28 citations · 71 across the 10 of their papers we have counts for
10 papers
Multi-fidelity hydrodynamic analysis of an autonomous surface vehicle at surveying speed in deep water subject to variable payload
Riccardo Pellegrini, Simone Ficini, Angelo Odetti +3
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 receiv…
On the use of dynamic mode decomposition for time-series forecasting of ships operating in waves
Andrea Serani, Paolo Dragone, Frederick Stern +1
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…
Analytical Benchmark Problems for Multifidelity Optimization Methods
L. Mainini, A. Serani, M. P. Rumpfkeil +11
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…
Parametric Model Embedding
Andrea Serani, Matteo Diez
Methodologies for reducing the design-space dimensionality in shape optimization have been recently developed based on unsupervised machine learning methods. These methods provide…
A Multi-Fidelity Active Learning Method for Global Design Optimization Problems with Noisy Evaluations
Riccardo Pellegrini, Jeroen Wackers, Riccardo Broglia +3
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 s…
Assessing the Performance of an Adaptive Multi-Fidelity Gaussian Process with Noisy Training Data: A Statistical Analysis
Simone Ficini, Umberto Iemma, Riccardo Pellegrini +2
Despite the increased computational resources, the simulation-based design optimization (SBDO) procedure can be very expensive from a computational viewpoint, especially if high-fi…
Comparing Multi-Index Stochastic Collocation and Multi-Fidelity Stochastic Radial Basis Functions for Forward Uncertainty Quantification of Ship Resistance
Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini +3
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 q…
Recurrent-type Neural Networks for Real-time Short-term Prediction of Ship Motions in High Sea State
Danny D'Agostino, Andrea Serani, Frederick Stern +1
The prediction capability of recurrent-type neural networks is investigated for real-time short-term prediction (nowcasting) of ship motions in high sea state. Specifically, the pe…
Data-driven Modelling of Ship Maneuvers in Waves via Dynamic Mode Decomposition
Matteo Diez, Andea Serani, Emilio F. Campana +1
A data-driven and equation-free approach is proposed and discussed to model ships maneuvers in waves, based on the dynamic mode decomposition (DMD). DMD is a dimensionality-reducti…
Uncertainty Quantification of Ship Resistance via Multi-Index Stochastic Collocation and Radial Basis Function Surrogates: A Comparison
Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini +3
This paper presents a comparison of two methods for the forward uncertainty quantification (UQ) of complex industrial problems. Specifically, the performance of Multi-Index Stochas…