Multi-objective hull-form optimization of a swath configuration via design-space dimensionality reduction, multi-fidelity metamodels, and swarm intelligence
Document typeConference report
Rights accessOpen Access
A multi-objective simulation-based design optimization (SBDO) is presented for the resistance reduction and displacement increase of a small water-plane area twin hull (SWATH). The geometry is realized as a parametric model with the CAESESQR software, using 27 design parameters. Sobol sampling is used to realize design variations of the original geometry and provide data to the design-space dimensionality reduction method by Karhunen-Lo`eve expan- sion. The hydrodynamic performance is evaluated with the potential flow code WARP, which is used to train a multi-fidelity metamodel through an adaptive sampling procedure based on prediction uncertainty. Two fidelity levels are used varying the computational grid. Finally, the SWATH is optimized by a multi-objective deterministic version of the particle swarm optimiza- tion algorithm. The current SBDO procedure allows for the reduction of the design parameters from 27 to 4, resolving more than the 95% of the original geometric variability. The metamodel is trained by 117 coarse-grid and 27 fine-grid simulations. Finally, significant improvements are identified by the multi-objective algorithm, for both the total resistance and the displacement.
CitationPellegrini, R. [et al.]. Multi-objective hull-form optimization of a swath configuration via design-space dimensionality reduction, multi-fidelity metamodels, and swarm intelligence. A: MARINE VII. "MARINE VII : proceedings of the VII International Conference on Computational Methods in Marine Engineering". CIMNE, 2017, p. 95-106. ISBN 978-84-946909-8-3.
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