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A New Approach for Thermal Resistance Prediction of Different Composition Plain Socks in Wet State. Part 2

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Socks’ comfort has vast implications in our everyday living. This importance increased when we have undergone an effort of low or high activity. It causes the perspiration of our bodies at different rates. In this study, plain socks with different fiber composition were wetted to a saturated level. Then after successive intervals of conditioning, these socks are characterized by thermal resistance in wet state at different moisture levels. Theoretical thermal resistance is predicted using combined filling coefficients and thermal conductivity of wet polymers instead of dry polymer (fiber) in different models. By this modification, these mathematical models can predict thermal resistance at different moisture levels. Furthermore, predicted thermal resistance has reason able correlation with experimental results in both dry (laboratory conditions moisture) and wet states.
Rocznik
Strony
238--247
Opis fizyczny
Bibliogr. 33 poz.
Twórcy
  • Faculty of Textile Engineering, Technical University of Liberec, Liberec, Czech Republic
autor
  • Faculty of Textile Engineering, Technical University of Liberec, Liberec, Czech Republic
  • Faculty of Textile Engineering, Technical University of Liberec, Liberec, Czech Republic
Bibliografia
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  • [9] Bogusławska-Bączek, M., Hes, L. (2013). Effective water vapour permeability of wet wool fabric and blended fabrics. Fibres & Textiles in Eastern Europe, 21(97), 67–71.
  • [10] Oğlakcioğlu, N., Marmarali, A. (2010). Thermal comfort properties of cotton knitted fabrics in dry and wet states. Tekstil ve Konfeksiyon, 20(3), 213–217.
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  • [14] Richards, M. G. M., Rossi, R., Meinander, H., Broede, P., Candas, V., et al. (2008). Dry and wet heat transfer through clothing dependent on the clothing properties under cold conditions. International Journal of Occupational Safety Ergonomics, 14(1), 69–76.
  • [15] Kanat, Z. E., Özdil, N. (2018). Application of artificial neural network (ANN) for the prediction of thermal resistance of knitted fabrics at different moisture content. The Journal of the Textile Institute, 109(9), 1247–1253.
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  • [17] Qian, X., Fan, J. (2006). Prediction of clothing thermal insulation and moisture vapour resistance of the clothed body walking in wind. Annals of Occupational Hygiene, 50(8), 833–842.
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-42501d27-e7ab-4f7f-bc6e-7e203f42ce85
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