Aerodynamic design via control theory
Journal of Scientific Computing
Algorithm 755: ADOL-C: a package for the automatic differentiation of algorithms written in C/C++
ACM Transactions on Mathematical Software (TOMS)
ADIC: an extensible automatic differentiation tool for ANSI-C
Software—Practice & Experience
Recipes for adjoint code construction
ACM Transactions on Mathematical Software (TOMS)
Evaluating derivatives: principles and techniques of algorithmic differentiation
Evaluating derivatives: principles and techniques of algorithmic differentiation
Domain optimization of a multi-element airfoil using automatic differentiation
Advances in Engineering Software
Aerofoil optimisation via AD of a multigrid cell-vertex Euler flow solver
Automatic differentiation of algorithms
Recomputations in reverse mode AD
Automatic differentiation of algorithms
Adifor 2.0: Automatic Differentiation of Fortran 77 Programs
IEEE Computational Science & Engineering
Automatic Generation of Efficient Adjoint Code for a Parallel Navier-Stokes Solver
ICCS '02 Proceedings of the International Conference on Computational Science-Part II
Computation of Sensitivity Information for Aircraft Design by Automatic Differentiation
ICCS '02 Proceedings of the International Conference on Computational Science-Part II
Efficient and accurate derivatives for a software process chain in airfoil shape optimization
Future Generation Computer Systems
Future Generation Computer Systems
Algorithmic Differentiation: Application to Variational Problems in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A methodology for the development of discrete adjoint solvers using automatic differentiation tools
International Journal of Computational Fluid Dynamics
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FastOpt's new automatic differentiation tool TAF is applied to the two-dimensional Navier-Stokes solver NSC2KE. For a configuration that simulates the Euler flow around an NACA airfoil, TAF has generated the tangent linear and adjoint models as well as the second derivative (Hessian) code. Owing to TAF's capability of generating efficient adjoints of iterative solvers, the derivative code has a high performance: running both the solver and its adjoint requires 3.4 times as long as running the solver only. Further examples of highly efficient tangent linear, adjoint, and Hessian codes for large and complex three-dimensional Fortran 77-90 climate models are listed. These examples suggest that the performance of the NSC2KE adjoint may well be generalised to more complex three-dimensional CFD codes. We also sketch how TAF can improve the adjoint's performance by exploiting self-adjointness, which is a common feature of CFD codes.