Surrogate model-based multi-objective design optimization of vibration suppression effect of acoustic black holes and damping materials on a rectangular plate

The acoustic black hole (ABH) is a ground-breaking passive technology for vibration reduction and noise attenuation, characterized by its ability to manipulate flexural waves. When multiple two-dimensional ABHs are embedded in an irregular shaped complex plate structure used in engineering, such as the support plate of a refrigerator compressor, its vibration characteristics often cannot be solved through analytical or semi-analytical methods, resulting in the inability to carry out subsequent ABH optimization design. To address this issue, we propose a high-precision modelling method that combines surrogate models with finite element methods to construct a vibration characteristic database of the compressor support plate embedded with multiple ABHs in all design spaces of the ABH and damping materials geometric parameters using limited sample data. A high-precision surrogate model was constructed based on the vibration response data of the ABH plate under 50 parameter combinations of ABH and damping layer, and the fitting accuracy of the surrogate model was verified through vibration response data under another 25 parameter combinations. Based on the constructed surrogate model, the Multi-objective Genetic Algorithm (MOGA) was employed to optimize the five parameters of ABH and damping layer simultaneously, aiming to maximize the vibration reduction effect of the ABHs. Our investigation reveals that the optimized ABH and damping materials significantly improve the vibration suppression effect in a wide frequency range compared to the unoptimized structures. Finally, experimental verification was conducted to solidify the accuracy and efficacy of our approach in enhancing vibration reduction effect for irregular shaped complex plate structures using acoustic black holes.