| Autor: |
Clément Olivier, David Ryckelynck, Julien Cortial |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Mathematical and Computational Applications, Vol 24, Iss 1, p 17 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2297-8747 |
| DOI: |
10.3390/mca24010017 |
| Popis: |
This work presents a novel approach to construct surrogate models of parametric differential algebraic equations based on a tensor representation of the solutions. The procedure consists of building simultaneously an approximation given in tensor-train format, for every output of the reference model. A parsimonious exploration of the parameter space coupled with a compact data representation allows alleviating the curse of dimensionality. The approach is thus appropriate when many parameters with large domains of variation are involved. The numerical results obtained for a nonlinear elasto-viscoplastic constitutive law show that the constructed surrogate model is sufficiently accurate to enable parametric studies such as the calibration of material coefficients. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
