融入先验知识的轮印载荷下三跨梁最危险工况求解方法

Embedded domain knowledge method for worst-case analysis of three-span beam under multiple patch loads

  • 摘要:
    目的 旨在解决多个轮印载荷作用时,直接调用优化算法进行最危险工况求解可能陷入局部最优解的问题。
    方法 将先验知识与最危险工况分析通用黑箱求解算法相融合,一方面将每个轮印载荷位置定义为设计变量,无需事先规定一组轮印载荷的相对位置,更具普适性;另一方面将载荷按照大小顺序紧密聚集会产生较大应力,载荷作用在梁结构跨中和支座附近产生较大弯矩和剪力等船舶结构力学知识融入优化求解过程,提出基于遗传算法的危险初始种群生成策略和轮印载荷整体平动策略以减少陷入局部最优解的可能。推导单轮印载荷作用下三跨梁结构的理论弯矩及剪力分布,通过枚举所有可能组合找出多轮印载荷理论最危险作用位置,借此验证所提出的最危险工况分析求解算法的正确性。
    结果 相比于经典方法,6个轮印载荷作用下,使用所提方法得到的最危险弯曲正应力值提升5.98%,剪应力提升8.59%,且多次计算结果与理论解误差不超过0.5%。
    结论 算例结果表明所提出的方法能够准确、稳定且快速搜索到最危险的载荷位置。

     

    Abstract:
    Objective This paper seeks to solve the problem in which directly invoking an optimization algorithm for the worst-case analysis of a three-span beam structure under multiple patch loads raises the possibility of falling into the local optimal solution rather than the global solution.
    Method An analysis method comprising embedded domain knowledge with the general black-box optimization algorithm is proposed for the worst-case analysis of the beam. On the one hand, the position of each wheel patch load is defined as a design variable, so there is no need to specify the relative position of the group of wheel patch loads in advance, which is more universal; on the other, by integrating knowledge of ship structural mechanics, such as “large stress resulting from the close aggregation of loads in order of magnitude, large bending moment and shear force usually generated by the load in the mid span of the beam and near the support”, into the optimization algorithm, a strategy for generating dangerous initial populations based on the genetic algorithm and the overall translational strategy of the wheel patch load are proposed respectively, thereby reducing the possibility of falling into the local optimal solution. The theoretical bending moment and shear force distribution of a three-span beam under a single wheel patch load are derived respectively. The theoretical most dangerous positions of multiple wheel patch loads are then determined by enumerating all possible combinations to verify the correctness of the proposed algorithm.
    Results Compared with the optimization algorithm without domain knowledge and under the same computational resources, the most dangerous bending normal stress and shear stress increase by 5.9% and 8.6% respectively under six wheel patch loads, and the error between the calculation results and the theoretical solution is less than 0.5%.
    Conclusion The numerical results show that the proposed method can accurately, stably, and quickly obtain the most dangerous load positions.

     

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