The performance of particle damper is strongly nonlinear, and the energy dissipation is derived from a combination of mechanisms including plastic collisions and friction between the particles and the walls and between the particles themselves. An optimized support vector regression model is built to predict the damping ratio of cantilever beam with particle damper. Then, the optimal parameters are adopted to construct the support vector regression models. In addition, genetic algorithm is used to select the optimal variables so as to improve the predictive ability of the models. Cross validation combined with support vector regression is used in this research and is compared with the genetic algorithm-support vector regression method. Genetic algorithm-support vector regression as research object to compare with the combination of cross validation and support vector regression. The experimental results demonstrate that the proposed genetic algorithm-support vector regression model provides better prediction capability. Therefore, the genetic algorithm-support vector regression model is proven to be an effective approach to predict the damping ratio of cantilever beam with particle damper.

Metamaterials, characterized by unique structures, exhibit exceptional properties applicable across various domains. Traditional methods like experiments and finite-element methods (FEM) have been extensively utilized to characterize these properties. However, exploring an extensive range of structures using these methods for designing desired structures with excellent properties can be time-intensive. This paper formulates a machine-learning-based approach to expedite predicting effective metamaterial properties, leading to the discovery of microstructures with diverse and outstanding characteristics. The process involves constructing 2D and 3D microstructures, encompassing porous materials, solid–solid-based materials, and fluid–solid-based materials. Finite-element methods are then employed to determine the effective properties of metamaterials. Subsequently, the Random Forest (RF) algorithm is applied for training and predicting effective properties. Additionally, the Aquila Optimizer (AO) method is employed for a multiple optimization task in inverse design. The regression model generates accurate estimation with a coefficient of determination higher than 0.98, a mean absolute percentage error lower than 0.088, and a root mean square error lower than 0.03, indicating that the machine-learning-based method can accurately characterize the metamaterial properties. An optimized structure with a high Young’s modulus and low thermal conductivity is designed by AO within the first 30 iterations. This approach accelerates simulating the effective properties of metamaterials and can design microstructures with multiple excellent performances. The work offers guidance to design microstructures in various practical applications such as vibration energy absorbers.

The vibration transmission characteristics of a three-degree of freedom nonlinear floating raft isolation system are studied in order to analyze the influence of magneto-rheological damper on primary resonance attenuation. A revised Bingham model verified by experiment is adopted to describe the nonlinear magneto-rheological damping force, and the dissipated energy based on the model is given which is more than general viscous damper. Then, the approximately analytic solution for primary resonance of floating raft isolation system is obtained by means of averaging method, and it is compared with numerical integration solution. Force transmissibility is proposed to evaluate the effectiveness of magneto-rheological damper. The influences of magneto-rheological damper parameters on force transmissibility are also investigated. The results show that force transmissibility decreases as the increase of viscous damping coefficient of magneto-rheological damper and zero-force velocity. The influence of control force is the same with in the first and third resonance frequency but has opposite effect in the second one. The results obtained from this work are benefit to control vibration transmission of rotating machine.

The vibration reduction device for the offshore platform truss structure has exposed to long term high-energy ultraviolet light and salt spray radiation, the traditional viscoelastic damping technology is easy to aging and failure, and its operational lifetime is limited. The semi-active particle damping technology has the advantages of high temperature resistance, anti-aging and so on, at the same time it is also able to adapt the changes of external complex load. The coupling simulation algorithm was used in this paper to study on vibration reduction performance of semi-active particle damping technology for the offshore platform truss structure. The control strategy, simulation algorithm and key parameters of semi-active particle damping are investigated to analyze the vibration reduction effect of the offshore platform truss structure with semi-active particle damper. The results have shown that the semi-active particle damping has a better effect of vibration reduction compared with the passive particle damping. In addition, the control strategy in different frequency bands has different vibration reduction effects to the system; and the simulation has a good agreement with the experimental results.

Using the band gap properties of the periodic structure, the truss structure of an offshore platform is designed as a one-dimensional periodic conduit structure, and the band gap characteristics are used to realize the vibration control of the truss structure of the offshore platform. The finite element method is used to simulate the vibration characteristics of the periodic conduit, and the influence of the structural parameters (length and wall thickness) of the periodic conduit on the vibration band gap of the periodic conduit is analysed. The frequency response characteristics of the periodic truss structure of an ocean platform are calculated and compared with those of a traditional truss structure. The results show that the periodic truss exhibits better suppression of vibration transmission than the traditional truss, especially for the vibration in the band gap, which is greatly attenuated. This study shows that the periodic structure has broad application prospects in vibration isolation design of truss structures for offshore platforms. The research provides a new technical approach for vibration control of truss structures on offshore platforms.

In this paper, the propagation characteristics of vibration waves in periodic pipelines were studied based on the band theory of phononic crystals, and we analyzed the influence of the geometrical structure parameters on the band gap characteristics of pipelines. The results show that, by increasing the number of layers of local resonant structure, both the initial frequency and the cutoff frequency of the band gap moved towards the lower frequency, while the width of the system band gap increased by 35 Hz, and the damping effect increased by 18.3 dB. By changing the thickness of the wall of the pipeline system, the width of the system band gap increased by 20 Hz, and the damping effect increased by 9.1 dB. The maximum vibration isolation of the offshore platform truss based on the periodic structure can be up to 7.93 dB. Therefore, it is feasible to apply the local resonant periodic structure to the vibration control of a practical offshore platform.