Report - PEER - University of California, Berkeley
Report - PEER - University of California, Berkeley Report - PEER - University of California, Berkeley
in predicting damage as well as repair method given an EDP. The steps in thedevelopment process are discussed in the following sections.4.1 Damage versus EDPExperimental data characterizing the progression of damage for the test specimenswere used to generate data sets linking the thirteen damage states with the threeprimary EDPs: drift, number of load cycles and joint shear strain. The functionalEDPs, defined by Eq. 2 and Eq. 3, were calibrated to minimize the dispersion of thedata for all damage states about a line spanning the range of damage states andfunctional values from 0 to 1. Figure 1 shows damage-EDP data for the five EDPs.121212Damage State108642108642108642000.0 2.0 4.0 6.00 10 20 30 40 5000.00 0.02 0.04 0.06 0.08 0.10 0.12(a) drift (b) number of cycles (c) joint shear strain1212Damage State10864210864200.0 0.2 0.4 0.6 0.8 1.0 1.200.0 0.2 0.4 0.6 0.8 1.0 1.2(d) F(D,N) per Eq. 2 (e) F(γ,N) per Eq. 3Figure 1. Damage versus EDP.The scatter of the data in Figure 1 reinforces the need for probabilistic modelslinking EDPs with damage and repair. The variability in these data is due in part tovariability in test specimen design and loading; however, it is due also to the datacollection procedures used in the laboratory. The typical procedure used in earthquaketesting in the laboratory is as follows:1. A half-cycle of loading to a new maximum displacement demand, at whichpoint loading is paused to allow for identification of new cracks and regionsof spalling, measurement of new and existing cracks and picture taking.216
2. Loading in the reversed direction to a new minimum displacement demand,at which point loading is paused to allow for data collecting as above.3. Multiple additional full load cycles, typically two additional cycles, to thenew maximum and minimum displacement demand levels.Thus, in monitoring the progression of damage, it is not possible to know exactlythe displacement demand level at which damage occurred, only that it occurred priorto reaching a particular maximum displacement demand level. Further it is notpossible to differentiate between damage that occurs during the second cycle to amaximum displacement demand level from that which occurs during the third cycleor from that which occurs during the first cycle to an increased maximumdisplacement demand.4.2 Predicting the Required Method of Repair4.2.1 Grouping Damage Data for Using in Prediction Method of RepairThe data presented in Figure 1 were used to develop models defining the probabilityof earthquake damage requiring, at least, the use of a specific method of repair. Thesedata could have been used to generate fragility curves defining the probability thatjoint damage would meet or exceed a specific damage state. However, since theultimate objective of this effort was the prediction of economic impact, thedevelopment of damage-state prediction models was not considered to be necessary.To generate repair-method prediction models, the data in Figure 1 werecombined so that individual data points define a specific EDP value and the requiredmethod of repair associated with that EDP value. This combination was accomplishedusing the relationships in Table 3. Because several damage states are linked with eachmethods of repair, there are several plausible approaches to combining the data:• Method One: All of the EDP-damage state pairs are used for each method ofrepair. This results in the most data. This also results in the data being biasedtowards higher EDP levels.• Method Two: For each individual specimen, the lowest EDP-damage statedata point associated with each method of repair is used. This results in nomore than 21 data points for each method of repair. This also results in thedata being slightly biased towards higher EDP levels, but the bias is less thanfor combination Method One.• Method Three: Only data for the lowest damage state are used for eachmethod of repair. This method results in the fewest data for each method ofrepair.All three approaches were employed for all five EDPs. For each combination method,the sample mean and coefficient of variation were computed for the EDP-method ofrepair data sets. Combination Method Two was identified as the preferred method foruse in the study. This method resulted in the smallest coefficient of variation for theEDP-method of repair data as well as well-spaced means.217
