• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.29-34
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• 2010

Wind speed and wind direction are usually taken using two parameters: wind speed and wind direction. This paper studies the average wind speed and direction calculation methods. The paper first introduces to basic wind's knowledge, and then presents several methods in calculating average wind speed and direction. Lastly some graphs are plotted base on these computational methods and the implementation of these methods in an actual buoy system.

• Wind and Structures
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• v.20 no.5
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• pp.701-718
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• 2015

The joint distribution of wind speed and wind direction at a bridge site is vital to the estimation of the basic wind speed, and hence to the wind-induced vibration analysis of long-span bridges. Instead of the conventional way relying on the weather stations, this study proposed an alternate approach to obtain the original records of wind speed and the corresponding directions based on field measurement supported by the Structural Health Monitoring System (SHMS). Specifically, SHMS of Sutong Cable-stayed Bridge (SCB) is utilized to study the basic wind speed with directional information. Four anemometers are installed in the SHMS of SCB: upstream and downstream of the main deck center, top of the north and south tower respectively. Using the recorded wind data from SHMS, the joint distribution of wind speed and direction is investigated based on statistical methods, and then the basic wind speeds in 10-year and 100-year recurrence intervals at these four key positions are calculated. Analytical results verify the reliability of the recorded wind data from SHMS, and indicate that the joint probability model for the extreme wind speed at SCB site fits well with the Weibull model. It is shown that the calculated basic wind speed is reduced by considering the influence of wind direction. Compared to the design basic wind speed in the Specification of China, basic wind speed considering the influence of direction or not is much smaller, indicating a high safety coefficient in the design of SCB. The results obtained in this study can provide not only references for further wind-resistance research of SCB, but also improve the understanding of the safety coefficient for wind-resistance design of other engineering structures in the similar area.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.299-307
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• 2023

Given that toxic substances are diffused by the various movements of the atmosphere, it is very important to evaluate the risks associated with this phenomenon. When analyzing the behavioral characteristics of these atmospheric diffusion models, the main input data are the wind speed and wind direction among the meteorological data. In particular, it is known that a certain wind direction occurs in summer and winter in Korea under the influence of westerlies and monsoons. In this study, synoptic meteorological observation data provided by the Korea Meteorological Administration were analyzed from January 1, 2012 to the end of August of 2022 to understand the regional wind characteristics of nuclear power plants and surrounding areas. The selected target areas consisted of 16 weather stations around the Hanbit, Kori, Wolsong, Hanul, and Saeul nuclear power plants that are currently in operation. The analysis was based on the temperature, wind direction, and wind speed data at those locations. Average, maximum, minimum, median, and mode values were analyzed using long-term annual temperature, wind speed, and wind direction data. Correlation coefficient values were also analyzed to determine the linear relationships among the temperature, wind direction, and wind speed. Among the 16 districts, Uljin had the highest wind speed. The median wind speed values for each region were lower than the average wind speed values. For regions where the average wind speed exceeds the median wind speed, Yeongju, Gochang, Gyeongju, Yeonggwang, and Gimhae were calculated as 0.69 m s^-1, 0.54m s^-1, 0.45m s^-1, 0.4m s^-1, and 0.36m s^-1, respectively. The average temperature in the 16 regions was 13.52 degrees Celsius; the median temperature was 14.31 degrees and the mode temperature was 20.69 degrees. The average regional temperature standard deviation was calculated and found to be 9.83 degrees. The maximum summer temperatures were 39.7, 39.5, and 39.3 in Yeongdeok, Pohang, and Yeongcheon, respectively. The wind directions and speeds in the 16 regions were plotted as a wind rose graph, and the characteristics of the wind direction and speed of each region were investigated. It was found that there is a dominant wind direction correlated with the topographical characteristics in each region. However, the linear relationship between the wind speed and direction by region varied from 0.53 to 0.07. Through this study, by evaluating meteorological observation data on a long-term synoptic scale of ten years, regional characteristics were found.

• Journal of Wind Energy
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• v.9 no.4
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• pp.9-15
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• 2018

In a previous study, a technique for measuring wind speed and direction by using a roll-rotating three-axis ultrasonic anemometer was proposed and verified by wind tunnel tests. In the tests, instead of a roll sensor, roll angle was trimmed to make no up flow in the transformed wind speeds. Verification was done in point of the residual error of the rotation effect treatment. In this study, roll angle was measured from the roll motor encoder and the transformed wind speed and direction on the test section axis were compared with the ones provided to the test section. As a result, up to yaw $20^{\circ}$ at a wind speed of 12 m/sec or over, the RMS error of wind speed was within the double of the ultrasonic anemometer error. But at yaw $30^{\circ}$, it was over the double of the ultrasonic anemometer error. Regardless of wind speed, at yaw $20^{\circ}$ and $30^{\circ}$, the direction error was within the double of the ultrasonic anemometer error. But at yaw $10^{\circ}$ or less, it was within the error of the ultrasonic anemometer itself. This is a very favorable characteristic to be used for wind turbine yaw control.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of Environmental Science International
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• v.10 no.2
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• pp.135-142
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• 2001

