Monte Carlo simulation advantages

The parametric method is an established statistical technique used for combining variables containing uncertainties, and has been advocated for use within the oil and gas industry as an alternative to Monte Carlo simulation. The main advantages of the method are its simplicity and its ability to identify the sensitivity of the result to the input variables. This allows a ranking of the variables in terms of their impact on the uncertainty of the result, and hence indicates where effort should be directed to better understand or manage the key variables in order to intervene to mitigate downside and/or take advantage of upside in the outcome. 

Monte Carlo simulations generate a large number of confonnations of tire microscopic model under study that confonn to tire probability distribution dictated by macroscopic constrains imposed on tire systems. For example, a Monte Carlo simulation of a melt at a given temperature T produces an ensemble of confonnations in which confonnation with energy E. occurs witli a probability proportional to exp (- Ej / kT). An advantage of tire Monte Carlo metliod is tliat, by judicious choice of tire elementary moves, one can circumvent tire limitations of molecular dynamics techniques and effect rapid equilibration of multiple chain systems [65]. Flowever, Monte Carlo... 

Molecular dynamics calculations are more time-consuming than Monte Carlo calculations. This is because energy derivatives must be computed and used to solve the equations of motion. Molecular dynamics simulations are capable of yielding all the same properties as are obtained from Monte Carlo calculations. The advantage of molecular dynamics is that it is capable of modeling time-dependent properties, which can not be computed with Monte Carlo simulations. This is how diffusion coefficients must be computed. It is also possible to use shearing boundaries in order to obtain a viscosity. Molec-... 

The combined QM/MM model can be used along with Statistical Perturbation Theory to carry out a Monte Carlo simulation of a chemical reaction in solution, with the advantage of allowing solute electronic structure relaxation in solution. Particularly, the combined AM1/TIP3P force field has recently been applied to simulate several chemical processes in solution. We will refer here briefly to the Claisen rearrangement and to the Menshutkin reaction. 

Efforts have been made to develop EOS for detonation products based on direct Monte Carlo simulations instead of on analytical approaches.35-37 This approach is promising given recent increases in computational capabilities. One of the greatest advantages of direct simulation is the ability to go beyond van der Waals 1-fluid theory, which approximately maps the equation of state of a mixture onto that of a single component fluid.38... 

Probabilistic approaches take advantage of current computational capabilities to combine all of the data in a pesticide residue distribution (rather than a single expected value) with food consumption data to develop a distribution of daily exposure. This approach is called a Monte Carlo simulation, although there are many ways to conduct this type of analysis. 

The detectable signal in the time intervals between the moments of exchanges can be determined by solving the time-dependent Schrodinger equation for the specific conformer however, in this case, the Hamiltonian is independent of time.18 The advantage of this method is its smaller memory requirement its disadvantage is the longer computational time because of the Monte Carlo simulation and that it was not possible to apply it to coupled spin systems so far. 

The above reasoning shows that the stretched exponential function (4.14), or Weibull function as it is known, may be considered as an approximate solution of the release problem. The advantage of this choice is that it is general enough for the description of drug release from vessels of various shapes, in the presence or absence of different interactions, by adjusting the values of the parameters a and b. Monte Carlo simulation methods were used to calculate the values of the parameters a and (mainly) the exponent b [87]. 

The advantage of the proposed modification is that is it much more efficient to attempt to increase the size of an existing molecule, than to attempt to place a molecule at a completely random position. In this respect the proposed modification is similar to the semigrand ensemble Monte Carlo simulation technique (2). 

Popkie s potential (Popkie et al., 1973) used in that Monte Carlo simulation has some advantages with respect to the empirical potentials used in the few preceding Monte Carlo (Barker and Watts, 1969) and molecular dynamics (Rahman and Stillinger, 1971) simulations of pure water, since the use of a QM definition of the AE(Rab) hypersurface allows one to improve the potential exploiting progresses in the QM calculations of variational energies. For many years, this approach has been limited to the use... 

One advantage of these Monte Carlo simulations is that both the thermodynamic and structural properties of the binary polymer mixture are simultaneously accessible, and can quantitatively be compared to analytic approaches. The mean field theory of polymers makes detailed predictions for the bulk [68-70] and interface properties [71-77] as a function of the incompatibility, 1 the spatial extension of the molecules as measured by the root mean squared end-to-end distance of the Gaussian coils, and the... 

The present author believes that many practical problems can be illuminated and even solved with the use Monte Carlo simulations like those presented above in this section. The simulations are inherently probabilistic and can incorporate both thermodynamic and kinetic factors. The simulations do not provide formulae, but their great advantage is the possibility to take into account real experimental conditions. Simulations do not take any significant time, even on standard PC workstations. On the other hand, deriving analytical formulae as a rule requires assuming idealized experimental conditions, which are often far from reality. 

Chapter 6 quotes some principal problems of the validity of the conclusions drawn from the experiments with only a few atoms. The last sections witness the advantages of using the Bayesian approach for the treatment of the data with poor statistics, in particular, in radiochemical experiments. When combined with Monte Carlo simulations of the experiment, the approach can easily account for peculiar situations like unsteady physicochemical conditions and performance of the radiation detectors during long runs on accelerator beam. It is demonstrated by concrete examples. 

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