Geotechnical data-driven possibility reliability assessment

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. • Step-by-step guidance for practitioners to conduct a novel reliability assessment. • Demonstration using a case study of an axially loaded pile. • The method leverages Big Indirect Databases to promote digitalization in Geotechnical Engineering. • Software is provided to generate data-driven design values. • The method supports both data-driven assessments and reliability-based design.