Bearing factors of cold-formed stainless steel double shear bolted connections at elevated temperatures

• FEM of cold-formed stainless steel double shear bolted connection was developed.
• FEA results were verified against test results at elevated temperatures.
• Bearing strength was defined based on strains in the bolt hole.
• Parametric study was performed at elevated temperatures.
• Bearing factors were proposed for bolted connections at elevated temperatures.

A numerical investigation on double shear bolted connections of cold-formed stainless steel at elevated temperatures is described in this paper. A finite element model is developed in this study. The model was verified against stainless steel double shear bolted connection tests. It is shown that the finite element model is able to predict the test strengths and failure modes of the connections. Therefore, an extensive parametric study of 225 stainless steel double shear bolted connections at 5 different temperature levels was performed. Based on both the test and numerical results, bearing factors are proposed for the bearing strengths of stainless steel double shear bolted connections at elevated temperatures. Two sets of bearing factors are proposed based on the true plastic strains in the bolt hole and the bolt hole deformation. The connection bearing strengths obtained from the tests and finite element analysis were compared with the nominal strengths calculated using the current American, Australian/New Zealand and European specifications for stainless steel structures as well as the modified design rules in this study. In calculating the nominal strengths of the connections, the material properties of stainless steel obtained at elevated temperatures were used. It is shown that the modified design rules provided more accurate predictions compared to the current design predications for bearing strengths of stainless steel double shear bolted connections at elevated temperatures. The reliability of the current and modified design rules was evaluated using reliability analysis.