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Evaluation of a semi-empirical numerical simulation method for level ice breaking

机译:半实物破冰数值模拟方法的评价

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摘要

A semi-empirical numerical method for level ice breaking is evaluated in this thesis by full scale data from ice trial of S.A. Agulhas II. The data are analysed and organised systematically for evaluation use with certain accuracy. The original model together with some improved versions are evaluated in terms of ship resistance, time history of speed and average speed. Additional resistance source is identified. A comparison between empirical formulas and simulation methods is conducted to find the advantages and deficiencies of this method.Results have shown that this model generally gives acceptable prediction on average resistance and velocity. However, there are obvious deviations in time history of velocity. Compared to empirical formulas, numerical method gives more ship-specific results. Besides, shoulder crushing is identified as an important phenomenon which introduces uncertainty in results. Randomness is suggested for ice breaking pattern to eliminate this problem.As suggestion, a combined modification including dynamic bending and random breaking radius is recommended. Resistance due to ice rubble under level ice is required to be included in ship resistance. A combined ice thickness measurement including electromagnetic method and stereo camera is suggested to grasp more information of the ice. Model and full scale tests are required to investigate more about ice breaking process, especially breaking pattern. This model can be improved when some empirical coefficients are replaced by conclusions from test results.
机译:本文利用来自S.A. Agulhas II的制冰试验的全面数据,评估了一种用于水平破冰的半经验数值方法。对数据进行系统地分析和组织,以便以一定的准确性进行评估。原始模型以及一些改进的版本将根据船的阻力,速度的时程和平均速度进行评估。确定了其他电阻源。通过对经验公式与仿真方法的比较,发现该方法的优缺点。结果表明,该模型对平均阻力和速度给出了可接受的预测。但是,速度的时间历史存在明显的偏差。与经验公式相比,数值方法给出了更多针对特定船舶的结果。此外,肩部挤压被认为是导致结果不确定的重要现象。建议采用破冰模式的随机性来消除此问题。建议将动态弯曲和随机破断半径结合起来使用。要求在平整的冰层下包括冰碎石引起的阻力。建议结合电磁方法和立体相机进行冰厚测量,以掌握更多的冰信息。需要进行模型测试和全面测试才能更多地了解破冰过程,尤其是破冰模式。如果将一些经验系数替换为测试结果的结论,则可以改进此模型。

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  • 作者

    Li Fang;

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  • 年度 2016
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  • 原文格式 PDF
  • 正文语种 en
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