| Budget Amount *help |
¥2,740,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥240,000)
Fiscal Year 2007: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2006: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2005: ¥800,000 (Direct Cost: ¥800,000)
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| Research Abstract |
National Research Institute for Earth Science and Disaster Prevention (NIED) deploys digital strong-motion seismographs (KiK-net) all over the country in Japan, which provide vertical array records of ground motions. The total number of observation sites is nearly 700. Data observed by KiK-net can be used to identify the dynamic properties of the subsurface ground.
In order to identify the properties using KiK-net data, however, some pre-processes such as the correction of sensor direction, wave synthesis, drawing wave, preparation of soil data are needed. Furthermore, the selection of the interval of time series, damping model and initial values used in the analysis of identification must be investigated, because they influence on the results of identification.
A new system is developed to identify the quality factor, in which quality factor is swept out of the feasible range in such the frequency band that the quality factor is not sensitive. The system is free from most of the troublesome operations, which makes the various analyses on various conditions possible.
Using the system, the dynamic soil properties are identified. The major results in this study are as follows.
(1) The trend of quality factor whose values increase according to frequencies can be recognized though the variations are not small enough.
(2) The similarity of the estimated values of quality factor can be seen at the identical site using different events of earthquakes.
Since the variations of estimated values of quality factor are not small enough, it is too early to discuss its dependency on frequencies quantitatively. Accumulation of analytical results of identification is necessary as well as the development of the method proposed in this study for the goal to model the frequency-dependent quality factor of subsurface ground.
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