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SUMMARY:MEchanics GAthering –MEGA- Seminar: FEM d-refinement
DTSTART:20230302T161500
DTEND:20230302T173000
DTSTAMP:20260929T053337Z
UID:59565a0c5ecc4a383c5c8da9ddfb2e4e6d77c0c49ea9c1792d0c9099
CATEGORIES:Conferences - Seminars
DESCRIPTION:Antonio Joaquin Garcia Suarez (LSMS\, EPFL)\nAbstract\nModel-f
 ree data-driven computational mechanics (DDCM) is a new paradigm for simul
 ations in solid mechanics. The modeling step associated to the definition 
 of a material constitutive law is circumvented through the introduction of
  an abstract phase space in which\, following a pre-defined rule\, physica
 lly-admissible states are matched to observed material response data (comi
 ng from either experiments or lower-scale simulations). In terms of comput
 ational resources\, the search procedure that performs these matches is th
 e most onerous step in the algorithm. One of the main advantages of DDCM i
 s the fact that it avoids regression-based\, bias-prone constitutive model
 ing. However\, many materials do display a simple linear response in the s
 mall-strain regime while also presenting complex behavior after a certain 
 deformation threshold. Motivated by this fact\, we introduce a novel refin
 ement technique that turns regular elements (equipped with a linear-elasti
 c constitutive law) into data-driven ones if they are expected to surpass 
 the threshold known to trigger material non-linear response. We term this 
 technique "data refinement''\, "d-refinement'' for short. Starting from an
  initially regular FEM mesh\, the proposed algorithm detects where the ref
 inement is needed and iterates until all elements presumed to display non-
 linearity become data-driven ones. The scheme is well-suited for simulatio
 ns that feature non-linear response in relatively small portions of the do
 main while the rest remains linear-elastic. The method is validated agains
 t a traditional incremental solver (i.e.\, Newton-Raphson method) and we s
 how that the d-refinement framework can outperform it in terms of speed at
  no loss of accuracy. We provide an application that showcases the advanta
 ge of the new method: bridging scales in architected metamaterials.\n\nBio
 graphy:\nJoaquin earned a PhD in Aeronautics (minor in Applied Mathematic
 s) from the California Institute of Technology in 2020\, and joined Prof.
  Molinari's group at EPFL (LSMS) as a postdoc in 2021. His current resea
 rch hinges on three intertwined themes: data-driven mechanics\, wave prop
 agation and tribology. \n\n 
LOCATION:MED 2 2423 https://plan.epfl.ch/?room==MED%202%202423 https://epf
 l.zoom.us/j/9032545447
STATUS:CONFIRMED
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