Approximate Hessian for accelerated convergence of aerodynamic shape optimization problems in an adjoint-based framework

DOI10.1016/j.compfluid.2018.04.019zbMath1390.74161OpenAlexW2798067359WikidataQ129980559 ScholiaQ129980559MaRDI QIDQ1649882

Doug Shi-Dong, Siva K. Nadarajah

Publication date: 28 June 2018

Published in: Computers and Fluids (Search for Journal in Brave)

Full work available at URL: https://escholarship.mcgill.ca/concern/theses/gb19f849v

zbMATH Keywords

Hessianadjointaerodynamic shape optimization

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) General aerodynamics and subsonic flows (76G25) Optimization of shapes other than minimal surfaces (49Q10) Topological methods for optimization problems in solid mechanics (74P15)

Related Items (2)

Efficient deep data assimilation with sparse observations and time-varying sensors ⋮ Full-space approach to aerodynamic shape optimization

Uses Software

• SNOPT
• PETSc
• NLPQLP
• Ipopt
• TAPENADE

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Implicit multigrid schemes for challenging aerodynamic simulations on block-structured grids
• Computation of the Hessian matrix in aerodynamic inverse design using continuous adjoint formulations
• The continuous direct-adjoint approach for second-order sensitivities in viscous aerodynamic inverse design problems
• First- and second-order aerodynamic sensitivity derivatives via automatic differentiation with incremental iterative methods
• Aerodynamic shape optimization using first and second order adjoint and direct approaches
• Mesh deformation using radial basis functions for gradient-based aerodynamic shape optimization
• Aerodynamic design via control theory
• Optimum aerodynamic design using the Navier-Stokes equations
• Analysis of the Hessian for aerodynamic optimization: Inviscid flow
• Inexact Hessian-vector products in reduced-space differential-equation constrained optimization
• On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
• Aerodynamic design using the truncated Newton algorithm and the continuous adjoint approach
• Adjoint Methods for Shape Optimization
• The Tapenade automatic differentiation tool
• A QUANTITATIVE FORMULATION OF SYLVESTER'S LAW OF INERTIA
• Direct, adjoint and mixed approaches for the computation of Hessian in airfoil design problems
• Relative Perturbation Theory: I. Eigenvalue and Singular Value Variations
• Flux-limited schemes for the compressible Navier-Stokes equations
• SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization

This page was built for publication: Approximate Hessian for accelerated convergence of aerodynamic shape optimization problems in an adjoint-based framework