文章基本信息

标题：Prediction of Penetration Resistance of a Spherical Penetrometer in Clay Using Multivariate Adaptive Regression Splines Model
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作者：Sayan Sirimontree ; Thira Jearsiripongkul ; Van Qui Lai 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2022
卷号：14
期号：6
页码：3222
DOI：10.3390/su14063222
语种：English
出版社：MDPI, Open Access Journal
摘要：This paper presents the technique for solving the penetration resistance factor of a spherical penetrometer in clay under axisymmetric conditions by taking the adhesion factor, the embedded ratio, the normalized unit weight, and the undrained shear strength into account. The finite element limit analysis (FELA) is used to provide the upper bound (UB) or lower bound (LB) solutions, then the multivariate adaptive regression splines (MARS) model is used to train the optimal data between input and output database. The accuracy of MARS equations is confirmed by comparison with the finite element method and the validity of the present solutions was established through comparison to existing results. All numerical results of the penetration resistance factor have significance with three main parameters (i.e., the adhesion factor, the embedded ratio, the normalized unit weight, and the undrained shear strength). The failure mechanisms of spherical penetrometers in clay are also investigated, the contour profiles that occur around the spherical penetrometers also depend on the three parameters. In addition, the proposed technique can be used to estimate the problems that are related or more complicated in soft offshore soils.