Abstract:The relationship between yarn properties, fabric parameters, and shear stiffness of worsted fabrics is modeled using the soft computing technique. Because of the small number of samples, the artificial neural network model to be established must be a small-scale one. Therefore, this soft computing approach includes two stages. First, the yarn properties and fabric parameters are selected by utilizing an input variable selection method, so as to find the most relevant yarn properties and fabric parameters as the input variables to fit the small-scale artificial neural network model. The first part of this method takes the human knowledge on the shear stiffness of fabrics into account. The second part utilizes a data sensitivity criterion based on a distance method. Second, the artificial neural network model of the relationship between yarn properties, fabric parameters, and shear stiffness of fabrics is established. The results show that the artificial neural network model yields accurate prediction and a reasonably good artificial neural network model can be achieved with relatively few data points by integrating with the input variable selecting method developed in this research. The results also show that there is great potential for this research in the field of computer-assisted design in textile technology. 

In order to improve the performance of sodium (Na) montmorillonite (MMT), in this study, 1-hexadecyl-2,3-dimethylimidazolium bromide was synthesized and used as a cationic surfactant for the organic modification of sodium MMT. The modification effect of pH was investigated, and the structure of the imidazole organic modifier was characterized by nuclear magnetic resonance and Fourier transform infrared spectroscopy (FTIR). In addition, the modified sodium MMT was systematically confirmed by FTIR and X-ray diffraction. The results showed that the imidazolium surfactant successfully intercalated into the galleries of MMT and enlarged the (001) d spacing of MMT.It was observed that the d (001) peaks largely shift to the left with decreasing pH, indicating low pH-facilitated intercalation, and its effect reached the best at pH 3, where the interlayer distance between MMT platelets increased from 1·31 to 3·52 nm. Thermogravimetric analysis showed that the modified sodium MMT exhibited excellent thermal stability; the onset and the maximum decomposition temperature were 343 and 406°C respectively.