浮体带漂角拖航阻力数值预报

Numerical Prediction of Towing Resistance of Floating Body with Drift Angles

采用RANS法预报浮体在不同漂角下的拖航阻力。结合模型试验,分别从网格因素和湍流模型因素2个方面提高数值预报的精度,得到各漂角下的最优数值预报方案。基于最优数值预报结果,进一步研究浮体周围的流场随漂角的变化。结果表明:合适的网格划分方案能在很大程度上节省计算成本。当漂角不大于60°时,湍流模型采用Standard k-ε湍流模型所得结果与试验值的吻合度最高;当漂角大于60°时,湍流模型建议采用SST k-ω湍流模型。Standard k-ε湍流模型的预报精度随漂角的增大而下降;SST k-ω湍流模型在漂角为45°和60°时模拟误差很大,但当漂角从45°减小或从60°增大时,其预报精度都在提升。30°、45°、60°和90°漂角对应的最优解与试验值相比,平均误差分别为2.58%、3.35%、6.64%和7.09%,满足一般工程问题的精度要求。

The towing resistances of the floating body with different drift angles are predicted adopting RANS method. Combining with the model test, the accuracy of numerical prediction is raised from two aspects such as grid configurations and turbulence models, gaining the optimum scheme for each drift angle. Based on the optimal numerical prediction results, the variation of the flow field around the floating body with different drift angles is further analyzed. The results show that proper grid partition greatly helps to improve computing efficiency. When the drift angle is less than 60°, the results by standard k-ε turbulence model have the best agreement with experimental values. However, when drift angle is greater than 60°, the SST k–ω turbulence model is much better. For standard k-ε turbulence model, the accuracy becomes worse with the increase of drift angle. For SST k-ω turbulence model, the accuracy is poor when the drift angle is 45° and 60°, while the prediction precision is improved gradually with the decrease of drift angle from 45° or the increase of drift angle from 60°. The average errors between the optimal numerical results and the experimental values for drift angle 30°, 45°, 60°, and 90° are 2.58%, 3.35%, 6.64%, and 7.09%, respectively, which satisfies the accuracy requirements of general engineering practice.