Marian 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(More)
A gradient-based Newton–Krylov algorithm is presented for the aerodynamic shape optimization of singleand multi-element airfoil configurations. The flow is governed by the compressible Navier–Stokes equations in conjunction with a one-equation transport turbulence model. The preconditioned generalized minimal residual method is applied to solve the(More)
OPTIMAL SHAPE DESIGN OF AERODYNAMIC CONFIGURATIONS: A NEWTON-KRYLOV APPROACH Marian Nemec <marian@oddjob.utias.utoronto.ca> Doctor of Philosophy Graduate Department of Aerospace Science and Engineering University of Toronto 2003 Optimal shape design of aerodynamic configurations is a challenging problem due to the nonlinear effects of complex flow features(More)
We present a versatile discrete geometry manipulation platform for aerospace vehicle shape optimization. The platform is based on the geometry kernel of an open-source modeling tool called Blender and offers access to four parametric deformation techniques: lattice, cage-based, skeletal, and direct manipulation. Custom deformation methods are implemented as(More)
This report concerns research performed in fulfillment of a 2.5-year NASA Seedling Fund grant to develop an adaptive shape parameterization approach for aerodynamic optimization of discrete geometries. The overarching motivations for this work were the potential to radically reduce manual setup time and achieve faster and more robust design improvement,(More)
A discrete-adjoint formulation is presented for the three-dimensional Euler equations discretized on a Cartesian mesh with embedded boundaries. The solution algorithm for the adjoint and flow-sensitivity equations leverages the Runge–Kutta time-marching scheme in conjunction with the parallel multigrid method of the flow solver. The matrix-vector products(More)
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)
We present a new approach for the computation of shape sensitivities using the discrete adjoint and flow-sensitivity methods on Cartesian meshes with general polyhedral cells (cutcells) at the wall boundaries. By directly linearizing the cut-cell geometric constructors of the mesh generator, an efficient and robust computation of shape sensitivities is(More)
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 efficient(More)