• Wind and Structures
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• 제27권3호
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• pp.163-173
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• 2018

The design wind pressure for low-rise buildings in the ASCE 7-10 is defined by procedures that are categorized into the Main Wind Force-Resisting System (MWFRS) and the Components and Cladding (C&C). Some of these procedures were originally developed based on steel portal frames of industrial buildings, while the residential structures are a completely different structural system, most of which are designed as low-rise light-frame wood constructions. The purpose of this study is to discuss the rationality (or irrationality) of the extension of the wind loads calculated by the ASCE 7-10 to the light-frame wood residential buildings that represent the most vulnerable structures under extreme wind conditions. To serve this purpose, the same approach as used in the development of Chapter 28 of the ASCE 7-10 that envelops peak responses is adopted in the present study. Database-assisted design (DAD) methodology is used by applying the dynamic wind loads from Louisiana State University (LSU) database on a typical residential building model to assess the applicability of the standard by comparing the induced responses. Rather than the postulated critical member demands on the industrial building such as the bending moments at the knee, the maximum values at the critical points for wood frame buildings under wind loads are used as indicators for the comparison. Then, the critical members are identified through these indicators in terms of the displacement or the uplift force at connections and roof envelope. As a result, some situations for each of the ASCE 7 procedures yielding unconservative wind loads on the typical low-rise residential building are identified.

• Wind and Structures
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• 제6권2호
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• pp.107-126
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• 2003

This paper describes a simple and practical approach through the application of Linear Stochastic Estimation (LSE) to reconstruct wind-induced pressure time series from the covariance matrix for structural load analyses on a low building roof. The main application of this work would be the reduction of the data storage requirements for the NIST aerodynamic database. The approach is based on the assumption that a random pressure field can be estimated as a linear combination of some other known pressure time series by truncating nonlinear terms of a Taylor series expansion. Covariances between pressure time series to be simulated and reference time series are used to calculate the estimation coefficients. The performance using different LSE schemes with selected reference time series is demonstrated by the reconstruction of structural load time series in a corner bay for three typical wind directions. It is shown that LSE can simulate structural load time series accurately, given a handful of reference pressure taps (or even a single tap). The performance of LSE depends on the choice of the reference time series, which should be determined by considering the balance between the accuracy, data-storage requirements and the complexity of the approach. The approach should only be used for the determination of structural loads, since individual reconstructed pressure time series (for local load analyses) will have larger errors associated with them.

• 한국해양공학회지
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• 제35권3호
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• pp.173-182
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• 2021

The maneuvering performance of a ship on the actual sea is very different from that in calm water due to wave-induced motion. Enhancement of a ship's maneuverability in waves at the design stage is an important way to ensure that the ship navigates safely. This paper focuses on the maneuvering prediction of a Russian trawler in wind and irregular waves. First, a unified seakeeping and maneuvering analysis of a Russian trawler is proposed. The hydrodynamic forces acting on the hull in calm water were estimated using empirical formulas based on a database containing information on several fishing vessels. A simulation of the standard maneuvering of the Russian trawler was conducted in calm water, which was checked using the International Maritime Organization (IMO) standards for ship maneuvering. Second, a unified model of seakeeping and maneuvering that considers the effect of wind and waves is proposed. The wave forces were estimated by a three-dimensional (3D) panel program (ANSYS-AQWA) and used as a database when simulating the ship maneuvering in wind and irregular waves. The wind forces and moments acting on the Russian trawler are estimated using empirical formulas based on a database of wind-tunnel test results. Third, standard maneuvering of a Russian trawler was conducted in various directions under wind and irregular wave conditions. Finally, the influence of wind and wave directions on the drifting distance and drifting angle of the ship as it turns in a circle was found. North wind has a dominant influence on the turning trajectory of the trawler.

• 한국항공우주학회지
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• 제49권4호
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• pp.263-272
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• 2021

본 논문은 외장 분리 풍동시험 기법을 적용한 전산유체해석을 통하여 획득한 데이터와 풍동시험을 통하여 획득한 데이터를 비교 연구한 것이다. 전산유체해석은 하모닉 방정식을 적용한 비정상해석 기법을 사용하여 수행하였으며, 비정상 해석으로부터 외장의 공력계수들과 6 자유도 외장 분리 시뮬레이션을 위한 공력 데이터베이스를 생성하였다. 해당 데이터베이스와 풍동시험 기반 데이터베이스를 이용한 외장의 분리 궤적 시뮬레이션 수행하였으며, 그 결과를 비행시험 결과와 비교하였다. 비교를 통하여 시뮬레이션의 적절성을 확인하였으며, 외장 분리 풍동시험 기법을 전산유체해석에 적용하여 획득한 외장 분리 공력 데이터베이스는 외장분리 궤적 시뮬레이션 적용에 타당함을 확인하였다.

