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    Physics-Informed Explainable AI and SMOTE-GPC for the Classification of Surrounding Rock Mass in Tunneling 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2025:;Volume ( 011 ):;issue: 002:;page 04025021-1
    Author(s): Chao Song; Tengyuan Zhao; Ling Xu
    Publisher: American Society of Civil Engineers
    Abstract: The classification of surrounding rock mass is essential for characterizing rock properties and geological conditions in tunneling engineering. While numerous empirical rock mass classification systems have been proposed ...
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    Simulation of Random Fields with Trend from Sparse Measurements without Detrending 

    Source: Journal of Engineering Mechanics:;2019:;Volume ( 145 ):;issue: 002
    Author(s): Yu Wang; Tengyuan Zhao; Yue Hu; Kok-Kwang Phoon
    Publisher: American Society of Civil Engineers
    Abstract: Although spatially varying quantities in real life (e.g., mechanical properties of soils) often contain a linear or nonlinear trend, stationary random fields with zero trend are often used to model these quantities ...
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    Bayesian Supervised Learning of Site-Specific Geotechnical Spatial Variability from Sparse Measurements 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2020:;Volume ( 006 ):;issue: 002
    Author(s): Yue Hu; Yu Wang; Tengyuan Zhao; Kok-Kwang Phoon
    Publisher: ASCE
    Abstract: Although the properties of geomaterials vary spatially, geotechnical site investigations often take sparse measurements from a limited number of locations. To estimate geotechnical properties at unsampled locations, ...
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