• Wind and Structures
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• v.30 no.3
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• pp.299-316
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• 2020

Based on wind tunnel tests, this paper investigates the aerodynamic behavior of a large span canopy roof with elliptical plan and hyperbolic paraboloid shape. The statistics of pressure coefficients and the peak factor distributions are calculated for the top and bottom faces of the roof, and the Gaussian or non-Gaussian characteristics of the pressure time-histories in different areas of the roof are discussed. The cross-correlation of pressures at different positions on the roof, and between the top and bottom faces is also investigated. Combination factors are also evaluated to take into account the extreme values of net loads, relevant to the structural design of canopies.

• Wind and Structures
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• v.22 no.5
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• pp.573-594
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• 2016

Simultaneous pressure measurements on 2D square prisms with various corner modifications were performed in uniform flow with low turbulence level, and the testing Reynolds numbers varied from $1.0{\times}10^5$ to $4.8{\times}10^5$. Experimental models were a square prism, three chamfered-corner square prisms (B/D=5%, 10%, and 15%, where B is the chamfered corner dimension and D is the cross-sectional dimension), and six rounded-corner square prisms (R/D =5%, 10%, 15%, 20%, 30%, and 40%, where R is the corner radius). Experimental results of drag coefficients, wind pressure distributions, power spectra of aerodynamic force coefficients, and Strouhal numbers are presented. Ten models are divided into various categories according to the variations of mean drag coefficients with Reynolds number. The mean drag coefficients of models with $B/D{\leq}15%$ and $R/D{\leq}15%$ are unaffected by the Reynolds number. On the contrary, the mean drag coefficients of models with R/D=20%, 30%, and 40% are obviously dependent on Reynolds number. Wind pressure distributions around each model are analyzed according to the categorized results.The influence mechanisms of corner modifications on the aerodynamic characteristics of the square prism are revealed from the perspective of flow around the model, which can be obtained by analyzing the local pressures acting on the model surface.

• Wind and Structures
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• v.19 no.6
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• pp.623-647
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• 2014

In this paper, a probability distribution which is consistent with the observed phenomenon at the roof corner and, also on other portions of the roof, of a low-rise building is proposed. The model is consistent with the choice of probability density function suggested by the statistical thermodynamics of open systems and turbulence modelling in fluid mechanics. After presenting the justification based on physical phenomenon and based on statistical arguments, the fit of alpha-stable distribution for prediction of extreme negative wind pressure coefficients is explored. The predictions are compared with those actually observed during wind tunnel experiments (using wind tunnel experimental data obtained from the aerodynamic database of Tokyo Polytechnic University), and those predicted by using Gumbel minimum and Hermite polynomial model. The predictions are also compared with those estimated using a recently proposed non-parametric model in regions where stability criterion (in skewness-kurtosis space) is satisfied. From the comparisons, it is noted that the proposed model can be used to estimate the extreme peak negative wind pressure coefficients. The model has an advantage that it is consistent with the physical processes proposed in the literature for explaining large fluctuations at the roof corners.

• Wind and Structures
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• v.36 no.6
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.4
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• pp.76-85
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• 1993

The purpose of this study was to analyze the wind force distribution on the two single-span arched plastic house depending upon the house spacing and wind direction, which may provide the fundamental criteria for the structural design. In order to specify the wind force distribution, the variation of the wind force coefficients, the mean wind force coefficients and the drag force coefficients were estimated from the wind tunnel test data. The results obtained are as follows : 1. At the wind direction of 90$^{\circ}$, there was a typical span interval at which the maximum negative pressure was occured at the edge of the inside walls. 2. In the consideration of wind loads, the wind force coefficients estimated from independent single-span arched plastic house should not be directly applied to the structural design on the double houses separated. 3. The average maximum negative wind force on the inside walls was occured at the wind direction of 90$^{\circ}$, and the variations depending on the span intervals was not significant. 4. The average maximum drag force was occured at the wind direction of 300, and the magnitude of drag force was more significant at the first house. As the distance between two houses was increased, the drag force was slightly increased for every wind direction.

• Wind and Structures
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• v.30 no.2
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• pp.199-210
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• 2020

Building wind pressure coefficient transiting test is a new method to test the building wind pressure coefficient by using the wind generated by a moving vehicle, which is susceptible to natural wind and other factors. In this paper, the Commonwealth Advisory Aeronautical Research Council standard model with a scale ratio of 1:300 is used as the test object, and the wind pressure coefficient transiting test is repeated under different natural wind conditions to study the influence of natural wind. Natural wind is measured by an ultrasonic anemometer at a fixed location. All building wind pressure coefficient transiting tests meet the test conditions, and the vehicle's driving speed is 72 km/h. The mean wind pressure coefficient, the fluctuating wind pressure coefficient, and the correlation coefficient of wind pressure are used to describe the influence of natural wind on the building wind pressure coefficient transiting test qualitatively and quantitatively. Some rules, which can also help subsequent transiting tests, are also summarized.

