Modeling precursory seismicity with numerical model

博士 === 國立中央大學 === 地球物理研究所 === 99 === The sandpile model (Bak et al., 1987) is very well known as the numerical earthquake model. The motivation of building the long-range connective sandpile model is earthquake triggering. Base on the concept of small-word network, we modify the original BTW sandpil...

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Main Authors: Ya-ting Lee, 李雅渟
Other Authors: Chien-chih Chen
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/41538399416489090773
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spelling ndltd-TW-099NCU051340142015-10-19T04:03:14Z http://ndltd.ncl.edu.tw/handle/41538399416489090773 Modeling precursory seismicity with numerical model 模擬地震前兆行為之數值模型 Ya-ting Lee 李雅渟 博士 國立中央大學 地球物理研究所 99 The sandpile model (Bak et al., 1987) is very well known as the numerical earthquake model. The motivation of building the long-range connective sandpile model is earthquake triggering. Base on the concept of small-word network, we modify the original BTW sandpile model. We call it is long range connective sandpile model (LRCS model). The b values (from Gutenberg-Richter law) decay before big earthquake is an important precursor. We try to explain why we have such precursor before big earthquake. In this study, we simulate the behavior of the B values (the slope of the frequency-size power-law distribution by numerical model) decay before big event by LRCS model. In the other way, we also calculate another parameter "Hurst exponent". We can get the negative relation between B value and Hurst exponent in the LRCS model. When the size of sandpile model is larger, the negative relation between B value and Hurst exponent is more conspicuous. By the thermodynamic concept, we explain that the b value decay before big earthquake is caused by the correlation length increasing. When the system is up to meta-stable, longer correlation length makes more intermediate earthquakes occur. That''s why we can get the precursor of b value decay before big earthquake. Further, the negative correlation between b value and Hurst exponent in the earthquake system means that the earthquake system will have persistence behavior when it is up to meta-stable. The original BTW sandpile model is characterized by the frequency-size power-law distribution. Earthquakes have been identified as an example of this phenomenon in nature (Bak and Tang, 1989; Sornette and Sornette, 1989; Ito and Matsuzaki, 1990) and the observation of the Gutenberg–Richter law has been suggested to be the manifestation of the self-organized critical (SOC) state of the dynamics of the earthquake faults. The state of the SOC system will keep staying in the meta-stable state. In this system, big events will occur randomly. So many researchers believe earthquake is unpredictable. Both of the original BTW sandpile model and LRCS model have frequency-size power-law distribution. But BTW sandpile model is difficult to show precursor before big event. The LRCS model can show the intermittent criticality behavior. The state of the system will change between meta-stable and non-meta-stable. Intermittent criticality system can have precursors before big event. This study supposes that the earthquake is an intermittent criticality system. Chien-chih Chen 陳建志 2011 學位論文 ; thesis 171 zh-TW
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description 博士 === 國立中央大學 === 地球物理研究所 === 99 === The sandpile model (Bak et al., 1987) is very well known as the numerical earthquake model. The motivation of building the long-range connective sandpile model is earthquake triggering. Base on the concept of small-word network, we modify the original BTW sandpile model. We call it is long range connective sandpile model (LRCS model). The b values (from Gutenberg-Richter law) decay before big earthquake is an important precursor. We try to explain why we have such precursor before big earthquake. In this study, we simulate the behavior of the B values (the slope of the frequency-size power-law distribution by numerical model) decay before big event by LRCS model. In the other way, we also calculate another parameter "Hurst exponent". We can get the negative relation between B value and Hurst exponent in the LRCS model. When the size of sandpile model is larger, the negative relation between B value and Hurst exponent is more conspicuous. By the thermodynamic concept, we explain that the b value decay before big earthquake is caused by the correlation length increasing. When the system is up to meta-stable, longer correlation length makes more intermediate earthquakes occur. That''s why we can get the precursor of b value decay before big earthquake. Further, the negative correlation between b value and Hurst exponent in the earthquake system means that the earthquake system will have persistence behavior when it is up to meta-stable. The original BTW sandpile model is characterized by the frequency-size power-law distribution. Earthquakes have been identified as an example of this phenomenon in nature (Bak and Tang, 1989; Sornette and Sornette, 1989; Ito and Matsuzaki, 1990) and the observation of the Gutenberg–Richter law has been suggested to be the manifestation of the self-organized critical (SOC) state of the dynamics of the earthquake faults. The state of the SOC system will keep staying in the meta-stable state. In this system, big events will occur randomly. So many researchers believe earthquake is unpredictable. Both of the original BTW sandpile model and LRCS model have frequency-size power-law distribution. But BTW sandpile model is difficult to show precursor before big event. The LRCS model can show the intermittent criticality behavior. The state of the system will change between meta-stable and non-meta-stable. Intermittent criticality system can have precursors before big event. This study supposes that the earthquake is an intermittent criticality system.
author2 Chien-chih Chen
author_facet Chien-chih Chen
Ya-ting Lee
李雅渟
author Ya-ting Lee
李雅渟
spellingShingle Ya-ting Lee
李雅渟
Modeling precursory seismicity with numerical model
author_sort Ya-ting Lee
title Modeling precursory seismicity with numerical model
title_short Modeling precursory seismicity with numerical model
title_full Modeling precursory seismicity with numerical model
title_fullStr Modeling precursory seismicity with numerical model
title_full_unstemmed Modeling precursory seismicity with numerical model
title_sort modeling precursory seismicity with numerical model
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/41538399416489090773
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