use of nonlinear curve fitting with Monte-Carlo analysis

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Farhan Ashraf
Farhan Ashraf 2018-4-3
Hi, I am trying to fit a non-linear model with experimental data and also want to run Monte-Carlo analysis with that but it seems very difficult. please help me in this regard. Thank you
temp=[24.88503903
78.50497273
139.9636403
194.6529783
297.4975938
397.283713
];
yieldstress=[45.00727678
36.79417319
37.5451424
33.05702304
30.41701789
28.98254504
];
nsample=1000;
for i=1:nsample
DD=1e12+2e12*randn(1);
self_coff=0.08+0.04*randn(1);
line_energy=0.5+0.5*randn(1);
conversion_factor=0.32+0.06*randn(1);
threshold_stress=25.9e9*2.86e-10.*sqrt(DD).*((0.5.*line_energy)+sqrt(self_coff));
ave_strainrate=2.86e-10*1e12.*sqrt(DD);
fun(i) =@(x,xdata)threshold_stress+(x(1).*0.89).*(1-((((8.617e-5.*temp)./x(2).*log(6.667e-
4./ave_strainrate)).^(1/1.5)).^(1/0.6667)))./(conversion_factor);
x0 = [1.8 4];
[x,resnorm,~,exitflag,output]=lsqcurvefit(fun(i),x0,temp,yieldstress);
end

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