Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Serani, Andrea"'
Autor:
Serani, Andrea, Diez, Matteo
The rapidly evolving field of engineering design of functional surfaces necessitates sophisticated tools to manage the inherent complexity of high-dimensional design spaces. This review delves into the field of design-space dimensionality reduction t
Externí odkaz:
http://arxiv.org/abs/2405.13944
This scoping review assesses the current use of simulation-based design optimization (SBDO) in marine engineering, focusing on identifying research trends, methodologies, and application areas. Analyzing 277 studies from Scopus and Web of Science, th
Externí odkaz:
http://arxiv.org/abs/2404.18654
Autor:
Seelinger, Linus, Reinarz, Anne, Lykkegaard, Mikkel B., Akers, Robert, Alghamdi, Amal M. A., Aristoff, David, Bangerth, Wolfgang, Bénézech, Jean, Diez, Matteo, Frey, Kurt, Jakeman, John D., Jørgensen, Jakob S., Kim, Ki-Tae, Kent, Benjamin M., Martinelli, Massimiliano, Parno, Matthew, Pellegrini, Riccardo, Petra, Noemi, Riis, Nicolai A. B., Rosenfeld, Katherine, Serani, Andrea, Tamellini, Lorenzo, Villa, Umberto, Dodwell, Tim J., Scheichl, Robert
Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-l
Externí odkaz:
http://arxiv.org/abs/2402.13768
Autor:
Pellegrini, Riccardo, Ficini, Simone, Odetti, Angelo, Serani, Andrea, Caccia, Massimo, Diez, Matteo
Autonomous surface vehicles (ASV) allow the investigation of coastal areas, ports and harbors as well as harsh and dangerous environments such as the arctic regions. Despite receiving increasing attention, the hydrodynamic analysis of ASV performance
Externí odkaz:
http://arxiv.org/abs/2209.03127
In order to guarantee the safety of payload, crew, and structures, ships must exhibit good seakeeping, maneuverability, and structural-response performance, also when they operate in adverse weather conditions. In this context, the availability of fo
Externí odkaz:
http://arxiv.org/abs/2207.04309
Autor:
Serani, Andrea, Diez, Matteo
Methodologies for reducing the design-space dimensionality in shape optimization have been recently developed based on unsupervised machine learning methods. These methods provide reduced dimensionality representations of the design space, capable of
Externí odkaz:
http://arxiv.org/abs/2204.05371
Autor:
Pellegrini, Riccardo, Wackers, Jeroen, Broglia, Riccardo, Serani, Andrea, Visonneau, Michel, Diez, Matteo
A multi-fidelity (MF) active learning method is presented for design optimization problems characterized by noisy evaluations of the performance metrics. Namely, a generalized MF surrogate model is used for design-space exploration, exploiting an arb
Externí odkaz:
http://arxiv.org/abs/2202.06902
Publikováno v:
In Aerospace Science and Technology December 2024 155 Part 1
Despite the increased computational resources, the simulation-based design optimization (SBDO) procedure can be very expensive from a computational viewpoint, especially if high-fidelity solvers are required. Multi-fidelity metamodels have been succe
Externí odkaz:
http://arxiv.org/abs/2107.02455
Autor:
Piazzola, Chiara, Tamellini, Lorenzo, Pellegrini, Riccardo, Broglia, Riccardo, Serani, Andrea, Diez, Matteo
This paper presents a comparison of two multi-fidelity methods for the forward uncertainty quantification of a naval engineering problem. Specifically, we consider the problem of quantifying the uncertainty of the hydrodynamic resistance of a roll-on
Externí odkaz:
http://arxiv.org/abs/2106.00591