Optimum Design of Segmented Passive-Constrained Layer Damping Treatment Through Genetic Algorithms

Abstract

The optimization of geometry and material properties of Passive Constrained Layer Damping (PCLD) treatments has been the subject of many research efforts in recent years. In this study, a genetic algorithm is used to investigate the relationship of the viscoelastic layer thickness, the constraining layer thickness, and the number of cuts initiated in the PCLD treatment as they all relate to optimum damping of beams. Genetic algorithms mimic the biological evolution process where potential solutions compete for survival based on their relative fitness. As a measure of the fitness of the PCLD treatment, a finite element model is used to compute the loss factor for the first mode of vibration with the capability of segmenting the treatment. It is found that, while the loss factor increases asymptotically with the increase in the viscoelastic layer thickness, an optimum constraining layer thickness for each viscoelastic layer thickness exists. The number of cuts in the segmented treatment tends to decrease with increasing thickness of the damping treatment. Furthermore, it was found that the optimum constraining layer thickness decreases with increasing the thickness of the viscoelastic layer. Physical insight is shed on all observations made which makes future optimization of PCLD treatment more focused in terms of criteria and goals.