This work discusses an approach, rst-order approximationand model management optimization (AMMO), for solving design optimization problems that involve computationally expensive simulations. AMMO maximizes the use of lower-delity, cheaper models in iterative procedures with occasional, but systematic, recourse to higherdelity, more expensive models for monitoring the progress of design optimization. A distinctive feature of the approach is that it is globally convergent to a solution of the original, high-delity problem. Variants of AMMO based on three nonlinear programming algorithms are demonstrated on a three-dimensional aerodynamic wing optimization problem and a two-dimensionalairfoil optimizationproblem. Euler analysison meshes of varying degrees of re nement provides a suite of variable-delity models. Preliminary results indicate threefold savings in terms of high-delity analyses for the three-dimensional problem and twofold savings for the two-dimensional problem. Nomenclature C D = drag coef cient C L = lift coef cient C l = rolling moment coef cient C M = pitching moment coef cient c E = equality constraints c I = inequality constraints f = objective function M 1 = freestream Mach number S = semispan wing planform area x; x L ; x U = design variables and bounds ® = angle of attack 1 = trust-region radius
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