Monte Carlo simulation history

Skaggs and Kabala [60] extended their study of TR using Monte Carlo simulation to answer the question of how far back one can use the Tikhonov procedure in recovering the release history of the plume, since the procedure always produces the recovered release curve that accurately reproduces the data. A table containing the percentage of test function recovery accuracy was produced. From the table, one can extract the information on how likely is that the recov-... 

It is also important to know that the interaction volume of electrons with a solid specimen is much larger than the beam size. According to a Monte Carlo simulation, in which the detailed history of an electron trajectory is calculated in a stepwise manner, the interaction volume is a function of the accelerating voltage and properties of the target specimen. 

Additional growth to form Earth-sized planets is thought to require colhsions between these planetary embryos. This is a stochastic process such that one cannot predict in any exact way the detailed growth histories for the terrestrial planets. However, with Monte Carlo simulations and more powerful computational codes the models have become quite sophisticated and yield similar and apparently robust results in terms of the kinds of timescales that must be... 

Monte Carlo Simulation of Individual Molecular Histories... 

To conclude, historical simulation with all its variants is another method that relies on past data to predict the future. It has problems coping with complex instruments, instruments with no history, and where the number of observations is limited. We look at a method that uses numerous computer simulations to overcome this, the Monte Carlo simulation, in the next section. 

Beyond the above computation, and with the help of a Monte Carlo simulation (see, also, Section 3), the degree to which the individual component contributes to a system failure was determined. The above method also permits taking into account specific maintenance strategies. The life histories of the individual components are created over a period of time from 5 x 10 h and thereby it is also determined whether the system failure can be traced to corresponding component failures at any specific point in time. Here the failure-prone components are recorded in connection with each individual failure. Results demonstrate that position transmission (2) is involved in 100% of all system failures, which is natural because of the system s logical structure (Figure 5.23). The mechanical system of the valve is involved in 12%, the hydraulic control element in 29%, and the control pulse in 59% of all cases of system failure. 

Monte Carlo simulations of charge transport in organic semiconductors have a long history, including the pioneering work of Bassler [1] which allowed the characteristics of the macroscopically measured mobility to be related to... 

Jennings et al. s (1969) model is chosen also for this model as in Eq. 6. The parameters for the time-modulating function are defined according to the real strong motion quantified as Ts = 23.86 s, namely, these are t = 1.65 s, G = 25.51 s total duration t/= 31 s and parameter fU = 3/ (tf — g) Finally to evaluate the simulated response spectra a number of 100 time histories were generated via Monte Carlo simulation method by Eq. 7. 

Monte Carlo (MC) techniques for molecular simulations have a long and rich history, and have been used to a great extent in studying the chemical physics of polymers. The majority of molecular modeling studies today do not involve the use of MC methods however, the sampling capabiUty provided by MC methods has gained some popularity among computational chemists as a result of various studies (95—97). Relevant concepts of MC are summarized herein. 

The history of the Monte Carlo method and molecular dynamics simulations is given in ... 

Polymerization rate represents the instantaneous status of reaction locus, but the whole history of polymerization is engraved within the molecular weight distribution (MWD). Recently, a new simulation tool that uses the Monte Carlo (MC) method to estimate the whole reaction history, for both hnear [263-265] and nonlinear polymerization [266-273], has been proposed. So far, this technique has been applied to investigate the kinetic behavior after the nucleation period, where the overall picture of the kinetics is well imderstood. However, the versatility of the MC method could be used to solve the complex problems of nucleation kinetics. 

Figure 7 The time-dependent history of the SB203386-HIV-1 protease system as a function of rmsd of the current ligand conformation relative to the crystal structure versus Monte Carlo cycle at 300K during equilibrium simulations with the ensemble of 6 protein conformations (a) and the ensemble of 32 protein conformations (b). The frequency of protein conformations for the SB203386-HIV-1 protease complex at T=300K in equilibrium simulations with the ensemble of 6 protein conformations (c) and the ensemble of 32 protein conformations (d). The piecewise energy function is used. The unfilled histogram is the total frequency for each conformation, the filled histogram is the frequency for ligand conformations that are within 2.0 A RMSD of the crystal structure.

Monte Carlo (MC) simulations of VESUVIO data can be performed using the computer code DINSMS, which has been described previously [Mayers 2002], The MC program follows individual neutron histories through the spectrometer and then bins them in t, according to the time they have taken to travel between moderator and detector. The input to the program is... 

There are two main approaches for the numerical simulation of the gas-solid flow 1) Eulerian framework for the gas phase and Lagrangian framework for the dispersed phase (E-L) and 2) Eulerian framework for all phases (E-E). In the E-L approach, trajectories of dispersed phase particles are calculated by solving Newton s second law of motion for each dispersed particle, and the motion of the continuous phase (gas phase) is modeled using an Eulerian framework with the coupling of the particle-gas interaction force. This approach is also referred to as the distinct element method or discrete particle method when applied to a granular system. The fluid forces acting upon particles would include the drag force, lift force, virtual mass force, and Basset history force.Moreover, particle-wall and particle-particle collision models (such as hard sphere model, soft sphere model, or Monte Carlo techniques) are commonly employed for this approach. In the E-E approach, the particle cloud is treated as a continuum. Local mean... 

Fig. 12.17. Series of snapshots in the growth history of a thin flhn simulated using the kinetic Monte Carlo scheme (adapted from Huang et al. (1998)).

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