Tadjouddine, MohamedForth, Shaun A.Keane, Andy J.2011-11-212011-11-212006-12-01Mohamed Tadjouddine, Shaun A. Forth & Andy J. Keane, Adjoint Differentiation of a Structural Dynamics Solver. Automatic Differentiation: Applications, Theory, and Implementations, Bücker, M.; Corliss, G.; Hovland, P.; Naumann, U.; Norris, B. (Eds.), Lecture Notes in Computational Science & Engineering, Volume 50, p309-319, 20063-540-28403-6http://dspace.lib.cranfield.ac.uk/handle/1826/3132http://dx.doi.org/10.1007/3-540-28438-9_27The 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.reverse mode ADhybrid GA-local searchstructural dynamicsperformanceArticle