Zobrazeno 1 - 10
of 434
pro vyhledávání: '"Rizzi, Francesco"'
This paper presents and evaluates a framework for the coupling of subdomain-local projection-based reduced order models (PROMs) using the Schwarz alternating method following a domain decomposition (DD) of the spatial domain on which a given problem
Externí odkaz:
http://arxiv.org/abs/2410.04668
Projection-based model order reduction on nonlinear manifolds has been recently proposed for problems with slowly decaying Kolmogorov n-width such as advection-dominated ones. These methods often use neural networks for manifold learning and showcase
Externí odkaz:
http://arxiv.org/abs/2303.09630
Autor:
Parish, Eric J, Rizzi, Francesco
Model reduction of the compressible Euler equations based on proper orthogonal decomposition (POD) and Galerkin orthogonality or least-squares residual minimization requires the selection of inner product spaces in which to perform projections and me
Externí odkaz:
http://arxiv.org/abs/2203.16492
Autor:
Cinquino, Marco, Demir, Suleyman Mahircan, Shumba, Angela Tafadzwa, Schioppa, Enrico Junior, Fachechi, Luca, Rizzi, Francesco, Qualtieri, Antonio, Patrono, Luigi, Mastronardi, Vincenzo Mariano, De Vittorio, Massimo
Publikováno v:
In Biosensors and Bioelectronics 1 January 2025 267
This work focuses on the space-time reduced-order modeling (ROM) method for solving large-scale uncertainty quantification (UQ) problems with multiple random coefficients. In contrast with the traditional space ROM approach, which performs dimension
Externí odkaz:
http://arxiv.org/abs/2111.06435
Autor:
Agullo, Emmanuel, Altenbernd, Mirco, Anzt, Hartwig, Bautista-Gomez, Leonardo, Benacchio, Tommaso, Bonaventura, Luca, Bungartz, Hans-Joachim, Chatterjee, Sanjay, Ciorba, Florina M., DeBardeleben, Nathan, Drzisga, Daniel, Eibl, Sebastian, Engelmann, Christian, Gansterer, Wilfried N., Giraud, Luc, Goeddeke, Dominik, Heisig, Marco, Jezequel, Fabienne, Kohl, Nils, Li, Xiaoye Sherry, Lion, Romain, Mehl, Miriam, Mycek, Paul, Obersteiner, Michael, Quintana-Orti, Enrique S., Rizzi, Francesco, Ruede, Ulrich, Schulz, Martin, Fung, Fred, Speck, Robert, Stals, Linda, Teranishi, Keita, Thibault, Samuel, Thoennes, Dominik, Wagner, Andreas, Wohlmuth, Barbara
This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by all the authors. Naive versions of conventional resilience techniques w
Externí odkaz:
http://arxiv.org/abs/2010.13342
This work aims to advance computational methods for projection-based reduced order models (ROMs) of linear time-invariant (LTI) dynamical systems. For such systems, current practice relies on ROM formulations expressing the state as a rank-1 tensor (
Externí odkaz:
http://arxiv.org/abs/2009.11742
This work introduces Pressio, an open-source project aimed at enabling leading-edge projection-based reduced order models (ROMs) for large-scale nonlinear dynamical systems in science and engineering. Pressio provides model-reduction methods that can
Externí odkaz:
http://arxiv.org/abs/2003.07798
Publikováno v:
Supply Chain Management: An International Journal, 2022, Vol. 28, Issue 2, pp. 300-323.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SCM-07-2021-0326
Autor:
Parish, Eric J., Rizzi, Francesco
Publikováno v:
In Journal of Computational Physics 15 October 2023 491