Single- and multiobjective design optimization of a fast multihull ship: numerical and experimental results |
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Authors: | Yusuke Tahara Daniele Peri Emilio Fortunato Campana Frederick Stern |
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Institution: | (1) Fluids Engineering Department, National Maritime Research Institute, 6-38-1 Shinkawa, Mitaka Tokyo, 181-0004, Japan;(2) INSEAN-CNR, Italian Ship Model Basin, Rome, Italy;(3) IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, USA |
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Abstract: | Numerical optimization of the initial design of a fast catamaran (high-speed sealift research model B, HSSL-B) has been carried
out through a simulation-based design (SBD) framework, based on an advanced free-surface unsteady Reynolds-averaged Navier–Stokes
(URANS) solver and a potential flow solver, and global optimization (GO) algorithms. The potential flow computational fluid
dynamics (CFD) SBD was used to guide the more expensive URANS CFD SBD. The fluid-dynamic analysis of the flow past the catamaran
proved that the use of the URANS solver was fundamental in dealing with the multihull interference problem. In the case investigated,
the separation distance was small and the viscous flow quite distorted by the proximity of the hulls, so that only viscous
solvers could correctly capture the flow details. Sinkage and trim effects, due to the high speed range and again to the small
separation distance investigated, are also relevant. The initial HSSL-B geometry and three optimization problems, including
single- and multiobjective optimization problems, proposed by designers from Bath Iron Works, were successfully optimized/solved,
and finally an experimental campaign was carried out to validate the optimal design. A new verification and validation methodology
for assessing uncertainties and errors in simulation-based optimization was used based on the trends, i.e., the differences
between the numerically predicted improvement of the objective function and the actual improvement measured in a dedicated
experimental campaign, including consideration of numerical and experimental uncertainties. Finally, the success of the optimization
processes was confirmed by the experimental measurements, and trends for total resistance, sinkage, and trim between the original
and optimal designs were numerically and experimentally verified and validated. |
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