This study introduces a multi-scale composite metamaterial capable of simultaneously achieving dual-directional sound absorption in both air and water. Following optimization through teaching–learning-based optimization algorithms, the composite metamaterial demonstrates an average sound absorption coefficient of 0.9811 in air and 0.828 in water in the frequency range of 1 Hz to 10 kHz, representing increases of 75.79% and 177.57%, respectively. Moreover, the optimized design reduces the thickness by 7.5 mm, offering crucial insights for the silent design of marine equipment.

To facilitate rapid and precise estimation of the acoustic performance of composite structures, this paper employs Deep Neural Networks (DNNs) within the realm of machine learning to tailor the design based on three key characteristics of the sound absorption performance of composite acoustic metamaterials: the frequency and magnitude of the maximum absorption peak, and the average absorption coefficient. Initially, a database comprising 100,000 randomly generated absorption curves was established, with 90 % of the data allocated for training and the remaining 10 % for test named data subset A. Subsequently, the database subjected to five-fold cross validation demonstrated a considerable level of prediction accuracy on data subset A and various ranges of data subset B. Finally, this paper randomly selected 10 sets of three sound-absorption characteristic parameters and conducted inverse prediction of the 28 geometric parameters for the corresponding composite acoustic metamaterials, using a fixed data subset A for each parameter set. These predicted geometric parameters were then used to derive the predicted sound absorption characteristics for the ten sets. When compared to the given values, the results exhibited a maximum relative error of 4.110 %, a minimum of 0.000 %, with the majority of errors falling within 0.100 %. This demonstrates that the DNN model presented in this paper can achieve accurate and swift predictions of the primary acoustic characteristics of acoustic composite structures, offering direct benefits in reducing the development cycle and saving labor and time costs.

This work presents a plug-in sonic black hole (SBH) designed for insertion at the termination of circular ducts to achieve broadband sound absorption. Unlike standard SBHs, which require tailoring the duct wall geometry, the plug-in configuration consists of an independently manufactured, axisymmetric insert. This alternative approach offers several acoustic advantages. For the same free cross-sectional area, the plug-in SBH exhibits a lower reflection coefficient than the standard design. Moreover, while the latter relies on the rainbow trapping effect-associated with cavity resonances-over a sometimes dominant frequency range, the black hole effect-associated with axial Fabry-P & eacute;rot resonances-operates over a significantly broader frequency band in the plug-in SBH. The performance of the device is assessed through a progressive modeling strategy: starting from a continuous waveguide approximation, followed by a discretized model with a finite number of rings, and finally validated experimentally. A prototype was 3D printed and tested in an impedance tube, demonstrating both the feasibility and effectiveness of the proposed concept, with good agreement with numerical simulations. From a practical perspective, the plug-in SBH is easy to fabricate using low-cost 3D printing and can be adapted to ducts of arbitrary geometry and material, making it highly versatile and suitable for retrofitting.

The acoustic response of a seven-bladed E1619 propeller operating in the turbulent wake of a SUBOFF bare hull is investigated numerically to clarify the hydrodynamic origin of turbulence-ingestion noise, particularly the role of suction-modified coherent structures in sound generation. The SUBOFF hull is considered at a length-based Reynolds number of 1.3×107, and two propeller advance ratios, J=0.85 and J=0.55, are examined. The stern wake and propeller interaction are resolved using scale-resolving large-eddy simulation, and the radiated sound is calculated using the Ffowcs Williams–Hawkings equation. The numerical framework is assessed against available hydrodynamic and unsteady-loading benchmark data. In addition to broadband turbulence-ingestion noise, haystacking humps near the blade-passing frequency and associated blue-shifted peaks are predicted. These features are linked to correlated unsteady blade loading generated when successive blades intercept the same elongated turbulent structures. Propeller suction accelerates the stern wake and elongates these structures before blade interaction. At the lower advance ratio, the higher rotational speed increases the blade-passing frequency and the likelihood of successive interception, accompanying stronger pressure fluctuations and radiated noise. The results support a stretching–cutting interpretation of propeller turbulence-ingestion noise in an axisymmetric hull wake.

