Tadjouddine, M., Forth, S.A. and Keane, A.J.
Adjoint differentiation of a structural dynamics solver.
Bücker, M., Corliss, G., Hovland, P., Naumann, U. and Norris, B. (eds.)
Automatic Differentiation: Applications, Theory, and Implementations.
AD2004: The 4th International Conference on Automatic Differentiation
(Lecture Notes in Computational Science & Engineering, 50).
The design of a satellite boom using passive vibration control by Keane [J. of Sound and Vibration, 1995, 185(3),441-453] has previously been carried out using an energy function of the design geometry aimed at minimising mechanical noise and vibrations. To minimise this cost function, a Genetic Algorithm (GA) was used, enabling modification of the initial geometry for a better design. To improve efficiency, it is proposed to couple the GA with a local search method involving the gradient of the cost function. In this paper, we detail the generation of an adjoint solver by automatic differentiation via ADIFOR. This has resulted in a gradient code that runs in 7.4 times the time of the function evaluation. This should reduce the rather time-consuming process (over 10 CPU days by using parallel processing) of the GA optimiser for this problem.
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