Simulation parameters

A typical molecular dynamics simulation comprises an equflibration and a production phase. The former is necessary, as the name imphes, to ensure that the system is in equilibrium before data acquisition starts. It is useful to check the time evolution of several simulation parameters such as temperature (which is directly connected to the kinetic energy), potential energy, total energy, density (when periodic boundary conditions with constant pressure are apphed), and their root-mean-square deviations. Having these and other variables constant at the end of the equilibration phase is the prerequisite for the statistically meaningful sampling of data in the following production phase. 

In general, Laiigeviii dynamics sim illation s run much the same as nioleciilar dynamics simulations. There are differences due Lo the presence of additional forces. Most of the earlier discussions (see pages 69-yO an d p. 3 10-327 of this man ual) on simulation parameters and strategies for molecular dyn amics also apply to Lan gevin dynamics exceptions and additional con sideraiion s are noted below. 

Eig. 3. Simulation parameters (a) splash onto cylindrical nosetip (b) attached wedge (—fixed -------, varied) and (c) detached wedge. See Table 3. 

MCBase offers the possibility to load the original CAMPUS data of different suppliers from version 3.0 and higher into one database, which allows direct comparison. It has been developed in close cooperation with the CAMPUS consortium. For more information see http //www.m-base.de/. MCBase is user friendly and offers extremely efficient handling of material data. All CAMPUS options are available define search profiles define and sort tables print tables and data sheets curve overlay scatter plots. In addition MCBase 4.1 offers search in curves search for comparable grades text search update via Internet calculation of simulation parameters. A French version of MCBase is available from the distribution agent in France. 

Figure 3. Comparison of the simulated diffusion coefficient (0) with the theoretical value Do (solid line). The simulation parameters are a = n/2, L/a = 100, i. m 1. and kBT =...

The methodology discussed previously can be applied to the study of colloidal suspensions where a number of different molecular forces and hydrodynamic effects come into play to determine the dynamics. As an illustration, we briefly describe one example of an MPC simulation of a colloidal suspension of claylike particles where comparisons between simulation and experiment have been made [42, 60]. Experiments were carried out on a suspension of AI2O3 particles. For this system electrostatic repulsive and van der Waals attractive forces are important, as are lubrication and contact forces. All of these forces were included in the simulations. A mapping of the MPC simulation parameters onto the space and time scales of the real system is given in Hecht et al. [42], The calculations were carried out with an imposed shear field. 

France, D. M., R. D. Carlson, R. R. Rhode, and G. T. Charmoli, 1974, Experimental Determination of Sodium Superheat Employing LMFBR Simulation Parameters, Trans. ASME, J. Heat Transfer 9(5 359. (4)... 

Fig. 7.18 Plots of relative N-C(a)-C angle values (surfaces of differences, in degrees, relative to the values at < > = / = 180°) for the ( ), /-space of ALA. The top surface represents values directly calculated for ALA as a whole by HF/4-21G geometry optimizations the center surface represents simulated parameter values which were obtained using the conformational geometry function additivity principle as described in the text. The bottom surface is the difference, top minus center. All surfaces were plotted with the same scale factor, but offset by arbitrary and constant amounts for the sake of graphical clarity. The numerical values used to construct this Figure were taken from L. Schafer, M. Cao, M. Ramek, B. J. Teppen, S. Q. Newton, and K. Siam, J. Mol. Struct., in press.

A host of successful methods have been devised that use two or more replicas of the system run in parallel and corresponding to different simulation parameters. The enhanced equilibrium averaging is achieved by Metropolis-type acceptance-rejection... 

Fig. 20. Excess compressibility yIS for a system of inelastic hard spheres, as function of the coefficient of normal restitution, for one solid fraction (as = 0.05). The excess compressibility has been normalized by the excess compressibility y is of the elastic hard spheres system. Other simulation parameters are as in Fig. 19.

Fig. 6.6 (a) k2 as a function of polymer thickness for the first three WGMs. Dashed line indicates the k2 position for the first order ring resonator wall mode in the absence of the polymer layer. The simulation parameters are the same as in Fig. 6.4, except that the polymer RI, n2, is 1.7. (b) The WGM radial distribution of the second order mode for various polymer thicknesses indicated by the arrows in (a). Vertical lines indicate the boundaries of the ring resonator wall and the polymer layer. Reprinted from Ref. 29 with permission. 2008 Optical Society of America... 

The algorithms discussed earlier for time averaging and local time stepping apply also to velocity, composition PDF codes. A detailed discussion on the effect of simulation parameters on spatial discretization and bias error can be found in Muradoglu et al. (2001). These authors apply a hybrid FV-PDF code for the joint PDF of velocity fluctuations, turbulence frequency, and composition to a piloted-jet flame, and show that the proposed correction algorithms virtually eliminate the bias error in mean quantities. The same code... 

Figure 6 shows the behavior of the reduced monomer density p z)Rp/Np at increasing anchoring density. The stretching of the chains with increasing surface coverage, which is due to the repulsion between monomers, is evident. This plot has to be compared with Fig. 3b, where the same type of rescaling has been used. However, note that at this point, direct and quantitative comparison is not possible, since it is a priori not clear which value of the interaction parameter /3 in the self-consistent calculation corresponds to which set of simulation parameters ct, N, pa. 

The electrode mechanisms treated, along with the rate laws and the appropriate digital simulation parameters, are shown in Table 16. The symbols for mechanisms 5 and 6, RS-2 and RS-3, indicate that these reactions represent cases of radical (primary intermediate B) reacting with substrate (A). Mechanism 5 foDows second-order kinetics while third-order kinetics characterize mechanism 6. The theoretical data for the mechanisms are summarized in Tables 17—23. The calculations are for EX — f revI equal to 300 mV. Data are also available for EX — Eiev — 100 mV. In the following paragraph, the data are explained with reference to the eC mechanism, i.e. Table 17. 

Analysis of NMRD data to obtain values for q, r, rR> rM> and rs is a complex process, complete with the problem of non-uniqueness of the best simulation parameters. New methods are being developed in which NMRD data is combined with data from other physical methods to assist in developing a best set of parameters [4,63]. 

Koh, J., Seo, H., Yoo, Y. and Eim, H. (2002) Consideration of numerical simulation parameters and heat transfer models for a molten carbonate fuel cell stack, Chemical Engineering Journal 87, 367-379. 

Fig. 10 Simulation results for a cylinder-forming A3B12A3 (6ab = 6.5) in thin films (thickness = 6 nm = ao) with varied strength of the symmetric surface field The isodensity profiles (Pa = 0.45) are shown for indicated simulation parameters. Reprinted from [58], with permission. Copyright 2004 American Institute of Physics...

Table 2, Minimum percent error and corresponding simulation parameters for the distributed-rate model...

With Dynamics tab active, enter simulation parameters (default settings step interval, 2.0 fs frame interval, 10 fs terminate after 1000 steps, heating/cooling rate, 1.0 kcal/atom/ps and target temperature, 300 K). 

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