The influence of fibers on the fatigue cracking resistance of asphalt concrete is investigated using fracture energy. Nylon, a popular facing yarn of carpets, is used for the actual recycled carpet fibers in asphalt pavement. The experimental program is designed with two phases: the single fiber pull-out test and the indirect tension strength test. Through pull-out tests of 15-denier single nylon fibers, the critical fiber embedded length is determined to be 9.2 mm. As for indirect tension strength tests, samples of asphalt concrete mixed with nylon fibers of two lengths, 6 and 12 mm, based on results of the pull-out tests (critical embedded length) and three volume fractions, 0.25, 0.5, and 1%, are prepared and tested. Asphalt concrete samples fabricated with fibers of 1% and 12 mm results in 85% higher fracture energy than non-reinforced specimens, showing improved fatigue cracking resistance. Although an optimized asphalt mix design with fibers has not been developed for this study, the increased fracture energy represents a potential for improving asphalt fatigue life, which may be facilitated through the use of recycled carpet fibers.

To act as an alternative to existing systems, image-based fiber length measurements must yield precise results in a reasonable amount of processing time. To be used as a calibration device for current systems, the processing time becomes less important than accuracy and precision. Here, we report on the accuracy and precision of image processing applications compared with existing methods of HVI, AFIS, and hand measurements. Further, we propose preferred system parameters for these two possible applications of the technology.

The purpose of this work is to further study the transfer function model for carding introduced in a previous paper. Our goal is to develop mathematical and computational tools that will ultimately lead to the design of real-time controllers for carding. In this paper, we discuss a linear, time-variant version of the model presented for one carding group. We also present a reduced order, linear model and use it to build a linear estimator (observer) as part of a full-state feedback controller design. Computer sim ulations and experimental results are shown.

The purpose of this work is to increase the understanding of carding system dynamics based on mathematical tools that will ultimately lead to the development of on-line real-time controllers for carding. The work comprises both modeling the process and comparing simulated results with experimental data. A mathematical model for one worker-stripper group is described and subsequently expanded to model a carding engine with six carding (worker-stripper) groups. The process variable in this work is restricted to fiber areal density on the main cylinder; the expanded model predicts output (web) fiber areal density in time. Both simulated and experimental results are presented.

Fabric hand, an important characteristic to the textile industry, is influenced by such fiber parameters as flexural rigidity and friction and by yarn parameters such as count, twist, CV%, hairiness, stiffness, and softness. This study deals primarily with predicting the softness of knitted T-shirts from yarn quality parameters. The work consists of a short literature review on the existing yam parameters as well as fabric hand evaluation and prediction techniques. The latest developments in measuring the roughness of textile material surfaces are, also covered. Using the surface profile as tested by the mechanical stylus surface analyzer (MSSA), developed at North Carolina State Uni versity, a novel yarn surface analysis parameter called the "surface response average" (SRA) is developed, along with a model for the fiber/stylus tip interaction. Ten T-shirts produced from ten different yarn samples are ranked based on their softness by a panel of judges. The yams used to make these T-shirts are tested by Uster III and MSSA, and standard roughness parameters are calculated. The results show no significant corre lation between standard roughness parameters and fabric softness. The correlation be tween hand and SRA is about -0.6, which suggests that a higher SRA corresponds to a softer fabric.