Running Simulations

Files that have been previously read into ISIM can be run by typing START after the prompt. A graph of one variable against time is plotted on the screen, and numerical values of other variables may also be displayed. In Section 8 it will be shown how to control this output. 

Runs with complex examples may sometimes fill up a hard disk. The variables in the PREPARE statement should be reduced and the run repeated. 

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These calculations can incorporate various types of constraints. It is most common to run simulations with a hxed number of atoms and a hxed volume. In this case, the temperature can be computed from the average kinetic energy of the atoms. It is also possible to adjust the volume to maintain a constant pressure or to scale the velocities to maintain a constant temperature. 

For a conformation in a relatively deep local minimum, a room temperature molecular dynamics simulation may not overcome the barrier and search other regions of conformational space in reasonable computing time. To overcome barriers, many conformational searches use elevated temperatures (600-1200 K) at constant energy. To search conformational space adequately, run simulations of 0.5-1.0 ps each at high temperature and save the molecular structures after each simulation. Alternatively, take a snapshot of a simulation at about one picosecond intervals to store the structure. Run a geometry optimization on each structure and compare structures to determine unique low-energy conformations. 

In this study the reader is introduced to the procedures to be followed in entering parameters into the CA program. For this study we will keep Pm = 1.0. We will first carry out 10 runs of 60 iterations each. The exercise described above will be translated into an actual example using the directions in Chapter 10. After the 10-run simulation is completed, determine (x)6o, y)60, and d )6o, along with their respective standard deviations. Do the results of this small sample bear out the expectations presented above Next, plot d ) versus y/n for = 0, 10,20, 30,40, 50, and 60 iterations. What kind of a plot do you get Determine the trendline equation (showing the slope and y-intercept) and the coefficient of determination (the fraction of the variance accounted for by the model) for this study. Repeat this process using 100 runs. Note that the slope of the trendline should correspond approximately to the step size, 5=1, and the y-intercept should be approximately zero. 

For the 100-run simulation, prepare a bar chart of the relative final positions of the ingredients... 

Variations on these include running simulations at a variety of temperatures or running Langevin dynamics with a low friction constant to increase the ability to cross barriers at a given temperature (Pastor, W. R. Karplus, M., to be published.). 

Derive the dimensionless form of the balances to show kx to be the governing parameter. Run simulations to confirm this. 

As a first attempt to modify the code to be able to run simulations on SiH4-H2 discharges, a hybrid PlC/MC-fluid code was developed [264, 265]. It turned out in the simulations of the silane-hydrogen discharge that the PIC/MC method is computationally too expensive to allow for extensive parameter scans. The hybrid code combines the PIC/MC method and the fluid method. The electrons in the discharge were handled by the fluid method, and the ions by the PIC/MC method. In this way a large gain in computational effort is achieved, whereas kinetic information of the ions is still obtained. 

Reaction-diffusion systems can readily be modeled in thin layers using CA. Since the transition rules are simple, increases in computational power allow one to add another dimension and run simulations at a speed that should permit the simulation of meaningful behavior in three dimensions. The Zaikin-Zhabotinsky reaction is normally followed in the laboratory by studying thin films. It is difficult to determine experimentally the processes occurring in all regions of a three-dimensional segment of excitable media, but three-dimensional simulations will offer an interesting window into the behavior of such systems in the bulk. 

Choose values of the equilibrium constant so that the separation is difficult. Run simulations with increased column length or number of plates to improve the separation. 

One possibility is to run simulated annealing refinement in torsion angle space as implemented in CNS (Briinger et ah, 1998). As this is one of the most powerful programs in terms of radius of convergence, it is especially useful to look for the decrease of the free-R-factor (Adams et al., 1999), but this is a rather cpu-intensive task if several possible solutions are to be tested. 

We are now done with the schematic. We will set up the transient analysis shown below. Once again, this is an advanced topic, and we assume that you are familiar with Capture, plotting traces with Probe, and running simulations in PSpice. 

Solvation effects were neglected in the Kubicki and Apitz study, in part, because of limited computer power.65 As a matter of general practice, however, one would probably run these types of gas-phase calculations prior to running simulations within a solvent even with unlimited computer resources. This is a common strategy to evaluate the effects of solvation on structure and one that provides an initial guess for the solvation calculations. One advantage of the molecular modeling approach is the ability to add and subtract components at will in order to assess the effects they have on the behavior of the system. 

Even with modem supercomputers it is rarely possible to run simulations for longer than 10 ns. If the probabilities of the events of interest (e g. a defect jump) are low in a period of this length, then the simulation may be of httle value. Thus, in practice, with currently available computer power, diffusion can only be studied for values of the diffusion coefficient D > 10 cm ... 

It is interesting to note that our worst case estimate of 18mgm was not reached in the 10 000 run simulation the highest prediction in this run (i.e., the 100th percentile) was 14.5 mg m. Similarly, the lowest value (i.e., the 0%tile) was 0.07mgm, which is relatively close to the 0.065 mg m value as the absolute best case. 

The optimnm phase type needs to be determined from core floods using reservoir cores. The phase type with the highest oil recovery factor is the optimnm salinity type. It is not necessarily type III. Meanwhile, the optimum salinity is determined. It is not necessarily the middle salinity of type III or a salinity in type III. Core flood experiments take into account all parameters snch as interfacial tension, relative permeability, phase trapping, and so on, becanse these experiments are essentially a replication of the flooding process that wonld occnr dnring the FOR process in the field. Practically, we cannot afford to rnn many core floods to identify the optimum type, but we can run simulations to preselect the type. 

Fig. 5 Screen capture of a 10-plate run simulation for the TNAP protocol of Fig. 4 for a (a) 30-min incubation and a (b) 40-min incubation for each plate. The various color-coded bars correspond to unit operations that are performed on each plate. Their duration is indicated by the length of the bars and the color code key is indicated at the bottom of the figures for the seven major operations...

In test runs simulating actual gas turbine conditions this approach produced less than Ippm NO with a combustor outlet temperature of 1400 °C [14]. Even at a combustor outlet temperature of 1500 °C NO levels were only 2.2 ppm, indicating that this approach will also be applicable to the next generation of gas turbines with higher inlet temperatures. In addition, the low catalyst temperature allows the use of metal substrates, which are resistant to thermal shock, and produces a durable, high-activity catalyst system. 

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