1988 Fiscal Year Final Research Report Summary
Design Ground Motion for Lifeline System Taking into AccountFault Rupture Process
| Project/Area Number |
62550336
|
|---|
| Research Category |
Grant-in-Aid for General Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
土木構造
|
|---|
| Research Institution | Kyoto University |
|---|
Principal Investigator |
SATO Tadanobu Kyoto University, Disaster Prevention Research Institute, Assoc. Prof. (00027294)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
KIYONO Junji Disaster Prevention Research Institute, Kyoto University, 防災研究所, Assoc Res. (00161597)
MATUMURA Kazuo Kyoto University, Disaster Prevention Research Institute, Assoc. P (70027283)
TOKI Kenzo Kyoto University, Disaster Prevention Research Institute, Prof. (10027229)
|
|---|
| Project Period (FY) |
1987 – 1988
|
| Keywords | Homomoropic filter / A train of impulses / Green function / Cepstrum analysis / 非線形逆解析法 |
|---|
| Research Abstract |
The cepstrum analysis was applied to deconvolute a seismec wave into a system response function and a train of impulses. Based on several criteria to minimize error, we propose a method to identify the source mechanism using identified trains of impulses. Simulated waves were anakyzed in order to examine the validity of the proposd decomvolution method. It was found that arrival time of an impulse was estimated within teh error of two sampling intervals and intensity of impulse was proportional to the difference between the exact and estimated arrival time of the impulse.
The accelerograms recorded at fourteen stations in El Centro Array are used to identify the fault mechanism of the 1979 Imperial Valley, California earthquake. The rupture velocity, the starting point of rupture, the direction of the rupture propagation and the rise tiome can be estimated by minimizing the error between deconvoluted trains of impulses and theoretically calculated ones by selecting proper values of fault parameters in the rupture process. The multiple rupture process was confirmed by the fact that five major small events were identified on the fault surface.
The identifide distribution of seismic moment on the fault surface compares well with that investigated from different approach. The analytical algorithm led to the nonlinear system inversion and non-uniqueness of identified parameters. To overcome these problems, we applied Bayes' rule which provided a quantitative error measure taking into account the effect of prior informartion for identfying parameters.
|
