PSI - Issue 84

Available online at www.sciencedirect.com

ScienceDirect

Procedia Structural Integrity 84 (2026) 1255–1263

© 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference Keywords: half-joint; strut-and-tie model; Monte Carlo simulation; uncertainty quantification; reinforced concrete; existing structures. 1. Introduction Reinforced concrete half-joints (also known as dapped ends or Gerber saddles) were widely used in bridge construction during the 1950s–1960s due to their ease of prefabrication, insensitivity to differential settlement and Abstract Existing reinforced concrete half-joints are susceptible to deterioration and brittle failure, yet current deterministic assessment methods neglect critical uncertainties in material properties, loading, and resistance modeling. This study presents a probabilistic framework combining Strut-and-Tie Models (STM) with Monte Carlo Simulation (MCS) to assess half-joint capacity. Four STM configurations (A, B, AB, and C) representing distinct load-transfer mechanisms were evaluated. Probabilistic analysis incorporated uncertainties in concrete strength, steel yield strength, applied loads, and model assumptions. Results identify STM AB as providing the most reliable capacity prediction. The integrated STM-MCS framework offers a practical tool for assessing existing half-joints, enabling engineers to quantify capacity while accounting for inherent variabilities. III Fabre Conference: Existing Bridges, Viaducts, and Tunnels: Research, Innovation, and Applications Probabilistic capacity assessment of RC half-joints using Monte Carlo simulation and strut-and-tie modeling Biruk Yenehun Lemlem a , Lorenzo Hofer a , Flora Faleschini a , Carlo Pellegrino a , Mariano Angelo Zanini a, * a Department of Civil, Environmental and Architectural Engineering, University of Padova, Padova, Italy

* Corresponding author. Tel.: +393282867447. E-mail address: marianoangelo.zanini@unipd.it

2452-3216 © 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference 10.1016/j.prostr.2026.06.160