In this study, an attempt has been made to predict the drape profile of woven fabrics using finite element analysis. The finite element method has been used in the prediction of structural instability and post buckling behaviour. The drape parameters like Drape coefficient, Drape distance ratio, Fold depth index, Amplitude to radius ratio and Number of nodes predicted by finite element analysis were correlated with those measured by Digital Image Processing method. The correlation between digital image processing method and finite element analysis proves to be very good. In all cases, R 2 value is found to be higher than 0.8. In particular maximum correlation (R 2 = 0.91) is found in case of drape coefficient, because it is based on the project area of draped fabric in both the methods.
Enzymes are being extensively used in industry as they are environmentally friendly. They show a variety of advantages over chemicals, like their specificity, high efficiency and eco-friendliness. Nowadays different kinds of cellulase enzyme mixtures are commercially formulated for the finishing of cellulosic fabrics. This study investigated the effect of acid cellulase treatment on bamboo knitted-fabric to reduce pill. It has been observed that specific range of concentration only can effectively reduce pills with substantial weight loss. The common process and method followed by a textile chemist to optimize or standardize the concentration of enzyme treatment to reduce pill is still cumbersome and doubtful. A quicker and objective method is proposed to optimize the concentration of enzyme. The effectiveness is evaluated using standard Martindale tester and the weight loss of the fabric.
Fabric drape is one of the most important factors which affect the graceful appearance of the garment. The drape coefficient is the widely used parameter to describe fabric drape but it needs other parameters to explain the fabric behavior. In this study, we have investigated the relationship between the fabric drape parameters such as drape coefficient, drape distance ratio, fold depth index, amplitude and number of nodes and low stress mechanical properties. Drape parameters were tested on a specially developed instrument based on a digital image processing technique and the low stress mechanical properties were tested by the Kawabata evaluation system. Then the drape parameters were predicted by constructing models using multiple regressions method and feed-forward back-propagation neural network technique. Simple equations are derived using regressions method to predict the five shape parameters of drape profile from the low stress mechanical properties. It is observed that bending, shear and aerial density affect the drape parameters most whereas the tensile and compression have little effect on the drape parameters.
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