Moving Toward Performance-based Engineering
SAC Steel Project

The SAC (SEAOC - ATC - CUREe) Steel project is a joint venture whose purpose is the development of a performance-based engineering framework for steel moment frame structures. The project builds on earlier efforts such as FEMA 273, but includes new and existing buildings. The target completion date for published guidelines is March 2000. The project considers two performance objectives:

  • Incipient Damage
    - elastic structural response
    -low drifts
  • Incipient Collapse
    - local plastic rotations
    - global instability
    - avoid premature failure modes

Multiple earthquake probabilities are considered: 50%, 10%, and 2% in 50 years. The procedure uses a consistent reliability approach which is described in Hamburger, and was developed and evaluated using a large scale Monte Carlo simulation effort. This procedure couples the treatment of randomness and uncertainty to focus on the confidence of achieving the performance goal during the specified period. The designer and/or owner can select the confidence level desired. Rational load, resistance and bias factors are used to handle various forms of uncertainties.

The basic approach can be stated as:

g1g2g3...gnD < f1f2f3...fnC

or by combining terms and adding the confidence level:

ggconD < fC

This approach is a multi-level design approach, as it provides both:

  • Standard default code approach with specified demand, capacity, and confidence values
  • Explicit methods allowing nonlinear analysis and testing to develop demand and capacity values, or to specify different target confidence levels

Procedure for New Buildings

For new buildings the procedure can be outlined in the following steps:

  • Select performance objective and earthquake probability to be evaluated - e.g. Incipient Collapse and 2% in 50 years
  • Determine design seismic hazard - e.g. spectral displacement at the fundamental period of the building
  • Develop a mathematical model of the building
  • Analyze mathematical model to determine the values of the key design parameters: maximum and permanent interstory drift; column load
  • Apply demand and bias factors to the predicted design parameter values to compensate for the various biases and uncertainties inherent in the predictive methodology as well as the randomness inherent in seismic structural response. Apply additional demand factor to achieve desired confidence level.
  • Compare the factored demand against the factored acceptance criteria value for the design parameter:
    ggconD < fC