Build-up Approach to Updating the Mock Quiet Spike Beam Model

Herrera, Claudia Y.; Pak, Chan-gi

doi:10.2514/6.2007-1776

Cited by 6 publications

(1 citation statement)

References 2 publications

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“…[9][10][11] There are two optimization algorithms adopted in NASA Dryden's MDAO tool: the traditional gradient-based algorithm 12 and the genetic algorithm. Gradient-based algorithms work well for continuous design variable problems, whereas GAs can handle continuous as well as discrete design variable problems easily.…”

Section: Structural Dynamic Model Tuning Proceduresmentioning

confidence: 99%

Updating the Finite Element Model of the Aerostructures Test Wing Using Ground Vibration Test Data

Lung

Pak

2009

50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the Aerostructures Test Wing (ATW), which was designed and tested at the National Aeronautics and Space Administration (

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Section: Structural Dynamic Model Tuning Proceduresmentioning

confidence: 99%