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船体阻力数值预报研究及黏性流场计算 被引量:7

Research on resistance prediction and calculation of viscous flow field
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摘要 采用SIMPLE算法求解不可压缩RANS方程,对KCS船体阻力计算精度进行研究。采用VOF方法捕捉自由液面,采用切割体网格技术划分整个流域。以自由模为例,首先分析边界层划分方式、湍流系数的确定对阻力的影响,为阻力的精确预报提供基础。其次,在合适的网格方式上,提出采用序列二次规划(NLPQL)法建立基于湍流系数的优化系统,以寻找到最适合船体阻力计算的湍流系数。然后,在最合适的网格及计算方法下计算不同航速下KCS船受到的总阻力、船体表面及周围流场分布,讨论约束模和自由模在阻力预报、流场捕捉上的差异,并分别将阻力计算结果与模型试验进行对比,从而验证本文算法的可靠性。本文研究内容能够为船体阻力的精确预报提供一定参考。 In this paper, the accuracy of resistance prediction was studied by using the RANS equations based on the SIMPLE algorithm with KCS. The free surface was simulated with volume of fluid(VOF) method. The whole computational domain was divided with trimmed mesh. Taking the MDOF model as an example, firstly, the influence of boundary layer and turbulence coefficients were analyzed, which provided the basis for accurate prediction of hull resistance. In the process of numerical simulation, the high-quality mesh and the high-precision numerical method are the key to CFD simulation. The paper established the optimization system of turbulence coefficients based on non-linear programming by quadratic lagrangian(NLPQL) algorithm to find the optimal solution parameters. Then, the total resistance, the pressure on wet surface of hull and the flow field under different Fr were calculated in the most suitable grids and turbulence coefficients. The differences between captive model and MDOF model in resistance prediction and flow field were discussed. Then the numerical results were compared with the experimental data. This study can give a reference for the future research in resistance prediction for the ship hull.
作者 王英第 陈彦臻 周伟健 张盛龙 WANG Ying-di;CHEN Yan-zhen;ZHOU Wei-jian;ZHANG Sheng-long(Bohai Shipbuilding Vocational College,Huludao 125105,China;Shanghai Maritime University,Merchant Maritime College,Shanghai 201306,China;Harbin Engineering University,College of Power and Energy Engineering,Haerbin 150001,China;Changshu Institute of Technology,Automotive Engineering,Changshu 215500,China)
出处 《舰船科学技术》 北大核心 2020年第1期17-22,共6页 Ship Science and Technology
基金 江苏省高等学校自然科学研究项目面上项目(19KJB580006)
关键词 SIMPLE算法 KCS船 阻力预报 NLPQL SIMPLE KCS resistance prediction NLPQL
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