PSI - Issue 78

Available online at www.sciencedirect.com

ScienceDirect

Procedia Structural Integrity 78 (2026) 513–520

© 2025 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 XX ANIDIS Conference organizers Keywords: braking force; traffic data; WIM data; probabilistic approach; Monte Carlo simulation Abstract This study proposes a probabilistic methodology for assessing horizontal braking forces induced by vehicular traffic on bridges, addressing the limitations of traditional deterministic models commonly adopted in structural design codes. The proposed approach leverages Weight-In-Motion (WIM) data collected from a provincial road to derive probabilistic distributions of vehicle characteristics, including gross mass, length, and inter-vehicle distance. Through extensive Monte Carlo simulations, realistic traffic convoys are synthesized, incorporating variable deceleration profiles informed by naturalistic driving datasets. The resulting probabilistic braking force model allows estimation of demand levels associated with defined return periods and bridge span lengths, consistent with modern reliability-based design frameworks. Comparative analyses indicate that, depending on span and return period, conventional code-based models may either underestimate or overestimate braking demands. To support practical implementation, simplified equations are also proposed for different design scenarios. The methodology provides a robust tool for the safety assessment and design of bridges subjected to stochastic traffic actions, particularly relevant for both new constructions and the evaluation of existing infrastructure. XX ANIDIS Conference Data-driven probabilistic braking force model for existing bridges using WIM traffic records Amirmahmoud Behzadi a, 0F *, Simone Celati b , M ichele D’Amato a , Agnese Natali b , Walter Salvatore b a Department for Humanistic, Scientific and Social Innovation (DIUSS), University of Basilicata, Via Lanera 20, Matera 75100, Italy b Department of Civil and Industrial Engineering (DICI), University of Pisa, Largo Lucio Lazzarino 2, Pisa 56126, Italy

* Corresponding author. Tel.: +39-345-057-6663. E-mail address: amirmahmoud.behzadi@unibas.it

2452-3216 © 2025 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 XX ANIDIS Conference organizers 10.1016/j.prostr.2025.12.066