• Title/Summary/Keyword: extreme speed

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A joint probability distribution model of directional extreme wind speeds based on the t-Copula function

  • Quan, Yong;Wang, Jingcheng;Gu, Ming
    • Wind and Structures
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    • v.25 no.3
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    • pp.261-282
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    • 2017
  • The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

An Estimation of Extreme Wind Speed of Typhoon Affecting the Damage of Public and Industrial Facilities (공공 및 산업시설 피해에 영향을 미치는 태풍의 최대풍속 도출)

  • Jung, Woo-Sik
    • Journal of Environmental Science International
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    • v.24 no.9
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    • pp.1199-1210
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    • 2015
  • There were 35 typhoons affecting Korean Peninsula from 1999 to 2009(The average annual number of typhoon is 3.18). Among these typhoons, the number of typhoon passing through the Yellow sea, the Southern sea and the East sea were 14, 6 and 15 respectively. Wind speed on the height of 10 m can be finally estimated using the surface roughness after we calculate wind speed on the height of 300 m from the data on the surface of 700 hPa. From the wind speeds on the height of 10 m, we can understand the regional distributions of strong wind speed are very different according to the typhoon tracks. Wind speed range showing the highest frequency is 10~20 m/s(45.69%), below 10 m/s(30.72%) and 20~30 m/s(17.31%) in high order. From the analysis of the wind speed on the hight of 80 m, we can know the number of occurrence of wind speed between 50 and 60 m/s that can affect wind power generation are 104(0.57%) and those of between 60 and 70 m/s that can be considered as extreme wind speed are even 8(0.04%).

Optimization of Fuzzy Learning Machine by Using Particle Swarm Optimization (PSO 알고리즘을 이용한 퍼지 Extreme Learning Machine 최적화)

  • Roh, Seok-Beom;Wang, Jihong;Kim, Yong-Soo;Ahn, Tae-Chon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.1
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    • pp.87-92
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    • 2016
  • In this paper, optimization technique such as particle swarm optimization was used to optimize the parameters of fuzzy Extreme Learning Machine. While the learning speed of conventional neural networks is very slow, that of Extreme Learning Machine is very fast. Fuzzy Extreme Learning Machine is composed of the Extreme Learning Machine with very fast learning speed and fuzzy logic which can represent the linguistic information of the field experts. The general sigmoid function is used for the activation function of Extreme Learning Machine. However, the activation function of Fuzzy Extreme Learning Machine is the membership function which is defined in the procedure of fuzzy C-Means clustering algorithm. We optimize the parameters of the membership functions by using optimization technique such as Particle Swarm Optimization. In order to validate the classification capability of the proposed classifier, we make several experiments with the various machine learning datas.

Extreme Offshore Wind Estimation using Typhoon Simulation (태풍 모의를 통한 해상 설계풍속 추정)

  • Ko, Dong Hui;Jeong, Shin Taek;Cho, Hongyeon;Kang, Keum Seok
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.26 no.1
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    • pp.16-24
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    • 2014
  • Long-term measured wind data are absolutely necessary to estimate extreme offshore wind speed. However, it is almost impossible to collect offshore wind measured data. Therefore, typhoon simulation is widely used to analyze offshore wind conditions. In this paper, 74 typhoons which affected the western sea of Korea during 1978-2012(35 years) were simulated using Holland(1980) model. The results showed that 49.02 m/s maximum wind speed affected by BOLAVEN(1215) at 100 m heights of HeMOSU-1 (Herald of Meteorological and Oceanographic Special Unit - 1) was the biggest wind speed for 35 years. Meanwhile, estimated wind speeds were compared with observed data for MUIFA, BOLAVEN, SANBA at HeMOSU-1. And to estimate extreme wind speed having return periods, extreme analysis was conducted by assuming 35 annual maximum wind speed at four site(HeMOSU-1, Gunsan, Mokpo and Jeju) in western sea of the Korean Peninsular to be Gumbel distribution. As a results, extreme wind speed having 50-year return period was 50 m/s, that of 100-year was 54.92 m/s at 100 m heights, respectively. The maximum wind speed by BOLAVEN could be considered as a extreme winds having 50-year return period.

Extreme Value Analysis of Metocean Data for Barents Sea

  • Park, Sung Boo;Shin, Seong Yun;Shin, Da Gyun;Jung, Kwang Hyo;Choi, Yong Ho;Lee, Jaeyong;Lee, Seung Jae
    • Journal of Ocean Engineering and Technology
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    • v.34 no.1
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    • pp.26-36
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    • 2020
  • An extreme value analysis of metocean data which include wave, wind, and current data is a prerequisite for the operation and survival of offshore structures. The purpose of this study was to provide information about the return wave, wind, and current values for the Barents Sea using extreme value analysis. Hindcast datasets of the Global Reanalysis of Ocean Waves 2012 (GROW2012) for a waves, winds and currents were obtained from the Oceanweather Inc. The Gumbel distribution, 2 and 3 parameters Weibull distributions and log-normal distribution were used for the extreme value analysis. The least square method was used to estimate the parameters for the extreme value distribution. The return values, including the significant wave height, spectral peak wave period, wind speed and current speed at surface, were calculated and it will be utilized to design offshore structures to be operated in the Barents Sea.

