SUMMARYThis paper presents the description, calibration and application of relatively simple hysteretic models that include strength and sti ness deterioration properties, features that are critical for demand predictions as a structural system approaches collapse. Three of the basic hysteretic models used in seismic demand evaluation are modiÿed to include deterioration properties: bilinear, peak-oriented, and pinching. The modiÿed models include most of the sources of deterioration: i.e. various modes of cyclic deterioration and softening of the post-yielding sti ness, and also account for a residual strength after deterioration. The models incorporate an energy-based deterioration parameter that controls four cyclic deterioration modes: basic strength, post-capping strength, unloading sti ness, and accelerated reloading sti ness deterioration. Calibration of the hysteretic models on steel, plywood, and reinforced-concrete components demonstrates that the proposed models are capable of simulating the main characteristics that in uence deterioration. An application of a peak-oriented deterioration model in the seismic evaluation of single-degree-of-freedom (SDOF) systems is illustrated. The advantages of using deteriorating hysteretic models for obtaining the response of highly inelastic systems are discussed.

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SUMMARYPerformance assessment implies that the structural, non-structural, and content systems are given and that decision variables, DVs, (e.g. expected annual loss, mean annual frequency of collapse) are computed and compared to speciÿed performance targets. Performance-based design (PBD) is di erent by virtue of the fact that the building and its components and systems ÿrst have to be created. Good designs are based on concepts that incorporate performance targets up front in the conceptual design process, so that subsequent performance assessment becomes more of a veriÿcation process of an e cient design rather than a design improvement process that may require radical changes of the initial design concept. In short, the design approach could consist of (a) specifying performance targets (e.g. tolerable probability of collapse, acceptable dollar losses) and associated seismic hazards, and (b) deriving engineering parameters for system selection, or perhaps better, using the relatively simple design decision support tools discussed in this paper.

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