Abstract
Continuous sedimentation processes in a clarifier-thickener unit can be
described by a scalar nonlinear conservation law whose flux density
function is discontinuous with respect to the spatial position. In the
applications of this model, which include mineral processing and
wastewater treatment, the rate and composition of the feed flow cannot
be given deterministically. Efficient numerical simulation is required
to quantify the effect of uncertainty in these control parameters in
terms of the response of the clarifier thickener system. Thus, the
problem at hand is one of uncertainty quantification for nonlinear
hyperbolic problems with several random perturbations. The presented
hybrid stochastic Galerkin method is devised so as to extend the
polynomial chaos approximation by multiresolution discretization in the
stochastic space. This approach leads to a deterministic hyperbolic
system, which is partially decoupled and therefore suitable for
efficient parallelisation. Stochastic adaptivity reduces the
computational effort. Several numerical experiments are presented. (C)
2016 Elsevier Ltd. All rights reserved.
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