BibTeX
@INCOLLECTION{
         Tadjouddine2005ADo,
       author = "Mohamed Tadjouddine and Shaun A. Forth and Andy J. Keane",
       title = "Adjoint Differentiation of a Structural Dynamics Solver",
       editor = "H. M. B{\"u}cker and G. Corliss and P. Hovland and U. Naumann and B.
         Norris",
       booktitle = "Automatic Differentiation: {A}pplications, Theory, and Implementations",
       series = "Lecture Notes in Computational Science and Engineering",
       publisher = "Springer",
       year = "2005",
       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 .4$ times the time of the function evaluation. This should reduce the rather time-consuming
         process (over $ CPU days by using parallel processing) of the GA optimiser for this problem.",
       crossref = "Bucker2005ADA",
       ad_area = "Structural Dynamics",
       ad_tools = "ADIFOR",
       pages = "309--319",
       doi = "10.1007/3-540-28438-9_27"
}