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ME3255S2017/lecture_08/lecture_08.ipynb

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"# Optimization\n",
"\n",
"Many problems involve finding a minimum or maximum based on given constraints. Engineers and scientists typically use energy balance equations to find the conditions of minimum energy, but this value may never go to 0 and the actual value of energy may not be of interest. "
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"The Lennard-Jones potential is commonly used to model interatomic bonding. \n",
"\n",
"$E_{LJ}(x)=4\\epsilon \\left(\\left(\\frac{\\sigma}{x}\\right)^{12}-\\left(\\frac{\\sigma}{x}\\right)^{6}\\right)$\n",
"\n",
"Considering a 1-D gold chain, we can calculate the bond length, $x_{b}$, with no force applied to the chain and even for tension, F. This will allow us to calculate the nonlinear spring constant of a 1-D gold chain. \n",
"\n",
"![TEM image of Gold chain](au_chain.jpg)\n",
"\n",
"Computational Tools to Study and Predict the Long-Term Stability of Nanowires.\n",
"By Martin E. Zoloff Michoff, Patricio Vélez, Sergio A. Dassie and Ezequiel P. M. Leiva \n",
"\n",
"![Model of Gold chain, from molecular dynamics simulation](Auchain_model.gif)\n",
"\n",
"[Single atom gold chain mechanics](http://www.uam.es/personal_pdi/ciencias/agrait/)\n",
"\n",
"### First, let's find the minimum energy $\\min(E_{LJ}(x))$\n",
"\n",
"## Brute force"
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"setdefaults\n",
"epsilon = 0.039; % kcal/mol\n",
"sigma = 2.934; % Angstrom\n",
"x=linspace(2.8,6,200); % bond length in Angstrom\n",
"\n",
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"ans = 3.2824\n",
"ans = 3.2985\n",
"ans = 3.3146\n"
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"x(imin-1)\n",
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"## Golden Search Algorithm\n",
"\n",
"We can't just look for a sign change for the problem (unless we can take a derivative) so we need a new approach to determine whether we have a maximum between the two bounds.\n",
"\n",
"Rather than using the midpoint of initial bounds, here the problem is more difficult. We need to compare the values of 4 function evaluations. The golden search uses the golden ratio to determine two interior points. \n",
"\n",
"![golden ratio](goldenratio.png)\n",
"\n",
"Start with bounds of 2.5 and 6 Angstrom. "
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"current_min = -0.019959\r\n"
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"source": [
"% define Au atomic potential\n",
"epsilon = 0.039; % kcal/mol\n",
"sigma = 2.934; % Angstrom\n",
"Au_x= @(x) lennard_jones(x,sigma,epsilon);\n",
"\n",
"% calculate golden ratio\n",
"phi = 1/2+sqrt(5)/2;\n",
"% set initial limits\n",
"x_l=2.8; \n",
"x_u=6; \n",
"\n",
"% Iteration #1\n",
"d=(phi-1)*(x_u-x_l);\n",
"\n",
"x1=x_l+d; % define point 1\n",
"x2=x_u-d; % define point 2\n",
"\n",
"\n",
"% evaluate Au_x(x1) and Au_x(x2)\n",
"\n",
"f1=Au_x(x1);\n",
"f2=Au_x(x2);\n",
"plot(x,Au_x(x),x_l,Au_x(x_l),'ro',x2,f2,'rs',x1,f1,'gs',x_u,Au_x(x_u),'go')\n",
"hold on;\n",
"\n",
"if f2<f1\n",
" plot([x_u,x1],[Au_x(x_u),f1],'k-')\n",
" x_u=x1;\n",
"else \n",
" plot([x_l,x2],[Au_x(x_l),f2],'k-')\n",
" x_l=x1;\n",
"end\n",
"hold off\n",
"%old_min = current_min;\n",
"current_min=min([f1,f2,Au_x(x_l),Au_x(x_u)])\n",
"%error_app=abs((current_min-old_min)/current_min)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
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{
"name": "stdout",
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"current_min = -0.033707\n",
