Search Results (466)

This study investigates the influence of heavy-layer thickness on shock-accelerated interfacial instabilities in single-mode stratifications using high-order discontinuous Galerkin simulations at a fixed shock Mach number ($M_s=1.22$). By systematically varying the layer thickness, we quantify how acoustic transit time, shock attenuation, and phase synchronization modulate vorticity deposition, circulation growth, and interface deformation. The results show that thin layers ($d=2.5$–5 mm) generate strong and early baroclinic vorticity due to frequent reverberations, leading to rapid circulation growth, vigorous Kelvin–Helmholtz roll-up, and early jet pairing. In contrast, thick layers ($d=20$–40 mm) attenuate and dephase shock returns, producing weaker baroclinic reinforcement, delayed shear-layer growth, and smoother interfaces with reduced small-scale activity, while the intermediate case ($d=10$ mm) exhibits transitional behavior. Integral diagnostics reveal that thin layers amplify dilatational, baroclinic, and viscous vorticity production; sustain stronger circulation and enstrophy growth; and transfer bulk kinetic energy more efficiently into interface deformation and small-scale mixing. Full article

The design and validation of a reverberation chamber (RC) specifically constructed for conducting large-scale experimental animal carcinogenicity studies using RF electromagnetic fields (EMF) relevant to contemporary 4G and 5G mobile communication (900 MHz, 2.12 GHz, and 3.65 GHz) is proposed. The RC’s electric field (E-field) uniformity is evaluated under four practical loading conditions: empty, apparatus only, and two apparatus variations with 80 experimental animals (Sprague–Dawley rats) with approximate weights 400 g and 520 g, respectively. Measurement results show E-field uniformity better than 1.36 dB under all test conditions, with frequency-dependent variation becoming negligible once the RC is loaded with cage racks and 80 rats. Additionally, a predictive method is introduced to estimate composite E-field intensities under simultaneous multi-frequency exposures, potentially reducing experimental measurements. These findings confirm that the designed RC is capable of accurately evaluating RF EMF exposure in biological studies. Full article

Simulated room impulse responses (RIRs) are important tools for studying architectural acoustics. Many methods exist to generate RIRs, each with unique properties that need to be considered when choosing an RIR synthesis technique. Despite the variation in synthesis techniques, there is a dearth of comparisons between these techniques. To address this, a comprehensive comparison of four major categories of RIR synthesis techniques was conducted: wave-based methods (hybrid FEM and modal analysis), geometrical acoustics methods (the image source method and ray tracing), delay-network reverberators (SDNs), and statistical methods (Sabine-NED). To compare these techniques, RIRs were recorded in a simple shoebox-shaped racquetball court, and we compared the synthesized RIRs against these recordings. We conducted both objective analyses, such as energy decay curves, normalized echo density, and frequency-dependent decay times, and a perceptual assessment of synthesized RIRs, which consisted of a listening assessment with 29 participants that utilized a MUSHRA comparison methodology. Our results reveal distinct advantages and limitations across synthesis categories. For example, the Sabine-NED technique was indistinguishable from the recorded IR, but it does not scale well with increasing geometric complexity. These findings provide valuable insights for selecting appropriate synthesis techniques for applications in architectural acoustics, immersive audio rendering, and virtual reality environments. Full article

This paper presents a bilinear framework for real-time speech source separation and dereverberation tailored to wearable augmented reality devices operating in dynamic acoustic environments. Using the Speech Enhancement for Augmented Reality (SPEAR) Challenge dataset, we perform extensive validation with real-world recordings and review key algorithmic parameters, including the forgetting factor and regularization. To enhance robustness against direction-of-arrival (DOA) estimation errors caused by head movements and localization uncertainty, we propose a region-of-interest (ROI) beamformer that replaces conventional point-source steering. Additionally, we introduce a multi-constraint beamforming design capable of simultaneously preserving multiple sources or suppressing known undesired sources. Experimental results demonstrate that ROI-based steering significantly improves robustness to localization errors while maintaining effective noise and reverberation suppression. However, this comes at the cost of increased high-frequency leakage from both desired and undesired sources. The multi-constraint formulation further enhances source separation with a modest trade-off in noise reduction. The proposed integration of ROI and LCMP within the low-complexity frameworks, validated comprehensively on the SPEAR dataset, offers a practical and efficient solution for real-time audio enhancement in wearable augmented reality systems. Full article

