50 resultados para Reverse Monte-carlo
Resumo:
The Monte Carlo Independent Column Approximation (McICA) is a flexible method for representing subgrid-scale cloud inhomogeneity in radiative transfer schemes. It does, however, introduce conditional random errors but these have been shown to have little effect on climate simulations, where spatial and temporal scales of interest are large enough for effects of noise to be averaged out. This article considers the effect of McICA noise on a numerical weather prediction (NWP) model, where the time and spatial scales of interest are much closer to those at which the errors manifest themselves; this, as we show, means that noise is more significant. We suggest methods for efficiently reducing the magnitude of McICA noise and test these methods in a global NWP version of the UK Met Office Unified Model (MetUM). The resultant errors are put into context by comparison with errors due to the widely used assumption of maximum-random-overlap of plane-parallel homogeneous cloud. For a simple implementation of the McICA scheme, forecasts of near-surface temperature are found to be worse than those obtained using the plane-parallel, maximum-random-overlap representation of clouds. However, by applying the methods suggested in this article, we can reduce noise enough to give forecasts of near-surface temperature that are an improvement on the plane-parallel maximum-random-overlap forecasts. We conclude that the McICA scheme can be used to improve the representation of clouds in NWP models, with the provision that the associated noise is sufficiently small.
Resumo:
By combining the results of both x-ray diffraction and neutron total-scattering experiments, we show that Ni(CN)(2) exhibits long-range structural order only in two dimensions, with no true periodicity perpendicular to its gridlike layers. Reverse Monte Carlo analysis gives an experimental distinction between M-C and M-N bond lengths in a homometallic cyanide framework and identifies the vibrational modes responsible for anomalous positive and negative thermal expansion in the title compound.
Resumo:
A new approach to the study of the local organization in amorphous polymer materials is presented. The method couples neutron diffraction experiments that explore the structure on the spatial scale 1–20 Å with the reverse Monte Carlo fitting procedure to predict structures that accurately represent the experimental scattering results over the whole momentum transfer range explored. Molecular mechanics and molecular dynamics techniques are also used to produce atomistic models independently from any experimental input, thereby providing a test of the viability of the reverse Monte Carlo method in generating realistic models for amorphous polymeric systems. An analysis of the obtained models in terms of single chain properties and of orientational correlations between chain segments is presented. We show the viability of the method with data from molten polyethylene. The analysis derives a model with average C-C and C-H bond lengths of 1.55 Å and 1.1 Å respectively, average backbone valence angle of 112, a torsional angle distribution characterized by a fraction of trans conformers of 0.67 and, finally, a weak interchain orientational correlation at around 4 Å.
Resumo:
The organization of non-crystalline polymeric materials at a local level, namely on a spatial scale between a few and 100 a, is still unclear in many respects. The determination of the local structure in terms of the configuration and conformation of the polymer chain and of the packing characteristics of the chain in the bulk material represents a challenging problem. Data from wide-angle diffraction experiments are very difficult to interpret due to the very large amount of information that they carry, that is the large number of correlations present in the diffraction patterns.We describe new approaches that permit a detailed analysis of the complex neutron diffraction patterns characterizing polymer melts and glasses. The coupling of different computer modelling strategies with neutron scattering data over a wide Q range allows the extraction of detailed quantitative information on the structural arrangements of the materials of interest. Proceeding from modelling routes as diverse as force field calculations, single-chain modelling and reverse Monte Carlo, we show the successes and pitfalls of each approach in describing model systems, which illustrate the need to attack the data analysis problem simultaneously from several fronts.
Resumo:
Determination of the local structure of a polymer glass by scattering methods is complex due to the number of spatial and orientational correlations, both from within the polymer chain (intrachain) and between neighbouring chains (interchain), from which the scattering arises. Recently considerable advances have been made in the structural analysis of relatively simple polymers such as poly(ethylene) through the use of broad Q neutron scattering data tightly coupled to atomistic modelling procedures. This paper presents the results of an investigation into the use of these procedures for the analysis of the local structure of a-PMMA which is chemically more complex with a much greater number of intrachain structural parameters. We have utilised high quality neutron scattering data obtained using SANDALS at ISIS coupled with computer models representing both the single chain and bulk polymer system. Several different modelling approaches have been explored which encompass such techniques as Reverse Monte Carlo refinement and energy minimisation and their relative merits and successes are discussed. These different approaches highlight structural parameters which any realistic model of glassy atactic PMMA must replicate.