• Wind and Structures
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• 제15권5호
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• pp.355-367
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• 2012

Atmospheric boundary layer winds experience two types of effects due to friction at the ground surface. One effect is the increase of the wind speeds with height above the surface. The second effect, called the Ekman layer effect, entails veering - the change of the wind speed direction as a function of height above the surface. In this study a practical procedure is developed within a database-assisted design (DAD) framework that accounts approximately for veering effects on tall building design. The procedure was applied in a case study of a 60-story reinforced concrete building, which also considered the dependence of veering effects on the orientation of the building. Comparisons are presented between response estimates that do not account for veering, and account for veering conservatively. For the case studied in this paper veering effects were found to be small.

• 한국환경과학회지
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• 제19권9호
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• pp.1169-1175
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• 2010

A case study for the design of a wind farm in complex terrain was carried out using the wind farm site analysis software OpenWind, which has an open-source platform and is free to use. The Youngdeok Wind Farm, constructed on mountainous terrain in Korea, was chosen as a model site; the design process reproduced using OpenWind. A comparison of the positions of the wind turbine derived from the OpenWind optimization process and the current positions were in good agreement. The annual energy production predicted by OpenWind compared with the prediction by the micrositing software, WindSim, were also validated to within 1%. Therefore, it was confirmed that OpenWind can be used for a practical wind farm design project. It is also anticipating that this paper will provide a prototype process for the design of a wind farm site and offer a database for the post-evaluation of a constructed wind farm in Korea.

• 풍력에너지저널
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• 제9권4호
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• pp.65-71
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• 2018

To establish an offshore wind turbine test site, a wind resource assessment of the candidate site is required as a preliminary procedure. The wind resource assessment must be performed with at least one year of wind data. If the assessment is performed with short-term wind data, the results cannot validate the wind conditions of the candidate site. This study performs wind resource assessment of Kokunsangun-do to investigate the wind conditions of the candidate site. The wind data is measured by the Automatic Weather System (AWS) of the Korea Meteorological Administration, located at Maldo. The data is for five years, measured from 2013 to 2017. Measured wind data is statistically processed with a 10-minute average scheme to find out the dominant wind direction and wind power density, with yearly wind speed distribution (Weibull-based). This study contributes to build a database of wind energy resources around Maldo. Also, the results of this study could be used for the establishment of an offshore wind turbine test site.

• Wind and Structures
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• 제36권6호
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• pp.393-404
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• 2023

Skewness and kurtosis are important higher-order statistics for simulating non-Gaussian wind pressure series on low-rise buildings, but their predictions are less studied in comparison with those of the low order statistics as mean and rms. The distribution gradients of skewness and kurtosis on roofs are evidently higher than those of mean and rms, which increases their prediction difficulty. The conventional artificial neural networks (ANNs) used for predicting mean and rms show unsatisfactory accuracy in predicting skewness and kurtosis owing to the limited capacity of shallow learning of ANNs. In this work, the deep neural networks (DNNs) model with the ability of deep learning is introduced to predict the skewness and kurtosis on a low-rise building. For obtaining the optimal generalization of the DNNs model, the hyper parameters are automatically determined by Bayesian Optimization (BO). Moreover, for providing a benchmark for future studies on predicting higher order statistics, the data sets for training and testing the DNNs model are extracted from the internationally open NIST-UWO database, and the prediction errors of all taps are comprehensively quantified by various error metrices. The results show that the prediction accuracy in this study is apparently better than that in the literature, since the correlation coefficient between the predicted and experimental results is 0.99 and 0.75 in this paper and the literature respectively. In the untrained cornering wind direction, the distributions of skewness and kurtosis are well captured by DNNs on the whole building including the roof corner with strong non-normality, and the correlation coefficients between the predicted and experimental results are 0.99 and 0.95 for skewness and kurtosis respectively.

• ETRI Journal
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• 제37권2호
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• pp.283-294
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• 2015

A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year-long period. A wind power pattern prediction stage uses a time interval feature that is essential for producing representative patterns through a projected clustering technique along with the existing temperature and wind direction from the classifier input. During this stage, this feature is applied to the wind speed, which is the most significant input of a forecasting model. As the test results show, nine hourly power patterns and seven daily power patterns are produced with respect to the Korean wind turbines used in this study. As a result of forecasting the hourly and daily power patterns using the temperature, wind direction, and time interval features for the wind speed, the ANFIS and SMO models show an excellent performance.

• Wind and Structures
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• 제30권3호
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• pp.289-298
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• 2020

Gusts generated by downburst have caused a great variety of structural damages in many regions around the world. It is of great significance to accurately evaluate the downburst-induced wind load on high-rise building for the wind resistance design. The main objective of this paper is to propose a computational modeling approach which can satisfactorily predict the mean and fluctuating wind pressure coefficients induced by downburst on high-rise building surfaces. In this study, using an impinging jet to simulate downburst-like wind, and simultaneous pressure measurements are obtained on a high-rise building model at different radial locations. The model test data are used as the database for developing back propagation neural network (BPNN) models. Comparisons between the BPNN prediction results and those from impinging jet test demonstrate that the BPNN-based method can satisfactorily and efficiently predict the downburst-induced wind pressure coefficients on single and overall surfaces of high-rise building at various radial locations.