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The capacity of Phononic crystals (PCs) to form bandgaps (BGs) that limit the transmission of elastic/acoustic waves is a key property that is particularly beneficial for vibration/sound isolation and signal processing. In this work, a parametric analysis of Poisson's ratio of rubber, and the density, geometry and size of scatterer on the BGs of porous, solid/solid, fluid/solid and solid/fluid PCs is presented. Based on the simulation results, it is found that the width of the first absolute bandgaps (FABGs) of porous PCs is not necessarily proportional to the porosity due to the pore shape; when Poisson's ratio of compressible and incompressible rubber is increased, the FABG width of porous PC decreases dramatically. In addition, the FABGs of solid/solid PCs are strongly dependent on whether the rubber is a matrix or scatterer; the fluctuation of the FABGs is also highly related to the density of the solid. Fluid–structure PCs have smaller FABGs than porous and solid/solid PCs, and these FABGs usually occur within higher-order energy bands. Rubber compressibility significantly affects the FABGs of porous and solid/solid PCs, but almost not fluid-structural PCs. The results presented in this work offer guidance to tune the BG and design acoustic devices in various practical applications such as noise and vibration insulators. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Mechanical metamaterials are valued for their diverse properties and potential applications. Due to the instability and large deformability of soft mechanical metamaterials (SMMs), geometric reorganization will occur and lead to some unusual properties. It is possible to change the properties of materials by varying the parameters. Conventional SMMs contain a periodic distribution of holes with the same size and shape, which can be changed to a lesser extent. Periodic dispersion of regular through-hole patterns of various sizes or shapes into elastomers, resulting in metamaterials with more mechanical functionality and deformation scenarios. In this paper, we investigated the influence of parameters on the buckling mechanical behavior of SMMs and the buckling mechanical behavior of structures with multiple sizes and geometric shapes. The parameters studied include geometric parameters (pore shape, porosity and area ratio) and physical parameters (Poisson's ratio and compression mode). Simulation of the buckling behavior of SMMs uses the finite element method. The finite element software ABAQUS is used, taking into account the almost incompressible characteristics of materials, the triangular quadratic plane strain hybrid element is selected (CPE6H). Numerical calculation gives the following results: Area ratio, pore shape and compression mode have obvious effects on buckling behavior, but Poisson's ratio has little effect; the influence of parameters on the buckling critical strains varied for SMMs with various pore shapes; very different buckling behaviors will result from swapping out the pattern of holes with the same size or shape for holes with two different sizes or shapes; the expression of buckling behavior is also varied when the mix of hole shapes is modified. These findings demonstrate that the design parameters may be used to achieve the desired buckling behaviors. This is a new method that can be used to control the deformation of structures; modify the properties of the SMMs without changing stiffness; simplify the structures without significantly changing the material properties. The design path of mechanical metamaterials is increased. [ABSTRACT FROM AUTHOR]

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.

This article proposes an advanced far-field acoustic hologram for vehicle sound source identification and investigates a method of performing contribution analyses in the far field. The hologram is applied for statistically optimized near-field acoustic holography used to identify vehicle sound sources (internal and external). An advanced far-field acoustic hologram is first proposed to improve the spatial resolution of low-frequency sound source locations in the far field. In addition, an acoustic contribution analysis based on near-field acoustic holography is used to provide a direction for low-noise optimization design. Next, a new sound source identification and low-noise technology is explored via the aforementioned methods and applied for sound source identification and acoustic contribution analyses for a vehicle. The analysis results showed that in the process of sound source identification, the contribution of each sound source can be simultaneously sorted, and this finding can help guide research on the low-noise control of a vehicle.