Sentence examples for dispersion modelling from inspiring English sources

"Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case". Atmospheric Chemistry and Physics 14, no.

This tool integrates CALPUFF's advanced dispersion modelling with the latest WHO recommendations on concentration-response functions.

In the current work the rhoReactingBuoyantFoam solver was customised for performing gas leak and gas dispersion modelling.

The CFD modelling is carried out to complement traditional atmospheric dispersion modelling undertaken as part of a study to develop odour reduction strategies for Alcoa's Wagerup refinery in Western Australia.

The aims of this review are to summarise current practices of nanoparticle dispersion modelling at five local scales (i.e. vehicle wake, street canyons, neighbourhood, city and road tunnels), together with highlighting associated challenges, research gaps and priorities.

MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling.

In addition the results can be used for identifying priority areas for more detailed dispersion modelling at the local-scale.

Quantifying volcanic ash hazard at the regional scale typically requires simplification of computationally intensive approaches to ash dispersion modelling using coarser input datasets.

The 2-D wind field above the vent can vary over the course of the dispersion modelling (i.e., a single eruption).

In addition, data on grainsize, chemical composition and aggregation are important for understanding health and environmental impacts, volcanological processes and dispersion modelling.

Without modelling the variance (over-dispersion), modelling mean response (EQ-5D-3L) as a function of the 15 QLQ-C30 variables requires using a simple logit function (because values are assumed to lie between 0 and 1), as in a logistic regression model.