Investigation and Prediction the Permeability of Woollen Fabrics

Year 2025, Volume: 8 Issue: 6, 1967 - 1976, 15.11.2025

Zehra Evrim Kanat

https://doi.org/10.34248/bsengineering.1684058

Abstract

The water vapor and air permeability properties of fabrics are the determining factors for thermal comfort. It is stated in the literature that the hygroscopic structure of wool fibre and the fibre surface properties improve the water vapor permeability property, thus increasing the sense of comfort. In this study water vapor and air permeability of 16 woollen fabric were investigated. It was shown that the effect of finishing process, weave type and raw material on air permeability is significant. In case of water vapor permeability, the effect of finishing process and weave type was found to be significant in the 95% confidence interval, while the effect of raw material was not found to be significant. Furthermore, permeability properties of woollen fabrics were predicted both multiple linear regression and artificial neural network. The R2 values of the models were 0.989 and 0.485 obtained with multiple linear regression and 0.988 and 0.773 obtained with artificial neural network, for air and water vapor permeability, respectively. Results of the artificial neural network were quite good especially for water vapor permeability.

Keywords

Air permeability , Water vapor permeability , Artificial neural network , Linear regression , Woollen fabric

Ethical Statement

Ethics committee approval was not required for this study because of there was no study on animals or humans.

Project Number

NKUBAP.00.17.AR.14.13.

Thanks

This work was supported by the Office of Scientific Research Projects Coordination at Namık Kemal University Project number: NKUBAP.00.17.AR.14.13. The author wishes to thank YÜNSA A.Ş. for providing the fabrics in the study.

