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Experimental data for fabric 1 with surface density 131 g/m 2 . irty two (32) setting points overlapped with the contour plots of responses: Y1-weight gain; Y2-sti ness; Y3-tensile strength; Y4-elongation, and generalised values Ygen1 = Y3*Y4/ Y1*Y2  

Experimental data for fabric 1 with surface density 131 g/m 2 . irty two (32) setting points overlapped with the contour plots of responses: Y1-weight gain; Y2-sti ness; Y3-tensile strength; Y4-elongation, and generalised values Ygen1 = Y3*Y4/ Y1*Y2  

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Figure 3: e architecture of feed-forward bottleneck (FFBN) neural network  
Figure 4: e architecture of FFBN neural network with input matrix...
Figure 5: Experimental data for fabric 1 with surface density 131 g/m 2...
New Approach for Optimising the Impregnations of Individual Batches of Aramid Fabrics
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  • Sep 2015
Innovate textile materials for special clothing are intended for providing trauma protection for the wearer. Fabrics made from high performance aramid fi bres are widely used nowadays for manufacturing athletic sportswear for extreme sports due to their high specifi c tensile modulus and strength. The aim of our study was to illustrate a new approa...
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... projection of 32 com- binations of experimental conditions and values of response within the same coordinates H1/H2 ena- bles determination of optima in the impregnation process. Figure 5 illustrates the experimental data for fab- ric 1 with surface density 131 g/m 2 . It represents the 34 setting points overlapped with the contour plots of responses: Y1-weight gain, Y2-sti ness, Y3-tensile strength, Y4-elongation and general- ised values Ygen1 = Y3*Y4/ Y1*Y2. ...