| Project/Area Number |
16360223
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Structural engineering/Earthquake engineering/Maintenance management engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
ISHIHARA Takeshi The University of Tokyo, Graduate School of Engineering, Associate Professor, 大学院・工学系研究科, 助教授 (20323511)
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| Co-Investigator(Kenkyū-buntansha) |
FUJINO Yozo The University of Tokyo, Graduate School of Engineering, Professor, 大学院・工学系研究科, 教授 (20111560)
UNO Itsushi Kyushu University, Research Institute for Applied Mechanics, Professor, 応用力学研究所, 教授 (70142099)
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| Project Period (FY) |
2004 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥14,600,000 (Direct Cost: ¥14,600,000)
Fiscal Year 2005: ¥4,800,000 (Direct Cost: ¥4,800,000)
Fiscal Year 2004: ¥9,800,000 (Direct Cost: ¥9,800,000)
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| Keywords | Information System for Wind Climate / Mesoscale Model / Microscale Model / Data base / Numerical Weather Prediction / Offshore Wind Energy Potential Assessment / 鉄道沿線強風発生地点抽出 / やまじ風 / 社会基盤維持管理 / 力学統計的局所化 / 標準実風況変換 |
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| Research Abstract |
It is important to accurately predict local wind climate, for improvement of maintenance strategy of engineering structures and efficient development. This study aims to develop a wind climate information system for providing a wind climate data with high resolution and verifying the accuracy of the proposed system. The main results obtained from this study are summarized as follows :
First, a Dynamical Statistical Downscaling Procedure was proposed in this study. It consists of predictions of the regional wind by mesoscale atmospheric models and statistical analysis determining regional wind climate. A nonlinear micro wind prediction model and Idealizing and Realizing Approach were used to downscale regional wind climate to micro wind climate. This procedure can describe accurately the micro topography and take the effect of local circulation such as sea-land breeze and mountain-valley wind into account.
Secondly, a database was established using the mesoscale model of RAMS, including 10 minutes mean wind speeds and directions with the minimum horizontal resolution of 2km. Offshore wind energy potential in the Kanto coastal region was estimated using the database for wind farm developments. Total theoretical potential reaches 277TWh/year accounting for 94% of the annual demand for Tokyo Electric Power Company, considering the area 50km from the shore and 2MW wind turbines situated with 8D by 8D spacing.
Finally, the applicability and accuracy of the proposed system were examined using the 10 minutes mean wind speeds observed at Tappi and Choshi. The annual mean wind speeds predicted by the proposed model demonstrated good agreement with observations with averaged prediction errors of 4.6% and 4.8%, respectively.
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