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- W1985325040 abstract "Acomputationalframework is presented for the design of large flexible space structures with nonperiodicgeometries to achieve passive vibration suppression. The present system combines an approximationmodel management framework (AMMF) developed for evolutionary optimization algorithms (EAs) with reduced basis approximate dynamic reanalysis techniques. A coevolutionary genetic search strategy is employed to ensure that design changesduring the optimization iterations lead to low-rank perturbations of the structural system matrices, for which thereduced basis methods give high-quality approximations. The k-means algorithm is employed for cluster analysisof the population of designs to determine design points at which exact analysis should be carried out. The fitness ofthe designs in an EA generation is then approximated using reduced basis models constructed around the pointswhere exact analysis is carried out. Results are presented for the optimal design of a two-dimensional cantileveredspace structure to achieve passive vibration suppression. It is shown that significant vibration isolation of the orderof 50 dB over a 100-Hz bandwidth can be achieved. Further, it is demonstrated that the AMMF can potentiallyarrive at a better design compared to conventional approaches when a constraint is imposed on the computationalbudget available for optimization." @default.
- W1985325040 created "2016-06-24" @default.
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- W1985325040 date "2001-07-01" @default.
- W1985325040 modified "2023-10-14" @default.
- W1985325040 title "Passive Vibration Suppression of Flexible Space Structures via Optimal Geometric Redesign" @default.
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- W1985325040 doi "https://doi.org/10.2514/2.1452" @default.
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