最简单的水平集法源程序及其程序说明
本帖最后由 yygao56 于 2011-8-24 15:13 编辑此水平集法源程序并非王煜老师的199行经典水平集程序，而是challis于2009年发表在SCI杂志上的程序，除去添加了“%”的解释说明程序，整个程序大约90行。对水平集初学者，或是想了解水平集法的人来说，不失为较好的教学工具。该程序最大的缺点是边界不好，单元密度不是0就是1，没有中间密度。优点是能开孔
源程序： （我将程序大致整理了一下，已确定能在matlab中运行。为防止程序中出现QQ表情，程序有少量符号的中英文改动。请将程序中红色部分改为英文字符）
% TOPOLOGY OPTIMIZATION USING THE LEVEL SET METHOD, VIVIEN J. CHALLIS 2009
function = lsm(nelx,nely,volReq,stepLength,numReinit,topWeight)
% Initialization
struc = ones(nely,nelx);
= reinit(struc);
shapeSens = zeros(nely,nelx); topSens =zeros(nely,nelx);
= materialInfo();
% Main loop:
for iterNum = 1:200
% FE-analysis, calculate sensitivities
= FE(struc,KE);
for ely = 1:nely
for elx = 1:nelx
n1 = (nely+1)*(elx-1)+ely;
n2 = (nely+1)* elx +ely;
Ue = U(,1);
shapeSens(ely,elx) = -max(struc(ely,elx),0.0001)*Ue'*KE*Ue;
topSens(ely,elx) = struc(ely,elx)*pi/2*(lambda+2*mu)/mu/(lambda+mu)*(4*mu*Ue'*KE*Ue+(lambda-mu)*Ue'*KTr*Ue);
end
end
% Store data, print & plot information
objective(iterNum) = -sum(shapeSens(：）);
volCurr = sum(struc(：）)/(nelx*nely);
disp([' It.: ' num2str(iterNum) 'Compl.: ' sprintf('%10.4f',objective(iterNum)) ' Vol.: ' sprintf('%6.3f',volCurr)])
colormap(gray); imagesc(-struc,[-1,0]);
axis equal; axis tight; axis off;
drawnow;
% Check for convergence
if iterNum > 5 && ( abs(volCurr-volReq)< 0.005 ) && all( abs(objective(end)-objective(end-5:end-1) ) < 0.01*abs(objective(end)) )
return;
end
% Set augmented Lagrangian parameters
if iterNum == 1
la = -0.01; La = 1000; alpha = 0.9;
else
la = la - 1/La * (volCurr - volReq); La= alpha * La;
end
% Include volume sensitivities
shapeSens = shapeSens - la + 1/La*(volCurr-volReq);
topSens = topSens + pi*(la - 1/La*(volCurr-volReq));
% Design update
= updateStep(lsf,shapeSens,topSens,stepLength,topWeight);
% Reinitialize level-set function
if ~mod(iterNum,numReinit)
= reinit(struc);
end
end
%%---- REINITIALIZATION OF LEVEL-SET FUNCTION ----
function = reinit(struc)
strucFull = zeros(size(struc)+2);
strucFull(2:end-1,2:end-1) = struc;
% Use "bwdist" (Image Processing Toolbox)
lsf = (~strucFull).*(bwdist(strucFull)-0.5) - strucFull.*(bwdist(strucFull-1)-0.5);
%%----- DESIGN UPDATE ----
function = updateStep(lsf,shapeSens,topSens,stepLength,topWeight)
% Smooth the sensitivities
= conv2(padarray(shapeSens,,'replicate'),1/6*,'valid');
= conv2(padarray(topSens,,'replicate'),1/6*,'valid');
% Load bearing pixels must remain solid -Bridge:
shapeSens(end,) = 0;
topSens(end,) = 0;
% Design update via evolution
= evolve(-shapeSens,topSens.*(lsf(2:end-1,2:end-1)<0),lsf,stepLength,topWeight);
%%---- EVOLUTION OF LEVEL-SET FUNCTION
function = evolve(v,g,lsf,stepLength,w)
% Extend sensitivites using a zero border
vFull = zeros(size(v)+2); vFull(2:end-1,2:end-1) = v;
gFull = zeros(size(g)+2); gFull(2:end-1,2:end-1) = g;
