Reference : Using higher-order adjoints to accelerate the solution of UQ problems with random fields

	Document type :	Scientific congresses, symposiums and conference proceedings : Poster
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Mathematics
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/34385

Title :	Using higher-order adjoints to accelerate the solution of UQ problems with random fields
Language :	English
Author, co-author :	Hale, Jack [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Hauseux, Paul [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Bordas, Stéphane [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Publication date :	8-Jan-2018
Number of pages :	A0
Peer reviewed :	No
On invitation :	No
Audience :	International
Event name :	Key UQ methodologies and motivating applications
Event date :	8-1-2018 to 12-1-2018
Event organizer :	Isaac Newton Institute for Mathematical Sciences
Event place (city) :	Cambridge
Event country :	United Kingdom
Keywords :	[en] monte carlo ; variance reduction ; uncertainty quantification ; taylor series ; FEniCS ; PETSc ; DOLFIN
Abstract :	[en] A powerful Monte Carlo variance reduction technique introduced in Cao and Zhang 2004 uses local derivatives to accelerate Monte Carlo estimation. This work aims to: develop a new derivative-driven estimator that works for SPDEs with uncertain data modelled as Gaussian random fields with Matérn covariance functions (infinite/high-dimensional problems) (Lindgren, Rue, and Lindström, 2011), use second-order derivative (Hessian) information for improved variance reduction over our approach in (Hauseux, Hale, and Bordas, 2017), demonstrate a software framework using FEniCS (Logg and Wells, 2010), dolfin-adjoint (Farrell et al., 2013) and PETSc (Balay et al., 2016) for automatic acceleration of MC estimation for a wide variety of PDEs on HPC architectures.
Funders :	University of Luxembourg - UL
Name of the research project :	R-AGR-0515 > MOmENTUM > 01/01/2015 - 31/10/2017 > BORDAS Stephane
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/34385
Framework Programme / European Project :	FP7 ; 279578 - REALTCUT - Towards real time multiscale simulation of cutting in non-linear materials with applications to surgical simulation and computer guided surgery
FnR project :	FnR ; FNR6693582 > Jack Samuel Hale > ACCeSS > Advanced Computational Methods For The Simulation Of Cutting In Surgery > 01/01/2014 > 31/12/2015 > 2013

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	Fulltext file(s): File Commentary Version Size Access Open access HALE_UNQ01_Newton_Institute_2018.pdf Poster Publisher postprint 211.24 kB View/Open Additional material(s): File Commentary Size Access Open access HALE_UNQ01_Slide.pdf 3 minute Poster Blitz Slide 496.47 kB View/Open

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