• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.223-231
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• 2007

Considering wind speed uncertainty, reliability analysis of the LNG unloading arm at Tongyoung Production Site was performed. Extreme distribution of wind speed was estimated from the data collected at the weather center and wind load was calculated using wind velocities and coefficients of wind pressure. The unloading arm was modeled with plate and solid elements. Contact elements were used to describe the interface between base of structure andground. Response surface for maximum effective stress was found for reliability analysis and then reliability functions was defined and used to determine exceeding probability of allowable and yield stresses. In addition, sensitivity analysis was also performed to estimate the effect of possible material deterioration in the future.

• Journal of Environmental Science International
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• v.25 no.2
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• pp.247-257
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• 2016

To predict annual energy production (AEP) accurately in the wind farm where located in Seongsan, Jeju Island, Equivalent wind speed (EQ) which can consider vertical wind shear well than Hub height wind speed (HB) is calculated. AEP is produced by CFD model WindSim from National wind resource map. EQ shows a tendency to be underestimated about 2.7% (0.21 m/s) than HB. The difference becomes to be large at nighttime when wind shear is large. EQ can be also affected by atmospheric stability so that is classified by wind shear exponent (${\alpha}$). AEP is increased by 11% when atmosphere becomes to be stabilized (${\alpha}$ > 0.2) than it is convective (${\alpha}$ < 0.1). However, it is found that extreme wind shear (${\alpha}$ > 0.3) is hazardous for power generation. This results represent that AEP calculated by EQ can provide improved accuracy to short-term wind power forecast and wind resource assessment.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.315-323
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• 2023

Marine accidents due to loss of stability of small ships have continued to increase over the past decade. In particular, since sudden winds have been pointed out as main causes of most small ship accidents, safety measures have been established to prevent them. In this regard, to prevent accidents caused by sudden winds, a systematic analysis technique is required. The aim of the present study was to develop a probabilistic approach to estimate extreme value and evaluate effects of wind on motion characteristics of ships. The present study included studies of motion analysis, extraction of extreme values, and motion characteristics. A series analysis was conducted for three conditions: wave only, wave with uniform wind speed, and wave with the NPD wind model. Hysteresis filtering and Peak-Valley filtering techniques were applied to time-domain motion analysis results for extreme value extraction. Using extracted extreme values, the goodness of fit test was performed on four distribution functions to select the optimal distribution-function that best expressed extreme values. Motion characteristics of a fishing boat were evaluated for three periodic motion conditions (Heave, Roll, and Pitch) and results were compared. Numerical analysis was performed using a commercial solver, ANSYS-AQWA.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.414-425
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• 2021

Overcrowding of high-rise buildings in urban zones change the airflow pattern in the surrounding areas. This causes building wind, which adversely affects the wind environment. Building wind can generate more serious social damage under extreme weather conditions such as typhoons. In this study, to analyze the wind speed and wind speed ratio quantitatively, we installed five anemometers in Haeundae, where high-rise buildings are dense, and conducted on-site monitoring in the event of typhoon OMAIS to determine the characteristics of wind over skyscraper towers surround the other buildings. At point M-2, where the strongest wind speed was measured, the maximum average wind speed in 1 min was observed to be 28.99 m/s, which was 1.7 times stronger than that at the ocean observatory, of 17.0 m/s, at the same time. Furthermore, when the wind speed at the ocean observatory was 8.2 m/s, a strong wind speed of 24 m/s was blowing at point M-2, and the wind speed ratio compared to that at the ocean observatory was 2.92. It is judged that winds 2-3 times stronger than those at the surrounding areas can be induced under certain conditions due to the building wind effect. To verify the degree of wind speed, we introduced the Beaufort wind scale. The Beaufort numbers of wind speed data for the ocean observatory were mostly distributed from 2 to 6, and the maximum value was 8; however, for the observation point, values from 9 to 11 were observed. Through this study, it was possible to determine the characteristics of the wind environment in the area around high-rise buildings due to the building wind effect.

• Wind and Structures
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• v.14 no.4
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• pp.337-357
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• 2011

The collection of wind speed time series by means of digital data loggers occurs in many domains, including civil engineering, environmental sciences and wind turbine technology. Since averaging intervals are often significantly larger than typical system time scales, the information lost has to be recovered in order to reconstruct the true dynamics of the system. In the present work we present a simple algorithm capable of generating a real-time wind speed time series from data logger records containing the average, maximum, and minimum values of the wind speed in a fixed interval, as well as the standard deviation. The signal is generated from a generalized random Fourier series. The spectrum can be matched to any desired theoretical or measured frequency distribution. Extreme values are specified through a postprocessing step based on the concept of constrained simulation. Applications of the algorithm to 10-min wind speed records logged at a test site at 60 m height above the ground show that the recorded 10-min values can be reproduced by the simulated time series to a high degree of accuracy.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.85-89
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• 2007

Data of the typhoon affecting Korean peninsula from 1951 to 2005 are obtained from the RSMC best track and six climatological characteristics of the typhoons are examined. Local wind speeds are obtained by the physical model for wind fields. Typhoons are generated by the Monte Carlo simulation and their wind speeds are distributed using Weibull CDF. Simulated typhoon wind speeds are used to obtain different wind speeds corresponding their mean recurrence intervals.

• Wind and Structures
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• v.4 no.3
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• pp.197-212
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• 2001

Observations of extreme wind speeds in the United Kingdom from 1970 to 1980, corrected for the influence of upwind ground roughness and topography, have been analysed using the recently-developed "Improved Method of Independent Storms" (IMIS). The results have been used to compile two new maps of base wind speed and to confirm the climatic factors in current use. One map is 'irrespective' of wind direction and the other is 'equally weighted' by direction. The 'equally weighted' map is expected to be more consistently reliable and appropriate for use with the climatic factors for the design of buildings and structures.

• Structural Engineering and Mechanics
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• v.45 no.1
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• pp.1-18
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• 2013

The typhoon wind characteristics designing for buildings or bridges located in complex terrain and typhoon prone region normally cannot be achieved by the very often few field measurement data, or by physical simulation in wind tunnel. This study proposes a numerical simulation procedure for predicting directional typhoon design wind speeds and profiles for sites over complex terrain by integrating typhoon wind field model, Monte Carlo simulation technique, CFD simulation and artificial neural networks (ANN). The site of Stonecutters Bridge in Hong Kong is chosen as a case study to examine the feasibility of the proposed numerical simulation procedure. Directional typhoon wind fields on the upstream of complex terrain are first generated by using typhoon wind field model together with Monte Carlo simulation method. Then, ANN for predicting directional typhoon wind field at the site are trained using representative directional typhoon wind fields for upstream and these at the site obtained from CFD simulation. Finally, based on the trained ANN model, thousands of directional typhoon wind fields for the site can be generated, and the directional design wind speeds by using extreme wind speed analysis and the directional averaged mean wind profiles can be produced for the site. The case study demonstrated that the proposed procedure is feasible and applicable, and that the effects of complex terrain on design typhoon wind speeds and wind profiles are significant.

• Journal of Environmental Science International
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• v.17 no.2
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• pp.195-201
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• 2008

Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10 m level wind speed using 700 hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700 hPa wind, 30 km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10 m level, landuse data of USGS are employed. For 10 m level wind speed of Typhoon Rusa in 2002, we sampled AWS site of $7.4{\sim}30km$ distant from typhoon center and compare them with observational data. The results show that the 10 m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10 m level wind speed is useful for estimating the damage structure from typhoon.