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Uncertainty propagation in puff-based dispersion models using polynomial chaos
Authors
Konda, U., Singh, T., Singla, P., and Scott, P.
Source
Environmental Modelling and Software
.
Abstract
Atmospheric dispersion is a complex nonlinear physical process with numerous uncertainties in model
parameters, inputs, source parameters, initial and boundary conditions. Accurate propagation of these
uncertainties through the dispersion models is crucial for a reliable prediction of the probability
distribution of the states and assessment of risk. A simple three-dimensional Gaussian puff-based
dispersion model is used as a testcase to study the effect of uncertainties in the model parameters and
initial conditions on the output concentration. A polynomial chaos based approach is used to numerically
investigate the evolution of the model output uncertainties due to initial condition and parametric
uncertainties. The polynomial chaos solution is found to be anaccurate approximation to ground truth,
established by Monte Carlo simulation, while offering an efficient computational approach for large
nonlinear systems with a relatively small number of uncertainties.
@article{Singh10_envsoft,
Author = {U. Konda, T. Singh, P. Singla and P. Scott},
Journal = {Environmental Modelling and Software},
Month = {December},
Title = {Uncertainty propagation in puff-based dispersion models using polynomial chaos},
Volume = {25},
Number = {12},
Pages = {1608--1618},
Year = {2010}
}
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