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Report - PEER - University of California, Berkeley

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An efficient demand model relating maximum displacement U max (or drift ratio)and Sa(T 1 ) is used in the last term <strong>of</strong> the kern in Equation 7. The middle term inEquation 7 is derived using simulation (Mackie 2004b). The first kern term inEquation 7 was computed in Method B. Using a DV limit state <strong>of</strong> 25% <strong>of</strong> trafficvolume reduction, the four methods are compared in Figure 6. The values <strong>of</strong> ζ, thelognormal parameter that describes the dispersion <strong>of</strong> the model, <strong>of</strong> the four methodsare 0.96, 0.80, 0.73, and 0.46, respectively. Therefore, while even Method D hasfairly high uncertainty, its prediction <strong>of</strong> the median value is better than the directapplication <strong>of</strong> Equation 5.Figure 6. Comparison <strong>of</strong> Methods A through D for decision fragilities.6. COLLAPSE-RELATED DECISIONThe collapse-prevention limit state used in this paper is a combination <strong>of</strong> the loss <strong>of</strong>lateral and vertical load capacity limit states shown in Table 1 (Mackie 2004a). Abridge would be considered closed, i.e., in collapse-prevention limit state, if thelateral load carrying capacity had been reduced by 25% or the vertical load carryingcapacity had been reduced by 50%. Thus, the remaining traffic volume crossing thisbridge is zero. These values are used as an example and will be changed once moredata becomes available. The damage fragility surfaces lateral (longitudinal) andvertical directions are presented in (Mackie 2004b). For the purposes <strong>of</strong> this example,the direct method (Method A) was used in order to maintain consistency between thelateral and vertical directions. Both <strong>of</strong> the limit states are plotted in Figure 7 alongwith the probability <strong>of</strong> closure, defined as the union <strong>of</strong> the two damage limit states.The probability <strong>of</strong> the union was approximated as a series system with thecorrelation coefficient computed using the response load carrying data for the lateraland vertical directions. As would be expected, the correlation (ρ = 0.85) betweenvertical and lateral loss <strong>of</strong> load carrying capacity is high. The probability was62

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