Multi-Objective Surrogate Based Hull-Form Optimization Using High-Fidelity RANS Computations
Author Scholcz, T.P. and Veldhuis, C.H.J.
Title Multi-Objective Surrogate Based Hull-Form Optimization Using High-Fidelity RANS Computations
Conference/Journal VII International Conference on Computational Methods in Marine Engineering (MARINE2017), Nantes, France
Month May
Year 2017
Pages 231-242

Abstract
RANS-based optimization procedures for ship design become increasingly complex
and require the development of more efficient optimization techniques. The four phases of
the design procedure are: shape parameterization, global sensitivity analysis, multi-objective
optimization and design review. The dimensions of the design space can be mitigated by a
smart choice for the shape parameterization and by screening and ranking the design variables
in the global sensitivity phase. Subsequently, Surrogate Based Global Optimization (SBGO) is
used to reduce the cost of the multi-objective optimization phase. For a practical application it
is shown that the computational time reduces from two weeks to only a day when using SBGO
instead of applying a Multi-Objective Genetic Algorithm (MOGA) directly to the solver. The
design review phase is then used to verify and further develop the optimal design. Here, we
focus on automatic ship design techniques which comprises the first three steps of the design
procedure. Accelerating the ship design process is subject of ongoing research at the Maritime
Research Institute Netherlands, making it useful for practical applications with turnaround times
of only a few weeks.

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