基于混合模型的群桩桩顶轴力分布预测
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摘要
结合大体积深水群桩基础在潮汐水文条件影响下群桩桩顶轴力沿平面分布的特性,研究了用来预测桩顶轴力沿平面分布的混合模型一般原理,提出了基于实测数据的混合模型。在某大桥群桩基础的工程实例中,结合了FLAC3D有限差分软件与PSO-SVM方法实现了混合模型的构建。并且将混合模型与RBF模型的预测结果进行了对比。研究表明,混合模型能较精准地刻画大体积群桩基础在运营期间桩顶轴力的分布规律,具有一定的工程应用价值。
Combined with the characteristics of the axial force distribution along the plane of pile cap under the influence of tidal and hydrological conditions, the general principle of the hybrid model used to predict the axial force distribution along the plane of pile cap is studied, and a hybrid model based on the measured data is proposed. In an engineering example of pile group foundation of a bridge, a hybrid model is constructed by combining FLAC3 D finite difference software and PSO-SVM method. The results of hybrid model and RBF model are compared. The reaserch show that the mixed model can accurately depict the distribution law of the axial force on the top of piles during the operation of large-volume pile group foundation, which has certain engineering application value.
Combined with the characteristics of the axial force distribution along the plane of pile cap under the influence of tidal and hydrological conditions, the general principle of the hybrid model used to predict the axial force distribution along the plane of pile cap is studied, and a hybrid model based on the measured data is proposed. In an engineering example of pile group foundation of a bridge, a hybrid model is constructed by combining FLAC3 D finite difference software and PSO-SVM method. The results of hybrid model and RBF model are compared. The reaserch show that the mixed model can accurately depict the distribution law of the axial force on the top of piles during the operation of large-volume pile group foundation, which has certain engineering application value.
引文
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[2]包腾飞,吴中如,顾冲时.基于统计模型与混沌理论的大坝安全监测混合预测模型[J].河海大学学报(自然科学版), 2003,31(5):534-538.
[3] BYON S, NA D, LEE Y. Flow stress equation in range of intermediate strain rates and high temperatures to predict roll force in four-pass continuous rod rolling[J]. Transactions of nonferrous metals society of China, 2013,(3):742-748.
[4]黄伟杰,陈志坚,俞俊平,等.基于PSO-SVM桥梁基础群桩轴力预测[J].低温建筑技术, 2014, 36(10):95-97.
[5]吴中如.混凝土坝安全监控的确定性模型及混合模型[J].水利学报, 1989, 10(5):64-70.
[6] WRAGG P D. Recent blooms of the dinoflagellate Ceratium in Albert Falls Dam(KZN):History, causes, spatial features and impacts on a reservoir ecosystem and its zooplankton[J]. Water SA,2009, 35(4):455-468.
[7] VAPNIK V N. The nature of statistical learning theory[M]. New York:Springer-Verlag, 1995.
[8] SHI Y, EBERHART R C. Empirical study of particle swarm optimization[C]//Proceeding of Congress on Evolutionary Computation.Piscataway, NJ:IEEE Service Center, 1999:1945-1949.
[9]王菲,刘元会,郭建青.粒子群优化算法确定非线性流含水层参数[J].勘察科学技术, 2013,(1):5-7.
[10]高大钊.土质学与土力学:第3版[M].北京:人民交通出版社,2007.