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Application of derivative-free multi-objective algorithms to reliability-based robust design optimization of a high-speed catamaran in real ocean environment

机译:无导数多目标算法在真实海洋环境中基于可靠性的高速双体船稳健设计优化中的应用

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摘要

A reliability-based robust design optimization (RBRDO) for ship hulls is presented. A real ocean environment is considered, including stochastic sea state and speed. The optimization problem has two objectives: (a) the reduction of the expected value of the total resistance in waves and (b) the increase of the ship operability (reliability). Analysis tools include a URANS solver, uncertainty quantification methods and metamodels, developed and validated in earlier research. The design space is defined by an orthogonal four-dimensional representation of shape modifications, based on the Karhunen-Loeve expansion of free-form deformations of the original hull. The objective of the present paper is the assessment of deterministic derivative-free multi-objective optimization algorithms for the solution of the RBRDO problem, with focus on multi-objective extensions of the deterministic particle swarm optimization (DPSO) algorithm. Three evaluation metrics provide the assessment of the proximity of the solutions to a reference Pareto front and their wideness.
机译:提出了一种基于可靠性的船体鲁棒设计优化(RBRDO)。考虑了真实的海洋环境,包括随机的海况和速度。优化问题有两个目标:(a)减小波浪中的总阻力的期望值;(b)提高船舶的可操作性(可靠性)。分析工具包括在早期研究中开发和验证的URANS求解器,不确定性量化方法和元模型。设计空间由形状修改的正交四维表示所定义,基于原始船体的自由变形的Karhunen-Loeve展开。本文的目的是评估确定性无导数的多目标优化算法,以解决RBRDO问题,重点是确定性粒子群优化(DPSO)算法的多目标扩展。三种评估指标可评估解决方案与参考帕累托前沿的接近程度及其范围。

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