• Wind and Structures
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• v.23 no.3
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• pp.231-251
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• 2016

This paper presents the experimental results of the wind tunnel tests for three symmetric, rectangular, tall building models on a typical open terrain considering the torsional motion-induced vibrations. The time histories of the wind pressure on these models under different reduced wind speeds and torsional amplitudes are obtained through the multiple point synchronous scanning pressure technique. Thereafter, the characteristics of both the Root Mean Square (RMS) coefficients and the spectra of the base shear/torque in the along-wind, across-wind, and torsional directions, respectively, are discussed. The results show that the RMS coefficients of the base shear/torque vary in the three directions with both the reduced wind speeds and the torsional vibration amplitudes. The variation of the RMS coefficients in the along-wind direction results mainly from the change of the aerodynamic forces, but sometimes from aeroelastic effects induced by torsional vibration. However, the variations of the RMS coefficients in the across-wind and torsional directions are caused by more equal weights of both the aerodynamic forces and the aeroelastic effects. As such, for the typical tall buildings, the modification of the aerodynamic forces in the along-wind, across-wind, and torsional directions, respectively, and the aeroelastic effects in the across-wind and torsional directions should be considered. It is identified that the torsional vibration amplitudes and the reduced wind speeds are two significant parameters for the aerodynamic forces on the structures in the three directions.

• Journal of Korean Association for Spatial Structures
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• v.20 no.4
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• pp.63-71
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• 2020

The fluctuating wind pressure of the low rise ratio(f/D=0.1) for the elliptical dome roof was analyzed to compare it with the previous studies of circular dome roofs. Wind tunnel test were conducted on a total of 10 wind directions from 0° to 90° while changing wall height-span ratios(H/D=0.1-0.5). For this, meanCP, rmsCP and wind pressure spectrum were analyzed. The analysis result leads to find differences in the shape of the spectra in the spanwise direction and leeward of the elliptical dome according to the wind direction variations of the elliptical dome roof.

• Wind and Structures
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• v.31 no.4
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• pp.287-298
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• 2020

This paper presents an experimental investigation on the surface pressures on the CAARC standard tall building model concerning the effects of freestream turbulence. Two groups of incidence turbulence are generated in the wind tunnel experiment. The first group has an approximately constant turbulence intensity of 10.3% but different turbulence integral scale varying from 0.141 m to 0.599 m or from 0.93 to 5.88 in terms of scale ratio (turbulence integral scale to building dimension). The second group presents similar turbulence integral scale but different turbulence intensity ranging from 7.2% to 13.5%. The experimental results show that the mean pressure coefficients on about half of the axial length of the side faces near the leading edge slightly decrease as the turbulence integral scale ratio that is larger than 4.25 increases, but respond markedly to the changes in turbulence intensity. The root-mean-square (RMS) and peak pressure coefficients depend on both turbulence integral scale and intensity. The RMS pressure coefficients increase with turbulence integral scale and intensity. As the turbulence integral scale increases from 0.141 m to 0.599 m, the mean peak pressure coefficient increases by 7%, 20% and 32% at most on the windward, side faces and leeward of the building model, respectively. As the turbulence intensity increases from 7.2% to 13.5%, the mean value of peak pressure coefficient increases by 47%, 69% and 23% at most on windward, side faces and leeward, respectively. The values of cross-correlations of fluctuating pressures increase as the turbulence integral scale increases, but decrease as turbulence intensity increases in most cases.

• Journal of Korean Association for Spatial Structures
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• v.13 no.2
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• pp.67-73
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• 2013

This paper attempted to bridge this gap by identifying the number of flat-plate solar collectors. The characteristics of wind pressure coefficients acting on flat-plate solar collectors which are most widely used were investigated for various wind direction. Findings from this study found that the location where the maximum wind pressure coefficient occurred in the solar collector was the edge of the collector. Regarding the characteristics according to the number of collectors, the paper found that downward wind pressure coefficient of the lower edge of the collector was higher than the upward wind pressure coefficient of the upper edge of the collector in the basic module (1 piece). However, as the number of collectors increases, the upward wind pressure coefficient of the upper edge become higher than the downward wind pressure coefficient of the lower edge. Finally yet important, it was found that the location of the maximum wind pressure coefficient was changed according to the number of solar collectors.