NSolve is a numerical algorithm. For exact results, use Solve.

Your code exactly evaluates "nc" already: 77/51 is an exact rational number. It has no exact, finite decimal representation: 77/51 is the best you can have. If you want to see lots of digits, try something like N[nc,1000].

Try NSolve with higher than default WorkingPrecision. And be prepared to wait.

If you want exact results, you must use exact input. You are using approximate numbers like 0.51 in your input. Any number expressed with a decimal point is approximate in Mathematica. 0.51 (approximate) is not the same thing as 51/100 (exact, rational). If you don't actually want exact results, but rather results with better precision than you're getting, you can try higher WorkingPrecision as Daniel suggests.

Consider an exact polynomial expression:

poly = -6 + 17 x - 32 x^2 + 26 x^3 - 20 x^4 + 14 x^5 - 8 x^6 + 3 x^7

Note that it contains no approximate numbers like 1.4: all of the coefficients are exact rational numbers (integers in this case). In Mathematica, any number containing a decimal point is an approximate number, not an exact number. You cannot expect exact results from approximate input.

Make an equation, solve it:

exact = Solve[poly == 0]
{{x -> 1/3 (1 - I Sqrt[2])}, {x -> 1/3 (1 + I Sqrt[2])}, {x -> 
   Root[-6 + 5 #1 - 4 #1^2 + 3 #1^3 - 2 #1^4 + #1^5 &, 1]}, {x -> 
   Root[-6 + 5 #1 - 4 #1^2 + 3 #1^3 - 2 #1^4 + #1^5 &, 2]}, {x -> 
   Root[-6 + 5 #1 - 4 #1^2 + 3 #1^3 - 2 #1^4 + #1^5 &, 3]}, {x -> 
   Root[-6 + 5 #1 - 4 #1^2 + 3 #1^3 - 2 #1^4 + #1^5 &, 4]}, {x -> 
   Root[-6 + 5 #1 - 4 #1^2 + 3 #1^3 - 2 #1^4 + #1^5 &, 5]}}

I get seven roots, all exact. Two are expressed as radicals, five have no such representation and are expressed using Root. These are the exact solutions, as we can verify:

Simplify[poly /. exact]
{0, 0, 0, 0, 0, 0, 0}

However, if I want numerical results:

approx = NSolve[poly == 0]
{{x -> -0.551685 - 1.25335 I}, {x -> -0.551685 + 1.25335 I}, {x -> 
   0.333333 - 0.471405 I}, {x -> 0.333333 + 0.471405 I}, {x -> 
   0.805786 - 1.2229 I}, {x -> 0.805786 + 1.2229 I}, {x -> 1.4918}}

The numerical solutions are necessarily approximate: exact numerical solutions of this equation are not possible. Most polynomial equations do not have exact numerical solutions: the solutions are irrational and thus have no finite numerical representation. Substituting the approximate solutions back into the original polynomial yields results that are approximately, but not exactly, zero:

poly /. approx
{1.84741*10^-13 + 1.91847*10^-13 I, 1.84741*10^-13 - 1.91847*10^-13 I,
  6.66134*10^-16 + 1.9984*10^-15 I, 
 6.66134*10^-16 - 1.9984*10^-15 I, -1.42109*10^-14 + 
  7.10543*10^-15 I, -1.42109*10^-14 - 
  7.10543*10^-15 I, -2.13163*10^-14}

And that is just as you should expect.

Sincere thanks for your valuable time.

Here in attachments I am uploading my original problem. I hope Instructions in file attached are clear to understand.

Attachments:

Thanks sir,

Sir, u rightly ponied the variation in the scales in-between different coefficients of the polynomial. I am working on it.

kindly answer one wore thing. I have following one example.

aw = 23; bw = 34; cw = 12; nc = (aw/bw) + 10/cw

How can I set Precision to evaluate "nc"