Develop Predictive Inelastic Models for Building Performance

Principal Investigator: Gary Hart 
University of California at Los Angeles 

    A systematic evaluation and development of nonlinear methods for performance prediction and evaluation of steel moment frame buildings will be conducted with the following objectives: 

- Determine the reliability of available nonlinear methods for predicting local and system strength and deformation demands for various performance goals or limit states. Develop bias coefficients for each nonlinear method in accordance with the reliability framework established for the SAC Phase 2 project. Instructions on how to develop these coefficients will be provided to the Investigator by the Team Leader. 

- Modify, if needed, these nonlinear methods to obtain and enhance the capability of these procedures to provide accurate performance prediction. 

- Based on results from previous work and other efforts within the SAC Phase 2 Project, evaluate the ability of the nonlinear procedures to predict the location of fractured beam-column connections. This evaluation will be based on comparison between predicted and observed behavior from case studies of actual buildings that have been objected to strong earthquake ground motions. 

- In conjunction with other SAC Phase 2 investigators and the Performance Prediction and Evaluation Technical Advisory Panel (TAP), develop specific information for incorporation into both the State of the Art Report on Performance Prediction and Evaluation and the Seismic Design Criteria for Steel Moment Frames. 

Detailed Workstatement: 

The detailed breakdown of the technical activities in this task are provided in the workstatement available here.