• journal_title：Bulletin of the Seismological Society of America
• Contributor：Swaminathan Krishnan ; Emanuele Casarotti ; Jim Goltz ; Chen Ji ; Dimitri Komatitsch ; Ramses Mourhatch ; Matthew Muto ; John H. Shaw ; Carl Tape ; Jeroen Tromp
• Publisher：Seismological Society of America
• Date：2012-12-01
• Format：text/html
• Language：en
• Identifier：10.1785/0120110339
• journal_abbrev：Bulletin of the Seismological Society of America
• issn：0037-1106
• volume：102
• issue：6
• firstpage：2646
• section：Articles

This article outlines a new approach to rapidly estimate the damage to tall buildings immediately following a large earthquake. The preevent groundwork involves the creation of a database of structural responses to a suite of idealized ground‐motion waveforms. The postevent action involves (1) rapid generation of an earthquake source model, (2) near real‐time simulation of the earthquake using a regional spectral‐element model of the earth and computing synthetic seismograms at tall building sites, and (3) estimation of tall building response (and damage) by determining the best‐fitting idealized waveforms to the synthetically generated ground motion at the site and directly extracting structural response metrics from the database. Here, ground‐velocity waveforms are parameterized using sawtoothlike wave trains with a characteristic period (T), amplitude (peak ground velocity, PGV), and duration (number of cycles, N). The proof‐of‐concept is established using the case study of one tall building model. Nonlinear analyses are performed on the model subjected to the idealized wave trains, with T varying from 0.5 s to 6.0 s, PGV varying from 0.125  m/s, and N varying from 1 to 5. Databases of peak transient and residual interstory drift ratios (IDR), and permanent roof drift are created. We demonstrate the effectiveness of the rapid response approach by applying it to synthetic waveforms from a simulated 1857‐like magnitude 7.9 San Andreas earthquake. The peak IDR, a key measure of structural performance, is predicted well enough for emergency response decision making.