Jon P. Rust
North Carolina State University
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Featured researches published by Jon P. Rust.
Textile Research Journal | 2005
S. Joon Lee; Jon P. Rust; Hechmi Hamouda; Y. Richard Kim; Roy H. Borden
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.
Textile Research Journal | 1992
Jon P. Rust; Shahram Peykamian
The influence of winding on yarn hairiness is examined, and increased hairiness during winding is verified using a Zweigle hairiness tester. Specifically, this study concentrates on the increase of wild hairs on the yarn surface after winding, and the relationship between winding tension and yarn hairiness. Fiber transfer is proposed to explain the increased wild hairs; experimental results verify that fiber transfer occurs. A theory is proposed to explain the mechanism of fiber transfer during winding, and experimental results are given to support this mechanism.
Textile Research Journal | 2001
Y. Ikiz; Jon P. Rust; W. J. Jasper; H. J. Trussell
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.
Textile Research Journal | 1995
Hector Gutierrez; Jon P. Rust; Abdelfattah M. Seyam
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.
Textile Research Journal | 1994
Jon P. Rust; Hector Gutierrez
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.
Textile Research Journal | 1996
L.F. Fryer; Jon P. Rust; P.R. Lord
To obtain a better understanding of the relationships between fiber properties of the constituents of a cotton blend and the processes up to drawing, a review is presented of the effects of blending, orienting, and removing crimp from fibers on HVI test results. These effects are also explored experimentally by testing fibers from the same laydown in bale, card sliver, and drawn sliver form using HVI equipment. Apparent reductions in upper half mean and increases in short fiber content of card sliver may be due to the formation of hooks. Significant correlations between micronaire and fiber properties related to length that are present in bale samples are lacking in both card and drawn sliver samples, suggesting that there is at least one unmeasured factor in this analysis. Measured micronaire values are sensitive to crimp and fiber packing density. Differences in fiber property distributions can have significant effects on HVI measurements, and distributions of single fiber properties of a blend may differ dras tically from those of single bales. Strength tests of blended bundles may not include all constituents in the blend, because only the longest fibers are clamped in the jaws. Testing the fiber population at various stages of processing yields different information about fiber bundles.
Textile Research Journal | 1994
Jon P. Rust; E. Koella
An optical means is presented for measuring areal fiber density on-line on com mercial carding elements. The splitting fractions of the various elements have been evaluated through a process of peeling fiber loads from the elements, and these fractions have subsequently been used in instrument calibration. The optical device is used to monitor fiber loading of the main cylinder while doffer fiber loading and feed roll speed are also being monitored. The instrumentation itself has been studied for sen sitivity, reproducibility, limitations, and possible sources of internal and external noise. The instrumentation is then used on-line to study mechanisms of fiber transfer and storage. Results of dynamic testing under conditions of varying feed rates offer insight into the process of carding. The complex nature of element loading and unloading has been partially elucidated. Hypotheses are proposed and experimental results pro vided as supporting evidence.
Journal of The Textile Institute | 1991
P. R. Lord; Jon P. Rust
Both classic and novel research methods were used to study a number of questions concerning the mechanisms involved with fiber assembly in friction open-end spinning of cotton yarns. The equipment used was a much-modified DREF-3 friction-spinning unit with replaced suction rolls and equipped with a comber-roll assembly from a Platt 881 rotor-spinning unit Reynolds-number simulation in a water medium provided a means of determining the source of flow instabilities in the vicinity of the nip. Considerable energy losses were found as a result of flow inefficiencies in the inner cylinders, and methods of improving the cylinder design were suggested. The use of short-duration flash techniques provided a means of determining fiber orientation prior to accumulation and assembly on the yarn tail. These techniques made it possible to photograph the yarn tail forming as well as the gradual tightening of the structure upstream of the original yarn-forming position. Determination of mechanisms of capture of the fiber...
Textile Research Journal | 1994
Jon P. Rust; T.L. Keadle; D.B. Allen; Itzhak Shalev; Roger L. Barker
A mechanical stylus surface analyzer (MSSA) system and the corresponding software were used to conduct standard surface analysis procedures. The MSSA instrumentation measures surface characteristics of soft bathroom tissue products. This paper describes the applicability of MSSA and how human tactile response may be modeled through characterization of surfaces. The concepts of passive and active touch as related to human perceived softness are reviewed. In particular, parameters pertinent to these kinds of tactile exploration are mentioned, as well as how they can be used to build a better model of human tactile response. A novel frequency analysis parameter called the frequency index for tactile sensitivity (FITS) is based on tissue paper surface analysis results from MSSA and provides the basis for the human response model. Included is a review of subjective human softness evaluation data for select tissues gathered to represent actual human responses. The MSSA and optical image analysis (OIA) data were collected on the same tissues, and the FITS parameter was found using MSSA. Also, MSSA data were used to reproduce an old standard parameter for evaluating tissue softness called the human tactile response (HTR) index. Since it is not possible to exactly reproduce HTR, the reproduced parameter calculated in this study is called HTR equivalent (HTR_EQ). Finally, standard deviation of luminance (SDL) and loosely bonded surface fibers (LBSF) parameters are determined for select tissues using OIA. Correlation results of the human data with FITS, HTR—EQ, SDL, and LBSF are discussed; FITS correlates best with the human response data and, together MSSA and FITS, has the ability to model human response to the softness of tissue paper products.
Textile Research Journal | 2000
Shahram Peykamian; Jon P. Rust
In this study, the authors use linear and nonlinear models and yarn parameters such as CV%, hairiness, and surface softness to classify the softness of knitted fabrics (T-shirts) for comparison to human subjective evaluations. All classification rates are verified with a leave-one-out cross-validation technique. The results show 20% misclassification when using a linear model to sort samples into two classes (low and high). When sorting into three classes, the misclassification is 30%. When sorting T-shirt softness into three classes using a tree modeling technique and the surface response average (SRA) and maximum peak-to-valley height (Ry), it is possible to match the human data at a 65% rate. When using surface response parameters and measured yam properties to sort T-shirt softness into three classes, with tree modeling it is possible to classify 91% of the samples accurately based on the human data.