- Page 182 and 183: quantification tools could be used
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- Page 188 and 189: Nigg, J. M. (1998). Empirical findi
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- Page 192 and 193: limit states, the suggestions given
- Page 194 and 195: ∆NSLsi= SϑH(5)iTFor column-sway
- Page 196 and 197: Pinto et al., 2004). The probabilit
- Page 198 and 199: The main difficulty in assigning a
- Page 200 and 201: Crowley, H., R. Pinho, and J. J. Bo
- Page 202 and 203: analytical models generally have si
- Page 204 and 205: Figure 2. Structure of the response
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- Page 208 and 209: 4. DERIVATION OF THE VULNERABILITY
- Page 210 and 211: 5. CONCLUSIONSDerivation of vulnera
- Page 212 and 213: REFERENCESAbrams, D. P., A. S. Elna
- Page 214 and 215: In general, these types of bench-mo
- Page 216 and 217: where & x&(t ) = acceleration at th
- Page 218 and 219: science building. The lateral load-
- Page 220 and 221: emain the same, the magnitude of sl
- Page 222 and 223: of sliding thresholds, are desirabl
- Page 224 and 225: Retrofit of Nonstructural Component
- Page 226 and 227: was developed to accommodate these
- Page 228 and 229: tested by Meinheit and Jirsa are us
- Page 230 and 231: where D is the maximum drift and N
- Page 234 and 235: 4.2.2 Modeling the Data Using Stand
- Page 236 and 237: that the defining demand using a no
- Page 238 and 239: • The influence on the dynamic re
- Page 240 and 241: deviations σ and correlation coeff
- Page 242 and 243: The first three modes of vibration
- Page 244 and 245: Details about the ten records selec
- Page 246 and 247: to allow a quantitative assessment
- Page 248 and 249: Cornell A. C., F. Jalayer, R. Hambu
- Page 250 and 251: limited possibilities of overcoming
- Page 252 and 253: uildings, up to five stories high (
- Page 254 and 255: Efficiency η, %100806040203D-RWBW-
- Page 256 and 257: Table 1. Performance criteria for c
- Page 258 and 259: Because the analytical model strong
- Page 260 and 261: REFERENCESAguilar, G., R. Meli, R.
- Page 262 and 263: tests of its type ever conducted. T
- Page 264 and 265: end work-point to work-point). And
- Page 266 and 267: Fig. 5 shows the actual application
- Page 268 and 269: 3Roof Disp. (mm)250200150100500-50-
- Page 270 and 271: Base Shear (kN)Base Shear (kN)40002
- Page 272 and 273: 8. CONCLUSIONSBased on the test and
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- Page 276 and 277: :::::2004) can be formulated using
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in predicting damage as well as repair method given an EDP. The steps in thedevelopment process are discussed in the following sections.4.1 Damage versus EDPExperimental data characterizing the progression <strong>of</strong> damage for the test specimenswere used to generate data sets linking the thirteen damage states with the threeprimary EDPs: drift, number <strong>of</strong> load cycles and joint shear strain. The functionalEDPs, defined by Eq. 2 and Eq. 3, were calibrated to minimize the dispersion <strong>of</strong> thedata for all damage states about a line spanning the range <strong>of</strong> damage states andfunctional values from 0 to 1. Figure 1 shows damage-EDP data for the five EDPs.121212Damage State108642108642108642000.0 2.0 4.0 6.00 10 20 30 40 5000.00 0.02 0.04 0.06 0.08 0.10 0.12(a) drift (b) number <strong>of</strong> cycles (c) joint shear strain1212Damage State10864210864200.0 0.2 0.4 0.6 0.8 1.0 1.200.0 0.2 0.4 0.6 0.8 1.0 1.2(d) F(D,N) per Eq. 2 (e) F(γ,N) per Eq. 3Figure 1. Damage versus EDP.The scatter <strong>of</strong> the data in Figure 1 reinforces the need for probabilistic modelslinking EDPs with damage and repair. The variability in these data is due in part tovariability in test specimen design and loading; however, it is due also to the datacollection procedures used in the laboratory. The typical procedure used in earthquaketesting in the laboratory is as follows:1. A half-cycle <strong>of</strong> loading to a new maximum displacement demand, at whichpoint loading is paused to allow for identification <strong>of</strong> new cracks and regions<strong>of</strong> spalling, measurement <strong>of</strong> new and existing cracks and picture taking.216