Modelling Thermal Performance of Unloaded Spiral Strand and Locked Coil Cables Subject to Pool Fires

Structural cables are used to design critical bridge structures. These are not typically redundant; a loss or compromise of a few cables can lead to the progressive collapse. Previous experimental research has shown that the degradation of material properties and thermal expansion of structural cabl...

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Bibliographic Details
Published inStructural engineering international : journal of the International Association for Bridge and Structural Engineering (IABSE) Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 11
Main Authors Watson, Scott, Nicoletta, Ben, Kotsovinos, Panagiotis, Al Hamd, Rwayda, Gales, John
Format Journal Article
LanguageEnglish
Published Taylor & Francis 02.10.2023
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Summary:Structural cables are used to design critical bridge structures. These are not typically redundant; a loss or compromise of a few cables can lead to the progressive collapse. Previous experimental research has shown that the degradation of material properties and thermal expansion of structural cables is more onerous than the standard carbon prestressing steel. Despite its importance for design no well-validated methodology exists to aid in the thermal performance of structural cables in the event of a fire, particularly for spiral and locked-coil cables which inherently are complex due to their cross-sectional geometry. A state-of-the-art methodology for modelling structural cables' thermal response is presented. The methodology will enable the development of an understanding of the temperature distribution and thermal deformation in a cable cross-section and allow estimation of post-fire resilience. Validation is performed against experiments of locked-coil and spiral cables, subjected to realistic pool fires. The cables range from 22 to 100 mm in diameter and are constructed of galvanized or stainless steel. The cables are modelled undergoing non-linear thermal analysis in LS-DYNA. 2D models are found to provide conservative estimates for critical values such as peak temperature with 90% accuracy, while 3D models provide slightly more conservative estimates.
ISSN:1016-8664
1683-0350
DOI:10.1080/10168664.2022.2101969