Hydrodynamic Optimization of Foreship Hull-Form Using Contrastive Optimization Algorithms

• Published in: Journal of coastal research Vol. 37; no. 5; pp. 1063 - 1078
• Main Authors: Yin, Xunbin, Lu, Qingliang, Lu, Yu, Zou, Jin, Wan, Lei
• Format: Journal Article
• Language: English
• Published: Fort Lauderdale Coastal Education and Research Foundation 01.09.2021; Allen Press Publishing; Allen Press Inc
• Subjects: Algorithms; Automation; Boundary conditions; Carbon dioxide; Coastal inlets; Coastal research; Computation; Deformation; Design; Design optimization; Free surfaces; Genetic algorithms; Hydrodynamics; Modules; Naval engineering; Nondominated sorting genetic algorithm; Nonlinear programming; nonlinear programming method; Numerical analysis; Objective function; Optimization algorithms; Panel method (fluid dynamics); Particle swarm optimization; Pressure distribution; Rankine source method; Robustness (mathematics); Shape optimization; Ship design; Ship hulls; Ships; Sorting algorithms; TECHNICAL COMMUNICATIONS; Velocity; wave making resistance; Wave resistance
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/JCOASTRES-D-20-00167.1

Yin, X.; Lu, Q.; Lu, Y.; Zou, J., and Wan, L., 2021. Hydrodynamic optimization of foreship hull-form using contrastive optimization algorithms. Journal of Coastal Research, 37(5), 1063–1078. Coconut Creek (Florida), ISSN 0749-0208. In this study, a hydrodynamic optimization design of the foreship hull-form for the Series 60 ship is presented in terms of minimum wave-making resistance by using contrastive optimization algorithms. The partially parametric approach was developed to modify the original foreship hull-form. The wave-making resistance as an objective function was obtained by the Rankine source panel method with nonlinear free-surface boundary conditions in which the numerical computation results were validated against available experimental data and found to be in good agreement with the test. Different optimal design methods were proposed based on the minimum wave-making resistance: the nonlinear programming method (NLP), the nondominated sorting genetic algorithm (NSGA-II), and particle swarm optimization (PSO). Through the implementation and integration of the hull-form deformation module, the hydrodynamic module, and the optimization module the hydrodynamic optimization framework can be established subsequently. This module realizes the full automation of ship-shape optimization design and searches for the most efficient target through intelligent optimization algorithm. The hydrodynamic optimization applications for the Series 60 ship indicate that the wave-making resistance is reduced distinctly at various Froude numbers by the contrastive optimization algorithms and each optimized foreship hull-form is smoothing. The present study demonstrates an effective and robust integrated approach for the hydrodynamic optimization of ship design.