"error_app = 0.40787\n"
]
},
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"source": [
"% Iteration #2\n",
"d=(phi-1)*(x_u-x_l);\n",
"\n",
"x1=x_l+d; % define point 1\n",
"x2=x_u-d; % define point 2\n",
"\n",
"% evaluate Au_x(x1) and Au_x(x2)\n",
"\n",
"f1=Au_x(x1);\n",
"f2=Au_x(x2);\n",
"plot(x,Au_x(x),x_l,Au_x(x_l),'ro',x2,f2,'rs',x1,f1,'gs',x_u,Au_x(x_u),'go')\n",
"hold on;\n",
"\n",
"if f2<f1\n",
" plot([x_u,x1],[Au_x(x_u),f1],'k-')\n",
" x_u=x1;\n",
"else \n",
" plot([x_l,x2],[Au_x(x_l),f2],'k-')\n",
" x_l=x1;\n",
"end\n",
"hold off\n",
"old_min = current_min;\n",
"current_min=min([f1,f2,Au_x(x_l),Au_x(x_u)])\n",
"error_app=abs((current_min-old_min)/current_min)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
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{
"name": "stdout",
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"text": [
"current_min = -0.038904\n",
"error_app = 0\n"
]
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"source": [
"% Iteration #3\n",
"d=(phi-1)*(x_u-x_l);\n",
"\n",
"x1=x_l+d; % define point 1\n",
"x2=x_u-d; % define point 2\n",
"\n",
"% evaluate Au_x(x1) and Au_x(x2)\n",
"\n",
"f1=Au_x(x1);\n",
"f2=Au_x(x2);\n",
"plot(x,Au_x(x),x_l,Au_x(x_l),'ro',x2,f2,'rs',x1,f1,'gs',x_u,Au_x(x_u),'go')\n",
"hold on;\n",
"\n",
"if f2<f1\n",
" plot([x_u,x1],[Au_x(x_u),f1],'k-')\n",
" x_u=x1;\n",
"else \n",
" plot([x_l,x2],[Au_x(x_l),f2],'k-')\n",
" x_l=x1;\n",
"end\n",
"hold off\n",
"old_min = current_min;\n",
"current_min=min([f1,f2,Au_x(x_l),Au_x(x_u)])\n",
"error_app=abs((current_min-old_min)/current_min)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
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},
"outputs": [
{
"name": "stdout",
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"text": [
"current_min = -0.039000\n",
"error_app = 0\n"
]
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"% Iteration #3\n",
"d=(phi-1)*(x_u-x_l);\n",
"\n",
"x1=x_l+d; % define point 1\n",
"x2=x_u-d; % define point 2\n",
"\n",
"% evaluate Au_x(x1) and Au_x(x2)\n",
"\n",
"f1=Au_x(x1);\n",
"f2=Au_x(x2);\n",
"plot(x,Au_x(x),x_l,Au_x(x_l),'ro',x2,f2,'rs',x1,f1,'gs',x_u,Au_x(x_u),'go')\n",
"hold on;\n",
"\n",
"if f2<f1\n",
" plot([x_u,x1],[Au_x(x_u),f1],'k-')\n",
" x_u=x1;\n",
"else \n",
" plot([x_l,x2],[Au_x(x_l),f2],'k-')\n",
" x_l=x1;\n",
"end\n",
"hold off\n",
"old_min = current_min;\n",
"current_min=min([f1,f2,Au_x(x_l),Au_x(x_u)])\n",
"error_app=abs((current_min-old_min)/current_min)"
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"## Parabolc Interpolation\n",
"\n",
"Near a minimum/maximum, the function resembles a parabola. With three data points, it is possible to fit a parabola to the function. So, given a lower and upper bound, we can choose the midpoint and fit a parabola to the 3 x,f(x) coordinates. \n",
"\n",
"$ x_{4} =x_{2} - \\frac{1}{2} \\frac{ \\left(x_{2} -x_{1} \\right)^{2} \\left[f\n",
" \\left(x_{2} \\right)-f \\left(x_{3} \\right) \\right]- \\left(x_{2} -x_{3} \\right)^{2}\n",
" \\left[f \\left(x_{2} \\right)-f \\left(x_{1} \\right) \\right]}{ \\left(x_{2} -x_{1} \\right) \\left[f \\left(x_{2} \\right)-f \\left(x_{3} \\right)\n",
" \\right]- \\left(x_{2} -x_{3} \\right) \\left[f \\left(x_{2} \\right)-f \\left(x_{1} \\right) \\right]}$\n",
"\n",
"Where $x_{4}$ location of the maximum or minimum of the parabola. "
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"source": [
"% define Au atomic potential\n",
"epsilon = 0.039; % kcal/mol\n",
"sigma = 2.934; % Angstrom\n",
"Au_x= @(x) lennard_jones(x,sigma,epsilon);\n",
"\n",
"% set initial limits\n",
"x_l=2.8; \n",
"x_u=3.5; \n",
