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Predicting triaxial compressive strength of high-temperature treated rock using machine learning techniques

Journal of Rock Mechanics and Geotechnical Engineering 2023年第8期15卷 2072-2082页

作者： Xunjian Hu Junjie Shentu Ni Xie Yujie Huang Gang Lei Haibo Hu Panpan Guo Xiaonan Gong Research Center of Coastal and Urban Geotechnical Engineering Zhejiang UniversityHangzhou310058China Faculty of Engineering China University of Geosciences(Wuhan)Wuhan430074China School of Mechanical Engineering North University of ChinaTaiyuan030051China Beijing Urban Construction Design and Development Group Co. Ltd.Beijing100037China

The accurate prediction of the strength of rocks after high-temperature treatment is important for the safety maintenance of rock in deep underground engineering.Five machine learning(ML)techniques were adopted in this study,i.***.back propagation neural network(BPNN),AdaBoost-based classification and regression tree(AdaBoost-CART),support vector machine(SVM),K-nearest neighbor(KNN),and radial basis function neural network(RBFNN).A total of 351 data points with seven input parameters(i.***.diameter and height of specimen,density,temperature,confining pressure,crack damage stress and elastic modulus)and one output parameter(triaxial compressive strength)were utilized.The root mean square error(RMSE),mean absolute error(MAE)and correlation coefficient(R)were used to evaluate the prediction performance of the five ML models.The results demonstrated that the BPNN shows a better prediction performance than the other models with RMSE,MAE and R values on the testing dataset of 15.4 MPa,11.03 MPa and 0.9921,respectively.The results indicated that the ML techniques are effective for accurately predicting the triaxial compressive strength of rocks after different high-temperature treatments.

关键词： Machine learning(ML) Triaxial compressive strength Temperature Confining pressure crack damage stress

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Analysis of the stress ratio of anisotropic rocks in uniaxial tests

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International Journal of Mining Science and Technology 2017年第3期27卷 531-535页

作者： Wang Miaomiao Li Pei Wu Xiaowa Xu Dan Key Laboratory of Shale Gas and Geoengineering Institute of Geology and Geophysics Chinese Academy of Sciences Beijing 100029 China Institute of Geomechanics Chinese Academy of Geological Sciences Beijing 100081 China

The effect of structural discontinuities on the progressive failure process of anisotropic rocks should be paid particular attention.The crack damage stress σ_(cd),also considered as the yield strength,and the relationship between σ_(cd) and the uniaxial peak strength σ_(ucs) of anisotropic rocks for different orientations 8 of the isotropy planes with respect to the loading directions were investigated theoretically and experimentally.A theoretical relation of σ_(cd)/σ_(ucs) with the function of the shape parameter m was established.Additionally,uniaxial compression tests of shale samples were conducted for several inclinations θ.The test result of σ_(cd)/σ_(ucs) was close to the theoretical value for a given orientation.Furthermore,both experimental results and theoretical solutions of σ_(cd)/σ_(ucs) were independent of the inclination θ while σ_(cd) andσ_(ucs) were strongly affected by θ.The strength ratio σ_(cd)/σ_(ucs) may therefore be an intrinsic property of anisotropic rocks and could be used to predict the failure of rock samples.

关键词： Anisotropic rocks Uniaxial compression test Brittle failure crack damage stress stress ratio

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