Mapping of coherent structures in parameterized flows by learning optimal transportation with Gaussian models
| hal.structure.identifier | Modeling Enablers for Multi-PHysics and InteractionS [MEMPHIS] | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | IOLLO, Angelo | |
| hal.structure.identifier | Modeling Enablers for Multi-PHysics and InteractionS [MEMPHIS] | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| dc.contributor.author | TADDEI, Tommaso | |
| dc.date.issued | 2022 | |
| dc.identifier.issn | 0021-9991 | |
| dc.description.abstractEn | We present a general (i.e., independent of the underlying model) interpolation technique based on optimal transportation of Gaussian models for parametric advection-dominated problems. The approach relies on a scalar testing function to identify the coherent structure we wish to track; a maximum likelihood estimator to identify a Gaussian model of the coherent structure; and a nonlinear interpolation strategy that relies on optimal transportation maps between Gaussian distributions. We show that well-known self-similar solutions can be recast in the frame of optimal transportation by appropriate rescaling; we further present several numerical examples to motivate our proposal and to assess strengths and limitations; finally, we discuss an extension to deal with more complex problems. | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.title.en | Mapping of coherent structures in parameterized flows by learning optimal transportation with Gaussian models | |
| dc.type | Article de revue | |
| dc.identifier.doi | 10.1016/j.jcp.2022.111671 | |
| dc.subject.hal | Mathématiques [math]/Analyse numérique [math.NA] | |
| dc.description.sponsorshipEurope | Accurate Roms for Industrial Applications | |
| bordeaux.journal | Journal of Computational Physics | |
| bordeaux.page | 111671 | |
| bordeaux.volume | 471 | |
| bordeaux.issue | 111671 | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-03441730 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-03441730v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal%20of%20Computational%20Physics&rft.date=2022&rft.volume=471&rft.issue=111671&rft.spage=111671&rft.epage=111671&rft.eissn=0021-9991&rft.issn=0021-9991&rft.au=IOLLO,%20Angelo&TADDEI,%20Tommaso&rft.genre=article |
Fichier(s) constituant ce document
| Fichiers | Taille | Format | Vue |
|---|---|---|---|
|
Il n'y a pas de fichiers associés à ce document. |
|||