dc.contributor.author | Gundersen, Kristian | |
dc.contributor.author | Oleynik, Anna | |
dc.contributor.author | Blaser, Nello | |
dc.contributor.author | Alendal, Guttorm | |
dc.date.accessioned | 2022-02-18T07:44:32Z | |
dc.date.available | 2022-02-18T07:44:32Z | |
dc.date.created | 2021-04-27T13:26:18Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 1070-6631 | |
dc.identifier.uri | https://hdl.handle.net/11250/2979870 | |
dc.description.abstract | We present a new data-driven model to reconstruct nonlinear flow from spatially sparse observations. The proposed model is a version of a Conditional Variational Auto-Encoder (CVAE), which allows for probabilistic reconstruction and thus uncertainty quantification of the prediction. We show that in our model, conditioning on measurements from the complete flow data leads to a CVAE where only the decoder depends on the measurements. For this reason, we call the model semi-conditional variational autoencoder. The method, reconstructions, and associated uncertainty estimates are illustrated on the velocity data from simulations of 2D flow around a cylinder and bottom currents from a simulation of the southern North Sea by the Bergen Ocean Model. The reconstruction errors are compared to those of the Gappy proper orthogonal decomposition method. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | American Institute of Physics | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Semi-conditional variational auto-encoder for flow reconstruction and uncertainty quantification from limited observations | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright Author(s) 2021 | en_US |
dc.source.articlenumber | 017119 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |
dc.identifier.doi | 10.1063/5.0025779 | |
dc.identifier.cristin | 1906698 | |
dc.source.journal | Physics of Fluids | en_US |
dc.relation.project | Norges forskningsråd: 254711 | en_US |
dc.relation.project | Norges forskningsråd: 305202 | en_US |
dc.relation.project | EC/H2020/654462 | en_US |
dc.identifier.citation | Physics of Fluids. 2021, 33 (1), 017119. | en_US |
dc.source.volume | 33 | en_US |
dc.source.issue | 1 | en_US |