Adaptive Maintenance Management Framework for Steel Truss Bridges Subjected to Climate Change-Induced Corrosion

Mutlu Seçer^*, Ali Alper Saylan
Department of Civil Engineering, Izmir Katip Celebi University, Cigli, Izmir, Turkey
* Corresponding Author: Mutlu Seçer. Email: mutlu.secer@ikcu.edu.tr
(This article belongs to the Special Issue: Numerical Modeling in Technical Diagnostics and Predictive Maintenance)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2026.084228

Received 18 April 2026; Accepted 02 July 2026; Published online 20 July 2026

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Abstract

Climate change modifies environmental exposure conditions and affects the corrosion-driven deterioration of steel bridges, thereby challenging conventional maintenance planning approaches. Thus, more advanced maintenance management strategies are required to address the challenges associated with varying corrosion rate projections. In this study, a novel adaptive maintenance management framework is proposed for steel truss bridges to address climate change-induced corrosion under evolving deterioration conditions. Adaptivity is achieved by updating corrosion rates to consider time-varying deterioration conditions associated with climate change. This enables time-dependent representation of corrosion progression under changing environmental conditions. The framework is demonstrated on a benchmark steel truss bridge and applied to two cities with distinct climate-induced corrosion scenarios to capture spatial variability in environmental exposure conditions. Structural performance objectives are defined in terms of preserving load-carrying capacity and limiting joint displacements to maintain the original design throughout the service life. To achieve an economical maintenance strategy, life cycle cost analyses are conducted for different maintenance alternatives under varying corrosion scenarios, incorporating preventive and essential maintenance actions. In addition, the impact of changes in economic and social indicators, specifically the discount rate and the average daily traffic, on the total cost is evaluated within the proposed adaptive framework. Analysis results reveal that lower discount rates and higher average daily traffic rates significantly increase total costs and amplify the economic consequences of climate change-induced corrosion. The results highlight the importance of integrating scenario-based corrosion evolution into adaptive maintenance frameworks for long-term infrastructure management under climate-driven deterioration conditions.