To realize machine learning reverse-assisted design for resonant sound-absorbing structures, this study introduces resonant composite metastructures, which are constructed from perforated sheets, cavities, insert plates, and porous materials. The sound absorption coefficients within the range of 10,000 Hz were theoretically derived, and the underlying sound absorption mechanisms were thoroughly discussed. A dataset comprising 100,000 randomly generated first peaks was constructed using Latin hypercube sampling to support machine learning applications. Two approaches, a one-stage deep neural network and a two-stage deep neural network incorporating a forward prediction component-were developed to inversely predict the structural dimension parameters of eight resonant sound-absorbing units based on 24 sets of desired first peak characteristics. The results demonstrated that the two-stage model significantly outperformed the one-stage approach, achieving markedly higher accuracy in predicting both the frequency and sound absorption coefficient of the first peaks. The effectiveness of the machine learning predictions was further validated through acoustic impedance tube experiments on two samples designed via the two-stage deep neural network. These findings underscore the potential of machine learning for the efficient and accurate reverse design of resonant sound-absorbing structures.

The development of multi-band, wide-frequency, spectrum-tunable topological acoustic transmission is essential for the practical application of topological acoustic insulators. However, conventional approaches rely on complex structural reconfiguration or parameter modulation, which severely limits their flexibility. This paper addresses this issue by proposing a universal method of optimising multi-band structures based on stacked composite resonators. The key advantage of this strategy is that it provides comprehensive and flexible control over the number, width and position of operational frequency bands, simply by stacking and arranging resonators vertically. This approach neither alters the original scatterer geometry nor introduces additional parameters. Furthermore, it simplifies multiband control, allowing the operating bandwidth and position to be adjusted by merely altering the number and order of resonator layers. Research indicates that this method enables the on-demand introduction of multiple Dirac cones, as well as the flexible adjustment of existing frequency band widths and Dirac cone spectral positions. Each cone can open a bandgap independently and generate topologically protected one-way edge states. Superlattice simulations, acoustic field simulations and experimental measurements collectively confirm that all frequency bands exhibit the low transmission loss and strong defect immunity characteristic of topologically protected edge states. The proposed layered paradigm in this work revolutionises conventional band control approaches, offering a new way to develop high-performance, customisable, multiband acoustic topological devices.

This study numerically investigates the acoustic response of a seven-bladed propeller under the axisymmetric turbulent boundary layer at the stern of the SUBOFF bare hull model, aiming to clarify the noise generation mechanism with focus on the effect of propeller suction on vortex structures. The Reynolds number based on hull length is 1.3*10^7, and two advance ratios (0.85 and 0.55) are adopted. Large-eddy simulation is used to resolve the boundary layer, and the FW-H equation computes the far-field sound. On the basis of previous studies, this work further analyzes how propeller suction stretching upstream vortex structures affects noise. Results show that the haystacking and blue-shift phenomena originate from successive cutting of the same upstream turbulent structures by adjacent blades. Driven by propeller suction, structures in the tail-cone boundary layer develop rapidly into slender vortex filaments and are prone to repeated cutting. This stretching-cutting coupling is closely related to rotational speed: as the advance ratio decreases, the turbulent length scale shifts from single cutting to successive cutting. Numerical results well capture the influence of advance ratio on the acoustic field and are verified by open-water simulations.

Current active and passive noise reduction methods heavily rely on factors such as material properties, structural design, and weight, with noise cancellation processes primarily focused on gaseous, liquid, and solid states. In this study, we propose a novel theoretical model for modulating incident noise using ionic acoustic waves generated by corona discharge in the plasma state. These ionic acoustic waves are produced through the combined effects of thermal pressure from plasma ions and electrostatic forces arising from charge separation. Plasma-acoustic wave modulation based on negative corona discharge alters the dielectric field within the ionization region by influencing the motion of charged ions and electrons, thereby affecting the acoustic wave propagation process. Specifically, the generated ionic acoustic waves interfere with incident noise waves, leading to noise reduction. By adjusting the applied voltage, electrode gap, and discharge position in a needle-plate discharge configuration, the frequency, phase, and amplitude of the ionic acoustic waves can be precisely controlled, thereby modifying the interference outcomes. Theoretical verification demonstrates that tailored ionic acoustic waves effectively cancel incident noise within the 1-1000 Hz and 1000-2000 Hz frequency ranges. This work confirms the robustness of plasma-based corona discharge for future acoustic wave modulation applications and provides a theoretical foundation for developing "plasma-state noise reduction" acoustic functional devices.

