Year: 2026
Type: article
Abstract: The aging of infrastructure necessitates a robust and rational methodology for the assessment of existing structures. Design codes provide general models which cover different design scenarios and are thus overly conservative. Also, such design approaches lack field data and, if applied directly to existing works, often lead to unnecessarily expensive retrofits or pre‐mature decommissioning of in‐service assets. This paper presents a comprehensive, data‐driven framework for tailored assessment of the design resistance of existing structures. Central to this approach is the role of field measurements, comprising not only material and geometrical data, but also structural response. This allows considering Bayesian inference to combine a priori knowledge and actual structural update on the reliability analysis. On that basis, the potential of splitting the model uncertainty is highlighted, particularly if governing and if it can be updated by site testing. This approach is applied to a real case in which failure tests were performed on existing prestressed girders. To that aim, several Levels‐of‐Approximation for structural analysis and reliability formats are investigated to determine the design values of the failure resistance. As a result, a series of practical conclusions is drawn, providing engineers with a pragmatic tool for making informed decisions on structural safety.
Source: Structural Concrete
DOI: 10.1002/suco.70754
Authors: Miguel Fernández Ruiz, Peter Tanner, Nicola Tarque Ruiz, Binbin Zhou, Duarte Viula Faria
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,820
Awards: G4121795456, G480849290
OpenAlex ID: W7204274095