Abstract
This work presents a methodology for the construction of an uncertain nonlinear computational model adapted to the static analysis of a complex mechanical system. The deterministic nonlinear computational model is constructed with the finite element method using a total Lagrangian formulation. The finite element nonlinear response is then considered as a reference deterministic solution from which a reduced-order basis is constructed using the POD (Proper Orthogonal Decomposition) methodology. The mean reduced nonlinear computational model is thus obtained by projecting the reference deterministic solution on this basis. The explicit construction of the mean reduced nonlinear computational model is proposed for any type of structure modeled with three-dimensional solid finite elements. A procedure for the robust identification of the uncertain nonlinear computational model with respect to experimental responses is then given. Finally the methodology is applied to a structure for which simulated experiments are given.
| Original language | English (US) |
|---|---|
| Title of host publication | ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012 |
| Pages | 123-132 |
| Number of pages | 10 |
| Volume | 1 |
| DOIs | |
| State | Published - 2012 |
| Event | ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012 - Nantes, France Duration: Jul 2 2012 → Jul 4 2012 |
Other
| Other | ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012 |
|---|---|
| Country | France |
| City | Nantes |
| Period | 7/2/12 → 7/4/12 |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Mechanical Engineering
Cite this
Uncertainty quantification in computational nonlinear elasticity. / Capiez-Lernout, E.; Soize, C.; Mignolet, Marc.
ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012. Vol. 1 2012. p. 123-132.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Uncertainty quantification in computational nonlinear elasticity
AU - Capiez-Lernout, E.
AU - Soize, C.
AU - Mignolet, Marc
PY - 2012
Y1 - 2012
N2 - This work presents a methodology for the construction of an uncertain nonlinear computational model adapted to the static analysis of a complex mechanical system. The deterministic nonlinear computational model is constructed with the finite element method using a total Lagrangian formulation. The finite element nonlinear response is then considered as a reference deterministic solution from which a reduced-order basis is constructed using the POD (Proper Orthogonal Decomposition) methodology. The mean reduced nonlinear computational model is thus obtained by projecting the reference deterministic solution on this basis. The explicit construction of the mean reduced nonlinear computational model is proposed for any type of structure modeled with three-dimensional solid finite elements. A procedure for the robust identification of the uncertain nonlinear computational model with respect to experimental responses is then given. Finally the methodology is applied to a structure for which simulated experiments are given.
AB - This work presents a methodology for the construction of an uncertain nonlinear computational model adapted to the static analysis of a complex mechanical system. The deterministic nonlinear computational model is constructed with the finite element method using a total Lagrangian formulation. The finite element nonlinear response is then considered as a reference deterministic solution from which a reduced-order basis is constructed using the POD (Proper Orthogonal Decomposition) methodology. The mean reduced nonlinear computational model is thus obtained by projecting the reference deterministic solution on this basis. The explicit construction of the mean reduced nonlinear computational model is proposed for any type of structure modeled with three-dimensional solid finite elements. A procedure for the robust identification of the uncertain nonlinear computational model with respect to experimental responses is then given. Finally the methodology is applied to a structure for which simulated experiments are given.
UR - http://www.scopus.com/inward/record.url?scp=84883882263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883882263&partnerID=8YFLogxK
U2 - 10.1115/ESDA2012-82246
DO - 10.1115/ESDA2012-82246
M3 - Conference contribution
AN - SCOPUS:84883882263
SN - 9780791844847
VL - 1
SP - 123
EP - 132
BT - ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2012
ER -