基于CPTU数据融合技术的黏性土应力历史与强度特性评价研究
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摘要
超固结比(OCR)和不排水抗剪强度(S_u)是土的基本力学参数,对土体沉降变形分析和稳定性计算具有重要影响。采用数据融合技术,结合孔压静力触探(CPTU)测试数据,提出了江苏典型黏性土超固结比和不排水抗剪强度的预测模型。利用特征级数据融合技术(回归树、模型树)与决策级数据融合技术(自举聚合、堆叠泛化)对预测模型的可行性进行分析。将土的超固结比和不排水抗剪强度的预测值、室内试验所得到的参考值以及CPTU传统方法所得到的估计值进行对比分析。结果表明,模型树预测结果比回归树要好,决策级融合算法可以提高回归树的预测结果,但对模型树的预测结果影响较小;叠加回归树和模型树的预测结果会使其预测的不排水抗剪强度比回归树预测的结果要好,但比模型树预测的结果要差;对于几种数据融合模型,OCR预测值大致相当,回归树模型在预测OCR方面稍优于其他数据融合模型,数据融合技术能更好地预测土的超固结比和不排水抗剪强度。
The overconsolidation ratio(OCR) and the undrained shear strength(S_u) are the basic mechanical parameters of soils,which can influence the deformation analysis and strength calculation of soils. A prediction model for OCR and S_u of typical clay in Jiangsu Province is proposed by using the data fusion technique and the data of piezocone penetration test(CPTU). The feasibility of the prediction model is analyzed by using the feature-level data fusion techniques(regression tree, model tree) and decision-level data fusion techniques(bagging, stacking). The predicted OCR and S_u, the reference values obtained by the laboratory tests and the estimated values obtained by the existing calculation methods are compared and analyzed. The results show that the predicted results of the model tree are better than those of the regression tree. The decision and fusion algorithms can improve the predicted results of the regression tree, but they have little influences on the predicted results of the model tree.The superimposed regression tree and model tree can make the predicted S_u better than that of the regression tree, but worse than that of the model tree. For several data fusion models, the predicted OCR is approximately close. The regression tree model is slightly better than other data fusion models in predicting the OCR. Compared with other prediction methods, the data fusion model can better predict the OCR and S_u.
The overconsolidation ratio(OCR) and the undrained shear strength(S_u) are the basic mechanical parameters of soils,which can influence the deformation analysis and strength calculation of soils. A prediction model for OCR and S_u of typical clay in Jiangsu Province is proposed by using the data fusion technique and the data of piezocone penetration test(CPTU). The feasibility of the prediction model is analyzed by using the feature-level data fusion techniques(regression tree, model tree) and decision-level data fusion techniques(bagging, stacking). The predicted OCR and S_u, the reference values obtained by the laboratory tests and the estimated values obtained by the existing calculation methods are compared and analyzed. The results show that the predicted results of the model tree are better than those of the regression tree. The decision and fusion algorithms can improve the predicted results of the regression tree, but they have little influences on the predicted results of the model tree.The superimposed regression tree and model tree can make the predicted S_u better than that of the regression tree, but worse than that of the model tree. For several data fusion models, the predicted OCR is approximately close. The regression tree model is slightly better than other data fusion models in predicting the OCR. Compared with other prediction methods, the data fusion model can better predict the OCR and S_u.
引文
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[18]CAI G,LIU S,PUPPALA A J.Comparison of CPT charts for soil classification using PCPT data:example from clay deposits in Jiangsu Province,China[J].Engineering Geology,2011,121(1/2):89-96.
[19]ZOU H,LIU S,CAI G,et al.Multivariate correlation analysis of seismic piezocone penetration(SCPTU)parameters and design properties of Jiangsu quaternary cohesive soils[J].Engineering Geology,2017,228(1/2):11-38.
[20]LIU H,MOTODA H.Feature extraction,construction and selection:a data mining perspective[M].Amsterdam:Kluwer Academic Publishers,1998.
[21]CHEN B S Y,MAYNE P W.Statistical relationships between piezocone measurements and stress history of clays[J].Canadian Geotechnical Journal,1996,33(3):488-498.
