Reverse Automatic Differentiation for Optimum Design: From Adjoint State Assembly to Gradient Computation

DOI10.1080/10556780310001610501zbMath1142.90524OpenAlexW1965045771MaRDI QIDQ4653555

Alain Dervieux, Bruno Koobus, Francois Courty, Laurent Hascoët

Publication date: 7 March 2005

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://hal.inria.fr/inria-00072225/file/RR-4363.pdf

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Flow control and optimization for compressible fluids and gas dynamics (76N25) Numerical methods for mathematical programming, optimization and variational techniques (65K99)

Related Items (5)

Aerodynamic shape optimization using first and second order adjoint and direct approaches ⋮ Continuous adjoint methods for turbulent flows, applied to shape and topology optimization: industrial applications ⋮ Nested and self-adaptive Bézier parameterizations for shape optimization ⋮ Consistent treatment of incompletely converged iterative linear solvers in reverse-mode algorithmic differentiation ⋮ Stabilisation of discrete steady adjoint solvers

Uses Software

• TAMC

Cites Work

• Unnamed Item
• Aerodynamic design via control theory
• Reduced functions, gradients and Hessians from fixed-point iterations for state equations
• Progressive optimization of inverse fluid dynamic design problems
• A semi-coarsening strategy for unstructured multigrid based on agglomeration
• Convergence Analysis of the Defect-Correction Iteration for Hyperbolic Problems

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