The aim of the research was to develop light and enhanced energy absorbed layered ballistic structures. For this reason, various ballistic structures were developed. These structures form two groups: multiaxially stitched and unstitched. Each group further consists of four structure types: (i) 14-layer Kevlar 29 woven fabric; (ii) 14-layer Kevlar 129 woven fabric; (iii) 7-layer Kevlar 29 fabric and 7-layer Kevlar 129 fabric; and (iv) 12-layer Kevlar 29 fabric oriented with respect to basic fabric direction at an angle of ±45° and 2-layer Kevlar 129 fabric. The Kevlar 29 and 129 fibers were considered to have 2.9 and 3.4 GPa tensile strengths and 70 and 99 GPa tensile modulus values, respectively, and the properties of the fibers were equalized in fabric form, but the Kevlar 129 fiber had a lower unit weight fabric (g/m2 ). Each of the developed structures were affected by five types of threat: 0.22, 0.38 round nose, 9 mm full metal jacketed, 0.357 jacketed soft point and 7.62 full metal jacketed projectiles. The results show that there were no significant energy absorption differences between multiaxis stitched and unstitched structures. However, conical depths upon impact on the multiaxis stitched structures were small compared to those of the unstitched structures. This result might be useful, especially in the design of soft vest applications.
Rotary dobby is a type of positive dobby which has been mainly used with rapier and projectile weaving machines. In recent years, manufacturers have demonstrated their rotary dobbies at the international exhibitions, running at speeds up to 1000 rpm. This makes it possible to employ a rotary dobby on high speed air jet and water jet weaving machines. Today, it is a dominant type of dobby in industry that can be used on all types of weaving machines.Material published on the rotary dobby is limited and mainly explains the system and principle of operation and written generally by the rotary dobby manufacturers [1, 2]. Eren et al. compared heald frame motion characteristics generated by rotary dobby and crank and cam shedding motions [3]. No other publication has been found on the theory of rotary dobby in the literature. This paper presents a kinematic design and analysis method explaining the theory of a rotary dobby system. Heald frame displacement, velocity and acceleration curves were obtained and the rotary dobby mechanism parameters affecting heald frame motion are discussed. Principle of Operation of a Rotary DobbyPrinciple of a rotary dobby is based on an eccentric mechanism shown in Figure 1(a). There is a ball bearing between the links 2 and 3. The link 2 is an eccentric, as its center of rotation (A 0 ) is different from its geometrical center 1 (A). Because of this, when the link 2 rotates, for example in counter clockwise direction, its motion is transmitted to the link 4 by the link 3. During one revolution of the link 2, the link 4 swings between its limit positions. When A 0 , A and B are on the same line and A 0 A and AB are extended, the link 4 reaches its most forward position. When A 0 A and AB are folded on top of each other, the rearmost position of the link 4 is reached. The motion of the link 4 is transmitted to the heald frame by motion transmission mechanism shown in Figure 1(b). The most forward position of the link 4 corresponds to the lower position and the rearmost position of the link 4 corresponds to the higher position of a heald frame. The eccentric mechanism with this construction generates a heald frame motion only for plain weave. To convert it to a rotary dobby mechanism, it is necessary to include the necessary means to get the link 4 (hence the heald frame) dwelt at its most forward and the rearmost positions as many loom revolutions as required by the weave.Abstract In this study, a mechanism model is introduced then kinematic design and analysis equations are presented for a rotary dobby. Heald frame motion curve is obtained and analyzed. Mechanism parameters affecting heald frame motion are discussed. It is shown that heald frame motion characteristics were mainly determined by the design of modulator mechanism. Eccentric mechanism of a rotary dobby also had a significant effect on heald frame motion.
We have studied the tearing strength of substrate woven fabric, substrate with adhesive, flocked fabric and washed flocked fabric on dry and wet conditions. The tensile strength of the rubbed flocked fabric and rubbed washed flocked fabrics in dry and wet conditions were also researched, and a statistical model was developed for the analysis of the tearing behavior of these fabric forms. Warp and weft tearing strengths of rubbed flocked fabric and rubbed washed flocked fabric in wet conditions were slightly higher than those in dry conditions. The reason was partly the high wet strength characteristic of cotton fiber and partly the lubrication effect of acrylic adhesive under wet conditions. Although the weft density of the substrate fabric was around half of its warp density, there was a small difference between warp and weft tearing strengths of dry and wet states of rubbed flocked fabric. This was attributed to the dense structure having less free space and less ultimate deformation potential and ultimately reducing the tearing strength. When the stroke number increased, the warp and weft tearing strengths of dry and wet states of rubbed flocked fabric generally decreased. It was also found that the stroke number of wet rubbed flocked fabric and rubbed washed flocked fabric was low in comparison with stroke number of dry rubbed flocked fabric and rubbed washed flocked fabric. The reason was that the wet acrylic adhesive had poor properties. The results from the regression model were compared with the measured values mainly by the mean absolute percent error parameter which enables us to conclude that the developed regression equations explain the tearing strength of flocked fabrics.
In this study, an artificial neural network (ANN) model is presented in order to predict the tenacity and hairiness of carded cotton yarns. Fiber measurement values generated by using a high-volume instrument (HVI) and an advanced fiber information system (AFIS) were used in the ANN model as input parameters. The radial basis function neural network (RBFNN) was used as ANN structure. The best RBFNN model was determined by analyzing the effect of epochs and the number of neurons on prediction performance. By using this ANN structure, the comparison between the performance of predicting yarn properties from HVIs and from AFISs was carried out. In the study, four different yarn counts (Ne20, Ne24, Ne30, and Ne40) for 10 different blends were applied. Each yarn count was spun at 4.34αe twist factor. In this study, the model presented a good rate of accuracy for predicting yarn tenacity and hairiness by using HVI and AFIS fiber values. The study showed that there was no significant difference between the accuracy of predicting these yarn properties from HVI fiber measurement results and those from an AFIS by using the RBF. From the results, it was noted that the performance of predicting yarn hairiness was better than that of predicting yarn tenacity. Also, this study could provide researchers with exclusive information on how to select the most appropriate ANN architecture and how to evolve the model for testing.
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