"\n",
"% Iteration #1\n",
"x1=x_l;\n",
"x2=mean([x_l,x_u]);\n",
"x3=x_u;\n",
"\n",
"% evaluate Au_x(x1), Au_x(x2) and Au_x(x3)\n",
" \n",
"f1=Au_x(x1);\n",
"f2=Au_x(x2);\n",
"f3=Au_x(x3);\n",
"p = polyfit([x1,x2,x3],[f1,f2,f3],2);\n",
"x_fit = linspace(x1,x3,20);\n",
"y_fit = polyval(p,x_fit);\n",
"\n",
"plot(x,Au_x(x),x_fit,y_fit,[x1,x2,x3],[f1,f2,f3],'o')\n",
"hold on\n",
"if f2<f1 && f2<f3\n",
" x4=x2-0.5*((x2-x1)^2*(f2-f3)-(x2-x3)^2*(f2-f1))/((x2-x1)...\n",
" *(f2-f3)-(x2-x3)*(f2-f1));\n",
" f4=Au_x(x4);\n",
"\n",
" if x4>x2\n",
" plot(x4,f4,'*',[x1,x2],[f1,f2])\n",
" x1=x2;\n",
" f1=f2;\n",
" else\n",
" plot(x4,f4,'*',[x3,x2],[f3,f2])\n",
" x3=x2;\n",
" f3=f2;\n",
" end\n",
" x2=x4; f2=f4;\n",
"else\n",
" error('no minimum in bracket')\n",
"end\n",
"hold off"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
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{
"name": "stdout",
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"text": [
"f3 = -0.038878\r\n"
]
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"source": [
"p = polyfit([x1,x2,x3],[f1,f2,f3],2);\n",
"x_fit = linspace(x1,x3,20);\n",
"y_fit = polyval(p,x_fit);\n",
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"plot(x,Au_x(x),x_fit,y_fit,[x1,x2,x3],[f1,f2,f3],'o')\n",
"hold on\n",
"if f2<f1 && f2<f3\n",
" x4=x2-0.5*((x2-x1)^2*(f2-f3)-(x2-x3)^2*(f2-f1))/((x2-x1)...\n",
" *(f2-f3)-(x2-x3)*(f2-f1));\n",
" f4=Au_x(x4);\n",
"\n",
" if x4>x2\n",
" plot(x4,f4,'*',[x1,x2],[f1,f2])\n",
" x1=x2;\n",
" f1=f2;\n",
" else\n",
" plot(x4,f4,'*',[x3,x2],[f3,f2])\n",
" x3=x2;\n",
" f3=f2;\n",
" end\n",
" x2=x4; f2=f4;\n",
"else\n",
" error('no minimum in bracket')\n",
"end\n",
"hold off\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"f3 = -0.038878\r\n"
]
},
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"source": [
"p = polyfit([x1,x2,x3],[f1,f2,f3],2);\n",
"x_fit = linspace(x1,x3,20);\n",
"y_fit = polyval(p,x_fit);\n",
"\n",
"plot(x,Au_x(x),x_fit,y_fit,[x1,x2,x3],[f1,f2,f3],'o')\n",
"hold on\n",
"if f2<f1 && f2<f3\n",
" x4=x2-0.5*((x2-x1)^2*(f2-f3)-(x2-x3)^2*(f2-f1))/((x2-x1)...\n",
" *(f2-f3)-(x2-x3)*(f2-f1));\n",
" f4=Au_x(x4);\n",
"\n",
" if x4>x2\n",
" plot(x4,f4,'*',[x1,x2],[f1,f2])\n",
" x1=x2;\n",
" f1=f2;\n",
" else\n",
" plot(x4,f4,'*',[x3,x2],[f3,f2])\n",
" x3=x2;\n",
" f3=f2;\n",
" end\n",
" x2=x4; f2=f4;\n",
"else\n",
" error('no minimum in bracket')\n",
"end\n",
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]
},
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"Parabolic interpolation does not converge in many scenarios even though it it a bracketing method. Instead, functions like `fminbnd` in Matlab and Octave use a combination of the two (Golden Ratio and Parabolic)"
]
},
{
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"source": [
"## Using the solutions to minimization for the nonlinear spring constant\n",
"\n",
"Now, we have two routines to find minimums of a univariate function (Golden Ratio and Parabolic). Let's use these to solve for the minimum energy given a range of applied forces to the single atom gold chain\n",
"\n",
"$E_{total}(\\Delta x) = E_{LJ}(x_{min}+\\Delta x) - F \\cdot \\Delta x$"
]
},
{
"cell_type": "code",
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"metadata": {
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{
"name": "stdout",
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"text": [
"xmin = 3.2933\r\n"
]
}
],
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"xmin = fminbnd(Au_x,2.8,6)\n",
"\n",
"Etotal = @(dx,F) Au_x(xmin+dx)-F.*dx;\n"
]
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