• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.290-292
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• 2008

we applied Wind Field Module of PHRLM so that disaster prevention agency concerned can effectively estimate the possible strong wind damages by typhoon. In this study, therefore, we estimated wind speed at 300m level using 700hPa wind according to the research method by Franklin(2003), PHRLM(2003), and Vickery and Skerlj(2005). Then we calculated wind speed at 10m level using the estimated wind speed at 300m level, and finally, peak 3.second gust on surface. The case period is from 18LST August 31 to 03LST September 1, 2002, when the typhoon Rusa in 2002 was the most intense. Among disaster prediction models in the US, Wind Field Module of PHRLM in Florida was used for the 2002 typhoon Rusa case. As a result, peak 3.second gust on the surface increased $10\sim20%$ in the typhoon's 700hPa wind speed.

• Wind and Structures
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• v.7 no.5
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• pp.345-357
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• 2004

In the 1990s, four strong typhoons hit the Kyushu area of Japan and inflicted severe damage on power transmission facilities, houses, and so on. Maximum gust speeds exceeding 60 m/s were recorded in central Kyushu. Although the wind speeds were very high, the gust factors were over 2.0. No meteorological stations are located in mountainous areas, creating a deficiency of meteorological station data in the area where the towers were damaged. Since 1995 the authors have operated a network for wind measurement, NeWMeK, that measures wind speed and direction, covering these mountainous areas, segmenting the Kyushu area into high density arrays. Maximum gusts exceeding 70 m/s were measured at several NeWMeK sites when Typhoon Bart (1999) approached. The gust factors varied widely in southerly winds. The mean wind speeds increased due to effects of the local terrain, thus further increasing gust speeds.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.561-564
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• 2009

In order to reduce damage from natural disasters, prevention activities through analysis and predicting based on meteorological factor and damage data is required. Other countries already have continuously studied on natural disasters and developed reducing disasters damage. But the risk assessment model for natural disaster is not to Korea. Therefore, a previous model of hurricane, Florida Public Hurricane Loss Model(FPHLM), is the basis and is applying to domestic situation. Accordingly, this study introduces the variables selecting process because input variables should be selected under Korea present state and be used. The estimating representative damage method would be necessary along with selecting housing types representing relevant areas because estimating damage amount of all over relevant areas housing was very hard during damage estimating process. But there is no exact representative housing types in the Korea. Therefore, we select housing types applicable to risk assessment model for natural disasters representing the Korea through previous studies and literature reviews. We using ASCE 7-98(Minimum Design Loads for Buildings and Other Structures, 1998) standard which estimated wind load using 3-second gust. ASCE 7-98 divided Main Wind Force Resistance System(MWFRS) and Component and Cladding(C&C) and it estimated wind load. Therefore, we estimate wind load affected by 3-second gust of a typhoon Maemi through calculating wind load process using selected representative detached house types in the process of selecting input variables for previous disaster predict model. The result of houses damage amount is about 230 hundred million won. This values are limit the 1-story detached dwelling, 19~29pyeong(62.81~95.56 $m^2$) of total area and flat roof. Therefore, this process is possible application to other type houses.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.