			Home About us Contact

Simulation Algorithm (simulation + algorithm)

Distribution by Scientific Domains

Mathematics and Statistics	40%
Chemistry	40%

Selected Abstracts

Modelling the effects of air pollution on health using Bayesian dynamic generalised linear models

ENVIRONMETRICS, Issue 8 2008
Duncan Lee
Abstract The relationship between short-term exposure to air pollution and mortality or morbidity has been the subject of much recent research, in which the standard method of analysis uses Poisson linear or additive models. In this paper, we use a Bayesian dynamic generalised linear model (DGLM) to estimate this relationship, which allows the standard linear or additive model to be extended in two ways: (i) the long-term trend and temporal correlation present in the health data can be modelled by an autoregressive process rather than a smooth function of calendar time; (ii) the effects of air pollution are allowed to evolve over time. The efficacy of these two extensions are investigated by applying a series of dynamic and non-dynamic models to air pollution and mortality data from Greater London. A Bayesian approach is taken throughout, and a Markov chain monte carlo simulation algorithm is presented for inference. An alternative likelihood based analysis is also presented, in order to allow a direct comparison with the only previous analysis of air pollution and health data using a DGLM. Copyright © 2008 John Wiley & Sons, Ltd. [source]

An electromagnetic modelling tool for the detection of hydrocarbons in the subsoil

GEOPHYSICAL PROSPECTING, Issue 2 2000
Carcione
Electromagnetic geophysical methods, such as ground-penetrating radar (GPR), have proved to be optimal tools for detecting and mapping near-surface contaminants. GPR has the capability of mapping the location of hydrocarbon pools on the basis of contrasts in the effective permittivity and conductivity of the subsoil. At radar frequencies (50 MHz to 1 GHz), hydrocarbons have a relative permittivity ranging from 2 to 30, compared with a permittivity for water of 80. Moreover, their conductivity ranges from zero to 10 mS/m, against values of 200 mS/m and more for salt water. These differences indicate that water/hydrocarbon interfaces in a porous medium are electromagnetically ,visible'. In order to quantify the hydrocarbon saturation we developed a model for the electromagnetic properties of a subsoil composed of sand and clay/silt, and partially saturated with air, water and hydrocarbon. A self-similar theory is used for the sandy component and a transversely isotropic constitutive equation for the shaly component, which is assumed to possess a laminated structure. The model is first verified with experimental data and then used to obtain the properties of soils partially saturated with methanol and aviation gasoline. Finally, a GPR forward-modelling method computes the radargrams of a typical hydrocarbon spill, illustrating the sensitivity of the technique to the type of pore-fluid. The model and the simulation algorithm provide an interpretation methodology to distinguish different pore-fluids and to quantify their degree of saturation. [source]

Implementation and evaluation of MPI-based parallel MD program

INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 1 2001
R. Trobec
Abstract The message-passing interface (MPI)-based object-oriented particle,particle interactions (PPI) library is implemented and evaluated. The library can be used in the n -particle simulation algorithm designed for a ring of p interconnected processors. The parallel simulation is scalable with the number of processors, and has the time requirement proportional to n2/p if n/p is large enough, which guarantees optimal speedup. In a certain range of problem sizes, the speedup becomes superlinear because enough cache memory is available in the system. The library is used in a simple way by any potential user, even with no deep programming knowledge. Different simulations using particles can be implemented on a wide spectrum of different computer platforms. The main purpose of this article is to test the PPI library on well-known methods, e.g., the parallel molecular dynamics (MD) simulation of the monoatomic system by the second-order leapfrog Verlet algorithm. The performances of the parallel simulation program implemented with the proposed library are competitive with a custom-designed simulation code. Also, the implementation of the split integration symplectic method, based on the analytical calculation of the harmonic part of the particle interactions, is shown, and its expected performances are predicted. © 2001 John Wiley & Sons, Inc. Int J Quant Chem 84: 23,31, 2001 [source]

A new class of models for bivariate joint tails

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 1 2009
Alexandra Ramos
Summary., A fundamental issue in applied multivariate extreme value analysis is modelling dependence within joint tail regions. The primary focus of this work is to extend the classical pseudopolar treatment of multivariate extremes to develop an asymptotically motivated representation of extremal dependence that also encompasses asymptotic independence. Starting with the usual mild bivariate regular variation assumptions that underpin the coefficient of tail dependence as a measure of extremal dependence, our main result is a characterization of the limiting structure of the joint survivor function in terms of an essentially arbitrary non-negative measure that must satisfy some mild constraints. We then construct parametric models from this new class and study in detail one example that accommodates asymptotic dependence, asymptotic independence and asymmetry within a straightforward parsimonious parameterization. We provide a fast simulation algorithm for this example and detail likelihood-based inference including tests for asymptotic dependence and symmetry which are useful for submodel selection. We illustrate this model by application to both simulated and real data. In contrast with the classical multivariate extreme value approach, which concentrates on the limiting distribution of normalized componentwise maxima, our framework focuses directly on the structure of the limiting joint survivor function and provides significant extensions of both the theoretical and the practical tools that are available for joint tail modelling. [source]

Operational Optimization of Ideal Internal Thermally Coupled Distillation Columns

ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 1-2 2001
Xing-Gao Liu
Lack of the optimal operation parameters in operation is one of major difficulties associated with the use of advanced energy saving distillation methods. In this paper, the operational optimization of the ideal Internal Thermally Coupled Distillation Column (ITCDIC) is considered. An optimization model and the related simulation algorithm are proposed. An optimization and the related result analysis are carried out, which pave the way for further design studies and its practical application. [source]