Mitja Nemec

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A Newton–Krylov algorithm is presented for two-dimensional Navier–Stokes aerodynamic shape optimization problems. The algorithm is applied to both the discrete-adjoint and the discrete ow-sensitivity methods for calculating the gradient of the objective function. The adjoint and ow-sensitivity equations are solved using a novel preconditioned generalized(More)
  • D W Zingg, S De Rango, M Nemec, T H Pulliam
  • 1989
Grid convergence studies for subsonic and transonic flows over airfoils are presented in order to compare the accuracy of several spatial discretizations for the compressible Navier–Stokes equations. The discretizations include the following schemes for the inviscid fluxes: (1) second-order-accurate centered differences with third-order matrix numerical(More)
  • M Nemec, M J Aftosmis, T H Pulliam
  • 2004
1 Abstract A modular framework for aerodynamic optimization of complex geometries is developed. By working directly with a parametric CAD system, complex-geometry models are modified and tessellated in an automatic fashion. The use of a component-based Cartesian method significantly reduces the demands on the CAD system, and also provides for robust and(More)
  • D W Zingg, M Nemec, T H Pulliam, marian Nemec, Gov, Résumé
  • 2008
A genetic algorithm is compared with a gradient-based (adjoint) algorithm in the context of several aerodynamic shape optimization problems. The examples include single-point and multipoint optimization problems, as well as the computation of a Pareto front. The results demonstrate that both algorithms converge reliably to the same optimum. Depending on the(More)
The implementation of the convective-upstream-split-pressure (CUSP) approach to numerical dissipation is presented for an approximately factored algorithm in conjunction with time-derivative local preconditioning. An inexpensive ux limiter is used to blend the low-and high-order CUSP dissipation to capture shocks without oscillations. The resulting(More)