% Choose time step for evolution based on CFL value
dt = 0.1/max(abs(v(：）));
% Evolve for total time stepLength * CFL value:
for i = 1：（10*stepLength)
% Calculate derivatives on the grid
dpx = circshift(lsf,)-lsf;
dmx = lsf - circshift(lsf,);
dpy = circshift(lsf,[-1,0]) - lsf;
dmy = lsf - circshift(lsf,);
% Update level set function using an upwind scheme
lsf = lsf - dt * min(vFull,0).*sqrt( min(dmx,0).^2+max(dpx,0).^2+min(dmy,0).^2+max(dpy,0).^2 )- dt * max(vFull,0) .*sqrt( max(dmx,0).^2+min(dpx,0).^2+max(dmy,0).^2+min(dpy,0).^2 ) - w*dt*gFull;
end
% New structure obtained from lsf
strucFull = (lsf<0); struc = strucFull(2:end-1,2:end-1);
%%---- FINITE ELEMENT ANALYSIS ----
function = FE(struc,KE)
= size(struc);
K = sparse(2*(nelx+1)*(nely+1), 2*(nelx+1)*(nely+1));
F = sparse(2*(nely+1)*(nelx+1),1); U =zeros(2*(nely+1)*(nelx+1),1);
for elx = 1:nelx
for ely = 1:nely
n1 = (nely+1)*(elx-1)+ely;
n2 = (nely+1)* elx +ely;
edof = ;
K(edof,edof) = K(edof,edof) + max(struc(ely,elx),0.0001)*KE;
end
end
% Define loads and supports - Bridge:
F(2*(round(nelx/2)+1)*(nely+1),1) = 1;
fixeddofs = ;
% Solving
alldofs = 1:2*(nely+1)*(nelx+1);
freedofs = setdiff(alldofs,fixeddofs);
U(freedofs,：） = K(freedofs,freedofs) \ F(freedofs,：）;
%%---- MATERIAL INFORMATION ----
function =materialInfo()
% Set material parameters, find Lame values
E = 1.; nu = 0.3;
lambda = E*nu/((1+nu)*(1-nu)); mu = E/(2*(1+nu));
% Find stiffness matrix "KE"
k =[ 1/2-nu/6 1/8+nu/8 -1/4-nu/12 -1/8+3*nu/8 ...
-1/4+nu/12 -1/8-nu/8 nu/6 1/8-3*nu/8];
KE = E/(1-nu^2)*stiffnessMatrix(k);
% Find "trace" matrix "KTr"
k=;
KTr = E/(1-nu)*stiffnessMatrix(k);
%%---- ELEMENT STIFFNESS MATRIX ----
function = stiffnessMatrix(k)
% Forms stiffness matrix from first row
K=[k(1) k(2) k(3) k(4) k(5) k(6) k(7) k(8)
k(2) k(1) k(8) k(7) k(6) k(5) k(4) k(3)
k(3) k(8) k(1) k(6) k(7) k(4) k(5) k(2)
k(4) k(7) k(6) k(1) k(8) k(3) k(2) k(5)
k(5) k(6) k(7) k(8) k(1) k(2) k(3) k(4)
k(6) k(5) k(4) k(3) k(2) k(1) k(8) k(7)
k(7) k(4) k(5) k(2) k(3) k(8) k(1) k(6)
k(8) k(3) k(2) k(5) k(4) k(7) k(6) k(1)];
程序运行结果：
lsm(60,30,0.3,3,2,4)
该程序的详细解释请看源文档（附件）
需要拓扑优化C程序的，请进此网页。这里的源程序不再是用matlab所写， 而是基于G. Allaire等人编写的一种名为FreeFem++的工具箱
http://www.cmap.polytechnique.fr/~allaire/freefem_en.html
网页内源程序资源丰富，主要包括：
Parametric (or sizing) shape optimization；
Geometric shape optimization ；
Topology optimization ；
Level set method 等 有点不太明白，为何形状优化导数是单元应变能，拓扑导数就不讨论了，方法应该很多，有的以应力或其他。
我倒是觉得单元应变能类似拓扑导数。 = conv2(padarray(shapeSens,,'replicate'),1/6*,'valid');
= conv2(padarray(topSens,,'replicate'),1/6*,'valid');
上述两句，是不是类似变密度法中的过滤？
这个水平集，是discrete的变量，能不能修改为连续的密度场？是不是对应在evolve程序中修改？ 是否加一个heaviside函数，实现连续化？连续化和离散化，有何优缺点？想听听编程体会。 看了一些文献和程序（大部分看不懂），水平集法的关键点包括速度场构造，水平集方程求解，水平集初始化，拓扑导数和开孔策略等。我觉得最关键的一步是速度场构造。如果LZ能把水平集稍微解释一下，不胜感激。
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