Output-driven mesh adaptation is used in conjunction with an embedded-boundary Cartesian meshing scheme for sonic-boom simulations. The approach automatically refines the volume mesh in order toâ€¦ (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 andâ€¦ (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 Blenderâ€¦ (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 discreteâ€¦ (More)

A gradient-based Newtonâ€“Krylov algorithm is presented for the aerodynamic shape optimization of singleand multi-element airfoil configurations. The flow is governed by the compressible Navierâ€“Stokesâ€¦ (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 andâ€¦ (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 wallâ€¦ (More)

We consider analysis and design of low sonic-boom aircraft through the use of an inviscid, embedded-boundary Cartesian mesh method. Adjoint error estimation and adaptive meshing are used in theâ€¦ (More)

A modular process for performing general parametric studies about an aerodynamic configuration using a Cartesian method is described. A novel part of this process is the automatic handling of generalâ€¦ (More)

We present a parallel adjoint framework for aerodynamic shape optimization problems using an embedded-boundary Cartesian mesh method. The design goals for the framework focus on an efficient andâ€¦ (More)