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基于直接概率积分法的水下航行器随机动力响应高效分析

EFFICIENT STOCHASTIC DYNAMIC RESPONSE ANALYSIS OF UNDERWATER VEHICLE VIA DPIM

  • 摘要: 海洋是人类的资源宝库, 随着海洋资源的不断发掘, 海洋资源的探测与合理开发成为了当今世界各国广泛关注的热点, 水下航行器的勘测活动也随之逐渐增多. 然而, 海洋环境具有极强的随机不确定性, 给水下航行器的操作及轨迹规划带来了巨大影响. 因此, 准确预测随机海洋环境中水下航行器的随机响应特性具有重要意义. 以无舵桨的新型水下航行器为研究对象, 基于概率守恒原理, 从随机积分的全新视角, 建立了随机海洋环境中水下航行器的概率密度积分方程. 在此基础上, 提出了一种基于分块并行计算的直接概率积分法, 该方法将水下航行器系统的控制方程与概率密度积分方程解耦, 通过分块并行计算, 实现了随机波浪激励下新型水下航行器的随机动力响应高效分析. 此外, 还将提出方法的计算结果与原直接概率积分法及蒙特卡洛模拟方法的计算结果进行了比较, 进一步验证了提出方法的精确性和高效性. 最终研究结果表明, 海浪的有义波高和流动速度是影响水下航行器响应的主要随机因素. 海浪有义波高和流动速度的增加会造成水下航行器偏离预定轨迹的概率显著提高. 此外, 较大的海浪流动速度还会引发随机跳跃现象, 从而降低水下航行器的航行安全性.

     

    Abstract: The ocean is a treasure trove of resources for humanity. With the continuous exploration of ocean resources, the detection and rational development of these resources has become a hot topic of widespread concern for countries around the world. Consequently, the exploration activities of underwater vehicles have been gradually increasing. However, the ocean environment is characterized by strong stochastic uncertainty, posing significant challenges for the operation and trajectory planning of underwater vehicles. Therefore, it is crucial to accurately predict the stochastic response characteristics of underwater vehicles in random ocean environments. In this paper, a new type of underwater vehicle, equipped with a rudderless paddle, is adopted as the research object. Based on the principle of probability conservation, a probability density integral equation of the underwater vehicle in a random ocean environment is established from a new perspective of stochastic integration. Then, a direct probability integral method (DPIM) based on block parallel computing is proposed in this paper. This method decouples the control equations of the underwater vehicle system from the probability density integral equation, and utilizes block-parallel computations, enabling the efficient stochastic dynamic response analysis of the new type of underwater vehicle under the random sea wave excitation. Furthermore, the computational results of the proposed method are compared with those of the original DPIM and Monte Carlo simulation method to further validate its accuracy and efficiency. The final research results reveal that sea wave significant height and flow velocity are the primary stochastic factors affecting the response of underwater vehicles. An increase in the sea wave's significant height and flow velocity will significantly raise the probability of deviation from the predetermined trajectory of underwater vehicles. In addition, it can be found that the higher sea wave flow velocity may induce the random jumping phenomena, thereby reducing the navigation safety of the underwater vehicle.

     

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