Probabilistic prediction of Load–Displacement curves of corroded strands

This study proposes a probabilistic method for predicting the non-linear mechanical behavior of corroded steel strands. The proposed method follows a four-step process: (1) Developing sophisticated finite element models that accurately represent various types of corrosion; (2) Constructing a multi-s...

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Bibliographic Details
Main Authors: Seungjun Lee, Jaebeom Lee, Chi-Ho Jeon, Young-Joo Lee
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Developments in the Built Environment
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666165925000444
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Summary:This study proposes a probabilistic method for predicting the non-linear mechanical behavior of corroded steel strands. The proposed method follows a four-step process: (1) Developing sophisticated finite element models that accurately represent various types of corrosion; (2) Constructing a multi-surrogate model using Gaussian process regression; (3) Predicting load–displacement curves based on a theoretical model; and (4) Implementing a probabilistic analysis using Monte Carlo simulation and kernel density estimation. Validation was performed through two approaches: (i) scenario-based synthetic simulations of 1000 corrosion cases, and (ii) experimental tensile tests on 39 real-world corroded seven-wire strand specimens. Predictions closely matched experimental results, capturing tensile strength and yield displacement within 99 % prediction bounds for 94.87 % and 89.74 % of specimens, respectively. This framework provides an effective tool for assessing corroded strands, enabling the probabilistic evaluation of prestressed concrete girders and supporting maintenance strategies for corrosion-affected infrastructure.
ISSN:2666-1659