In order to investigate horizontal wind field in the boundary layer around Pusan area, wind speed and wind direction measured at 14 AWS(Automatic Weather Station), 1997, was used. The wind direction at PRM(Pusan Regional Meterological Office) was showed that southwest and northeast wind dominated for spring and summer, northeast wind for fall and northwest for winter. Anticline flow was showed at \`Gaekumm\` which is located between Mt. Backyang(641m) and Mt. Yumkwang(503m) and affected on wind field at \`Pusanjin\`. The low wind speed and various wind direction was represented at the basin topography, \`Buckgu\`, \`Jeasong\`, \`Ilkwang\` and \`Kijang\`. The annual mean wind speed at 14 sites, 2.5ms(sup)-1, was lower than that measured at PRMO, 3.9ms(sup)-1. The wind direction analysis showed that the case of same direction in compare with that measured at PRMO is about 54% and case of opposite direction is about 12%. Annual and seasonal mean windrose showed wind direction is affected by not only synoptic weather state but also topography.

• Proceedings of KOSOMES biannual meeting
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• 2003.11a
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• pp.163-166
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• 2003

The seasonal mean wind direction and wind speed in a greater coasting area are investigated using the ECMWF(European Centre for Medium-Range Weather Forecasts) data for 11 years from 1985 to 1995. In winter, the main wind direction in Korea and vicinity, Taiwan and vicinity, and the North Pacific Ocean of middle latitudes is a northwesterly wind, northeasterly wind, and westerly wind respectively. The wind speed is strongest in the East China Sea, the South China Sea, and the North Pacific Ocean of low latitudes(Beaufort wind scale 5-6). A distribution pattern of wind direction in spring and fall is similar to that in winter. Seasonal mean wind speed is strongest in winter and the next is fall. The wind speed in summer is generally weak. However, that in the Indochina and vicinity is strong by the influence of Asian monsoon.

• Wind and Structures
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• v.39 no.2
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• pp.85-100
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• 2024

In light of extreme value distribution probability, an improved prediction method of the Recurrence Period Wind Speed (RPWS) is constructed considering wind direction, with the Equivalent Independent Wind Direction Number (EIWDN) introduced as a parameter variable. Firstly, taking the RPWS prediction of Beijing city as an example, the traditional Cook method is used to predict the RPWS of each wind direction based on the measured wind speed data in Beijing area. On basis of the results, the empirical formulae to determine the parameter variables are fitted to construct an improved expression of the non-exceedance probability of the RPWS. In this process, the statistical model of the optimal threshold is established, and thus the independent wind speed samples exceeding the threshold are extracted and fitted to follow the Generalized Pareto Distribution (GPD) model for analysis. In addition, the Extreme Value Type I (EVT I) distribution model is used to predict and analyze the RPWS. To verify its wide applicability, the improved method is further used in cities like Jinan, Nanjing, Wuxi, Shanghai and Shenzhen to predict and analyze the RPWS of each wind direction, and the prediction results are compared against those gained via the traditional Cook method and the whole direction. Results show that the 50-year RPWS results predicted by the improved method are basically consistent with those predicted by the traditional method, and the RPWS prediction values of most wind directions are within the envelope range of the whole wind direction prediction value. Compared with the traditional method, the improved method can readily predict the RPWS under different return periods through empirical formulae, and avoid the repeated operation process and some assumptions in the traditional Cook method, and then improve the efficiency of prediction. In addition, the improved RPWS prediction results corresponding to the GPD model are slightly larger than those of the EVT I distribution model.

• Architectural research
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• v.18 no.4
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• pp.137-144
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• 2016

The objective of this study was to determine the optimal angle of a wind louver that would induce the optimal wind speed for indoor. Being controlled to have an optimized angle depending on the direction from which wind is blowing and the wind speed, the wind louver to be installed on the building envelop comes to create indoor comfort through a constant wind speed using the function that reduces the indoor wind speed by changing the angle when the wind speed is not lower than a certain level and makes wind flow into the room to the maximum when the wind direction is adverse to catching the wind or the wind speed is not higher than a certain level. To determine the optimal wind louver angle, a core-centered office building with cross-ventilation problems in the climate of Seoul, Korea, which experiences four distinct seasons, was considered for analysis in this study. A module 1 office space model was used for the CFD simulation to analyze the average indoor wind speed with respect to the outdoor wind speed (varied between 1 and 8 m/s), the wind louver angle, and the outdoor wind direction (varied between $0^{\circ}$ and $180^{\circ}$ in steps of $10^{\circ}$).

• 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.