• Wind and Structures
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• v.16 no.6
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• pp.617-627
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• 2013

In wind load calculations based on pressure measurements, the concept of 'tributary area' is usually used. The literature has less guidance for a systematic computational methodology for calculating tributary areas, in general, and for scattered pressure taps, in particular. To the best of the author's knowledge, there is no generic mathematical equation that helps calculate the tributary areas for irregular pressure taps. Traditionally, the drawing of tributary boundaries for scattered and intensively distributed taps may not be feasible (a time and resource consuming task). To alleviate this problem, this paper presents a proposed numerical approach for tributary area calculations on rectangular surfaces. The approach makes use of the available coordinates of the pressure taps and the dimensions of the surface. The proposed technique is illustrated by two application examples: first, quasi-regularly distributed pressure taps, and second, taps that have scattered distribution on a rectangular surface. The accuracy and the efficacy of the approach are assessed, and a comparison with a traditional method is presented.

• Wind and Structures
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• v.36 no.6
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• pp.405-421
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• 2023

Strong wind is the main factors of wind-damage of high-rise buildings, which often creates largely economical losses and casualties. Wind pressure plays a critical role in wind effects on buildings. To obtain the high-resolution wind pressure field, it often requires massive pressure taps. In this study, two traditional methods, including bilinear and bicubic interpolation, and two deep learning techniques including Residual Networks (ResNet) and Generative Adversarial Networks (GANs), are employed to reconstruct wind pressure filed from limited pressure taps on the surface of an ideal building from TPU database. It was found that the GANs model exhibits the best performance in reconstructing the wind pressure field. Meanwhile, it was confirmed that k-means clustering based retained pressure taps as model input can significantly improve the reconstruction ability of GANs model. Finally, the generalization ability of k-means clustering based GANs model in reconstructing wind pressure field is verified by an actual engineering structure. Importantly, the k-means clustering based GANs model can achieve satisfactory reconstruction in wind pressure field under the inputs processing by k-means clustering, even the 20% of pressure taps. Therefore, it is expected to save a huge number of pressure taps under the field reconstruction and achieve timely and accurately reconstruction of wind pressure field under k-means clustering based GANs model.

• The KSFM Journal of Fluid Machinery
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• v.9 no.3 s.36
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• pp.22-28
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• 2006

The discharge coefficient in segmental wedge haying ninety degrees yeller angle for the five kinds of opening ratio with differential pressure taps located at both upstream and downstream of one diameter of pipe was measured. Main purpose of this work is placed on specifying the characteristic of discharge coefficient of a segmental wedge used as a primary element of flow metering devices, and suggestion for the fixed location of pressure taps useful. Although the range of the opening ratio over this work is more expanded than previous studies. The opening ratios of segmental wedge, namely 0.3, 0.4, 0.5, 0.6 and 0.7 were investigated. The Reynolds number based on the spool inside diameter ranges from 12,000 to 380,000.

• Wind and Structures
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• v.13 no.3
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• pp.257-273
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• 2010

The aerodynamic and aero-elastic model tests of the China''s highest cooling tower has been carried out in the TJ-3 Boundary Layer Wind Tunnel of Tongji University. By adopting a scanivalve system, the external wind pressure is firstly measured on $12{\times}36$ taps for a single tower, two and four grouped towers under the condition of both smooth flow and the boundary layer due to surrounding geographic and building topography. The measurements of internal wind pressure distribution of $6{\times}36$ taps are taken for a single tower under the various ventilation ratios ranging from 0% to 100% of stuffing layers located at the bottom of the tower. In the last stage, the wind tunnel tests with an aero-elastic model are carefully conducted to determine wind-induced displacements at six levels (each with eight points) with laser displacement sensors. According to the measurement results of wind pressure or vibration response, the extreme aerodynamic loading values of the single or grouped towers are accordingly analyzed based on probability correlation technique.

• Wind and Structures
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• v.36 no.4
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• pp.237-247
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• 2023

