Proceedings of the 2017 2nd International Conference on Civil, Transportation and Environmental Engineering (ICCTE 2017)

Correlation of the Emergency Handling Peak Ground Acceleration (PGA) for High-speed Railway and Strong-motion Indices using K-net Data

Authors
Linjuan Bai
Corresponding Author
Linjuan Bai
Available Online July 2017.
DOI
https://doi.org/10.2991/iccte-17.2017.12How to use a DOI?
Keywords
Emergency Handling; Peak Ground Acceleration; High-speed Railway; Strong Motion.
Abstract
The emergency handling Peak Ground Acceleration (PGA) has been used as a measure of braking for High-speed Railway (Shinkansen) during earthquake in Japan, and it necessitates to know the correlation between PGA and other strong motion indices, e.g. un-filtered Peak Ground Acceleration (PGAu), Japan Meteorological Agency seismic instrumental intensity (IJMA), Spectrum Intensity (SI), Arias Intensity (Ia), Cumulative Absolute Velocity (CAV), and Cumulative Differential of Energy (DE). The PGA and other ground motion indices were calculated using the selected data set from K-net, in which consists of 2714 three-component records selected from 16 earthquake events occurred in Japan. The relationships between the PGA, and PGAu, IJMA, SI, Ia, CAV, and DE were then derived performing a linear regression analysis. Our Results indicate that the PGA shows higher correlation with IJMA or SI than other ground motion indices, which may be useful for deployment of new parameters of emergency handling during earthquake for High-speed Railway.
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This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Linjuan Bai
PY  - 2017/07
DA  - 2017/07
TI  - Correlation of the Emergency Handling Peak Ground Acceleration (PGA) for High-speed Railway and Strong-motion Indices using K-net Data
BT  - Proceedings of the 2017 2nd International Conference on Civil, Transportation and Environmental Engineering (ICCTE 2017)
PB  - Atlantis Press
SP  - 67
EP  - 70
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccte-17.2017.12
DO  - https://doi.org/10.2991/iccte-17.2017.12
ID  - Bai2017/07
ER  -