Benchmark examples for data-driven site characterisation

ABSTRACT

Decision making in geotechnical engineering is always related to a project carried out at a specific site. It is natural for data-driven site characterization (DDSC) to attract the most attention in data-centric geotechnics. This paper proposed eight benchmark examples and a benchmarking procedure to support unbiased and competitive evaluation of emerging ML methods. The primary goal of DDSC is to bring the value of a “data first” agenda to practice, specifically to produce a 3D stratigraphic map of the subsurface volume below a full-scale project site and to estimate relevant engineering properties at each spatial point based on site investigation data and other relevant Big Indirect Data (BID). A reasonable full-scale ground 20 m long × 20 m wide × 10 m deep is adopted. Virtual grounds containing horizontal, inclined, or discontinuous soil layers and spatially varying synthetic cone penetration test data are created to test the performance of DDSC methods over a range of ground conditions. A benchmark example is defined by a combination of a virtual ground (“reality”) and a training dataset (measured “reality”). An additional benchmark example based on actual CPT data is included to check whether performance under virtual ground conditions holds under real ground conditions.

KEYWORDS:

• data-driven site characterisation (DDSC)
• benchmark examples
• data-centric geotechnics
• virtual ground
• GLasso

Acknowledgements

This paper was presented as a keynote lecture at the 2nd TC304 Forum on Georisk Assessment and Management: Data-driven modelling for geotechnical spatial variability, 3 July 2021, organised by the ISSMGE Technical Committee of Engineering Practice of Risk Assessment & Management (TC304) and Advanced Retrofit Technology Center, Tokyo City University, and supported by the Tokyo City University and Japanese Geotechnical Society (JGS). The first author is grateful to the Forum co-chairs, Professor Ikumasa Yoshida and Takayuki Shuku, for the gracious invitation. The authors would like to thank the members of the TC304 Committee on Engineering Practice of Risk Assessment & Management of the International Society of Soil Mechanics and Geotechnical Engineering for developing the database 304 dB (http://140.112.12.21/issmge/Database_2010.htm) used in this study and making it available for scientific inquiry.

Disclosure statement

No potential conflict of interest was reported by the author(s).