Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Monte Carlo simulation procedures

Demarquay and Fraissard have shown that the intercept, o0, can be interpreted in terms of a "mean free path" of xenon in the zeolite and have related this NMR-derived mean free path to structural parameters such as channel diameter by a Monte Carlo simulation procedure. They empirically determined the intercept to depend on mean free path as... [Pg.318]

It is possible to eliminate all mass effects and all dynamical information in determining the ensemble averages by the use of Monte Carlo simulation procedures. The direct application of such fully stochastic techniques is not common in the field of macromolecular simulations because the presence of... [Pg.70]

The remainder of this article is organized as follows. Section 2 presents the proposed degradation model for systems with degradation dependency. Monte Carlo simulation procedures to solve the model are presented in Section 3. Section 4 presents one case study on one subsystem of a residual heat removal system (Coudray Mattel 1984) from Electricite de France (EDF). Numerical results and analysis are presented in Section 5. Section 6 concludes the work. [Pg.775]

Figure 3. Flow diagram of the Monte-Carlo simulation procedure... Figure 3. Flow diagram of the Monte-Carlo simulation procedure...
Monte Carlo simulation, a procedure for mimicking observations on a random variable, pennits verification of results tliat ordinarily would require difficult inatliematical calculations or extensive experimentation. [Pg.592]

A general method has been developed for the estimation of model parameters from experimental observations when the model relating the parameters and input variables to the output responses is a Monte Carlo simulation. The method provides point estimates as well as joint probability regions of the parameters. In comparison to methods based on analytical models, this approach can prove to be more flexible and gives the investigator a more quantitative insight into the effects of parameter values on the model. The parameter estimation technique has been applied to three examples in polymer science, all of which concern sequence distributions in polymer chains. The first is the estimation of binary reactivity ratios for the terminal or Mayo-Lewis copolymerization model from both composition and sequence distribution data. Next a procedure for discriminating between the penultimate and the terminal copolymerization models on the basis of sequence distribution data is described. Finally, the estimation of a parameter required to model the epimerization of isotactic polystyrene is discussed. [Pg.282]

In this case the shooting and shifting procedure may be viewed as a particular move in a Monte Carlo simulation similar to hybrid Monte Carlo [30]. [Pg.263]

Monte Carlo simulations and energy minimization procedures of the non-bonding interactions between rigid molecules and fixed zeolite framework provide a reasonable structural picture of DPP occluded in acidic ZSM-5. Molecular simulations carried out for DPB provide evidence of DPB sorption into the void space of zeolites and the preferred locations lay in straight channels in the vicinity of the intersection with the zigzag channel in interaction with H+ cation (figure 1). [Pg.378]

In order to describe the fluorescence radiation profile of scattering samples in total, Eqs. (8.3) and (8.4) have to be coupled. This system of differential equations is not soluble exactly, and even if simple boundary conditions are introduced the solution is possible only by numerical approximation. The most flexible procedure to overcome all analytical difficulties is to use a Monte Carlo simulation. However, this method is little elegant, gives noisy results, and allows resimulation only according to the method of trial and error which can be very time consuming, even in the age of fast computers. Therefore different steps of simplifications have been introduced that allow closed analytical approximations of sufficient accuracy for most practical purposes. In a first... [Pg.235]

LaBerge, L. J. and Tully, J.C., Arigorous procedure for combining molecular dynamics and Monte Carlo simulation algorithms, Chem. Phys., 260, 183, 2000. [Pg.302]


See other pages where Monte Carlo simulation procedures is mentioned: [Pg.146]    [Pg.713]    [Pg.255]    [Pg.321]    [Pg.143]    [Pg.998]    [Pg.999]    [Pg.2632]    [Pg.228]    [Pg.1751]    [Pg.298]    [Pg.128]    [Pg.98]    [Pg.146]    [Pg.713]    [Pg.255]    [Pg.321]    [Pg.143]    [Pg.998]    [Pg.999]    [Pg.2632]    [Pg.228]    [Pg.1751]    [Pg.298]    [Pg.128]    [Pg.98]    [Pg.2537]    [Pg.291]    [Pg.383]    [Pg.443]    [Pg.534]    [Pg.535]    [Pg.598]    [Pg.707]    [Pg.70]    [Pg.312]    [Pg.197]    [Pg.167]    [Pg.74]    [Pg.211]    [Pg.263]    [Pg.512]    [Pg.255]    [Pg.55]    [Pg.220]    [Pg.255]    [Pg.280]    [Pg.118]    [Pg.141]    [Pg.143]    [Pg.605]   
See also in sourсe #XX -- [ Pg.70 ]




SEARCH



Carlo simulation

Monte Carlo procedure

Monte Carlo simulation

Monte Carlo simulation sampling procedures

Monte simulations

© 2024 chempedia.info