Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Abel Sancarlos"'
Publikováno v:
Advanced Modeling and Simulation in Engineering Sciences, Vol 10, Iss 1, Pp 1-26 (2023)
Abstract Regressions created from experimental or simulated data enable the construction of metamodels, widely used in a variety of engineering applications. Many engineering problems involve multi-parametric physics whose corresponding multi-paramet
Externí odkaz:
https://doaj.org/article/cc493a1262a64e32a3900b4f6a472e0b
Autor:
Tarek Frahi, Abel Sancarlos, Mathieu Galle, Xavier Beaulieu, Anne Chambard, Antonio Falco, Elias Cueto, Francisco Chinesta
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
The present paper aims at analyzing the topological content of the complex trajectories that weeder-autonomous robots follow in operation. We will prove that the topological descriptors of these trajectories are affected by the robot environment as w
Externí odkaz:
https://doaj.org/article/58bc56363a7648fcb2957b2c47c4bb98
Autor:
Abel Sancarlos, Morgan Cameron, Jean-Marc Le Peuvedic, Juliette Groulier, Jean-Louis Duval, Elias Cueto, Francisco Chinesta
Publikováno v:
Data-Centric Engineering, Vol 2 (2021)
The concept of “hybrid twin” (HT) has recently received a growing interest thanks to the availability of powerful machine learning techniques. This twin concept combines physics-based models within a model order reduction framework—to obtain re
Externí odkaz:
https://doaj.org/article/7edeee34cbf443bbb2167f50b8d54587
Autor:
Abel Sancarlos, Chady Ghnatios, Jean-Louis Duval, Nicolas Zerbib, Elias Cueto, Francisco Chinesta
Publikováno v:
Energies, Vol 14, Iss 5, p 1454 (2021)
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric solutions for electromagnetic fields in synchronous machines. Specifically, the intrusive version of the Proper Generalized Decomposition (PGD) is emplo
Externí odkaz:
https://doaj.org/article/123dffd259854f58ad6e798dcb8aa0e5
Autor:
Simona Vermiglio, Victor Champaney, Abel Sancarlos, Fatima Daim, Jean Claude Kedzia, Jean Louis Duval, Pedro Diez, Francisco Chinesta
Publikováno v:
Sensors, Vol 20, Iss 19, p 5686 (2020)
Efficient and optimal design of radar-based Advanced Driver Assistant Systems (ADAS) needs the evaluation of many different electromagnetic solutions for evaluating the impact of the radome on the electromagnetic wave propagation. Because of the very
Externí odkaz:
https://doaj.org/article/6985ba18427f41c683a54c4e5cd70327
Publikováno v:
ATZextra. 26:20-23
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8abdc2f42d22957ebd02c5374668e98
https://doi.org/10.1007/s35778-021-0457-4
https://doi.org/10.1007/s35778-021-0457-4
Autor:
Abel Sancarlos
Publikováno v:
FISITA World Congress 2021 - Technical Programme.
"It is worthy to say that the Electric Vehicle (EV) with their batteries are a cornerstone to be positioned in the new automotive market industry. Platforms such as Batteries Europe are a great example. Nowadays, Lithium-ion batteries are the ones us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::716a0ccf1d5238557da94b0084a7b538
https://doi.org/10.46720/f2021-adm-153
https://doi.org/10.46720/f2021-adm-153
Autor:
Icíar Alfaro, Jean Louis Duval, Anne Chambard, Elías Cueto, Simon Guevelou, David González, Francisco Chinesta, Abel Sancarlos, Philippe Mourgue, Victor Champaney
Publikováno v:
ESAFORM 2021.
This work retraces the main recent advances in the so-called non-intrusive model order reduction, and more concretely, the construction of parametric solutions related to parametric models, with special emphasis on the technologies enabling allying a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c97668a9eadd6b5ab52f6ab980b2a764
https://doi.org/10.25518/esaform21.2017
https://doi.org/10.25518/esaform21.2017
Publikováno v:
Zaguán: Repositorio Digital de la Universidad de Zaragoza
Universidad de Zaragoza
SN Applied Sciences
SN Applied Sciences, Springer Verlag, 2021, 3, pp.1-19. ⟨10.1007/s42452-021-04310-3⟩
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Universidad de Zaragoza
SN Applied Sciences
SN Applied Sciences, Springer Verlag, 2021, 3, pp.1-19. ⟨10.1007/s42452-021-04310-3⟩
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
A novel model order reduction (MOR) technique is presented to achieve fast and real-time predictions as well as high-dimensional parametric solutions for the electromagnetic force which will help the design, analysis of performance and implementation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11b199f2e12e5c8da29015e590a90f56
http://zaguan.unizar.es/record/102174
http://zaguan.unizar.es/record/102174
Autor:
Juliette Groulier, Elías Cueto, Abel Sancarlos, Jean-Marc Le Peuvedic, Francisco Chinesta, Morgan Cameron, Jean Louis Duval
Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
instname
The concept of “hybrid twin” (HT) has recently received a growing interest thanks to the availability of powerful machine learning techniques. This twin concept combines physics-based models within a model order reduction framework—to obtain re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51868f3bc2632ba603fa6d99920e5ff3