calculations, is unlikely to lead to large... 

Future work in methanol will involve accurate tuning of the models developed so far to allow further optimisation of the unit. As well as this the simulations will provide some of the process design calculations for expansion studies (eg direct injection of CO into the methanol loop) and case studies into different operating modes of the plants. 

Information flow in a standard simulation problem calculates unit outputs (stream values) given input streams and unit parameters (simulation problem). Design requires specification of an output variable and then calculating an input value or equipment parameter (design problem). 

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