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camshape.gms : Shape optimization of a cam COPS 2.0 #4


Maximize the area of the valve opening for one rotation of a
convex cam with constraints on the curvature and on the radius
of the cam.

This model is from the COPS benchmarking suite.
See http://www-unix.mcs.anl.gov/~more/cops/.

The number of discretization points can be specified using the command
line parameter --n. COPS performance tests have been reported for n =
100, 200, 400, 800

References:
Large Model of Type: NLP
$Title Shape optimization of a cam COPS 2.0 #4 (CAMSHAPE,SEQ=232) $ontext Maximize the area of the valve opening for one rotation of a convex cam with constraints on the curvature and on the radius of the cam. This model is from the COPS benchmarking suite. See http://www-unix.mcs.anl.gov/~more/cops/. The number of discretization points can be specified using the command line parameter --n. COPS performance tests have been reported for n = 100, 200, 400, 800 Dolan, E D, and More, J J, Benchmarking Optimization Software with COPS. Tech. rep., Mathematics and Computer Science Division, 2000. Anitescu, M, and Serban, R, A Sparse Superlinearly Convergent SQP with Applications to Two-Dimensional Shape Optimization. Tech. rep., Argonne National Laboratory, 1998. $offtext $if not set n $set n 100 Set i discretization points /i1 * i%n%/; Alias (i,j); Scalar R_v design parameter related to the valve shape /1/ R_max maximum allowed radius of the cam /2/ R_min minimum allowed radius of the cam /1/ pi a famous constant alpha curvature limit parameter /1.5/ d_theta angle between discretization points; pi = 2*arctan(inf); d_theta = 2*pi/(5*(%n%+1)); set first(i), last(i), middle(i); first('i1') = yes; last('i%n%') = yes; middle(i) = yes; middle(first) = no; middle(last) = no; Variables r(i) radius of the cam at discretization points rdiff(i) intermediate area valve area; Equations obj objective convexity(i) convex_edge1(i) convex_edge3(i) convex_edge4(i) eqrdiff(i); obj.. area =e= ((pi*R_v)/%n%) * sum(i, r(i)); convexity(middle(i)).. -r(i-1)*r(i) - r(i)*r(i+1) + 2*r(i-1)*r(i+1)*cos(d_theta) =l= 0; convex_edge1(first(i)).. -R_min*r(i) - r(i)*r(i+1) + 2*R_min*r(i+1)*cos(d_theta) =l= 0; convex_edge3(last(i)).. -r(i-1)*r(i) - r(i)*R_max + 2*r(i-1)*R_max*cos(d_theta) =l= 0; convex_edge4(last(i)).. -2*R_max*r(i) + 2*sqr(r(i))*cos(d_theta) =l= 0; eqrdiff(j(i+1)).. rdiff(i) =e= r(i+1) - r(i); r.lo(i) = R_min; r.up(i) = R_max; rdiff.lo(i(j+1)) = -alpha*d_theta; rdiff.up(i(j+1)) = alpha*d_theta; r.lo('i1') = max(-alpha*d_theta + R_min, r.lo('i1')); r.up('i1') = min( alpha*d_theta + R_min, r.up('i1')); r.lo('i%n%') = max(R_max - alpha*d_theta, r.lo('i%n%')); r.up('i%n%') = min(R_max + alpha*d_theta, r.up('i%n%')); r.up('i1') = min( R_min/(2*cos(d_theta)-1), r.up('i1')); r.l(i) = (R_min+R_max)/2; model camshape /all/; $if set workspace camshape.workspace = %workspace%; solve camshape using nlp maximizing area;