References

• Afzal A, Hussain T, Malik MH, Javed Z. 2014. Statistical model for predicting the air permeability of polyester/cotton-blended interlock knitted fabrics. J Text Inst, 105(2): 214-222.
• Afzal A, Hussain T, Malik MH, Rasheed A, Ahmad S, Basit A, Nazir A. 2014. Investigation and modeling of air permeability of cotton/polyester blended double layer interlock knitted fabrics. Fibers Polym, 15(7): 1539-1547.
• Asfand N, Petraitienė S, Daukantienė V. 2024. Linear regression analysis of properties related to moisture management using cotton–polyester knitted fabrics. Text Res J, 94(15-16): 1737-1751.
• Atmaca M, Dal V, Yılmaz A, Kurtulus AB. 2015. Investigation of the effects of fabric parameters on air permeability of woolen fabrics. Text Res J, 85(20): 2099–2107.
• Baghdadi R, Alibi H, Fayala F, Zeng X. 2016. Investigation on air permeability of finished stretch plain knitted fabrics. I. Predicting air permeability using artificial neural networks. Fibers Polym, 17(12): 2105-2115.
• Bedek G, Salaün F, Martinkovska Z, Devaux E, Dupont D. 2011. Evaluation of thermal and moisture management properties on knitted fabrics and comparison with a physiological model in warm conditions. Appl Ergon, 42(6): 792-800.
• Behera BK, Mishra R. 2007. Comfort properties of non-conventional light weight worsted suiting fabrics. Indian J Fibre Text, 32:72-79.
• Benltoufa S, Boughattas A, Fayala F, Algamdy H, Alfaleh A, Hes L, Aljuaid A. 2024. Water vapour resistance modelling of basic weaving structure. J Text Inst, 115(12): 2456-2468.
• Bogusławska-Bączek M, Hes L. 2013. Effective water vapour permeability of wet wool fabric and blended fabrics. Fibres Text East Eur, 21, 1(97): 67-71.
• Çay A, Tarakçioğlu I. 2008. Relation between fabric porosity and vacuum extraction efficiency: Energy issues, J Text Inst, 99(6): 499-504.
• Das B, Das A, Kothari VK, Fanguiero R, de Araújo M. 2007. Moisture transmission through textiles Part I: Processes involved in moisture transmission and the factors at play. Autex Res J, 7(2): 100-110.
• Das B, Das A, Kothari VK, Fanguiero R, de Araújo M. 2009. Studies on moisture transmission properties of PV-blended fabrics. J Text Inst, 100(7):588-597.
• Das B, de Araújo M, Kothari VK, Fanguiero R, Das A. 2012. Modeling and simulation of moisture transmission through fibrous structures part i: water vapour transmission. J Fiber Bioeng Inform, 5(4): 1–20.
• Erenler A, Oğulata RT. 2015. Investigation and prediction of chosen comfort properties on woven fabrics for clothing. Tekst Konfeksiyon, 25(2):125-134.
• Ghorbani E, Zarrebini M, Hasani H, Shanbeh M. 2015. Modeling the moisture and heat transfer of warp knitted spacer fabrics using artificial neural network algorithm. Text Light Ind Sci Tech, 4(1): 17-26.
• Havlová M. 2020. Air permeability, water vapour permeability and selected structural, parameters of woven fabrics. Fibres Text, 27 (1):12-18.
• Hristian L, Ostafe MM, Manea LR, Apostol LL. 2017. Study of Mechanical Properties of Wool Type Fabrics using ANCOVA Regression Model. IOP Conf. Ser.: Mater Sci Eng, 209.
• Irandoukht S, Irandoukht A. 2011. Development of the predictive models for the fabric water vapor resistance. J Eng Fiber Fabr, 6(2): 40-49.
• Karaca E, Kahraman N, Omeroglu S, Becerir B. 2012. Effects of fiber cross sectional shape and weave pattern on thermal comfort properties of polyester woven fabrics. Fibres Text East Eur, 20(3(92)): 67-72.
• Li X, Cong H, Gao Z, Dong Z. 2020. Thermal-wet model of knitted double jersey based on backpropagation algorithm of neural network. J Eng Fibers Fabr, 15: 1-11.
• Li Y. 2005. Perceptions of temperature, moisture and comfort in clothing during environmental transients. Ergonomics, 48(3): 234-248.
• Malik SA, Kocaman RT, Kaynak HK, Gereke T, Aibibu D, Babaarslan O, Cherif C. 2017. Analysis and prediction of air permeability of woven barrier fabrics with respect to material, fabric construction and process parameters. Fibers Polym, 18(10): 2005-2017.
• Malik SA, Saleemi S, Mengal N. 2016. Predicting hydrophobicity of silica sol-gel coated dyed cotton fabric by artificial neural network and regression. Indian J Fibre Text, 41: 67-72
• Manshahia M, Das A. 2014. Thermophysiological comfort characteristics of plated knitted fabrics. J Text Inst, 105(5): 509-519.
• Maqsood M, Nawab Y, Shaker K, Umair M, Ashraf M, Baitab DM, Hamdani STA, Shahid S. 2016. Modelling the effect of weave structure and fabric thread density on mechanical and comfort properties of woven fabrics. Autex Res J, 16(3): 160-164.
• Militký J, Kovačič V, Rubnerova J, Trávničková M. 2001. Air Permeability and Porosity Evaluation of Antiallergical Bed Linen. In Medical Textiles, Woodhead Publishing, pp: 117-123.
• Neway SD. 2021. Statistical analysis of effects of fabric thickness, loop shape factor, fabric tightness factor and aerial weight on water vapor permeability of single jersey polyester knitted fabric. Int J Sci Res Comp Sci Eng, 9(6): 55-62. URL: https://ssrn.com/abstract=4014390 (accessed date: July 24, 2024).
• Ogulata RT, Mavruz S. 2010. Investigation of porosity and air permeability values of plain knitted fabrics. Fibres Text East Eur, 18(5 (82)):71-75.
• Önder E. 1995. Tekstil mekaniği ii dokunmuş kumaş geometrisi ve mekaniği, İ.T.Ü. Makine Fakültesi Ofset Atölyesi, İstanbul, Türkiye, pp: 103.
• Öner E, Atasağun HG, Okur A, Beden AR, Durur G. 2013, Evaluation of moisture management properties on knitted fabrics. J Text Inst, 104(7): 699-707.
• Shabaridharan, Das A. 2013. Statistical and ANN analysis of thermal and evaporative resistances of multilayered fabric ensembles. J Text Inst, 104(9):950-964.
• Tashkandi S, Fergusson SM, Wang L, Kanesalingam S. 2013. Thermal comfort properties of wool and polyester/wool woven fabrics dyed in black. Fiber Bioeng Inform, 6(3): 265- 275.
• Varshney RK, Kothari VK, Dhamija S. 2010. A study on thermophysiological comfort properties of fabrics in relation to constituent fibre fineness and cross-sectional shapes. J Text Inst, 101 (6): 495-505.
• Zhou L, Feng X, Du Y, Li Y. 2007. Characterization of liquid moisture transport performance of wool knitted fabrics. Text Res J, 77(12):951-956.