Sunday, March 17, 2013

Program Untuk Menghitung Bilangan Reynolds dari Aliran Fluida di dalam Pipa Menggunakan MATLAB

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

Saya mencoba untuk membuat program menghitung bilangan Reynolds untuk kondisi aliran fluida di dalam pipa sebagai berikut :



===========

function Re = Reynolds()
disp ('This program is for fluid flowing inside a pipe')
Rho = input (' Input Density of Working Fluid in kg/m3 : ');
V = input (' Input Velocity in m/s : ');
Lc = input (' Input Characteristic Length in m : ');
M = input (' Input Viscosity of Working Fluid in kg.s/m2 : ');

Re = (Rho*V*Lc)/M;
disp (' ')
disp (' ===> Value of Dimensionless Reynolds Number = ', num2str(Re))
disp (' ')

if Re < 2100
disp ('Laminar Flow')
elseif Re > 4000
disp ('Turbulen Flow')
else disp ('Transitional Flow')
end


===========


Segala bentuk masukan terkait program ini akan sangat membantu.
Semoga bermanfaat.

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