Multilevel Monte Carlo Methods for Elliptic Problems with Applications to Radioactive Waste Disposal
Lead Research Organisation:
University of Oxford
Department Name: Mathematical Institute
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
People |
ORCID iD |
Mike Giles (Principal Investigator) |
Publications
Giles M
(2018)
Random Bit Quadrature and Approximation of Distributions on Hilbert Spaces
in Foundations of Computational Mathematics
Giles M
(2019)
Random bit multilevel algorithms for stochastic differential equations
in Journal of Complexity
Giles, MB
(2020)
Multivariate Algorithms and Information-Based Complexity
Croci M
(2021)
Multilevel Quasi Monte Carlo Methods for Elliptic PDEs with Random Field Coefficients via Fast White Noise Sampling
in SIAM Journal on Scientific Computing
Giles M
(2019)
Multilevel Nested Simulation for Efficient Risk Estimation
in SIAM/ASA Journal on Uncertainty Quantification
Cliffe K
(2011)
Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients
in Computing and Visualization in Science
Giles M
(2015)
Multilevel Monte Carlo methods
in Acta Numerica
Fang W
(2019)
Multilevel Monte Carlo method for ergodic SDEs without contractivity
in Journal of Mathematical Analysis and Applications
Hironaka T
(2020)
Multilevel Monte Carlo Estimation of the Expected Value of Sample Information
in SIAM/ASA Journal on Uncertainty Quantification
Giles M
(2015)
Multilevel Monte Carlo Approximation of Distribution Functions and Densities
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 |