Project Title/ID Number Engineering Assessment Methodology—3192002
Start/End Dates 10/1/02—9/30/03
Project Leader Helmut Krawinkler (Stanford/Faculty)
Team Members Ricardo Medina (Stanford/Grad Student), Luis Ibarra Olivas (Stanford/Grad Student), Farzin Zareian (Stanford/Grad Student), Christoph Adam (Stanford/Grad Student)
Project goals and objectives

The objective is to develop quantitative information and simplified procedures that permit approximate performance assessment by means of commonly employed engineering analysis methods. Performance is expressed in terms of confidence levels and mean annual frequencies of exceedance of selected performance parameters (collapse, story drifts, inelastic deformations, and selected damage measures). The expected outcomes of the research are information and procedures that will assist the engineering profession in carrying out performance assessment with currently available tools and with tools that are under development by the research community.

Role of this project in supporting PEER’s vision

PEER’s past efforts have focused on a rigorous performance assessment methodology, with an emphasis on the probabilistic evaluation of decision variables associated with discrete limit states (e.g., collapse) or with losses and downtime. This rigorous approach may be too complex for most of the performance assessment tasks encountered in engineering practice (at least in the near future). It is the subject of this research to develop quantitative information and simplified procedures for an engineering approach to performance assessment.

Methodology employed

This research builds on the knowledge and information generated by the PI and other investigators within and outside PEER. In the context of the PEER framework equation, the work focuses on IM-EDP-DM relationships. Evaluation of decision variables (DVs) is not within the scope, except for the assessment of global collapse.

The research will consist of extensive simulations, synthesis of simulation results, assessment of uncertainties, derivation of bias factors for standard engineering analysis methods, development of EDP and DM hazard curves, and development of simplified procedures for performance assessment that are based on standard engineering analysis methods but account for important sources of uncertainty.

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Brief description of past year’s accomplishments and more detail on expected Year 6 accomplishments

This research is continuation of the work performed in Year 5 under the same project title. Previously, a comprehensive set of EDP values for different generic frame structures at different hazard levels has been evaluated using incremental dynamic analysis. The results have been stored in a database for easy and systematic access. Figure 1 shows a typical graph illustrating the variation of maximum interstory drift over height, an EDP, with Sa(T1)/g, an IM, for a 9 story generic frame.

This year it is intended to complete this database by introducing generic frames with vertical irregularities and wall structures with a variety of structural properties. These new systems along with the previously evaluated generic frame structures provide a comprehensive spectrum of representative structures, which will allow us to generalize the simplified procedures developed in this project for performance assessment and uncertainty propagation.


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Another task is testing and implementing procedures that help us track the dispersion in EDPs and DMs, and evaluating the sensitivity of EDPs to ground motion randomness and modeling uncertainties. So far we are using a First Order Second Moment (FOSM) approach, but we may also utilize other reliability methods (FORM and full Monte Carlo simulation).

Along with the aforementioned tasks, derivation of bias factors and dispersion in EDP and DM predictions using standard engineering analysis methods is another major goal of this project. These methods include linear static procedure (LSP), Linear Dynamic Procedure (LDP), Nonlinear Static Procedure (NSP), and Nonlinear Dynamic Procedure (NDP) using an equivalent SDOF system. Figure 2 shows representative results of the difference in interstory drift prediction between the results from nonlinear time history and pushover analyses, NSP, for a nine-story generic frame structure.

Other similar work being conducted within and outside PEER and how this project differs

The development of engineering approaches to performance assessment has been addressed by many researchers worldwide. In the US, the ATC-33 project (resulting in the FEMA 273 report), the SEAOC Vision 2000 project, the ATC-40 project, and the FEMA SAC program are representative examples of past work in this area. New work on this subject has started in the ATC-55 and ATC-58 projects and in a CERL project. Much work is being performed also in foreign countries, for instance in the multi-year performance-based design effort by the Building Research Institute in Japan and the effort by European Community researchers in the multi-institutional project SAFER.

Plans for Year 7 if this project is expected to be continued

Describe any instances where you are aware that your results have been used in industry

It is expected that the results of this study will be used extensively in industry, but first the results will have to be documented in a final project report.

Expected milestones
  1. Quantification of the sensitivity of EDPs and DMs to customary engineering analysis procedures (elastic static, elastic dynamic, and inelastic pushover)
  2. Quantification of representative EDP hazard curves and DMs for frame and wall structures.
  3. Quantification of collapse fragility curves and collapse probabilities for regular frame and wall structures.
  4. Assessment of the importance of various sources of uncertainty in the EDP and DM hazard curves.

Development of simplified procedures for performance assessment (in terms of confidence levels or of mean annual frequencies of exceedance of selected performance parameters [collapse, story drifts, inelastic deformations, and selected damage measures for structural, nonstructural, and content damage].


The deliverables include written documentation of the results of each milestone, databases of results wherever appropriate, and modeling and analysis tools to facilitate implementation of performance assessment in engineering practice.