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竖向不规则多层轻钢结构强震倒塌预测的细胞自动机与相关向量机联合法 被引量:2

CA and RVM combined method for predicting collapse of vertical irregular mid-rise cold-formed steel structures under strong earthquake
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摘要 为提高竖向不规则多层轻钢龙骨复合剪力墙结构强震倒塌预测精度,对已有细胞自动机(cellular automata, CA)方法进行改进。通过增加邻居细胞数目,采用结构归一化Pushover分析后的层间位移定义细胞状态值。在此基础上,采用相关向量机(relevance vector machine, RVM)代替已有相似区域匹配准则,得到CA与RVM的联合预测方法。采用联合法和已有CA法,预测竖向不规则多层轻钢结构在强震作用下倒塌时的层间位移(倒塌判别准则为强震作用下多层轻钢结构层间位移角分别超过2.0%、3.5%、4.0%),并将预测结果与非线性时程分析结果对比。结果表明:联合法以弹塑性阶段特征值作为细胞状态值,且选用RVM建立细胞状态值与结构倒塌时层间位移的非线性关系,可准确预测竖向不规则多层轻钢结构倒塌时的层间位移,较原有CA方法预测精度明显提高。 The existing cellular automata(CA) method is improved to increase the prediction accuracy of vertical irregular mid-rise cold-formed steel framed structures with composite shear walls under strong earthquake. Firstly, the number of neighbor cells is increased, and the normalized inter-story drift is regarded as the cell state value through performing Pushover analysis on the structure. Then the combined method of CA and relevance vector machine(RVM) is developed by replacing the existing similar region matching criteria with RVM. Finally, the combined method and the existing CA method are used to predict the collapse inter-story drift of vertical irregular mid-rise cold-formed steel structure under strong earthquake(the collapse criterion is that the inter-story drift angle is more than 2.0%, 3.5% or 4.0%). The prediction results are compared with the results of nonlinear time history analysis.The results show that by taking the eigenvalue of the elastic-plastic stage as the cell state value, and selecting RVM to establish the nonlinear relationship between the cell state value and the inter-story drift when the structure collapses, the combined method can accurately predict the inter-story drift of vertical irregular mid-rise cold-formed steel structures when they collapse. Compared with the original CA method, the prediction accuracy is significantly improved.
作者 王坤 叶继红 WANG Kun;YE Jihong(Jiangsu Key Laboratory Environmental Impact and Structural Safety in Engineering,China University of Mining and Technology,Xuzhou 221116,China;Xuzhou Key Laboratory for Fire Safety of Engineering Structures,China University of Mining&Technology,Xuzhou 221116,China)
出处 《建筑结构学报》 EI CAS CSCD 北大核心 2022年第8期232-239,共8页 Journal of Building Structures
基金 国家自然科学基金重点项目(51538002) “十三五”国家重点研发计划课题(2017YFC1500702)。
关键词 多层轻钢龙骨复合剪力墙结构 竖向不规则 强震倒塌预测 细胞自动机 相关向量机 mid-rise cold-formed steel framed structure with composite shear walls vertical irregular strong earthquake collapse prediction cellular automata relevance vector machine
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