Journal article
Hull-form stochastic optimization via computational-cost reduction methods
Engineering with computers, Vol.38(3 supplement ), pp.2245-2269
03/24/2021
DOI: 10.1007/s00366-021-01375-x
Abstract
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 hull-form optimization is presented, where (a) physics-informed design-space dimensionality reduction, (b) adaptive metamodeling, (c) uncertainty quantification (UQ) methods, and (d) global multi-objective algorithm are efficiently and effectively combined to achieve high-fidelity simulation-based design optimization (SBDO) solutions. The application pertains to the multi-objective optimization for resistance and seakeeping (operational efficiency and effectiveness) of a destroyer-type vessel. Two hierarchical multi-objective SBDO problems are presented, with a level of complexity decreasing from the most general (stochastic sea state, heading, and speed) to the least general (deterministic regular wave, at fixed sea state, heading, and speed). Design-space dimensionality reduction is based on a generalized Karhunen-Loève expansion of the shape modification vector combined with low-fidelity-based physical variables. A multi-objective deterministic particle swarm optimization algorithm is applied to a stochastic radial-basis-function metamodel that provides objective predictions. UQ methods include Gaussian quadrature and metamodel-based importance sampling. Numerical simulations are based on unsteady Reynolds-averaged Navier–Stokes and potential flow solvers. The paper shows and discusses the joint effort of computational-cost reduction methods in enabling high-fidelity SBDO, providing guidelines for future research directions in this area.
Details
- Title: Subtitle
- Hull-form stochastic optimization via computational-cost reduction methods
- Creators
- Andrea Serani - National Research CouncilFrederick Stern - University of IowaEmilio F Campana - National Research CouncilMatteo Diez - National Research Council
- Resource Type
- Journal article
- Publication Details
- Engineering with computers, Vol.38(3 supplement ), pp.2245-2269
- DOI
- 10.1007/s00366-021-01375-x
- ISSN
- 0177-0667
- eISSN
- 1435-5663
- Grant note
- DOI: 10.13039/100007297, name: Office of Naval Research Global, award: N62909-15-1-2016
- Language
- English
- Electronic publication date
- 03/24/2021
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9984196604002771
Metrics
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