44 citations · 143 across the 17 of their papers we have counts for
7 papers · 1 filter
A probabilistic peridynamic framework with an application to the study of the statistical size effect
Mark Hobbs, Hussein Rappel, Tim Dodwell
Mathematical models are essential for understanding and making predictions about systems arising in nature and engineering. Yet, mathematical models are a simplification of true ph…
Scalable multiscale-spectral GFEM with an application to composite aero-structures
Jean Bénézech, Linus Seelinger, Peter Bastian +4
In this paper, the first large-scale application of multiscale-spectral generalized finite element methods (MS-GFEM) to composite aero-structures is presented. The crucial novelty…
Novel design and analysis of generalized FE methods based on locally optimal spectral approximations
Chupeng Ma, Robert Scheichl, Tim Dodwell
In this paper, the generalized finite element method (GFEM) for solving second order elliptic equations with rough coefficients is studied. New optimal local approximation spaces f…
Multilevel Monte Carlo Simulations of Composite Structures with Uncertain Manufacturing Defects
T. J. Dodwell, S. Kinston, R. Butler +3
By adopting a Multilevel Monte Carlo (MLMC) framework, we show that only a handful of costly fine scale computations are needed to accurately estimate statistics of the failure of…
High-performance dune modules for solving large-scale, strongly anisotropic elliptic problems with applications to aerospace composites
Richard Butler, Tim Dodwell, Anne Reinarz +3
The key innovation in this paper is an open-source, high-performance iterative solver for high contrast, strongly anisotropic elliptic partial differential equations implemented wi…
Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies
Gianluca Detommaso, Tim Dodwell, Rob Scheichl
In this paper, we present a generalisation of the Multilevel Monte Carlo (MLMC) method to a setting where the level parameter is a continuous variable. This Continuous Level Monte…
A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow
T. J. Dodwell, C. Ketelsen, R. Scheichl +1
In this paper we address the problem of the prohibitively large computational cost of existing Markov chain Monte Carlo methods for large--scale applications with high dimensional…