18—the Relation Between the Length and Linear Density of Jute and Flax Fibres Obtained After Carding and Drawing Operations

Banerjee, B. L.

doi:10.1080/00405008208658936

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…The present author uses the Gamma function to obtain the same result very quickly Biswas [6][7][8] and f EW (l) has been considered Biswas [1] to obtain f LW (l). He has also considered all the other possible routes of transformations of one type of length distribution to the other types of length distribution and presented their rederivation through Gamma function to achieve a considerable simplification Biswas [9].…”

Section: Effect Of Sampling and Testing Methodsmentioning

confidence: 88%

“…In addition, the single filaments in the longer elements may be thicker and stronger than those in the shorter ones. On both these counts, the linear density of the longer elements will be greater than that of the shorter ones Banerjee [1]. When the meshy structure of raw jute reeds is broken down randomly into fibrous elements in a carding machine, the frequency of such elements by number can be expected to decrease exponentially with increase in their length Banerjee [2].…”

Section: Introductionmentioning

confidence: 99%

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Presentation of Jute Fibre Length via Graphics and Computer Simulation with Gamma Distribution Function

Biswas¹

2017

JTEFT

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Notwithstanding the complexity of production of jute fibre filaments a simple graphical presentation of jute fibre length distribution is made. The computer simulation of four types of frequency distribution of jute fibre length depending on method of sampling and testing is presented. These four distribution curves give six points of intersections which merit technological significance. A study of fibre length-frequency distribution depending on methods of sampling and testing may lead to a general form of Gamma distribution function. The parameters in the mathematical formulae may serve as characteristics of condition giving the benchmark for valid experiment. This type of work involving exponential distribution was not done previously and provides a deeper insight into the characterisation of its comparative features with respect to normal distribution of fibre length.

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Section: Effect Of Sampling and Testing Methodsmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Presentation of Jute Fibre Length via Graphics and Computer Simulation with Gamma Distribution Function

Biswas¹

2017

JTEFT

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32—a Simplified Method of Determining the Length and Fineness Characteristics of Fibres in Jute Slivers and Yarns

Banerjee

1984

The Journal of The Textile Institute

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The normal method of studying the length and fineness characteristics of fibres in jute slivers and yarns involves classifying the fibres in a sample into a suitable number of length groups and determination of the frequency and hnear density of fibres in all the length groups. The simplified method described in this paper requires evaluation of the cumulative frequency and linear density of fibres of one particular length only, and is hence less time-consuming than the normal method. Graphical relations and tables are provided with the simplified method to reduce the computation time, which is considerable with the normal method. The data obtained on several yarn samples of different qualities by the normal method of testing are used to show the agreement between the results arrived at by the two methods. A procedure for carrying out the tests required in the simplified method is also suggested.

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Computational and Simulation Studies of Modal Length of Jute Fiber

Biswas¹

2010

Journal of Natural Fibers

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18—the Relation Between the Length and Linear Density of Jute and Flax Fibres Obtained After Carding and Drawing Operations

Cited by 3 publications

References 2 publications

Presentation of Jute Fibre Length via Graphics and Computer Simulation with Gamma Distribution Function

Presentation of Jute Fibre Length via Graphics and Computer Simulation with Gamma Distribution Function

32—a Simplified Method of Determining the Length and Fineness Characteristics of Fibres in Jute Slivers and Yarns

Computational and Simulation Studies of Modal Length of Jute Fiber

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