The aerodynamic roughness of textile materials

Hsu, X. Y.; Miau, Jiun‐Jih; Tsai, J. H.; Tsai, Z. X.; Lai, Yi Hsuan; Ciou, Y. S.; Shen, Peihui; Chuang, Pei Chin; Wu, Chang-Mou

doi:10.1080/00405000.2018.1518636

Cited by 9 publications

(9 citation statements)

References 20 publications

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“…In the C D distribution of 2RT, a minimum C D value can be identified at Re between 7 Â 10 5 and 8 Â 10 5 , beyond which the C D value gets increased. This appearance infers the existence of a (Hsu et al, 2019). A similar finding was pointed out by Basu (1985) in reviewing the experimental results of flows over roughened two-dimensional circular cylinders.…”

Section: Results Of the Wind-tunnel Experimentssupporting

confidence: 82%

“…In the literature, a number of studies have modeled the flow phenomenon using single circular cylinder or multiple circular cylinders roughened with textile materials (Chowdhury et al, 2009(Chowdhury et al, , 2014Oggiano et al, 2007Oggiano et al, , 2009. Recently, Hsu et al (2019) performed an experimental work with 38 fabric samples tested on a circular cylinder in a wind tunnel experiment, and concluded that the roughness of the textile materials could be expressed in terms of the Nikuradse's sand-grain roughness (Nikuradse, 1937). By this finding, the effect of textile roughness on the drag crisis phenomenon could be described by the empirical relations originally proposed for other types of roughness elements (Basu, 1985).…”

Section: Introductionmentioning

confidence: 99%

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A study of drag reduction with textile roughness on a cyclist model

Hsu

Miau

et al. 2021

The Journal of The Textile Institute

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Efforts were made to examine the effect of textile roughness for the reduction of aerodynamic drag experienced on a cyclist model. First of all, flow visualization experiments were conducted in a water channel with a 1/5 scale cyclist model to identify the flow separation lines on the contoured surface. Subsequently, based on the information learned, the idea of delaying flow separation on the model surface was implemented by means of sport suits. Seven sport suits featuring different textile materials and local roughness patterns were tested on a full-scale cyclist model in wind tunnel experiments, in addition to a reference case without a sport suit. From the C D data deduced, we identified a critical condition in most of the cases studied, featuring a least drag coefficient occurred at a Reynolds number within the flow speed range studied. For the best case found, the drag coefficient is amounted 7.5% less than that of the reference case at the same Reynolds number. Furthermore, the C p and C prms values reduced from the pressure measurements on the cyclist model with the sport suits unveil a trend that the reduction of drag actually infers the retreat of the local flow separation lines toward the rear side of the body accompanied with less severe the flow unsteadiness.

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Section: Results Of the Wind-tunnel Experimentssupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

A study of drag reduction with textile roughness on a cyclist model

Hsu

Miau

et al. 2021

The Journal of The Textile Institute

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“…A cyclist is regarded as a blunt body since a large portion of the drag produced is associated with the form drag. For a cyclist at a fixed posture, the drag coefficient may vary with the Reynolds number (Defraeye et al 2010a(Defraeye et al , 2011 as well as the surface roughness as introduced by the sportware (Oggiano et al 2007(Oggiano et al , 2009Chowdhury and Alam 2014;Hsu et al 2019).…”

Section: Introductionmentioning

confidence: 99%

On the aerodynamic flow around a cyclist model at the hoods position

Miau

Tsai

et al. 2019

J Vis

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Aerodynamic flow around an 1/5 scale cyclist model was studied experimentally and numerically. First, measurements of drag force were performed for the model in a low-speed wind tunnel at Reynolds numbers from 5:5 Â 10 4 to 1:8 Â 10 5. Meanwhile, numerical computation using a large eddy simulation method was performed at three Reynolds numbers of 1:1 Â 10 4 , 6:5 Â 10 4 and 1:5 Â 10 5 to obtain the drag coefficients for comparison. Second, flow visualization was made in a water channel and the wind tunnel mentioned to examine the three-dimensional flow separation pattern on the model surface, which could also be realized from the numerical results. Finally, a wake flow survey based on the hot-wire measurements in the wind tunnel showed that in the near-wake region, the flow was featured with the formation of multiple streamwise vortices. The numerical results further indicated that these vortices were evolved from the separated flows occurred on the model surface.

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“…Some researchers 11,12 have used roughness as the characteristic quantity of fabric morphology to predict the drag crisis. However, this method could result in many fabrics with effectively the same roughness but with very different morphologies.…”

mentioning

confidence: 99%

“…Therefore, the creation of a prediction model for quickly determining the aerodynamic characteristics of fabric is essential. Some researchers 11,12 have used roughness as the characteristic quantity of fabric morphology to predict the drag crisis. However, this method could result in many fabrics with effectively the same roughness but with very different morphologies.…”

mentioning

confidence: 99%

Quantification of fabric morphology and prediction of drag crisis based on the fractal dimension

Jiang

Sun²,

Qiu

et al. 2022

Textile Research Journal

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This paper focused on investigating the relationship between fabric morphology and aerodynamic drag. The fractal theory is used to quantify the fabric surface morphology, and its influence on the minimum drag coefficient and critical Reynolds number is evaluated. In addition, the effectiveness of the fractal dimension in predicting the drag crisis is verified. It is observed that with the increase of the fractal dimension, the minimum drag coefficient increases, and the correlation coefficient can reach 0.9728, while the corresponding critical Reynolds number decreases, and the correlation coefficient can reach 0.9334. In addition, the accuracy of predicting drag crisis by the fractal dimension is verified and the relative error of predicting the drag crisis by the fractal dimension is less than 10%, which is significantly better than that by roughness.

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The aerodynamic roughness of textile materials

Cited by 9 publications

References 20 publications

A study of drag reduction with textile roughness on a cyclist model

A study of drag reduction with textile roughness on a cyclist model

On the aerodynamic flow around a cyclist model at the hoods position

Quantification of fabric morphology and prediction of drag crisis based on the fractal dimension

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