Abstract: The Hangzhou-Ningbo Canal is of great significance to the economy and material circulation in the eastern Zhejiang region. This study focuses on the automatic modeling and hull form optimization of container vessels sailing in the Hangzhou-Ningbo Canal by coupling CAESES with computational fluid dynamics (CFD). First, the hull structure is deformed based on semi-parametric modeling. A new hull form is iteratively generated according to the geometric parameters given by the optimization algorithm. In each iteration, the hydrodynamic performance of the hull model is solved by using CFD software to provide geometric parameters for the next iteration. The optimal hull form is eventually identified in the geometric configuration space through this iterative process. The results show that the optimized hull form achieves a drag reduction of 5.8%, and the pressure distribution on the hull surface is significantly improved, with a reduced negative pressure area and less stress concentration. This study can provide theoretical and technical support for the hull form optimization of inland container vessels.

Key words: Hangzhou-Ningbo Canal, hull optimization, resistance performance, computational fluid dynamics (CFD)

摘要： 杭甬运河对于浙东区域的经济与物资流通意义重大。该文将CAESES与CFD软件耦合,针对杭甬运河运营的集装箱船船体,开展自动建模与型线优化：首先基于半参数化建模对船体型线进行变形,根据优化算法给出的几何参数,迭代生成新的船体型线;然后通过CFD软件求解船体模型的水动力性能,给出下一个循环的几何参数。通过这种不断迭代的方式,最终在几何构型空间中获得最优船型。结果表明：优化后船型阻力降低5.8%,同时船体表面压力分布得到明显改善,负压区范围缩小、应力集中现象得以缓解。该项研究可为内河集装箱船的型线优化提供理论和技术支持。

关键词: 杭甬运河, 船型优化, 阻力性能, CFD