Work

Geotechnical data-driven possibility reliability assessment

Year: 2025

Type: article

Abstract: Managing scarce, incomplete, or corrupted data is a persistent challenge in geotechnical engineering, often leading to conservative designs. However, the ongoing digitalization has enabled access to large, national-scale databases of indirect geotechnical data containing both qualitative and quantitative information, which can be exploited to support optioneering, site characterization, and design. Based on a newly proposed concept of possibilistic data-driven reliability, this Technical Note outlines a practical, fast, and accessible implementation procedure that does not require specialized expertise. Step-by-step guidance is provided for reliability-based assessment and design of geotechnical problems, ensuring consistency with standard code safety prescriptions. The procedure demonstrates how to utilize possibility distributions generated from Big Indirect Databases managed by third-party administrators, such as the British Geological Survey, to derive design input values for deterministic evaluations of geotechnical capacity or limit state domains. Engineering judgement is rigorously incorporated through a three-tier ‘degree of understanding’ framework worked example of an axially-loaded pile in bilayer soil, characterized using cone penetration test data, is also provided.

Source: Computers and Geotechnics

DOI: 10.1016/j.compgeo.2025.107311

Authors: Alessandro Tombari, Luciano Stefanini, Giovanni Li Destri Nicosia, Liam M.J. Holland, Marcus Dobbs

Institutions: University of Exeter, University of Urbino, Cowi (Denmark), British Geological Survey

Language: English

Topic: Geotechnical Engineering and Analysis

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,640