Analytical benchmark problems for multifidelity optimization methods

L Mainini, A Serani, MP Rumpfkeil, E Minisci… - arXiv preprint arXiv …, 2022 - arxiv.org
The paper presents a collection of analytical benchmark problems specifically selected to
provide a set of stress tests for the assessment of multifidelity optimization methods. In …

Raal: Resource aware active learning for multifidelity efficient optimization

F Grassi, G Manganini, M Garraffa, L Mainini - AIAA Journal, 2023 - arc.aiaa.org
TRADITIONAL methods for black-box optimization require a considerable number of
evaluations of the objective function. This can be time consuming, impractical, and …

Reduced order modeling of hydrodynamic interactions between a submarine and unmanned underwater vehicle using non-myopic multi-fidelity active learning

B Hammond, TP Sapsis - Ocean Engineering, 2023 - Elsevier
Several efforts have been dedicated to developing computational tools capable of predicting
the hydrodynamic forces and moments of Unmanned Underwater Vehicles (UUVs) …

A derivative-free line-search algorithm for simulation-driven design optimization using multi-fidelity computations

R Pellegrini, A Serani, G Liuzzi, F Rinaldi, S Lucidi… - Mathematics, 2022 - mdpi.com
The paper presents a multi-fidelity extension of a local line-search-based derivative-free
algorithm for nonsmooth constrained optimization (MF-CS-DFN). The method is intended for …

[HTML][HTML] Cost-effective framework for gradual domain adaptation with multifidelity

S Sagawa, H Hino - Neural Networks, 2023 - Elsevier
In domain adaptation, when there is a large distance between the source and target
domains, the prediction performance will degrade. Gradual domain adaptation is one of the …

Diagnosing Incipient Faults for a Faster Adoption of Sustainable Aerospace Technologies

F Di Fiore, PC Berri, L Mainini - AIAA Journal, 2024 - arc.aiaa.org
Next-generation aircraft require the development and integration of a deal of innovative
green technologies to meet the ambitious sustainability goals set for aviation. Those …

Prediction of short-term non-linear response using screening combined with multi-fidelity Gaussian Process Regression

S van Essen, T Scholcz… - International …, 2023 - asmedigitalcollection.asme.org
Predicting wave impact design loads is crucial for ensuring safety and performance of
maritime structures, but it is challenging due to the complexity and rarity of these events …

[PDF][PDF] Hull-shape optimisation using adaptive multi-fidelity Kriging

T Scholcz, J Klinkenberg - 2022 - sto.nato.int
The paper presents and discusses the development and assessment of an active learning
multi-fidelity Kriging method for military vehicle design within the NATO AVT-331 task group …

Cost-effective Framework for Gradual Domain Adaptation with Multifidelity

S Sagawa, H Hino - arXiv preprint arXiv:2202.04359, 2022 - arxiv.org
In domain adaptation, when there is a large distance between the source and target
domains, the prediction performance will degrade. Gradual domain adaptation is one of the …

Multifidelity Framework for the Efficient Identification of Damages in Complex Aerospace Systems

F Di Fiore, PCC Berri, L Mainini - AIAA AVIATION 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-4449. vid Next generation aircraft
require the development and integration of a deal of innovative technologies to meet the …