Simulation saving results

The second procedure is to use a small number of large particles in the beginning of the simulation. The results of that are used as the initial conditions for a simulation with a large number of small particles. Thus, in the final results, the statistical fluctuations are reduced. Also, results from a previous simulation can be used as initial conditions for a new simulation with changed parameters, which saves a large amount of time during parameter scans. 

One approach to verifying functionality is to simulate the netlist with the same set of stimulus as used during design model simulation, save the results in a results file and compare to see if the results are identical. This scenario is shown in Figure 5-2. 

The new tool to investigate the neural structure of stimulus-response sequences was the computer. Now it was possible to measure the reaction times by using special programs, to compute the elementary times and the pathway structures from these reaction times, to evaluate the results statistically, to simulate the results, and to write this text. It was this instrument which permitted to save large amounts of data and evaluate them by special software written for this purpose. Thus it was possible to compute the time quanta and the pathways and to understand each reaction time as an integer multiple of this time quantum (plus a constant value). Computers were also used to record the event-related potentials. Two of the both fundamental parameters of this work (the time quantum called elementary time and the length of the linear pathway) have been confirmed by event-related potentials. 

The positive results and savings due to use of NDT and TD are hundred times grater than made investments. This is the main reason why the philosophy of safety management was changed, i.e. from the philosophy to react and correcf to the principle to predict and reduce the losses . The use of NDT and TD allows to foresee the results of economic-technical activity, to make mostly efficient decisions, to reduce the risks, to simulate mutual processes relations in technogenic, ecological and social-economical fields. 

Figure 1 shows the effect of initiator concentration on optimum temperature and optimum time. It is noticed that increasing the initiator concentration hardly affects the optimum temperatures. However, optimum time decreases considerably from 297 minutes (lo = 0.03 mol/L) to 99 minutes (Iq = 0.15mol/L). As is well known, and shown in Figure 2, equilibrium monomer concentration (M, ) increases with temperature. If temperature is increased further, the monomer concentration can not be reduced to the desired final level because of high values. The initiator concentration should be chosoi taking into account the cost of the initiator and the savings due to reduced time of reaction. An initiator concentration Io=0.10 mol/L that resulted in t,=128 minutes was chosen for further simulation studies. 

There are recent building projects in Canada that generally confirm the simulation results presented. Cost-effectiveness of some of these buildings is even greater than the simulated results due to savings in areas not modeled. 

PPII helix-forming propensities have been measured by Kelly et al. (2001) and A. L. Rucker, M. N. Campbell, and T. P. Creamer (unpublished results). In the simulations the peptide backbone was constrained to be in the PPII conformation, defined as (0,VO = ( — 75 25°, +145 25°), using constraint potentials described previously (Yun and Hermans, 1991 Creamer and Rose, 1994). The AMBER/ OPLS potential (Jorgensen and Tirado-Rives, 1988 Jorgensen and Severance, 1990) was employed at a temperature of 298° K, with solvent treated as a dielectric continuum of s = 78. After an initial equilibration period of 1 x 104 cycles, simulations were run for 2 x 106 cycles. Each cycle consisted of a number of attempted rotations about dihedrals equal to the total number of rotatable bonds in the peptide. Conformations were saved for analysis every 100 cycles. Solvent-accessible surface areas were calculated using the method of Richmond (1984) and a probe of 1.40 A radius. 

A mutual information based information measure is adopted to select the most informative subset of sensors to actively participate in the distributed data fusion framework. The duty of the sensors is to accurately localize and track the targets. Simulation results show 36% energy saving for a given tracking quality can be achievable by selecting the sensors to cooperate according to the mutual information metric. 

This selection specifies that only the Bias Point simulation will run. We do not need to specify any output file options because we will be displaying the results on the schematic. Click the OK button to save the simulation profile and return to the circuit. 

The results of the Fourier analysis will be saved in the output file. When PSpice has finished the simulation, Probe will run and display the waveforms at the markers (we set this up in the previous section). Select View and then Output File... 

Vapour phase enthalpies were calculated using ideal gas heat capacity values and the liquid phase enthalpies were calculated by subtracting heat of vaporisation from the vapour enthalpies. The input data required to evaluate these thermodynamic properties were taken from Reid et al. (1977). Initialisation of the plate and condenser compositions (differential variables) was done using the fresh feed composition according to the policy described in section 4.1.1.(a). The simulation results are presented in Table 4.8. It shows that the product composition obtained by both ideal and nonideal phase equilibrium models are very close those obtained experimentally. However, the computation times for the two cases are considerably different. As can be seen from Table 4.8 about 67% time saving (compared to nonideal case) is possible when ideal equilibrium is used. 

It is clear from Table 5.9 that the results obtained are in very good agreement with the objectives set for each individual optimisation problem. Table 5.9 also deary shows the advantages of optimal reflux policies over the conventional constant reflux operation. Table 5.9 shows that the time optimal control policy (variable reflux) saves about 63% of the operation time compared to that required in the simulation (Table 4.6). Even the time optimal constant reflux policy saves about 33% of the operation time compared to the original simulation... 

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