1986 Fiscal Year Final Research Report Summary
Design Ground Motion for Lifeline System Taking into Account Fault Rupture Process
| Project/Area Number |
60550324
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
土木構造
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| Research Institution | Kyoto University |
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Principal Investigator |
SATO Tadanobu Disaster Prevention Research Institute, Kyoto University, Assoc. Prof., 防災研究所, 助教授 (00027294)
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| Co-Investigator(Kenkyū-buntansha) |
KIYONO Junji Disaster Prevention Research Institute, Kyoto University, Res. Assoc., 防災研究所, 助手 (00161597)
TOKI Kenzo Disaster Prevention Research Institute, Kyoto University,Prof., 防災研究所, 教授 (10027229)
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| Project Period (FY) |
1985 – 1986
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| Keywords | Design ground motion / Cepstrum analysis / System response function / A train of impulses / Fault mechanism / El Centro array / Non-linear system inversion |
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| Research Abstract |
The cepstrum analysis was applied to deconvolute a seismic 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 analyzed in order to examine the validity of the proposed deconvolution method. It was found that arrival time of an impulse was estimated within the 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 acceleograms recorded at fourteen stations in El Centro Array are used to identify the fault mechanism of the 1979 Imperial Valley, California earthquake. Because deconvoluted fourteen trains of impulses contain information about the fault mechanism, the rupture process defined by such fault parameters as the rupture velocity, the starting point of rupture, the direction of the rupture propagation and the rise time 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 is confirmed by the fact that five major small events are identified on the fault surface.
The identified distribution of seismic moment on the fault surface compares well with that investigated from different approach. The analytical algorithm led to the non-linear 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 information for identifying parameters.
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