Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions

verfasst von

Yue Hu, Yu Wang, Kok Kwang Phoon, Michael Beer

Abstract

In geotechnical engineering, an appreciation of local geological conditions from similar sites is beneficial and can support informed decision-making during site characterization. This practice is known as “site recognition”, which necessitates a rational quantification of site similarity. This paper proposes a data-driven method to quantify the similarity between two cross-sections based on the spatial variability of one soil property from a spectral perspective. Bayesian compressive sensing (BCS) is first used to obtain the discrete cosine transform (DCT) spectrum for a cross-section. Then DCT-based auto-correlation function (ACF) is calculated based on the obtained DCT spectrum using a set of newly derived ACF calculation equations. The cross-sectional similarity is subsequently reformulated as the cosine similarity of DCT-based ACFs between cross-sections. In contrast to the existing methods, the proposed method explicitly takes soil property spatial variability into account in an innovative way. The challenges of sparse investigation data, non-stationary and anisotropic spatial variability, and inconsistent spatial dimensions of different cross-sections are tackled effectively. Both numerical examples and real data examples from New Zealand are provided for illustration. Results show that the proposed method can rationally quantify cross-sectional similarity and associated statistical uncertainty from sparse investigation data. The proposed method advances data-driven site characterization, a core application area in data-centric geotechnics.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

City University of Hong Kong
Singapore University of Technology and Design
The University of Liverpool
Tongji University

Typ

Artikel

Journal

Engineering geology

Band

331

Anzahl der Seiten

21

ISSN

0013-7952

Publikationsdatum

03.2024

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Geotechnik und Ingenieurgeologie, Geologie

Elektronische Version(en)

https://doi.org/10.1016/j.enggeo.2024.107445 (Zugang: Geschlossen)