The continuous strength method for structural stainless steel design

• Published in: Thin-walled structures Vol. 68; pp. 42 - 49
• Main Authors: Afshan, S., Gardner, L.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-07-2013
• Subjects: Continuous strength method; Cross-section classification; Cross-section resistance; Local buckling; Reliability analysis; Stainless steel; Strain hardening; Cross-section classification; Cross-section resistance; Stainless steel; Local buckling; Reliability analysis; Continuous strength method; Strain hardening
• ISSN: 0263-8231; 1879-3223
• DOI: 10.1016/j.tws.2013.02.011

Current stainless steel design standards are based on elastic, perfectly plastic material behaviour providing consistency with carbon steel design expressions, but often leading to overly conservative results, particularly in the case of stocky elements. More economic design rules in accordance with the actual material response of stainless steel, which shows a rounded stress–strain curve with significant strain hardening, are required. Hence, the continuous strength method (CSM) was developed. The CSM replaces the concept of cross-section classification with a cross-section deformation capacity and replaces the assumed elastic, perfectly plastic material model with one that allows for strain hardening. This paper summarises the evolution of the method and describes its recent simplified form, which is now suitable for code inclusion. Comparison of the predicted capacities with over 140 collected test results shows that the CSM offers improved accuracy and reduced scatter relative to the current design methods. The reliability of the approach has been demonstrated by statistical analyses and the CSM is currently under consideration for inclusion in European and North American design standards for stainless steel structures.
► Development of a new method for the design of stainless steel structures, known as the continuous strength method (CSM). ► Collection of stub column and beam test data from a broad spectrum of existing testing programs. ► Comparison of the predicted capacities with collected experimental results. ► Demonstration of the reliability of the approach by means of codified statistical analyses procedures.