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作 者:何林 梁冠亭 李庆轩 付军[2] 余昆 HE Lin;LIANG Guanting;LI Qingxuan;FU Jun;YU Kun(Wuhan Municipal Construction Group Co.Ltd.,Wuhan 430056,China;School of Transportation&Ship,Wuhan University of Technology,Wuhan 430070,China;China Railway Bridge Bureau No.7 Company,Wuhan 430056,China)
机构地区:[1]武汉市市政建设集团有限公司,武汉430056 [2]武汉理工大学交通与船海学部,武汉430070 [3]中铁大桥局七公司,武汉430056
出 处:《武汉理工大学学报(交通科学与工程版)》2024年第1期141-145,共5页Journal of Wuhan University of Technology(Transportation Science & Engineering)
基 金:国家自然科学基金(51708433)。
摘 要:文中以香溪长江大桥主拱肋合龙利用施工风险模型构建为例,考虑先验数据与主拱肋合龙误差的因果关系,构建贝叶斯网络拓扑结构.以中心极限定理(CLT)方式,利用动态多源监控数据更新网络中父节点先验分布.有限元分析与BP神经网络结合,在合龙误差与系列影响参数之间建立对应关系,通过蒙特卡罗法确定了概率分布,实现了联合施工风险误差的定量预测.结果表明:香溪长江大桥的拱肋竖向误差风险概率具有传递性,拱肋合龙误差在75~125 mm的风险等级达到了IV级,因此施工过程中应该对锚索预应力、扣塔偏移、当地气温严密监控.施工风险联合预测模型的计算值与工程实际合龙控制误差趋势吻合.Taking the construction risk model of main arch rib closure of Xiangxi Yangtze River Bridge as an example,considering the causal relationship between prior data and main arch rib closure error,a Bayesian network topology structure was constructed.Using the central limit theorem(CLT),the prior distribution of parent nodes in the network was updated by using dynamic multi-source monitoring data.By combining finite element analysis with BP neural network,the corresponding relationship between closure error and a series of influencing parameters was established.The probability distribution was determined by Monte Carlo method,and the quantitative prediction of joint construction risk error was realized.The results show that the risk probability of arch rib vertical error of Xiangxi Yangtze River Bridge is transitive,and the risk level of arch rib closure error is(75~125)mm,reaching Grade IV.Therefore,the prestress of anchor cable,tower buckling deviation and local temperature should be closely monitored during construction.The calculated value of the joint prediction model of construction risk is consistent with the trend of closure control error in engineering practice.
分 类 号:U445[建筑科学—桥梁与隧道工程]
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