How can I apply 'for' cycle for two arrays?

Hello,

I have these parameters:

D=0.030;
A=7.0685*10^-4;
Jo=0.763;
Jw=[0.778090833 0.998156927 1.194644511 1.395061847 1.583689928 1.772318008 1.964875841 2.369640264];
ro_o=910;
ro_w=1000;
mu_w=0.001;
mu_o=[1.057 1.079 1.057 1.117 1.086 1.050 1.057 0.993];

and the function as:

Hw = fsolve(@(Hw) (((8*ro_o*((D-(2*sqrt(Hw*A/pi)))*(Jo/(1-Hw))*ro_o/mu_o)^-1.0)*(((Jo/(1-Hw))-(Jw/Hw))*((Jo/(1-Hw))-(Jw/Hw))))*(pi*(D-(2*sqrt(Hw*A./pi)))*(1/(1-Hw))))-((0.023*(((Jw*D*ro_w)/mu_w)^-.2)*ro_w*(Jw/Hw)^2*(pi*D))), 0.9)

For each value of Jw and mu_o, there must be one value of Hw, how can I write 'for' loop to take into consideration of two vectors Jw and mu_o?

Answer 1

[Roger Stafford]

It depends on what you mean by "For each value of Jw and mu_o". If you mean for each of eight corresponding pairs of numbers from these two vectors, do this:

   for k = 1:8
     Hw(k) = fsolve(@(Hw) .....mu_o(k).....Jw(k).....
   end

If you mean for each of the sixty-four possible combination of pairs from these two arrays, then do:

   for k1 = 1:8
     for k2 = 1:8
       Hw(k1,k2) = fsolve(@(Hw) .....mu_o(k1).....Jw(k2).....
     end
   end

Let us hope that the initial estimate of 0.9 will lead to successful convergence for all cases.

There is also the possible problem of multiple solutions for this equation.

[Parham Babakhani Dehkordi]

I meant the first case. Thanks, it works