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RC偏压构件精细抗力概率模型 被引量:3

Refined Probabilistic Model of Resistance of RC Eccentric Compression Members
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摘要 现行可靠度统一标准给出的RC偏压构件抗力统计参数较为粗糙,对其随偏心距值的变化考虑不够充分。针对此不足,采用Monte Carlo抽样方法并结合已有的各种抗力因素的概率模型,得到了不同偏心距和配筋率下的改进抗力概率模型。结果表明采用正态分布变量来拟合RC偏压构件抗力的分布具有较好的精度。在此基础上,对此改进模型应用于随机偏心距下RC偏压构件可靠度计算的适用性进行了实例分析。结果证实,当偏心距设计值接近或者大于界限偏心距值时,采用现行标准中的抗力概率模型来计算可靠度均会产生较大的误差,而采用文中建议的抗力概率模型则具有较高的精度;且现行可靠度统一标准因对抗力随偏心距值增大而减小的效应考虑不够而使得RC大偏压构件的设计偏于不安全。 The probabilistic model of resistance in the current unified standard for reliability design is imprecise for RC members subjected to eccentric compression. The reason is that it lacks full considerations of influences of varying eccentricities. An improved probabilistic model of resistance with different eccentricities and reinforcement ratios is obtained by using the Monte Carlo sampling method and the current probabilistic models of all resistant factors. The results indicate that it is accurate to fit the probabilistic distribution of resistance with normal distribution. Given that, the applicability of the improved model is analyzed for reliability analysis of RC members subjected to eccentric compression with random eccentricities. It shows that when the design value of eccentricity is close to or larger than the eccentricity producing balanced failure, there would be large errors in reliability analysis if the probabilistic model of resistance given in the current reliability unified standard is used. However, it is accurate when using the proposed probabilistic model. The results also show that the design of RC members subjected to large eccentric compression is unsafe based on the current reliability unified standard because it lacks full considerations of effects that the resistance decreases as eccentricity increases.
出处 《土木建筑与环境工程》 CSCD 北大核心 2014年第4期15-21,共7页 Journal of Civil,Architectural & Environment Engineering
基金 国家自然科学基金(11102029)
关键词 抗力概率模型 RC偏压构件 偏心距 可靠度 MONTE Carlo抽样 probabilistic model of resistance RC member subjected to eccentric compression eccentricity reliability Monte Carlo sampling
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