Collisions simulation

The loose virtual bond set works best at maximizing the simulation timescale per million collisions. As listed in Table 3, a simulation of 50 lysozymes shows that for a 100-million-collision simulation, the simulation-reduced time achieved with the loose virtual bond set is 1.4 times that with the moderate virtual bond set and 3.3 times that with the rigid virtual bond set. DMD simulations of complex molecules such as proteins spend more than 90 % of the simulation time in collisions between the bonded beads, indicating that the timescale of a DMD simulation heavily depends on the bond flexibility. A loose virtual bond set allows the simulation to advance much faster than a rigid one. However, the loose set may also increase the risk that the protein will deform. This risk should be taken into account when selecting proper virtual bonds. 

State of the art for evaluation on the physiological level are injury probability models (in case detailed collision simulations are not available or feasible). In many cases, e.g., if used in combination with a stochastic simulation, those models provide a translation of physical measurements at the moment of impact into physiological quantities. Considering pedestrians, models currently available are based on the person level (overall injury severity) and are mainly univariate using impact speed of... 

Figure 8. Evolution of N in a set of 11 runs using common dynamical data. Same parameters and initial conditions as Figure 6. The first 10% of the full 10 -collision simulation is shown. Fluctuations about the trajectories have been suppressed, hut the range of fluctuations about the two steady states is indicated at right (22).

Before any physical movement is done in the real inspection environment, the optimal robot configuration and motion are planned and simulated in a virtual iuspection environment in the ROBCAD 3D robot simulation system. If any collisions or near-collisions are occurring or all the calculated inspection points can not be reached the robot configuration and/or robot inspection programs can be adjusted off-line accordingly without the need of the physical robot or inspection environment. This ensures that the time scheduled for the physical inspection is used actively for inspection instead of testing and configuration. 

Two simulation methods—Monte Carlo and molecular dynamics—allow calculation of the density profile and pressure difference of Eq. III-44 across the vapor-liquid interface [64, 65]. In the former method, the initial system consists of N molecules in assumed positions. An intermolecule potential function is chosen, such as the Lennard-Jones potential, and the positions are randomly varied until the energy of the system is at a minimum. The resulting configuration is taken to be the equilibrium one. In the molecular dynamics approach, the N molecules are given initial positions and velocities and the equations of motion are solved to follow the ensuing collisions until the set shows constant time-average thermodynamic properties. Both methods are computer intensive yet widely used. 

If we wish to know the number of (VpV)-collisions that actually take place in this small time interval, we need to know exactly where each particle is located and then follow the motion of all the particles from time tto time t+ bt. In fact, this is what is done in computer simulated molecular dynamics. We wish to avoid this exact specification of the particle trajectories, and instead carry out a plausible argument for the computation of r To do this, Boltzmann made the following assumption, called the Stosszahlansatz, which we encountered already in the calculation of the mean free path ... 

Straub J E and Berne B J 1986 Energy diffusion in many dimensional Markovian systems the consequences of the competition between inter- and intra-molecular vibrational energy transfer J. Chem. Phys. 85 2999 Straub J E, Borkovec M and Berne B J 1987 Numerical simulation of rate constants for a two degree of freedom system in the weak collision limit J. Chem. Phys. 86 4296... 

Classical ion trajectory computer simulations based on the BCA are a series of evaluations of two-body collisions. The parameters involved in each collision are tire type of atoms of the projectile and the target atom, the kinetic energy of the projectile and the impact parameter. The general procedure for implementation of such computer simulations is as follows. All of the parameters involved in tlie calculation are defined the surface structure in tenns of the types of the constituent atoms, their positions in the surface and their themial vibration amplitude the projectile in tenns of the type of ion to be used, the incident beam direction and the initial kinetic energy the detector in tenns of the position, size and detection efficiency the type of potential fiinctions for possible collision pairs. 

Fig. 3. Stepsize r used in the simulation of the collinear photo dissociation of ArHCl the adaptive Verlet-baaed exponential integrator using the Lanczos iteration (dash-dotted line) for the quantum propagation, and a stepsize controlling scheme based on PICKABACK (solid line). For a better understanding we have added horizontal lines marking the collisions (same tolerance TOL). We observe that the quantal H-Cl collision does not lead to any significant stepsize restrictions.

The first molecular dynamics simulation of a condensed phase system was performed by Alder and Wainwright in 1957 using a hard-sphere model [Alder and Wainwright 1957]. In this model, the spheres move at constant velocity in straight lines between collisions. All collisions are perfectly elastic and occur when the separation between the centres of... 

A number of simulation methods based on Equation (7.115) have been described. Thess differ in the assumptions that are made about the nature of frictional and random forces A common simplifying assumption is that the collision frequency 7 is independent o time and position. The random force R(f) is often assumed to be uncorrelated with th particle velocities, positions and the forces acting on them, and to obey a Gaussiar distribution with zero mean. The force F, is assumed to be constant over the time step o the integration. 

A7 Ethane/methane selectivity calculated from grand canonical Monte Carlo simulations of mixtures in slit IS at a temperature of 296 K. The selectivity is defined as the ratio of the mole fractions in the pore to the ratio of mole fractions in the bulk. H is the slit width defined in terms of the methane collision diameter (Tch,- (Figure awn from Crackncll R F, D Nicholson and N Quirke 1994. A Grand Canonical Monte Carlo Study ofLennard-s Mixtures in Slit Pores 2 Mixtures of Two-Centre Ethane with Methane. Molecular Simulation 13 161-175.)... 

The first energy derivative is called the gradient g and is the negative of the force F (with components along the a center denoted Fa) experienced by the atomic centers F = -g. These forces, as discussed in Chapter 16, can be used to carry out classical trajectory simulations of molecular collisions or other motions of large organic and biological molecules for which a quantum treatment of the nuclear motion is prohibitive. 

Langevin dynamics simulates the effect of molecular collisions and the resulting dissipation of energy that occur in real solvents, without explicitly including solvent molecules. This is accomplished by adding a random force (to model the effect of collisions) and a frictional force (to model dissipative losses) to each atom at each time step. Mathematically, this is expressed by the Langevin equation of motion (compare to Equation (22) in the previous chapter) ... 

Modeling and Simulation subsection.) It is necessary to determine both the mechanism and kernels which describe growth. For fine powders within the noninertial regime of growth, all collisions result in successful coalescence provided binder is present. Coalescence occurs via a random, size-independent kernel which is only a func tion of liquid loading, or... 

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