Multilevel Monte Carlo Methods for Elliptic Problems with Applications to Radioactive Waste Disposal
Lead Research Organisation:
University of Oxford
Department Name: Mathematical Institute
Abstract
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People |
ORCID iD |
Mike Giles (Principal Investigator) |
Publications
Giles M
(2015)
Multilevel Monte Carlo methods
in Acta Numerica
Giles M
(2018)
Decision-making under uncertainty: using MLMC for efficient estimation of EVPPI
in Statistics and Computing
Giles M
(2019)
Random bit multilevel algorithms for stochastic differential equations
in Journal of Complexity
Giles M
(2018)
Monte Carlo and Quasi-Monte Carlo Methods
Giles M
(2018)
Multilevel Estimation of Expected Exit Times and Other Functionals of Stopped Diffusions
in SIAM/ASA Journal on Uncertainty Quantification
Giles M
(2013)
Monte Carlo and Quasi-Monte Carlo Methods 2012
Giles M
(2015)
Multilevel Monte Carlo Approximation of Distribution Functions and Densities
in SIAM/ASA Journal on Uncertainty Quantification
Giles M
(2016)
Monte Carlo and Quasi-Monte Carlo Methods
Giles, MB
(2020)
Multivariate Algorithms and Information-Based Complexity
Hironaka T
(2020)
Multilevel Monte Carlo Estimation of the Expected Value of Sample Information
in SIAM/ASA Journal on Uncertainty Quantification
Description | This project has demonstrated that the multilevel Monte Carlo method provides major improvements in the computational efficiency of Monte Carlo methods applied to the simulation of nuclear waste repositories. |
Exploitation Route | There is major potential for its use in the simulation of nuclear waste repositories, and also oil reservoir simulation. |
Sectors | Education,Energy |
URL | http://people.maths.ox.ac.uk/gilesm/mlmc.html |
Description | The mathematical approach we have developed has not yet been adopted by industry, although it is now being widely used within academia and both government and industry research labs. |
First Year Of Impact | 2011 |
Sector | Aerospace, Defence and Marine,Education,Electronics,Financial Services, and Management Consultancy |