[2]周四望,林亚平,聂雅琳,等.无线传感器网络中基于数据融合的移动代理曲线动态路由算法研究[J].计算机学报,2007(6):894-904.(ZHOU Si-wang,LIN Ya-ping,NIEYa-lin,et al.A study of trajectory-based mobile agent dynamic routes algorithm for data fusion in wireless sensor networks[J].Chinese Journal of Computers,2007(6):894-904.(in Chinese))
[3]刘明贵,杨永波.信息融合技术在边坡监测与预报系统中的应用[J].岩土工程学报,2005,27(5):607-610.(LIUMing-gui,YANG Yong-bo.Application of information fusion in slope monitoring and prediction system Chinese[J].Chinese Journal of Geotechnical Engineering,2005,27(5):607-610.(in Chinese))
[4]GRIFFIN E P,KURUP P U.Prediction of OCR and su from PCPT data using tree-based data fusion techniques[J].Journal of Geotechnical and Geoenvironmental Engineering,2017,143(9):04017045.
[5]陈昌彦,王思敬,沈小克.边坡岩体稳定性的人工神经网络预测模型[J].岩土工程学报,2001,23(2):157-161.(CHEN Chang-yan,WANG Si-jing,SHEN Xiao-ke.Predicting models to estimate stability of rock slope based on artificial neural network[J].Chinese Journal of Geotechnical Engineering,2001,23(2):157-161.(in Chinese))
[6]赵忠杰,田梅.数据融合技术在公路隧道火灾探测中的应用[J].西安科技大学学报,2007,23(3):435-438.(ZHAO Zhong-jie,TIAN Mei.Application of data fusion technology to highway tunnels fire detection[J].Journal of Xi'an University of Science and Technology,2007,23(3):435-438.(in Chinese))
[7]刘松玉,蔡国军,邹海峰.基于CPTU的中国实用土分类方法研究[J].岩土工程学报,2013,35(10):1765-1776.(LIU Song-yu,CAI Guo-jun,ZOU Hai-feng.Practical soil classification methods in China based on piezocone penetration tests[J].Chinese Journal of Geotechnical Engineering,2013,35(10):1765-1776.(in Chinese))
[8]SENNESET K,JANBU N,SVANO G.Strength and deformation parameters for CPT[C]//Proceedings of the 2nd European Symposium on Penetration Testing,Amsterdam,1982:863-870.
[9]LUNNE T,CHRISTOFFERSEN H P,TJELTA T I.Engineering use of piezocone data in North Sea clays[C]//Proceedings of the 11th International Conference on Soil Mechanics and Foundation Engineering.Rotterdam,1985.
[10]TONG L,WANG Q,DU G,et al.Determination of undrained shear strength using piezocone penetration test in clayey soil for bridge foundation[J].Journal of Southeast University,2011,27(2):201-205.
[11]LI X,CAI G,LIU S,et al.Undrained shear strength and pore pressure changes due to prestress concrete pile installation in soft clay[J].International Journal of Civil Engineering,2019,17(2):193-203.
[12]MAYNE P W.Determination of OCR in clays by piezocone tests using cavity expansion and critical state concepts[J].Soils and Foundations,1991,31(2):65-76.
[13]CHEN B S Y,MAYNE P W.Profiling the OCR of clays by piezocone tests tests[R].Atlanta:Georgia Institute of Technology,1994.
[14]刘松玉,蔡国军,童立元,等.基于CPTU测试的先期固结压力确定方法试验研究[J].岩土工程学报,2007,29(4):490-495.(LIU Song-yu,CAI Guo-jun,TONG Li-yuan,et al.On preconsolidation pressure of clays from piezocone tests[J].Chinese Journal of Geotechnical Engineering,2007,29(4):490-495.(in Chinese))
[15]LUNNE T,ROBERTSON P K,POWELL J M.Cone penetration testing in geotechnical practice[M].London:Blackie Academic&Professional,1997:16-24.
[16]HALL D L,MCMULLEN S A H.Mathematical techniques in multi-sensor data fusion[M].Boston:Artech House,2004.
[17]CAI G,PUPPALA A J,LIU S.Characterization on the correlation between shear wave velocity and piezocone tip resistance of Jiangsu clays[J].Engineering Geology,2014,171(13):96-103.
[18]CAI G,LIU S,PUPPALA A J.Comparison of CPT charts for soil classification using PCPT data:example from clay deposits in Jiangsu Province,China[J].Engineering Geology,2011,121(1/2):89-96.
[19]ZOU H,LIU S,CAI G,et al.Multivariate correlation analysis of seismic piezocone penetration(SCPTU)parameters and design properties of Jiangsu quaternary cohesive soils[J].Engineering Geology,2017,228(1/2):11-38.
[20]LIU H,MOTODA H.Feature extraction,construction and selection:a data mining perspective[M].Amsterdam:Kluwer Academic Publishers,1998.
[21]CHEN B S Y,MAYNE P W.Statistical relationships between piezocone measurements and stress history of clays[J].Canadian Geotechnical Journal,1996,33(3):488-498.
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