The emergence of high-rise buildings has necessitated frequent structural health monitoring and maintenance for safety reasons. Wind causes damage and structural changes on tall structures; thus, safe structures should be designed. The pressure developed on tall buildings has been utilized in previous research studies to assess the impacts of wind on structures. The wind tunnel test is a primary research method commonly used to quantify the aerodynamic characteristics of high-rise buildings. Wind pressure is measured by placing pressure sensor taps at different locations on tall buildings, and the collected data are used for analysis. However, sensors may malfunction and produce erroneous data; these data losses make it difficult to analyze aerodynamic properties. Therefore, it is essential to generate missing data relative to the original data obtained from neighboring pressure sensor taps at various intervals. This study proposes a deep learning-based, deep convolutional generative adversarial network (DCGAN) to restore missing data associated with faulty pressure sensors installed on high-rise buildings. The performance of the proposed DCGAN is validated by using a standard imputation model known as the generative adversarial imputation network (GAIN). The average mean-square error (AMSE) and average R-squared (ARSE) are used as performance metrics. The calculated ARSE values by DCGAN on the building model's front, backside, left, and right sides are 0.970, 0.972, 0.984 and 0.978, respectively. The AMSE produced by DCGAN on four sides of the building model is 0.008, 0.010, 0.015 and 0.014. The average standard deviation of the actual measures of the pressure sensors on four sides of the model were 0.1738, 0.1758, 0.2234 and 0.2278. The average standard deviation of the pressure values generated by the proposed DCGAN imputation model was closer to that of the measured actual with values of 0.1736,0.1746,0.2191, and 0.2239 on four sides, respectively. In comparison, the standard deviation of the values predicted by GAIN are 0.1726,0.1735,0.2161, and 0.2209, which is far from actual values. The results demonstrate that DCGAN model fits better for data imputation than the GAIN model with improved accuracy and fewer error rates. Additionally, the DCGAN is utilized to estimate the wind pressure in regions of buildings where no pressure sensor taps are available; the model yielded greater prediction accuracy than GAIN.

• Wind and Structures
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• v.12 no.6
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• pp.505-517
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• 2009

Synchronous wind-induced pressures, measured in wind-tunnel tests on model buildings instrumented with hundreds of pressure taps, are an invaluable resource for designing safe buildings efficiently. They enable a much more detailed, accurate representation of the forces and moments that drive engineering design than conventional tables and graphs do. However, the very large volumes of data that such tests typically generate pose a challenge to their widespread use in practice. This paper explains how a wavelet representation for the time series of pressure measurements acquired at each tap can be used to compress the data drastically while preserving those features that are most influential for design, and also how it enables incremental data transmission, adaptable to the accuracy needs of each particular application. The loss incurred in such compression is tunable and known. Compression rates as high as 90% induce distortions that are statistically indistinguishable from the intrinsic variability of wind-tunnel testing, which we gauge based on an unusually large collection of replicated tests done under the same wind-tunnel conditions.

• Wind and Structures
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• v.8 no.5
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• pp.357-372
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• 2005

Mean and extreme pressure distributions on a large cantilevered flat roof model are measured in a boundary layer wind tunnel. The largest peak suction values are observed from pressure taps beneath conical "delta-wing type" corner vortices that occur for oblique winds, then the characteristics and causes of the local peak suctions are discussed in detail. Power spectra of fluctuating wind pressures measured from some typical taps located at the roof edges under different wind directions are presented, and coherence functions of fluctuating pressures are also obtained. Based on these results, it is verified that the peak suctions are highly correlated with the conical vortices. Furthermore, according to the characteristics of wind loads on the roof, an aerodynamic solution to minimize the peak suctions by venting the leading edges and the corners of the roof is recommended. The experimental results show that the suggested strategy can effectively control the generation of the conical vortices and make a reduction of 50% in mean pressures and 25% in extreme local pressures at wind sensitive locations on the roof.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2177-2183
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• 1994

The rapid expansion or condensible gas such as moist air of steam gives rise to nonequilibrium condensation. As a result of irreversibility of condensation process in the supersonic cascade flow of low pressure steam turbine, the entropy of the flow is increased, and the efficiency of the turbine is decreased. In the present study, to investigate the flow of moist air in 2-dimensional cascade made as the configuration of the tip section of the last actual steam turbine moving blade, the static pressure at both sides of pressure and suction of blade are measured by static pressure taps and the distribution of Mach number on both surfaces of the blade are obtained by using the measured static pressure. Also, the flow field is visualized by a schlieren system. From the experimental results, the effects of the stagnation temperature and specific humidity on the flow properties in a 2-dimensional stationary cascade of a practical steam turbine blade are clearly identified.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.11
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• pp.3022-3030
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• 1995

The irreversibility of condensation process in the supersonic flow of steam turbine cascade causes the entropy to increase and the total pressure loss to be generated. In the present study, in order to investigate the moist air flow in two dimensional steam turbine cascade made as the configuration of the last stage tip section of the actual steam turbine moving blade, the static and total pressures along suction side of the blade are measured by pressure taps and Pitot tube. The flow field is visualized by a Schlieren system. The effects of stagnation temperature and the degree of supersaturation on energy loss and entropy change in the flow are clearly identified.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.73-79
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• 2004

An experimental and computational study has been performed for investigation of the jet interaction in supersonic flow with a ramp located behind a sonic, lateral jet. The experimental techniques include schlieren, pressure taps, and Pressure Sensitive Paint. The numerical solver used in this study is AeroSoft's structured flow solver GASP Version 4.0. A Mach 4 crossflow with a pressure ratio of 532, and the 3D ramp was designed by parametric study using GASP. The results showed that the ramp located downstream of the jet decrese the nose-down pitching moment by 70% without a force loss.