RED-ACT Report for Jan. 25, Japan Nagano-ken Nambu Earthquake

RED-ACT Report

Real-time Earthquake Damage Assessment using City-scale Time-history analysis

Jan. 25, Japan Nagano-ken Nambu Earthquake

Research group of Xinzheng Lu at Tsinghua University

luxz@tsinghua.edu.cn

First reported at 22:40, Jan. 25, 2019 (Beijing Time, UTC +8)

Acknowledgments and Disclaimer

The authors are grateful for the data provided by K-NET and KiK-net.

This analysis is for research only. The actual damage resulting from the earthquake should be determined according to the site investigation.

1. Introduction to the earthquake event

At 21: 10, Jan. 25, 2019 (Local Time, UTC +9), an M 3.4 (JMA) earthquake occurred in Nagano-ken Nambu, Japan. The epicenter was located at 36.0N, 137.6E, with a depth of 10.0 km.

2. Recorded ground motions

Ten ground motions near to epicenter of this earthquake were analyzed. The maximal recorded peak ground acceleration (PGA) is 87cm/s/s.

No.Station NameLongitudeLatitude

1GIF003137.30136.3322

2GIF004137.51736.2492

3GIF007137.48636.0378

4GIF008137.2635.9515

5GIF010137.24535.8029

6NGN013137.78536.1833

7NGN017137.82635.9748

8NGN018137.5335.8132

9NGN019137.70835.8562

10NGN022137.61335.6079

3. Seismic damage analysis for target region subjected to the recorded ground motions

Using the real-time ground motions obtained from the strong motion networks and the city-scale nonlinear time-history analysis (see the Appendix of this report), the damage ratios of buildings located in different places can be obtained. These damage ratios can provide a reference for post-earthquake rescue work. The damage ratio distribution of the buildings near to different stations is shown in Figure 1. The human comfortableness distribution near to different stations is shown in Figure 2.

The details can be accessed at

http://www.luxinzheng.net/software/2019-01-25-Japan-3.4.html

http://www.luxinzheng.net/software/2019-01-25-Japan-3.4-Acc.html

Figure 1 Damage ratio distribution of the buildings near to different stations

Figure 2 Human comfortableness distribution near to different stations

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