Abstract

The present paper reports an in-depth testing and numerical modelling programme, to study the post-fire local buckling behaviour and residual resistances of austenitic stainless steel circular hollow section (CHS) stub columns under combined compression and bending moment. The testing programme employed twelve austenitic stainless steel CHS stub column specimens and included heating and cooling of the stub column specimens, post-fire material testing and post-fire combined loading tests. The testing programme was followed by a numerical modelling programme, where finite element models were developed and validated against the test results and then employed to perform parametric studies to generate additional numerical data. It is worth noting that there are currently no design standards established specifically for stainless steel structures after exposure to fire. In this study, the relevant design rules (i.e. cross-section interaction curves) for stainless steel CHS under combined loading at ambient temperature, as set out in the European, American and Australian/New Zealand standards and given in the continuous strength method, were assessed for their applicability to austenitic stainless steel CHS under combined loading after exposure to fire, based on the obtained test and numerical data. The results of the assessments revealed that all the codified design cross-section interaction curves have certain shortcomings, including the lack of rational exploitation of material strain hardening and the use of linear interaction, and thus yield excessively high degrees of conservatism and scatter when used for austenitic stainless steel CHS under combined loading after exposure to fire. The continuous strength method was shown to lead to accurate and consistent post-fire residual resistance predictions for austenitic stainless steel CHS under combined loading, due principally to the rational consideration of material strain hardening. Finally, the reliability of the continuous strength method was confirmed by means of statistical analyses.

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