Project Summaries

05-755  Project Manager: E. M. Barnes


J. Alex Thomasson and Yufeng Ge, Texas AgriLife Research

Lint cleaning is performed in cotton gins to remove foreign matter, improve color and leaf grades, and prepare fibers in an open/combed state. Unfortunately, lint cleaning also removes desirable fiber, increases the waste and reduces the bale weight, and damages fibers by reducing staple length and uniformity, and particularly increasing the number of neps and amount of short fiber content. Thus there is a balance among several aims: minimizing fiber damage, minimizing fiber loss, maximizing cotton price and sales value, and maximizing the profitability of ginning operations.

In research into the fundamental mechanisms of saw-type lint cleaning over the last few years, we have used two approaches: basic engineering theory on mechanical properties of materials; and empirical studies to either validate the theoretical models or establish statistical relationships. With the first approach, in previous years of this project we have developed theoretical relationships to predict: how leaves, sticks, and burs are attached to fibers; the sequential interactions between fibers and machine surfaces effect on neps and short-fiber content; and the important mechanical properties of cotton fibers that result in fiber breakage. Empirical studies have included addition of a lubricant to reduce friction also reduce fiber fracture; and development of a computer simulation model to assist in use and design of current lint cleaners based on published empirical relationships.

In 2012, the principal objectives were to: 1) Develop and test a web-based simulation model for saw-type lint cleaning; and 2) Conceptualize an experiment to investigate frictional force between a bundle of fibers and metallic surfaces.

For objective 1, the model is based on existing data and empirical models on saw-type lint cleaners in the literature (all peer reviewed articles), much of which has come from USDA-ARS gin labs at Lubbock, Stoneville and Mesilla Park. The model requests inputs from users on a machinery figuration and what output variables are of interest. The simulation results are presented as curves for continuous variables (such as combining ratio) and bar graphs for discrete variables (such as # of lint cleaners). Results presented in graphs enable the user to determine optimal ginning conditions.

For the second objective, research activities are mainly focused on understanding interactions between cotton fibers and various parts of a saw-type lint cleaner machine. Specifically, we were interested in recognizing and classifying the physical and mechanical phenomena which take place between a tuft of cotton fibers and the grid bars (in other words, the moment when the saw cylinder drags cotton fibers across the grid bars to expel trash particles trapped between the fibers). We hypothesize that two major forces, frictional and bending forces, are applied to the fibers which may cause breakage of cotton fibers. Relationships from material science were used to predict breaking force as a function of lateral load applied on the region of contact, the number of asperities in contact, and the hardness of the junctions in contact under lateral pressure. Bending force of a single cotton fiber can be defined as the force required to bend the fiber to unit curvature (that is, the reciprocal of radius of curvature). Bending properties of fiber are sometimes known as their flexural rigidity. It is stated that flexural rigidity of a cotton fiber depends on the fiber diameter, the maturity of fiber, the tensile modulus and, most of all, its fineness (or linear density). Flexural rigidity of fibers with different cross-section shapes can be estimated theoretically from the specific modulus, density of the material, cross-section shape, and the linear density of the fiber. Now that the model is in place, we will design and construct an instrument to study frictional force between a single fiber and metallic surfaces next year.


Project Year: 2012

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