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 PART - I
Chapter 3

The Algebraic Expressions for the General Equation
Basic Considerations
 

Some important points emerge from the analysis that we carried out to formulate the structure of the general equation:

 
To obtain accurate estimates of yarn CSP at different twists we need to be able to estimate the fibre tenacity at any finite gauge length over a wide range. For this we need to have the tenacity measured not only at 3-mm., but also at zero gauge.
In the general equation the number of fibres at the place of break is an important fundamental variable. Now, the number of fibres at the place of break is a fraction of the average numbers of fibres in the cross-section of the yarn. The number of fibres in the cross-section can only be calculated from yarn count and fibre fineness, millitex, not micronaire index. Therefore, micronaire index is not appropriate for use in the general equation; we need the gravimetric fibre fineness, millitex. Fortunately, instrumental evaluation of fibre millitex is today there for the asking.
The yarn irregularity fraction in the general equation must take into consideration the fibre characteristics that determine the susceptibility of a cotton to incur drafting irregularity.
 
We will now discuss how we can formulate the algebraic expressions that go to make up the general equation taking into consideration these requirements.
   
The Numerical Value Of R, The Conversion Factor
 
The value of R can be shown to be 208.35. In the lea-strength test 160 threads together resist the imposed stress. The theoretically possible maximum contribution per thread can be the zero-gauge fibre bundle tenacity, Z g/tex. Therefore the theoretical maximum breaking stress that the lea can sustain is
  = 160 x Z x yarn tex in grammes.
 
Replacing tex by NE, and grammes by pounds, we find that the theoretical maximum load that a lea can sustain is
  = 160 x Z x (590.551/C) x (2.205/1000) pounds.
  Therefore the theoretical maximum lea count-strength product,
  CS=C x 160 x Z x (590.551/C) x (2.205/1000)
                = 160 x 590.551 x (2.205/1000) x Z = 208.35 x Z.
  The actually realized CS is, therefore,
  =208.35 x Z x F1 x F2 x F3 x F4
  We note in passing that lea-CS can numerically be converted into lea cN per tex:-
  cN/tex =(CS/ 208.35)X 0.981 =CS x 0.00471.
 
The Irregularity Function F1
 
Even when the same cotton is spun on the same set of machinery, the irregularity of the yarn increases with increasing count. There is an important consequence of this. The English count-strength product, CS, which was originally proposed as a measure of yarn tenacity that is independent of the count of yarn, is in reality not so. The CS of yarns spun from the same cotton, and on the same set of machines, decreases with increasing English count. The expression that is in industrial use to quantify this fall in CS with increasing count is
 
 
where S1 and S2 are the breaking strengths of yarns of count respectively. The commonly used value of K is 18, irrespective of the cotton used to spin the yarn. This generalization yields estimates that are accurate enough for the purpose for which it is used, namely, for correcting the CS for small discrepancies of the actual count from the nominal count.
  The shop-floor equation relating tenacity to count can be rewritten :
 
  When z is a fractional value, (1-z) is very close to . Therefore, we can write,
 
 
This equation accounts for the drop in CS with increasing yarn-count as a result of increasing irregularity. In practice, the increase in yarn irregularity with yarn count is less for the finer of two cottons. This implies that the expression for irregularity effect on CS should be written not in terms of C, but in terms of N, the average number of fibres in the cross-section of yarn, that is in terms of both yarn-count and fibre-fineness, and not in terms of only C, the count of the yarn. Furthermore, practical observation tells us that K is the smaller for the longer of two cottons (26). This is because the increase in irregularity with increasing count is less for the longer of two cottons. Examination of experimental data suggests that a plausible expression for F1 :-
 
  where is a function of the parameters that characterize the fibre-length distribution of the cotton.
   
Expressions For Contributing-Fibre Fraction And Fibre-Breaking Gauge-Length Fraction, F2 And F3
  If at any twist, the number of fibres that slip and therefore do not contribute to yarn tenacity is U, then,
 
 
  where N is the average number of fibres in the cross-section of the yarn.
 
Data offered by E. Lord (24) show that the fibre-bundle tenacity at gauge-length g in units of 1/32-inch is given by
 
 
where G is a cotton-specific parameter. If, therefore, the length of fibre-elements that break when yarn of twist multiplier M fails in tenacity testing is g in units of 1/32-inch,
 
 
In writing the algebra relating U and g to M we are guided by certain premises, that seem quite plausible on basic considerations. The premises are as follows.
 
With increasing twist, the number of fibres that slip, and do not contribute to yarn tenacity decreases. The longer the fibre, the steeper will be this fall, with twist, of the number of fibres that slip at breaking point with increasing twist. This fall could also be steeper for a yarn that has more fibres in the cross-section than for a yarn that has less fibres in the cross-section. The rate of fall of U with M is, therefore, determined by fibre-length, fibre-fineness and yarn count. Examination of the two broken ends of a high-twisted yarn shows that all the fibre-ends appear broken. We can therefore, take the asymptotic value of U to be equal to zero.
 
