SETTING UP A STEADY-STATE SIMULATION

In this chapter we begin at the beginning. We take a simple binary separation and go through all the details of setting up a simulation of this system in Aspen Plus using the rigorous distillation column simulator RadFrac. 

All the pieces of a distillation column will be specified (column, control valves, and pumps) so that we can perform a dynamic simulation after the steady-state simulation is completed. If we were only interested in a steady-state simulation, pumps and control valves would not have to be included in the flowsheet. However, if we want the capability to do simultaneous design (steady-state and dynamic), these items must be included to permit a pressure-driven dynamic simulation. 

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All the details of setting up and running a steady-state simulation of a simple distillation column have been presented in this chapter. These methods are applied to a variety of columns in later chapters. 

The spatial temperature distribution established under steady-state conditions is the result both of thermal conduction in the fluid and in the matrix material and of convective flow. Figure 2. 9.10, top row, shows temperature maps representing this combined effect in a random-site percolation cluster. The convection rolls distorted by the flow obstacles in the model object are represented by the velocity maps in Figure 2.9.10. All experimental data (left column) were recorded with the NMR methods described above, and compare well with the simulated data obtained with the aid of the FLUENT 5.5.1 [40] software package (right-hand column). Details both of the experimental set-up and the numerical simulations can be found in Ref. [8], The spatial resolution is limited by the same restrictions associated with spin... 

Our experimental set-up (described in ref. 7), allows us to record steady state absorption and emission spectra over a wide range of densities (10 5 to 20 at/nm3) in the Ar supercritical domain (Tc = 150.8 K, Pc = 49 bar). Representative absorption and emission spectra are shown in figure 1. These spectra could be reproduced with a good accuracy by means of equilibrium MD simulations performed with a standard procedure [8], In these simulations, the NO X-Ar and Ar-Ar interaction potentials were taken from the literature [9], We extracted an analytical NO A-Ar pair potential by an iterative fit of the experimental spectra, valid for the whole supercritical domain. 

All of the dynamic simulations discussed in this book use pressure-driven flows. The alternative of using a flow-driven simulation is more simple, but not at all realistic of the actual situation in a real physical process. The plumbing in the real process has to be set up so that water flows downhill. Pumps, compressors, and valves must be used in the appropriate locations to make the hydraulics of the system operate. If valves are not designed with sufficient pressure drop under steady-state conditions, they may not be able to provide the required increase in flow even when wide open. So valve saturation must be included in the rigorous nonlinear dynamic simulation. It is much better to simulate a realistic system by using a pressure-driven simulation. 

For many mechanisms, the steady-state Eia or N tt value is a function of just one or two dimensionless parameters. If simulations are used to generate the working curve (or surface) to a sufficiently high resolution, the experimental response may be interpolated for intermediate values without the need for further simulation. A free data analysis service has been set up (Alden and Compton, 1998) via the World-Wide-Web (htttp //physchem.ox.ac.uk 8000/wwwda/) based on this method. As new simulations are developed (e.g. for wall jet electrodes), the appropriate working surfaces are simulated and added to the system. It currently supports spherical, microdisc, rotating disc, channel and channel microband electrodes at which E, EC, EC2, ECE, EC2E, DISP 1, DISP 2 and EC processes may be analysed. 

A very remarkable property exhibited by non equilibrium systems is the appearance of coherence and long range order [1] Once subjected to a constraint which maintains a system in a nonequilibrium steady state, fluctuations which occur in its different parts, are not independent. The correlation extends over the size of the sample [2-5]. We shall here study the origin of this behaviour in a simple example and describe a simulation set up in order to demonstrate this property. 

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