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of a surface treatment is highly sensitive to the variability in operational temperature. This paper proposes a statistical approachto modelthe variabilityof viscoelastic damping material in aconstrained-layer dampinglayout, to predict variability in the dynamic responses of viscoelastic damping material, and to obtain an optimal robust layout that accounts for severe variability in operational temperature. The viscoelastic damping material property can be modeled as a sum of 1) a random complex modulus due to operational temperature variability and 2) experiment/model errors in the complex modulus. The eigenvector dimension reduction method is used in probability analysis to predict the variability in the dynamic responses of the viscoelastic damping material. It is concluded that temperature variability is strongly propagated to that in the dynamic responses of the damping material. This study also performs reliability-based design optimization for an optimal robust design of the constrained-layer damping structure. It is shown that reliability-based design optimization gives a more robust and reliable damping layout design amidst severe variability in operational temperature.
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