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作 者:Zida Liu Diyuan Li Yongping Liu Bo Yang Zong-Xian Zhang
机构地区:[1]School of Resources and Safety Engineering,Central South University,Changsha,410083,China [2]Nickel Cobalt Research and Design Institute,Jinchuan Group Co.,Ltd.,Jinchang,737104,China [3]Oulu Mining School,University of Oulu,Oulu,Finland
出 处:《Rock Mechanics Bulletin》2023年第4期56-69,共14页岩石力学通报(英文)
基 金:supported by the National Natural Science Foundation of China (No.52374153 and No.52074349);the Fundamental Research Funds for the Central Universities of Central South University (No.2023zzts0726).
摘 要:Uniaxial compressive strength(UCS)of rock is an essential parameter in geotechnical engineering.Point load strength(PLS),P-wave velocity,and Schmidt hammer rebound number(SH)are more easily obtained than UCS and are extensively applied for the indirect estimation of UCS.This study collected 1080 datasets consisting of SH,P-wave velocity,PLS,and UCS.All datasets were integrated into three categories(sedimentary,igneous,and metamorphic rocks)according to lithology.Stacking models combined with tree-based models and linear regression were developed based on the datasets of three rock types.Model evaluation showed that the stacking model combined with random forest and linear regression was the optimal model for three rock types.UCS of metamorphic rocks was less predictable than that of sedimentary and igneous rocks.Nonetheless,the proposed stacking models can improve the predictive performance for UCS of metamorphic rocks.The developed predictive models can be applied to quickly predict UCS at engineering sites,which benefits the rapid and intelligent classification of rock masses.Moreover,the importance of SH,P-wave velocity,and PLS were analyzed for the estimation of UCS.SH was a reliable indicator for UCS evaluation across various rock types.P-wave velocity was a valid parameter for evaluating the UCS of igneous rocks,but it was not reliable for assessing the UCS of metamorphic rocks.
关 键 词:Uniaxial compressive strength Point load strength P-wave velocity Schmidt hammer rebound number Stacking models
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