静力触探识别场地土层分布的贝叶斯学习方法研究

IDENTIFICATION OF SUBSURFACE SOIL STRATIFICATION USING CONE PENETRATION TESTS AND BAYESIAN LEARNING

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageChinese (Simplified)
Pages (from-to)966-972
Journal / Publication工程地质学报
Volume28
Issue number5
Publication statusPublished - Oct 2020

Abstract

静力触探试验 (CPT) 通常是垂直于地表进行的, 用以识别工程场地土层分布情况。实际工程中, 常常由于时间和预算的限制, 工程场地中的 CPT 探测点数量有限且分布稀疏。准确推测CPT探测点之间未测区域的数据和分层情况非常困难。本文提出了一种贝叶斯学习算法来解决这一难题。该方法可使用少量 CPT 探测点来预测二维剖面中土的分类和分层。该方法包括3部分: (1) 使用贝叶斯学习对CPT数据进行二维空间插值 ; (2) 利用Robertson 土性分类图在二维剖面中确定每个位置 (包括已探测和未探测的位置) 土性分类 (SBT); (3) 使用边缘探测方法描绘二维剖面中的土层边界。本方法仅利用少量 CPT 探测点可直接得到表征二维地质剖面的高分辨率CPT数据和土体分类信息, 并自动划定土层边界。本文用模拟算例探讨了该方法的效果。结果表明, 仅使用5个 CPT 探测点的数据即可得到合理的推测结果。此方法可应用于地质信息化研究和城市地下空间建模。
Cone penetration test (CPT) is usually performed vertically to identify subsurface soil stratification.  However, due to time and budget constraints, the number of CPT soundings performed in a site is often limited, leading to a great challenge in properly interpreting CPT data and identifying stratification in unsounded area along horizontal direction.  A Bayesian learning method is presented in this paper to address this difficulty.  The method can predict soil classification and stratification in a two-dimensional (2D) vertical cross-section using a limited number of CPT soundings.  The method consists of three components: (1) 2D interpolation of CPT data using Bayesian learning; (2) determination of soil behavior type (SBT) using Robertson chart at every location in the 2D cross-section, including locations with and without CPT soundings; (3) and soil layer/zone delineation using an edge detection method.  High-resolution CPT data and SBT information in the 2D vertical cross-section can be obtained.  Soil layer/zone boundaries are delineated automatically.  The method is illustrated using a simulated example.  The results suggest that the method performs well even when only five sets of CPT soundings are available.  

Research Area(s)

  • 地质勘察, 静力触探, 机器学习, 压缩感知, 插值方法, Site investigation, Cone penetration test, Machine learning, Compressed sensing, Spatial interpolation