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随机锈蚀H型钢柱偏压承载力分析

Bearing Capacity of Randomly Corroded H-Shaped Steel Columns Under Eccentrical Compression
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摘要 为了揭示随机锈蚀对H型钢柱在偏压作用下极限承载能力的影响,采用随机有限元方法对随机点蚀钢柱的抗弯承载力的变化规律进行了研究,考虑了轴压比、几何参数以及锈蚀深度对H型钢柱抗弯承载力折减系数的影响;得到了不同几何尺寸下H型钢柱的适用性,揭示了折减系数随锈蚀深度的变化规律,提出了用于预测抗弯承载力折减系数的理论计算公式。结果表明,所提出的理论公式可以准确预测随机点蚀H型钢柱的抗弯承载力,可为评估既有H型钢柱的极限承载力提供理论基础。 The variation law of flexural bearing capacity of random pitting steel columns was studied based on the stochastic finite element method to reveal the influence of random corrosion on the ultimate bearing capacity of H-shaped steel columns under eccentric compression.The effects of axial compression ratio,geometrical parameters and corroded depth on the reduction factor of bending capacity for H-shaped steel columns were considered.The applicability of the conclusions of this paper to H-shaped steel columns with different geometrical sizes was obtained.The variation of the reduction factor with the corroded depth was revealed,and the theoretical calculation formula for predicting the reduction factor of bending capacity was proposed.The results indicate that the proposed theoretical formula can accurately predict the bending capacity of H-shaped steel columns with random pitting corrosion.The conclusions of this work can provide help for evaluating the service life and maintenance of existing H-shaped steel members.
作者 赵炳震 杜颜胜 李存良 郭晓程 王晓龙 王建涛 赵中伟 ZHAO Bingzhen;DU Yansheng;LI Cunliang;GUO Xiaocheng;WANG Xiaolong;WANG Jiantao;ZHAO Zhongwei(Shaanxi Construction Engineering Group Co.LTD.,Xi'an 710000,China;Department of Civil Engineering,Tianjin University,Tianjin 300072,China;Xi'an Rail Transit Group Co.,LTD,Xi'an 710018,China;Department of Civil Engineering,Xi'an University of Architecture and Technology,Xi'an 710054,China;Liaoning Technical University School of Civil Engineering,Fuxin 123000,China)
出处 《结构工程师》 2024年第2期33-41,共9页 Structural Engineers
基金 陕西省自然科学基础研究计划(2024JC-YBQN-0509),陕西省交通运输厅交通科研项目(23-49)。
关键词 钢柱 随机点蚀 质量损失率 折减系数 锈蚀深度 随机数值分析 steel column pitting corrosion mass-loss ratio reduction factor corrosion depth stochastic numerical analysis
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