Optimum Design of the Heating Equipment by Influence of Wind Speed at Cryogenic Temperature (극저온에서 풍속의 영향에 따른 발열기자재의 최적설계)

  • Cho, Hyun Jun;Yun, Won Young
    • Journal of Korean Society for Quality Management
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    • v.48 no.3
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    • pp.463-479
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    • 2020
  • Purpose: The purpose of this study is to evaluate the performance of heating equipments by implementing the extreme environment in which ships navigating the ice zone are exposed and to study and apply the experimental method to infer the optimized design for each factors. Methods: It is required to verify by analysis and experiment how the environment with low temperature and wind speed implemented through the test facility affects the heating walk-way and The optimum design of the heating walk-way in that extreme environment is derived using the Taguchi technique. Results: The results of this study are as follows; It was found the effect on the condition of each factor and derive optimized conditions that satisfy the performance condition of the heating walk-way in extreme use environment. Conclusion: Ships operating in Polar waters require reliable and durable facilities for all environments during sailing.

Analysis on wind condition characteristics for an offshore structure design (해상풍력 구조물 설계를 위한 풍황 특성분석)

  • Seo, Hyun-Soo;Kyong, Nam-Ho;Vaas, Franz;Kim, Hyun-Goo
    • 한국신재생에너지학회:학술대회논문집
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    • 2008.10a
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    • pp.262-267
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    • 2008
  • The long-term wind data are reconstructed from the short-term meteorological data to design the 4 MW offshore wind park which will be constructed at Woljeong-ri, Jeju island, Korea. Using two MCP (Measure-Correlate-Predict) models, the relative deviation of wind speed and direction from two neighboring reference weather stations can be regressed at each azimuth sector. The validation of the present method is checked about linear and matrix MCP models for the sets of measured data, and the characteristic wind turbulence is estimated from the ninety-percent percentile of standard deviation in the probability distribution. Using the Gumbel's model, the extreme wind speed of fifty-year return period is predicted by the reconstructed long-term data. The predicted results of this analysis concerning turbulence intensity and extreme wind speed are used for the calculation of fatigue life and extreme load in the design procedure of wind turbine structures at offshore wind farms.

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Reliability of microwave towers against extreme winds

  • Deoliya, Rajesh;Datta, T.K.
    • Structural Engineering and Mechanics
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    • v.6 no.5
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    • pp.555-569
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    • 1998
  • The reliability of antenna tower designed for a n-year design wind speed is determined by considering the variability of the strength of the component members and of the mean wind speed. For obtaining the n-year design wind speed, maximum annual wind speed is assumed to follow Gumbel Type-1 distribution. Following this distribution of the wind speed, the mean and standard deviation of stresses in each component member are worked out. The variability of the strength of members is defined by means of the nominal strength and a coefficient of variation. The probability of failure of the critical members of tower is determined by the first order second moment method (FOSM) of reliability analysis. Using the above method, the reliability against allowable stress failure of the critical members as well as the system reliabilities for a 75 m tall antenna tower, designed for n-year design wind speed, are presented.

Extreme wind speeds from multiple wind hazards excluding tropical cyclones

  • Lombardo, Franklin T.
    • Wind and Structures
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    • v.19 no.5
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    • pp.467-480
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    • 2014
  • The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

Investigations on coefficient of variation of extreme wind speed

  • Xu, Fuyou;Cai, Chunsheng;Zhang, Zhe
    • Wind and Structures
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    • v.18 no.6
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    • pp.633-650
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    • 2014
  • The uncertainty of extreme wind speeds is one key contributor to the uncertainty of wind loads and their effects on structures. The probability distribution of annual extreme wind speeds may be characterized using a classical Gumbel Type distribution. The expression that establishes the relationship between the extreme wind speeds at different recurrence periods and the corresponding coefficients of variation is formulated, and its efficacy is validated. The coefficients of variation are calibrated to be about 0.125 and 0.184 according to defined Chinese and US design specifications, respectively. Based on the wind data of 54 cities in China, 49 meteorological stations in the US, 3 stations in Singapore, the coefficients span intervals of (0.1, 0.35), (0.08, 0.20) and (0.06, 0.14), respectively. For hurricanes in the US, the coefficients range approximately from 0.3 to 0.4. This convenient technique is recommended as one alternative tool for coefficient of variation analyses in the future revisions of related codes. The sensitivities of coefficients of variation for 49 meteorological stations in the US are quantified and demonstrated. Some contradictions and incompatibilities can be clearly detected and illustrated by comparing the coefficients of variation obtained with different combinations of recurrence period wind data.