Solving PDEs with random data by stochastic collocation
In many science and engineering problems there is uncertainty in the input data. The ability to suitably model and handle this uncertainty is crucial for obtaining meaningful information about solutions. In this thesis, we consider the numerical approximation of statistics of solutions to partial di...
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University of Manchester
2013
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.568594 |