This study proposes a data-driven design framework for the lightweight optimization of metamaterial beams with enhanced vibration-isolation performance. Dual acoustic black hole (ABH) beams with dual bandgap characteristics, namely a complete bandgap and an ABH bandgap, are adopted as unit cells, and topologically optimized hollow configurations are introduced in the root regions for mass reduction. A dataset containing 15,000 distinct hollow patterns and their corresponding bandgap distributions is constructed using parameterized finite-element simulations. A convolutional neural network (CNN) is then developed to establish the nonlinear mapping between geometric configurations and bandgap characteristics. Numerical results show that the proposed model achieves a prediction accuracy above 99.9% within 300 training epochs, with a mean squared error on the order of 10(-6) and excellent robustness (Delta accuracy < 0.0004). For representative samples with eta = 0.16-0.445, the model achieves 99.87% - 99.99% accuracy for the complete bandgap and 99.97% - 99.99% accuracy for the first ABH bandgap, while the latter exhibits higher numerical stability. The root excavation strategy enables 21.9% - 44.5% mass reduction while preserving the longitudinal, flexural, and ABH bandgap characteristics, demonstrating substantial lightweight potential. Compared with conventional design approaches, the proposed machine-learning-assisted framework significantly reduces the computational cost and design cycle, providing an efficient route for the lightweight design of ABH beam structures.

To address the issue of human resource wastage and the lack of direction in phononic crystal design, this study adopts the network structures of variational autoencoder, multi-layer perceptron, and twin neural network, to achieve high-precision forward and inverse predictions for two-dimensional phononic crystals. Five-fold cross-validation was conducted on the dataset, and the resulting accuracy demonstrated the strong generalization capability and robustness of the model structures of the multi-layer perceptron and twin neural network. Specifically, 90% of the accuracy values in forward predictions are equal to or greater than 0.98, while 98% of the accuracy values in inverse predictions are no less than 0.95. From a practical design standpoint, by incorporating a loss function into the twin neural network while considering both lightweight and bandgap performance, we can achieve high-precision, on-demand design with multiple objectives. The approach and methodology presented in this study offer significant insights for the rapid and accurate development of composite or structured materials.

Currently, the development of multiband acoustic topological systems is constrained by the dimensional characteristics of scattering elements. The number of bands in edge mode is limited and the bandgap width is also affected. Therefore,this paper presents a construction method for multi-band acoustic topology through spatial stacking. This method mainly involves stacking of resonant cavities in the vertical spatial direction of the scatterer, and utilizes the local resonance of the resonant cavities to excite additional operating frequency bands. Compared with the conventional acoustic topology, it can break the limitation of structure size and improve the space utilization. The results simulated by finite element simulation show that more number of working frequency bands can be constructed by superposing resonant cavities in its vertical spatial direction. Moreover, the number of layers of spatial stacking is positively correlated with the number of working bands. Finally, we focus on the acoustic topology when the space is superimposed to three layers of resonant cavities, and verify the correctness of this method by experimentally comparing and demonstrating that there are indeed ten effective acoustic transmission channels. This study breaks the limitation of the traditional acoustic topology in terms of structural size and realizes the construction of more operating frequency bands, which provides a new idea for the acoustic control field of multiband acoustic topology, multiband filter and acoustic sensor.

We propose a broadband multi-unit composite metamaterial consisting of nine sub-units capable of simultaneously achieving broadband noise reduction and electromagnetic wave absorption. A theoretical model was established to calculate the sound absorption coefficient and the teaching-learning-based algorithm was used to optimize the geometric dimensions. The optimized average sound absorption coefficients were 0.836, 0.907, 0.957, and 0.97 within the frequency ranges of 1-500 Hz, 1-1000 Hz, 1-3000 Hz, and 1-20000 Hz, respectively. Complex plane analysis indicated that the broadband multi-unit composite metamaterial exhibits quasi-perfect sound absorption. In addition, the change of the metal patch comprises double-C open circular rings, and the bottom plate is composed of dielectric substrates and metal substrates could affect the electromagnetic wave absorption effects under TE and TM modes and explain the reason for the excitation of Fano resonance absorption peaks under the TE mode. Next, the optimized double-C open circular rings result in the broadband multi-unit composite metamaterial exhibiting an absorption coefficient exceeding 0.5 between 12 and 30 GHz. The advantage of this design were verified through acoustic impedance tube and bow-shaped reflectance system. These results provide a reference for the development of multifunctional stealth technologies.

