Continuing Education

Cyclic Fracture Simulation Framework for Stability and Collapse Simulation in Steel Structures

This paper presents a finite element based framework for direct simulation of cyclic fracture in steel components and connections with application to predict failure and collapse of steel structures. Collapse and failure of steel structures subjected to extreme loads, such as seismic loads, often is preceded by large inelastic deformations that could lead to fracture in components and connections. However, direct simulation of damage and fracture in the performance assessment of steel structures is challenging and it has not been a common practice in prior work. The framework presented combines a plasticity model for large deformations that captures plastic work stagnation and the Bauschinger effect, with a damage model to simulate fracture initiation, propagation and failure through an element deletion strategy. The damage model includes the effects of non-proportional loading and plastic strain history in the fracture initiation and propagation process. Calibration of the model parameters is discussed for common grades of structural steel, weldments and bolts using typical material tests. The framework capabilities are validated against experiments including ancillary material tests, steel components, and subassemblies of steel structures that experienced fracture subjected to monotonic and cyclic loading. This proposed framework provides a robust and valuable tool for stability analysis and simulations of collapse triggered by fracture in components and connections of three-dimensional steel structures subjected to extreme loads.
This SSRC paper, available via the link below, is restricted to members only.
If you haven't already done so, please log in to your AISC member profile or review membership options at
  • Date: 4/10/2018 - 4/13/2018
  • PDH Credits: 0


David A. Padilla-Llano and Jerome F. Hajjar; Northeastern University; Boston, MA; Matthew R. Eatherton and W. Samuel Easterling; Virginia Tech; Blacksburg, VA; Benjamin W. Schafer; Johns Hopkins University; Baltimore, MD

View Content