1997 Fiscal Year Final Research Report Summary
Study on Information System of Grand Motions For Earthquake Disaster
| Project/Area Number |
07558058
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (A)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 展開研究 |
|---|
| Research Field |
Natural disaster science
|
|---|
| Research Institution | KYOTO UNIVERSITY |
|---|
Principal Investigator |
IRIKURA Kojiro Disas.Prev.Res.Inst., KYOTO UNIVERSITY Professor, 防災研究所, 教授 (10027253)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
IWATA Tomotaka Disas.Prev.Res.Inst., Research Associate, 防災研究所, 助手 (80211762)
KUGE Keiko Dept.of Science, Research Associate, 大学院・理学研究科, 助手 (50234414)
KAMAE Katsuhiro Res.Reactor Institute, Research Associate, 原子炉実験所, 助手 (50161196)
SHINOZAKI Yuzo Dept.of Technology, Associate Professor, 大学院・工学研究所, 助教授 (80026236)
HORIKE Masanori Osaka Inst.Tech., Associate Professor, 助教授 (80221571)
|
|---|
| Project Period (FY) |
1995 – 1997
|
| Keywords | Prediction of Strong Ground Motion / Numerical Simulation / Underground Structure Model / Prediction of liquefaction / Strong Motion Network / Real Time Seismology / Automatic Source Mechanism Determination / Internet Home Page |
|---|
| Research Abstract |
The purposes of this study are to compile earthquake information and to construct a prototype real-time information system for the mitigation of earthquake disaster. Our results are mainly three parts, improvement of strong motion network, automatic estimation of source and ground motions using strong motion data, and basic studies related to prediction of strong ground motions.
(1) We improved instrumentation of seismic strong ground motion network in Kansai area. Maximum values of velocity will be sent almost on real-time and waveforms will be downloaded simultaneously.
(2) An automatic source mechanism determination system is developed by using strong motion network data and we also improved this algorithm more robustly by applying strong motion data base.
(3) Theoretical, semi-empirical, and empirical prediction methods of strong ground motions of source area are examined using seismic network data. For the seismic early-warning system, we developed a new estimation method of seismic intensity distribution based on the empirical method and real-time waveform data.
(4) We summarized researches concerning to the liquefaction conditions and examined the automatic estimation method of ground earthquake disaster using ground motion data, seismic intensity distribution, and GIS information. This method was applied to the past large disaster earthquakes.
(5) We demonstrate several ways to open our ground motion information to the public using the internet home page and the internet mail.
(6) We made the report of these results and some basic studies concerning to prediction and evaluation of strong ground motions.
|