This study proposes an underwater coating with sound absorption ability in the middle-to-low frequency range and establishes an acoustic theoretical model combining the equivalent medium theory and the transfer matrix method. The sound absorption coefficient, surface characteristic impedance, equivalent volume longitudinal wave modulus, and equivalent sound velocity are calculated and solved. Using the preset 20 sensitive parameters and the hypercube sampling method, this study establishes 100,000 random sound absorption coefficient curves in the frequency range of 1 Hz–1,000 Hz. Further, deep neural networks are employed to predict the average value of the sound absorption coefficient curve. The overall loss function is derived by combining the mean square error between the expected average sound absorption coefficient and its predicted value and the network-optimized loss function to ensure that the 20 sensitive parameters that meet the acoustic performance can be predicted. Finally, two randomly selected sound absorption curves are used for prediction tests. The verification results indicate that the error between the expected average absorption coefficient and the predicted average absorption coefficient corresponding to the 20 sensitive parameters is only 0.026 % and 0.33 %. The proposed method can be extended to predict the average absorption coefficient value for any acoustic structure, which could be beneficial for the performance development of acoustic functional devices.

Directional induction of acoustic waves has gained increasing attention in recent years. Conventional acoustic topological insulators have drawbacks such as geometrical complexity and difficult processing, which increase the difficulty of engineering applications. In this paper, we propose a scatterer-free and easy-to-machine sonic crystal structure to realize topological acoustic transmission by embedding a cylindrical cavity on a solid substrate. Compared with conventional acoustic metamaterial plates, this structure can significantly enhance the acoustic transmission capability due to the absence of dissipative effect of resonant cavities. The acoustic interlayer structure was designed in parallel, and it was found that band modulation could be realized by changing the distance between the interlayers. This modulation method is different from the traditional method of changing the scatterer structure, which is simpler and more convenient. In addition, the design of the interlayer with no scatterer on the surface allows the placement of various acoustic sensors in the interlayer to realize specific functions. This study provides new design ideas for lightweight devices, high-precision acoustic sensing and low-loss acoustic devices. It also provides a more convenient and effective tuning method to accelerate the engineering of acoustic metamaterials.

In this paper, a composite structure with a micro-perforated boundary acoustic black hole is designed to control low-frequency band and wide-band noise. Firstly, the finite element and transfer matrix theoretical models for calculating the sound absorption coefficient of this system are respectively established and compared to verify. In addition, the acoustic properties inside the composite structure and the acoustic black hole effect of the composite structure were investigated at different frequencies. Secondly, this paper investigates the effects of the different parameters of composite structures on their sound absorption performance. Furthermore, the parameters of the composite structure are optimized using the Nelder-Mead simplex method. After optimization, the sound absorption coefficient of the composite structure is consistently above 0.9 from 325 Hz (735 Hz before optimization). Finally, the experimental results validate the accuracy of the finite element and transfer matrix methods. The optimized composite structure with microperforated boundary acoustic black holes has excellent sound absorption performance, which provides a new solution for efficient low-frequency broadband noise control in small-volume structures.

The aim of this paper is to design acoustic black hole structures for underwater pressure-resistant shells (PRSs), including single- and double-leaf structures, which are applied to the inner and outer PRS surfaces. The mean square velocity and displacement modes on the shell surface indicate that surface vibrations above the cutoff frequency can be effectively attenuated. Three sets of experiments are designed, i.e., PRS under white noise point excitation and underwater vehicle motor under no-load and load conditions. The data acquired at key measuring points reveal that the vibration acceleration on the shell surface has a significant attenuation effect in most of the frequency bands from 0.001 to 25 kHz, with a maximum attenuation of up to two orders of magnitude. It is particularly effective in suppressing strong vibrations at the switching frequency of underwater vehicle motors. The paper conclusions of this study can be directly applied to vibration and noise reduction systems for underwater equipment. Moreover, they offer another insights for developing potential broadband vibration and noise reduction structures.

