Performance profiles of metallic bridges subject to coating degradation and atmospheric corrosion. Issue 4 (3rd April 2017)

• Record Type: Journal Article
• Authors: Kallias, Alexandros N.; Imam, Boulent; Chryssanthopoulos, Marios K.
• Is Part Of: Structure and infrastructure engineering. Volume 13:Issue 4(2017)
• Page Start: 440
• Page End: 453
• Publication Date: 2017-04-03
• Subjects: Performance profiles -- corrosion -- coatings -- degradation -- metallic bridges; Structural analysis (Engineering) -- Periodicals; Structural engineering -- Periodicals; Buildings -- Performance -- Periodicals; 620.005
• DOI: 10.1080/15732479.2016.1164726
• Languages: English
• ISSNs: 1573-2479

Abstract

Abstract: This study focuses on deterioration modelling and performance assessment of metallic bridges affected by atmospheric corrosion, considering also the contribution of typical protective systems in the form of multi-layer coatings. The mechanisms leading to coating degradation are reviewed and the main coating types used by infrastructure owners are highlighted. Building on information contained in industry manuals, a simple model for coating degradation is proposed. Atmospheric corrosion models are then presented, with emphasis given to exposure classification, in line with corrosivity classification guidelines and recent research quantifying the influence of corrosion through dose–response functions. Coating degradation and corrosion models are integrated into a modelling framework, aimed at producing performance profiles of elements in metallic railway bridges. Finally, the framework is implemented in a case study in which a range of condition and resistance performance criteria are presented for different elements, such as girders and stiffeners, and their constituent parts, such as webs and flanges. It is shown that the proposed methodology is sufficiently detailed to enable differentiated performance predictions based on key external factors, and has scope for improvement, especially as coating and corrosion models are informed by the collection of field data.