Adjoint Differentiation of a Structural Dynamics Solver.

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dc.contributor.author Tadjouddine, Mohamed -
dc.contributor.author Forth, Shaun A. -
dc.contributor.author Keane, Andy J. -
dc.date.accessioned 2011-11-21T23:00:56Z
dc.date.available 2011-11-21T23:00:56Z
dc.date.issued 2006-12-01T00:00:00Z -
dc.identifier.citation Mohamed 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, 2006 -
dc.identifier.isbn 3-540-28403-6 -
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/3132
dc.identifier.uri http://dx.doi.org/10.1007/3-540-28438-9_27
dc.description.abstract 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. en_UK
dc.subject reverse mode AD en_UK
dc.subject hybrid GA-local search en_UK
dc.subject structural dynamics en_UK
dc.subject performance en_UK
dc.title Adjoint Differentiation of a Structural Dynamics Solver. en_UK
dc.type Article -


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