To further enhance the sound absorption capabilities of porous materials, we employed electrospinning technology to prepare electrospinning nanofilms using polyvinyl butyral solution. These nanofilms were then applied in varying thicknesses onto the surfaces of both flexible and rigid porous materials, specifically melamine foam and foam nickel. Utilizing an acoustic impedance tube testing system, we measured the sound absorption coefficient within the frequency range of 200∼6400 Hz. The results reveal that, within this testing frequency range, the electrospinning nanofilm modestly enhances the sound absorption performance of flexible porous materials. However, for rigid porous materials, the improvement in sound absorption performance exhibits more significant variations. As the thickness of the electrospinning nanofilm increases, its enhancement becomes notably pronounced in the mid-to-low frequency range, while slightly decreasing in the high-frequency range. In composite porous structures, which consist of a stack of flexible and rigid porous materials, the effectiveness of the electrospinning nanofilm in enhancing sound absorption performance varies depending on its application location. When applied onto the surface of rigid porous materials, the sound absorption coefficient is significantly improved at medium and low frequencies, albeit with a decrease at high frequencies. Conversely, when the nanofilm is inserted between rigid and flexible materials, it enhances the sound absorption coefficient across the entire frequency range. Electrospinning nanofilm offers valuable insights into enhancing sound absorption performance and sheds light on the development of novel lightweight sound absorption structures.

AbstractThe interest of this article is to obtain the underwater broadband sound absorption characteristics by filling three layers of bubbles in Polydimethylsiloxane polymer (PDMS). In this underwater ultra‐thin metamaterial, three‐layer bubbles are arranged from small to large with the same radius center. The finite element analysis (FEA) method and transfer matrix (TM) method have good consistency in calculating the sound absorption coefficient of this metamaterial. The results reveals that sub‐wavelength metamaterial properties can be achieved below 6.4 MHz. Bubble coupling critical viscosity, waning coupling between layers, waveform transformation, and increasing scattering (reflection) waves all affect broadband sound absorption characteristics. The position and size of three bubbles are discussed, and design summary could be potentially in underwater ultrasound filter devices and medical ultrasound field.

In this study, a composite meta-absorber with a flexible size is proposed, and a genetic algorithm is used to optimize the geometric dimensions under normal incidence and free field conditions. With an overall thickness of 0.2 m, the quasi-perfect sound absorption is achieved in the 200 Hz - 20 kHz range. The sound pressure and sound intensity distributions inside the composite meta-absorber prove the incident sound wave is effectively localized inside the structure. Comparing the effective sound velocities in layers 1 and 10 with the sound velocity in air, it is possible to infer that the slow sound phenomenon is more pronounced at the bottom of THE composite meta-absorber, due to the different combinations of lateral plates and cavities. The coupling relationship between internal loss and radiation loss of the meta-absorber was revealed using the zero and pole method, proving the ultra-broadband and quasi-perfect sound absorption characteristics. Tests of the sound absorption coefficient in impedance tubes and reverberation chambers confirm the effective broadband sound absorption performance. The composite meta-absorber in this study can be directly used to reduce broadband noise. Moreover, it also provides ideas for the design of sound-absorbing metamaterials.

In order to determine the damping characteristics of the electromagnetic shock absorber under different working conditions,the theoretical modeling and test of the electromagnetic shock absorber with mechanical rectification device were carried out.Firstly,the dynamic transmission model and electromechanical coupling model of electromagnetic shock absorber were built theoretically,and its dynamics and electrics characteristics are analyzed.Secondly,a test bench of electromagnetic shock absorber is built from the engineering point of view,and the experimental study of its damping characteristics under different working conditions was carried out.Finally,the theoretical simulation results were compared with the test results.The results show that theoretical results and test results have the same variation trend.The equivalent damping coefficient of electromagnetic shock absorber will decrease from 1 208 N·s/m to 496 N·s/m when the load resistance increases from 5 Ω to 100 Ω.In addition,the results of decrease of equivalent damping coefficient from 874 N·s/m to 660 N·s/m when the increase of excitation frequency from 0.5 Hz to 2 Hz or the increase of excitation amplitude from 20 mm to 40 mm.