Theoretical Study of the Strength of Single Jet False Twist Spun Yarns

Krause, Hartmut; Soliman, H.A.

doi:10.1177/004051759006000601

Cited by 25 publications

(7 citation statements)

References 6 publications

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“…Thus, in this section, was designed for optimizing both mechanical and triboelectrification performance. Figure 3 a shows the geometry and forces acting on a warping pitch of the co-wrapped yarn [ 49 – 52 ]. When the co-wrapped yarn is subjected to longitudinal force ( ), the force is separately shared by the warp ( ) and core ( ) sections.…”

Section: Resultsmentioning

confidence: 99%

“…The contribution of wrapper stress to the yarn strength ( ) can be expressed as Eq. 4 [ 49 , 50 ]: Thus, as the wrapping density is increased, is increased, and the contribution of wrapped fiber to the yarn strength is decreased. In our cases, the contribution of wrapper fibers can be ignored because SSF is much stiffer and ductile than both SF and PTFEF.…”

Section: Resultsmentioning

confidence: 99%

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Ultrastable and High-Performance Silk Energy Harvesting Textiles

Dong

Ren

et al. 2019

Nano-Micro Lett.

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• An energy harvesting textile with an elegant trade-off of mechanical and triboelectric performance was constructed by hierarchical structural design. • Modified rotor co-spinning technique was developed to produce triboelectric yarns in large scale. • Mass-producible energy harvesting textiles show ultrahigh stability withstands millions of multi-type cyclic deformations and various applications. ABSTRACT Energy harvesting textiles (EHTs) have attracted much attention in wearable electronics and the internet-of-things for real-time mechanical energy harvesting associated with human activities. However, to satisfy practical application requirements, especially the demand for long-term use, it is challenging to construct an energy harvesting textile with elegant trade-off between mechanical and triboelectric performance. In this study, an energy harvesting textile was constructed using natural silk inspired hierarchical structural designs combined with rational material screening; this design strategy provides multiscale opportunities to optimize the mechanical and triboelectric performance of the final textile system. The resulting EHTs with traditional advantages of textiles showed good mechanical properties (tensile strength of 237 ± 13 MPa and toughness of 4.5 ± 0.4 MJ m −3 for single yarns), high power output (3.5 mW m −2), and excellent structural stability (99% conductivity maintained after 2.3 million multi-type cyclic deformations without severe change in appearance), exhibiting broad application prospects in integrated intelligent clothing, energy harvesting, and human-interactive interfaces.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Ultrastable and High-Performance Silk Energy Harvesting Textiles

Dong

Ren

et al. 2019

Nano-Micro Lett.

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“…Empirical models are easy to establish. 5,6 However, the establishment of the empirical relationship between yarn tenacity and parameters is based on the data obtained from experiments which are expensive and time-consuming. The most obvious shortcoming of the empirical model is that it is not applicable for the prediction outside the range within which the data were collected.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the vortex yarn tenacity from some process and nozzle parameters based on numerical simulation and artificial neural network

Pei

2011

Textile Research Journal

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In this study, two methods, the numerical simulation and the artificial neural network, are adopted to predict the vortex yarn tenacity from some process and nozzle parameters. The fiber-airflow interaction and the motional characteristics of the fiber inside the vortex spinning nozzle are analyzed through the numerical simulation method to predict the yarn tenacity from the parameters of the jet orifice diameter and the yarn delivery speed. The back-propagation multilayer perceptron (MLP) neural network is adopted to predict the tenacity of vortex yarn spun from modal fibers. The following parameters are used as inputs: nozzle pressure, jet orifice angle, distance between the guiding needle and the spindle, and spindle cone angle. The predicted and measured tenacities show low relative errors and a high correlation coefficient, indicating the artificial neural network method provides accurate prediction results. In addition, the effects of these parameters on the yarn tenacity are also analyzed.

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“…The strength of wrapping fibers, the core fibers and the frictional resistance of the slipping fibers in the core is the load bearing components of the yarn. Their equation indicated to what extent yarn strength depends on the following major parameters: position of the wrapping fibers, average wrapping length, the angle, fiber strain, fiber-to-fiber friction and fiber slenderness 20 . Tyagi, Goyal, and Salhotra studied the effect of various process parameters on the sheath slippage resistance of air-jet spun yarns.…”

Section: Introductionmentioning

confidence: 99%

Tensile Behaviour of Spun Yarns under Static State

Das¹

2010

Journal of Engineered Fibers and Fabrics

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The tensile properties of spun yarn are accepted as one of the most important parameters for assessment of yarn quality. The tensile properties decide the performance of post spinning operations; warping, weaving and knitting and the properties of the final textile structure; hence its accurate technical evaluation carries much importance in industrial applications. There is no doubt that all the studies related to tensile behaviour of spun yarns are invaluable both in theory and practice. In this article, a critical review of the theoretical and practical aspect of static tensile behaviour of staple yarns has been discussed.

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Theoretical Study of the Strength of Single Jet False Twist Spun Yarns

Cited by 25 publications

References 6 publications

Ultrastable and High-Performance Silk Energy Harvesting Textiles

Ultrastable and High-Performance Silk Energy Harvesting Textiles

Prediction of the vortex yarn tenacity from some process and nozzle parameters based on numerical simulation and artificial neural network

Tensile Behaviour of Spun Yarns under Static State

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