Reference : Multi-scale methods for fracture: model learning across scales, digital twinning and ...

	Document type :	Diverse speeches and writings : Speeches/Talks
	Discipline(s) :	Engineering, computing & technology : Multidisciplinary, general & others
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/28854

Title :	Multi-scale methods for fracture: model learning across scales, digital twinning and factors of safety : primer on Bayesian Inference
Language :	English
Author, co-author :	Bordas, Stéphane [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Hale, Jack [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Beex, Lars [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Rappel, Hussein [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Kerfriden, Pierre []
	Goury, Olivier []
	Akbari, Ahmad []
Publication date :	18-Nov-2015
Audience :	International
Event name :	EMPA High-performance Multiscale-Scale Day
Event date :	2015, November, 18
Event organizer :	EMPA, ETHZ, Switzerland
Event place (city) :	Dübendorf
Event country :	Switzerland
Keywords :	[en] multi-scale ; model reduction ; fracture ; digital twin ; lack of scale separation ; bayesian inference ; model selection ; model error ; discretisation error
Abstract :	[en] Fracture and material instabilities originate at spatial scales much smaller than that of the structure of interest: delamination, debonding, fibre break- age, cell-wall buckling, are examples of nano/micro or meso-scale mechanisms which can lead to global failure of the material and structure. Such mech- anisms cannot, for computational and practical reasons, be accounted at structural scale, so that acceleration methods are necessary. We review in this presentation recently proposed approaches to reduce the computational expense associated with multi-scale modelling of frac- ture. In light of two particular examples, we show connections between algebraic reduction (model order reduction and quasi-continuum methods) and homogenisation-based reduction. We open the discussion towards suitable approaches for machine-learning and Bayesian statistical based multi-scale model selection. Such approaches could fuel a digital-twin concept enabling models to learn from real-time data acquired during the life of the structure, accounting for “real” environmental conditions during predictions, and, eventually, moving beyond the era of factors of safety.
Target :	Researchers ; Professionals ; Students ; General public ; Others
Permalink :	http://hdl.handle.net/10993/28854
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

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	Fulltext file(s): File Commentary Version Size Access Open access empa2015_multiscaleDay.pdf PDF of presentation - medium image quality Author preprint 24.63 MB View/Open Additional material(s): File Commentary Size Access Open access empaTalk2015.pdf Abstract 28.84 kB View/Open Private access empa2015_multiscaleDay.key Presentation source 179.4 MB Request a copy

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