钢制闸门冰载荷识别与静强度分析

Ice load identification and static strength analysis of a steel gate

为研究闸门在冰载荷作用下的结构是否安全,本文在2015-2016冬季对闸门结构变形进行了连续监测,并通过ANSYS仿真建立了冰载荷识别的数学模型。结合Tikhonov正则法与粒子群优化算法对冰载荷识别数学模型进行求解,利用水工钢结构监测数据识别出了冰载荷的近似分布,并在此基础上计算了闸门的应力分布、刚度与稳定性。计算结果表明:混合算法优于常规的正则化方法和M-P逆法,能够给出较高精度的求解结果;闸门安全性足够,冰载荷未对闸门安全造成过大影响。研究结果表明:正则法的灵活应用及其与优化算法的合理结合能得到比传统正则法更精确的求解结果,其对冰载荷的间接监测具有较高的工程参考价值。

The structural deformation of a steel gate was monitored during the winter of 2015-2016,and the mathematical model for ice load identification was established by ANSYS to analyze the safety of the gate considering ice load.In this paper,a hybrid method composed of the Tikhonov regularization method and a particle swarm optimization algorithm was developed to solve the mathematical model used for ice load identification.Based on the monitoring data of hydraulic steel,the approximate distribution of ice load was identified,and the stress distribution,stiffness,and stability of the gate were calculated.The calculated result showed that the hybrid method was superior to the normal regularization method and the M-P inverse method,and was able to solve the problem with high precision;the gate was adequately safe,and the ice extrusion force did not have a significant impact on the safety of the gate.The research results in this paper showed that by flexibly applying the regularization method and reasonably combining it with another optimization algorithm,a more accurate solution can be obtained than with the traditional regularization method,which had a higher engineering reference value for indirect monitoring of ice load.