Application of Earthquake Early Warning System and Real-time Strong-motion Monitoring System to Earthquake Disaster Mitigation of a High-Rise Building in Tokyo, Japan

We apply Earthquake Early Warning System (EEWS) and Real-time Strong-motion Monitoring System (RSMS) to reduce earthquake-related damage of the 29-story building of Kogakuin University in the downtown Tokyo, Shinjuku, Japan. EEWS, which is operated by National Research Institute for Earth Science and Disaster Prevention, is the system to provide earthquake information, such as the location and magnitude of an earthquake, the arrival time of the S-wave, and the estimated seismic intensities, before the actual arrivals of S-waves. We estimate the ground motion using EEWS, not only the S-wave, Using EEWS, we estimate not only the arrival time and the amplitude of the S-wave and the surface waves, but also the building response. We apply EEWS to the emergency control systems of the elevators by estimating ground motions at the Shinjuku site and the corresponding building response. To do this, first, we construct a Green’s function library to estimate roughly the strong ground motions including the surface waves using the wavenumber integration method for various seismic regions, and a library of the corresponding maximum response values of the building using the modal analysis. To check the accuracy of the library, we compare between the observed record for the 2004 Chuetsu Earthquake and the estimated waves. The results show good agreements with the observations in the first half of the records in the arrival time, the amplitudes. Once an earthquake occurs, the ground motion and the building response are quickly estimated using the proposed method. And, the emergency control systems stop automatically the elevators at the nearest floors to prevent people from trapping. On the other hand, we use RSMS to estimate the building damage during earthquakes, and to reduce secondary damages, such as making an announcement for the building safety to prevent a panic.