A sco** review on simulation-based design optimization in marine engineering: trends, best practices, and gaps

A Serani, TP Scholcz, V Vanzi - Archives of Computational Methods in …, 2024 - Springer
This sco** review assesses the current use of simulation-based design optimization
(SBDO) in marine engineering, focusing on identifying research trends, methodologies, and …

Multi-fidelity Co-Kriging surrogate model for ship hull form optimization

X Liu, W Zhao, D Wan - Ocean Engineering, 2022 - Elsevier
For the simulation-based hull form optimization design, there are many methods to evaluate
the hydrodynamic performance of the hull form. Although the high fidelity of the surrogate …

Applications of multi-fidelity multi-output Kriging to engineering design optimization

DJJ Toal - Structural and Multidisciplinary Optimization, 2023 - Springer
Surrogate modelling is a popular approach for reducing the number of high fidelity
simulations required within an engineering design optimization. Multi-fidelity surrogate …

Hull-form stochastic optimization via computational-cost reduction methods

A Serani, F Stern, EF Campana, M Diez - Engineering with Computers, 2022 - Springer
The paper shows how cost-reduction methods can be synergistically combined to enable
high-fidelity hull-form optimization under stochastic conditions. Specifically, a multi-objective …

Dynamic of a planing hull in regular waves: Comparison of experimental, numerical and mathematical methods

S Tavakoli, RN Bilandi, S Mancini, F De Luca… - Ocean …, 2020 - Elsevier
The unsteady planing motion in waves is a complicated problem, that can lead to
uncomfortable riding situation and structural damages due to large wave-induced dynamic …

Machine learning-aided design optimization of a mechanical micromixer

FJ Granados-Ortiz, J Ortega-Casanova - Physics of Fluids, 2021 - pubs.aip.org
In real-life mechanical engineering applications, it is often complex to achieve an optimal
multi-objective design, because of the costs related to fabrication and test of different …

On kernel functions for bi-fidelity Gaussian process regressions

PS Palar, L Parussini, L Bregant, K Shimoyama… - Structural and …, 2023 - Springer
This paper investigates the impact of kernel functions on the accuracy of bi-fidelity Gaussian
process regressions (GPR) for engineering applications. The potential of composite kernel …

Comparison of multi-fidelity approaches for military vehicle design

PS Beran, D Bryson, AS Thelen, M Diez… - AIAA Aviation 2020 …, 2020 - arc.aiaa.org
This paper overviews the efforts of a technical team within the NATO Applied Vehicle
Technology Panel to apply multi-fidelity methods to vehicle design. The objectives of the …

Multi-fidelity data-driven design and analysis of reactor and tube simulations

T Savage, N Basha, J McDonough, OK Matar… - Computers & Chemical …, 2023 - Elsevier
Optimizing complex reactor geometries is vital to promote enhanced efficiency. We present a
framework to solve this nonlinear, computationally expensive, and derivative-free problem …

A multi-fidelity active learning method for global design optimization problems with noisy evaluations

R Pellegrini, J Wackers, R Broglia, A Serani… - Engineering with …, 2023 - Springer
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 …