The gauge length of fibre-break in yarn-break is very likely to be determined by the intimacy of intermingling of fibre assemblies inside the yarn (8). The intermingling is quite likely governed by the number of fibres in the cross-section of the yarn. The fall of g with M is, therefore, not likely to be dependent upon fibre-length, but upon the number of fibres in the cross-section, being steeper for a yarn with more fibres in the cross-section than for a yarn with less fibres in the cross-section. The fall of g to its asymptotic minimum is thus dependent upon fibre-fineness and yarn-count. A corollary is that the minimum value of g may not necessarily be zero, but may itself be dependent upon fibre-fineness. We can therefore write,
 
 
where lm, the asymptotic minimum value as M tends to infinity, is dependent upon fibre-fineness, and the increment over lm at any finite twist, is dependent upon fibre-fineness, as well as upon yarn count and twist.
   
The Fibre-Obliquity Fraction
  For F4, the obliquity fraction we use Bogdan’s expression (19)
 
  where M is the twist-multiplier in the English system of units.
 
The Final CS Equation
  From the foregoing analysis, we get,
   
   
 
To construct the algebraic expressions for FL, U, lm, and LM, in terms of fibre parameters, we need data on fibre and yarn tests of a number of disparate cottons. Brown and co-workers (7) have provided such data. In our first attempt to formulate expressions for the general equation we made use of these data. We were able to construct a general equation that gives yarn CS estimates of acceptable accuracy over a range of yarn counts and twist. The procedure that we followed for arriving at these expressions is also explained in Part II.
   
Agreement Of CSP Estimates From The General Equation With Actual Yarn CSP Values
 
We can assess the predictive accuracy of the equation by examining the proximity of the experimental points to the smooth curves that are generated by the equations. The results of this exercise are available in Figure I - 3 - i. In most of the resulting 18 cases, the experimental points are seen to be close to the smooth curve.
 
The error in the estimate of CSP in each of the 133 yarns is given in Table I – 3 – ii. Only in 14 cases out the total number of 133 does the error exceed 6%; out of these 14 cases, in only one does the error exceed 10%. With his equations, Neelakantan (6) found, “Only 17 out of 133 cases showed errors of prediction beyond 6% and only in two cases errors were beyond 10%.” Thus, in terms of the accuracy of estimates, The General Equation is not at all inferior to Neelakantan’s equations. At the same time The General Equation has been constructed with a logical framework that renders it capable of explaining the roles of fibre-length and fibre-fineness in governing the contributions of yarn count and twist to the realization of fibre-tenacity as yarn tenacity. Neelakantan’s equations do not help us glean any such insight: they contain nine terms, each a medley of fibre characteristics.
 
The interacting contributions of fibre length and fibre fineness on the one hand, and yarn count and twist on the other to the translation of fibre tenacity into yarn tenacity is highlighted in Table I – 3 - i.
 
A closer examination of the graphs in Figure I – 3 - i shows that there are feeble systematic errors, or bias, in some cases. Naturally the question arises as to which of the expressions needs be improved upon. Further scrutiny of the data leads to a surmise: the expression for the irregularity fraction introduces avoidable errors in the estimates. The inference is that the parameter of fibre-length in Brown’s data (6) namely, UHML, is by itself not adequate for quantifying the contribution of fibre-length to yarn irregularity. The algebraic expression for FL, the irregularity fraction, therefore appeared to deserve a re-look. We will do this in the sequel.
 
 
 
 
Figure I – 3 -i. Showing proximity of experimental points to smooth curve given by algebraic expressions for F1, F2, F3 and F4 (Brown’s data)
 
 
Fraction

Fibre-
Length

Fibre-
Fineness

Gauge Length Parameter

Yarn Count

Yarn Twist Factor

F1, irregularity fraction

Yes

Yes

No

Yes

No

F2, contributing-fibre fraction

Yes

Yes

No

Yes

Yes

F3, test-length fraction

No

Yes

Yes

Yes

Yes

F4, obliquity fraction

No

No

No No Yes
 
Table I-3-i Fibre Characteristics And Yarn Count And Twist as Contributing Factors To F1, F2, F3 and F4
 
RANGE OF
      ERR %

 

NUMBER OF CASES
0 to 2 50
2 to 4 50
4 to 6 19
6 to 8 11
8 to 10 2
>10

1

TOTAL 133

 
Table I – 3 - ii: Brown’s Data : Distribution of % Error In Estimates
 
 
Part - I
 
Understanding And Making Use Of The Equation
   
Chapter 1

Why Do We Need Another Equation for the Prediction of Yarn Tenacity?

Chapter 2

Strcturing the General Equation for Yarn Tenacity

Chapter 3

The Algebraic Expressions for the General Equation

Chapter 4

The Choice of Parameters of Fibre-Length Distribution for Use in the Irregularity Fraction

Chapter 5
Chapter 6

Making Use of the Equation in a Mill

Chapter 7

What Does the General Equation Tell Us?

Chapter 8

How General Is The General Equation ?

Chapter 9

Can We Use the General Equation to Estimate the CSP of Yarns from Mixings of Cottons?

Chapter 10

Can We Modify the General Equation to Estimate CSP Of Combed Yarns?

Chapter 11 A Note of Caution
Chapter 12
Chapter 13 The General Equation, A Tool for Economic Cotton Selection
 
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