GUIDELINES FOR MODELING THREE DIMENSIONAL STRUCTURAL CONNECTION MODELS USING FINITE ELEMENT METHODS

Simple shear (fin plate) connections, which are designed to resist shear loads only, are commonly used in the US. However, as observed in the Cardington large-scale building experiment, these connections carry large compressive forces during the heating phase of a fire that can lead to local buckling of the connecting members (i.e. beam). Further, large tensile forces develop near the connection during the fire decay which can lead to the failure of the connections. The objective of this research is to provide guidelines and address common problems to researchers in modeling three dimensional connection details using commercial finite element software such as ABAQUS. Modeling such FE models, which consists of several parts in contact, requires knowledge in contact mechanics with friction, meshing techniques, matrix solver and stability and convergence algorithms. In recent studies, researchers have made several attempts to model and run double angle (web cleat) or single plate connection models under a given fire load. A general consensus has been difficulty in setting up a proper contact surface configuration and overcoming rigid body motions and convergence problems related to contact and local buckling. With some examples from previous and ongoing research on simple shear connections at Princeton University, we aim to give suggestions on how to improve convergence characteristics of such models by selecting an optimum meshing level near contact areas, using stability methods and matrix solver techniques. Steel connections under fire events have been the least researched yet crucial area in the structural engineering and fire practice. Due to the high cost of conducting experiments of connections in a furnace, the finite element method is a cost-effective way to investigate the strength and behavior of connections under fire. We have observed that contact surfaces with edges or corners create convergence difficulties. Although using an explicit solver might look like a better alternative to an implicit solver for large models, the results from an explicitly solved solution could be unreliable and hence this technique requires careful attention by the user during postprocessing. Since an implicit solver requires the balance of forces for each iteration, the results are inherently stable.