| Project/Area Number |
16201038
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Natural disaster science
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| Research Institution | The University of Tokyo |
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Principal Investigator |
HORI Muneo The University of Tokyo, Earthquake Research Institute, Professor (00219205)
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| Co-Investigator(Kenkyū-buntansha) |
KATO Teruyuki The University of Tokyo, Earthquake Research Institute, Professor (80134633)
KOKETU Kazuki The University of Tokyo, Earthquake Research Institute, Professor (90134634)
OGUNI Kenji The University of Tokyo, Earthquake Research Institute, Associate Professor (20323652)
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| Project Period (FY) |
2004 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥21,710,000 (Direct Cost: ¥16,700,000、Indirect Cost: ¥5,010,000)
Fiscal Year 2007: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2006: ¥15,470,000 (Direct Cost: ¥11,900,000、Indirect Cost: ¥3,570,000)
Fiscal Year 2005: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2004: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | stochastic model / crust deformation / seismic activity / GPS data / large-scale computation / Monte-Carlo simulation / crust deformation monitor / 地震データ / 逆解析 / カルマンフィルタ / GPS / 破壊解析 / 数値計算 / 不確定性 / 地震 |
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| Research Abstract |
Background of research: The estimation of three-dimensional distribution of stress in the crust of the Japanese Islands is essential for earthquake hazard and disaster prediction, since an earthquake is triggered by crust stress. However, it is impossible to measure stress as deep as 10 kilometer below the ground. An alternative is the construction of a stochastic model which accounts for the uncertainty of the stress distribution by using a probabilistic distribution function; the function is defined by using limited measurement for the curst deformation and the seismic activities. A set of admissible stochastic models are found by integrating data which will be accumulated through measurement of the crust deformation and the seismic activities.
Objective of research: The primary of objective of this research is the construction of a stochastic model for the stress distribution which is stored in the crust of the Japanese Island. Aset of admissible models are found by reproducing data
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for the curst deformation that is measured by GPS and for the seismic activities which are measured by seismograph network. This set will provide a certain model which is able to make prediction for future events. Anew analysis method for the stochastic model is developed, so that numerical computation that is required for the analysis is minimized.
Methodology of research: First, a physical model which has the configuration that matches the actual plates is constructed. A stochastic model is constructed by using limited information for stress which are expressed in terms of a probabilistic function. Arational method for constructing the stochastic model based on the physical model is studied. A set of admissible models are determined by means of the Monte-Carlo simulation which uses large-scale computation, and a most suitable model is chosen so that it will be a prototype which produces prediction of crust deformation and seismic activities.
Major results: A physical model is constructed for the crust of the Japanese Islands, and this model is of highest spatial resolution so that it is analyzed only by a large-scale parallel computation. This physical model is extended to a stochastic model in which three-dimensional distribution of stress in the crust is given as a probabilistic function. An analysis method that uses a new discretization scheme for functions is developed, so that the probabilistic behavior of the stochastic model is efficiently analyzed. The data which are measured for the crust deformation and the seismic activities are used in analyzing the stochastic model. The potential usefulness of analyzing this stochastic model with large-scale numerical computation is studied. Less
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