Solving symbolic equation using solve
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Vithusha T
le 8 Fév 2021
Commenté : Vithusha T
le 9 Fév 2021
Hi,
I am trying to minimize the value of phi here. I want the values of E for which phi becomes zero but the code is not providing any solution, also there is some problem in the execution of solve function.
Can someone please help with the proper function to be used here for minimization.
b = [(5/60) (10/60) ];
syms E xfun Ifun phi phidiff
xfun = sym(zeros(10,2));
Ifun = sym(zeros(10,2));
phi = sym(zeros(10,2));
phidiff = sym(zeros(10,1));
E_Vyas = zeros(10,1);
for prog = 1:1:2
for conv = 1:1:10
xfun(conv,prog) = -(E)./(8.314.*T(conv,prog)); %here T is temperature file(10 by 2 matrix)
Ifun(conv,prog) = (T(conv,prog).*exp(xfun(conv,prog)))-(Eiget(-xfun(conv,prog))./8.314);
end
end
for conv = 1:1:10
phi(conv) = (Ifun(conv,1).*b(2))./(Ifun(conv,2).*b(1)) + (Ifun(conv,2).*b(1))./(Ifun(conv,1).*b(2));
phidiff = diff(phi,E);
E_Vyas(conv) = (real(solve(phidiff,E)))/1000;
conv;
show = E_Vyas(conv);
end
E_Vyas = smooth(E_Vyas,0.1,'loess');
function [Eix] = Eiget(xfun) %function for approximation for I(E,T)
A = log((0.56146./xfun)+0.65).*(1+xfun);
B = (xfun.^4).*(exp(7.7*xfun)).*((2+xfun).^3.7);
Eix= (((A.^-7.7)+B).^-0.13)-((exp(-xfun))./xfun);
end
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Walter Roberson
le 9 Fév 2021
b = [(5/60) (10/60) ];
syms E xfun Ifun phi phidiff
xfun = sym(zeros(10,2));
Ifun = sym(zeros(10,2));
phi = sym(zeros(10,1));
phidiff = sym(zeros(10,1));
E_Vyas = zeros(10,1);
for prog = 1:1:2
for conv = 1:1:10
xfun(conv,prog) = -(E)./(8.314.*T(conv,prog)); %here T is temperature file(10 by 2 matrix)
Ifun(conv,prog) = (T(conv,prog).*exp(xfun(conv,prog)))-(Eiget(-xfun(conv,prog))./8.314);
end
end
guess = sym('1.0');
for conv = 1:1:10
phi(conv) = (Ifun(conv,1).*b(2))./(Ifun(conv,2).*b(1)) + (Ifun(conv,2).*b(1))./(Ifun(conv,1).*b(2));
phidiff(conv) = diff(phi(conv),E);
tic
sol = vpasolve(phidiff(conv),E,guess);
toc
if isempty(sol)
E_Vyas(conv) = nan;
else
E_Vyas(conv) = real(sol)/1000;
guess = sol;
end
end
E_Vyas_smooth = smooth(E_Vyas,0.1,'loess');
function [Eix] = Eiget(xfun) %function for approximation for I(E,T)
A = log((0.56146./xfun)+0.65).*(1+xfun);
B = (xfun.^4).*(exp(7.7*xfun)).*((2+xfun).^3.7);
Eix= (((A.^-7.7)+B).^-0.13)-((exp(-xfun))./xfun);
end
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