| Project/Area Number |
14550485
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
構造工学・地震工学
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| Research Institution | Musashi Institute of Technology |
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Principal Investigator |
MARUYAMA Osamu Musashi Institute of Technology, Faculty of Engineering, Assistant Professor, 工学部, 助教授 (50209699)
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| Co-Investigator(Kenkyū-buntansha) |
HOSHIYA Masaru Musashi Institute of Technology, Faculty of Engineering, Professor, 工学部, 教授 (30061518)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2004: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2003: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2002: ¥1,600,000 (Direct Cost: ¥1,600,000)
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| Keywords | first excursion probability / first passage probability / Kalman Filter / Monte Carlo Simulation / performance based design / Kalman filter / performance base design / nonlinear system reliability / stochastic structural dynamics |
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| Research Abstract |
In random vibration, probability of an event that system performance function becomes negative during the time duration is a means to discuss the system safety. This probability is well known as first excursion probability. Since nonlinear stochastic structural dynamics is of significant importance for reliability evaluation of earthquake, wind and ocean wave engineering problems, the development of procedures to predict structural responses has received considerable attention by engineers and consequently there are many methods proposed up to date, or being under development so far.
This research also proposes a method to evaluate the first excursion probability for nonlinear systems. The proposed methods are class of variance reduction techniques for Monte Carlo simulation, which is the importance sampling technique utilizing the measure transformation method and pseudo linearization techniques. To attain the purpose, an importance sampling function is obtained by online data processing based on the stochastic terminal state control theory with the help of numerically simulated response data. The efficiency of the proposed method is demonstrated by numerical examples of non-linear restoring force systems under the external white noise excitation.
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