Sandwich panels typically exhibit inadequate low-frequency sound insulation owing to their inherently high ratio of stiffness to mass. While fully filling the core layer with magnetorheological fluids (MRFs) enhances acoustic tunability, it severely compromises practical applicability. Consequently, partially filling the panels offers a viable compromise; however, the complex fluid–structure interaction introduced by discrete fluid columns remains largely unexplored. This study investigates the sound transmission loss (STL) mechanisms of sandwich panels partially filled with MRFs to achieve targeted acoustic controllability. A theoretical acoustic model and a structural–acoustic coupled finite element model are established to evaluate the vibroacoustic behavior. Simulations derived from the theoretical model were initially conducted for fully MRF-filled configurations to elucidate the fundamental field-dependent acoustic tunability. Experimental investigations are performed on panels with different MRF column arrangements under varying magnetic fields. The results demonstrate that the STL is governed by field-dependent stiffness and damping mechanisms. As the magnetic field increased, STL peaks elevated due to enhanced shear storage and loss moduli. The spatial arrangement and number of MRF columns dictate the specific frequency bands sensitive to magnetic tuning, offering an independent structural dimension to regulate the acoustic response. Overall, partially filled MRF panels provide a highly practical solution for adaptive sound insulation. This targeted controllability is realized through the selective regulation of STL amplitudes and localized modes within specific frequency bands by adjusting the magnetic field intensity and structural configuration.
Model order reduction (MOR) can significantly reduce the computational cost of vibroacoustic simulations. While most MOR studies focus on single-domain problems, such as structural dynamics or acoustics, this work compares MOR techniques for large coupled heavy-fluid-loaded vibroacoustic systems and evaluates their efficiency, accuracy, and scalability. Harmonic response simulations of vibroacoustic fluid–structure coupled systems used to compute frequency response functions from an input force to either structural acceleration or pressure in the heavy fluid domain are of particular interest. To assess the feasibility and accuracy of these techniques for different system sizes, a scalable model of a water-filled Plexiglass (PMMA) cylinder is developed, with mesh sizes from 10,000 to 1,000,000 Degrees of Freedom (DOF). The quality of the models is assessed through validation against experimental data and convergence studies within the frequency range of interest. The geometry, model data, and experimental results are made available so that they can be used as a benchmark for further studies. For medium-sized models up to approximately 100,000 DOFs, both modal and Krylov-subspace-based reduction methods are feasible. Modal approaches are advantageous because they are independent of a specific excitation and, therefore, provide a more general approximation of the physical system. However, for larger systems, the investigated modal methods become impractical due to memory limitations. In contrast, a Krylov-subspace two-level orthogonal Arnoldi method (TOAR), combined with matrix symmetrization and conditioning, provides an accurate and efficient approximation for a prescribed excitation scenario. For 1000 frequency steps, this approach achieves speedups of up to 600 × compared with the full-order model.
The growing demand for noise control in transportation, urban environments, and advanced equipment systems is driving sound-absorbing materials toward broader bandwidths, lower weight, and more compact configurations. Conventional porous materials dissipate acoustic energy mainly through thermoviscous friction near pore walls. Under low-frequency and thin-layer conditions, however, their performance is often constrained by the need to reduce incident reflection while maintaining sufficient energy loss within a limited thickness. Existing reviews on porous sound-absorbing materials have mostly been organized around material categories, structural parameters, theoretical models, or fabrication routes, while the common physical basis by which different gradient architectures achieve broadband absorption has rarely been discussed from a unified sound-energy management perspective. Here, we use spatial acoustic-function partitioning as an interpretive framework linking depth-dependent structural variation to the frequency-dependent input impedance, internal acoustic field, and irreversible energy loss. These acoustic functions are not tied to fixed geometric layers and may shift with frequency, boundary conditions, and the gradient profile. The discussion draws on established acoustic models to connect depth-dependent structural variation with impedance, field redistribution, and irreversible loss. Three representative routes are considered: parameter gradients in dual-gradient microperforated networks, multiscale interfacial gradients in gradient fiber/aerogel–porous scaffold composites, and continuous topological gradients in triply periodic minimal surface (TPMS) structures. The roles of additive manufacturing and intelligent design in realizing and optimizing these structures are also discussed. Representative quantitative studies show that no single-gradient profile is universally optimal: Monotonic, reversed, and non-monotonic profiles can each be favorable depending on the complete absorber configuration and target frequency range. Manufacturing fidelity and physics-constrained inverse design are discussed in terms of whether numerically optimized structures can be fabricated reliably and tested experimentally.
Listening to landscapes is becoming a key approach in global efforts to understand and protect biodiversity. Highly biodiverse regions, such as mediterranean climate-type forest ecosystems, will become increasingly affected by severe, frequent, long-lasting, and complex disturbance events, requiring robust contemporary baselines to inform management. Passive acoustic monitoring was conducted across twelve Northern Jarrah (Eucalyptus marginata) Forest plots within southwestern Australia, over several days in the 2023 austral summer, stratified to equally represent open and dense forest habitats. Broadband and taxon-specific acoustic indices were used to characterise soundscape structure, with principal component analysis applied to examine multivariate soundscape patterns. Soundscapes were comprised of a complex mixture of biological, geological, and anthropogenic contributions, dominated by avian, chiropteran, and insect vocalisations. While overall composition showed limited association with vegetation characteristics, avian and low-frequency insect acoustic activity was greater in denser forest areas, whereas high-frequency insect acoustic activity was higher in open habitats. Principal component analysis revealed clear structuring associated with overall biotic intensity and frequency-specific contributions, highlighting the importance of considering multiple taxon-specific frequency bands when interpreting forest soundscapes. This study provides the first characterisation of the summer acoustic structure of the Northern Jarrah Forest and an initial reference point for future acoustic monitoring. While findings should be interpreted within the temporal and spatial scope of the study, the results highlight the potential of ecoacoustic approaches to characterise forest soundscape structure and demonstrate the value of passive acoustic monitoring as a complementary tool to support ecological monitoring and biodiversity management.
This work investigates the propagation of elastic waves in soil induced by a leaking buried pipe, emphasizing the influence of uncertainty on ground-surface responses. The analysis is grounded in the underlying wave physics and employs a stochastic modelling framework to capture variability in soil properties and system parameters. While previous studies have primarily focused on pipe vibrations, the present work extends the analysis to ground-surface responses, which are directly relevant to non-invasive monitoring techniques. A probabilistic model is developed to characterize the resulting ground vibrations, enabling a systematic quantification of uncertainty inherent in leak-related signals. The proposed approach employs a polynomial chaos expansion surrogate model and is validated against Monte Carlo simulations, demonstrating excellent agreement and computational efficiency. The analysis reveals the distinct contributions of shear and compressional waves and shows that their interference can cause abrupt phase changes coinciding with local minima in displacement magnitude, an effect absent when only shear waves are radiated. Additional simulations show how burial depth influences these features, confirming the robustness of the proposed framework across typical installation conditions. The proposed stochastic framework represents an important step towards enhancing the reliability and interpretability of ground-based techniques for buried pipe localization.
