Prediction and optimization of passive damping treatment's efficiency

Excessive noise and vibration are persistent challenges in many engineering applications, from aeronautics to civil engineering and biomechanics. These phenomena can degrade performance, reduce service life, and affect user comfort and safety. As design trends continue toward lighter, thinner, and more flexible structures, the tendency for such systems to exhibit pronounced dynamic responses increases. Among the broad variety of vibration damping treatment, passive viscoelastic damping treatments remain the preferred solution in many industrial contexts, particularly where reliability, low maintenance, and simplicity are crucial.

Among them, constrained-layer damping (CLD) configurations (consisting of a viscoelastic core layer sandwiched between structural and constraining layers) have proven to be especially efficient in dissipating vibrational energy across broad frequency ranges. However, their performance is highly dependent on a number of parameters, including material properties, layer thicknesses, temperature, frequency, and pres-stress. The design and optimisation of passive damping systems, and CLDs in particular, remain a challenge. The viscoelastic materials used in such configurations exhibit complex time- and frequency-dependent behaviours that are sensitive to temperature and loading conditions. Predicting the damping efficiency of a viscoelastic treatment from numerical simulations requires accurate material characterisation and reliable constitutive models capable of reproducing these dependencies and exploring the influence of design parameters systematically.

The research presented in this HDR thesis addresses these challenges by establishing a comprehensive framework linking material characterisation, constitutive modelling, numerical simulation, and experimental validation for viscoelastically damped structures. The overall research approach is strongly interdisciplinary, combining insights from materials science, structural dynamics, and computational mechanics. Through this integrated methodology, this work contributes to a more predictive and physically grounded understanding of viscoelastic damping in complex structures. The results are expected to facilitate the rational design and optimisation of damping treatments in a wide range of engineering applications, bridging the gap between laboratory characterisation and full-scale structural performance.