This paper proposes a robust blind algorithm for direction of arrival (DOA) estimation in challenging acoustic environments. The method introduces a novel Time Difference of Arrival (TDOA) consensus framework that effectively identifies and filters outliers using Median and Median Absolute Deviation (MAD) statistics. By combining this consensus approach with whitening transformation and Lawson norm optimization, the algorithm achieves superior performance in noisy and reverberant conditions. Comprehensive simulations demonstrate that the proposed method significantly outperforms traditional approaches and modern alternatives such as SRP-PHAT and robust MUSIC, particularly in environments with high reverberation times and low signal-to-noise ratios. The algorithm’s robustness to impulsive noise and varying microphone array configurations is also evaluated. Results show consistent improvements in DOA estimation accuracy across diverse acoustic scenarios, with root mean square error (RMSE) reductions of up to 30% compared to standard methods. The computational complexity analysis confirms the algorithm’s feasibility for real-time applications with appropriate implementation optimizations, showing significant improvements in estimation accuracy compared to conventional approaches, particularly in highly reverberant conditions and under impulsive noise. The proposed algorithm maintains consistent performance without requiring prior knowledge of the acoustic environment, making it suitable for real-world applications. Full article

People’s perceptions of architectural spaces are shaped by multiple senses, including vision and hearing. While vision has received extensive attention, hearing is often overlooked in architectural design, with a primary focus on sound insulation and noise reduction rather than on using acoustics to enhance spatial experience. Therefore, this study aims to investigate the impact of acoustic environments on two key spatial perceptions: Spaciousness and transparency. Two laboratory experiments were conducted with 60 participants. Thirty subjects evaluated 96 audiovisual stimuli for perceived spaciousness, and another 30 subjects assessed 128 audiovisual stimuli for perceived transparency. The results indicate that sound type significantly affects perceived spaciousness, while sound type and sound pressure level (SPL) significantly influence perceived transparency. Reverberation time (RT, T60) had no effect on either spatial perception. Interaction analysis further revealed that sound type affects transparency across different space sizes and window proportions, while SPL only influences small spaces and standard window proportions, with transparency decreasing as SPL increases. Mediation analysis showed that the effects of sound type on both spaciousness and transparency are partially mediated by subjective spatial perceptions, such as building environment preference and alignment with the outdoor environment. These findings emphasize the importance of integrating acoustic considerations into architectural design, which can enhance spatial experiences and provide valuable insights for future design practices. Full article

In this work, we show the probability density functions (PDFs) and cumulative density functions (CDFs) of the nonnormalized field components and the associated powers received inside coupled reverberation chambers (CRCs), considering two canonical cases of single electrically small coupling apertures (ESCAs). These two cases involve one-dimensional (1D) and two-dimensional (2D) single electrically small CAs, respectively. We achieve normalized statistics from the nonnormalized ones for both field components and associated powers. We show that the comparison of the mean square values (MSVs) of the nonnormalized PDFs of the field components to the mean values (MVs) of the related nonnormalized PDFs of the powers is a proper method to corroborate the accuracy of the same achieved theoretical distributions, when they are achieved in an independent way. The achieved theoretical results are also validated by measurements. Moreover, for the sake of completeness and rigor of published results, we show two useful cases of the results from the measurements using two electrically large CAs. Full article

The acoustic field of an opera house is much more difficult to predict than those of concert halls because, in the fly tower, the absorption characteristics vary from time to time, according to the opera piece layout. For this reason, the paper aims to find a simplified fly tower model to be used as a fixed reference in a preliminary acoustic prediction for opera houses. Firstly, referring to a case study, the effects of the fly tower Depth and absorptive characteristics are investigated to identify the simplified model. As a traditional opera is set on an empty stage, and modern pieces are supported by a virtual projected environment, the influence of the variable stage elements on Reverberation Time RT, Clarity C80, and Strength G is considered, comparing the traditional Semiramide opera to a modern digital one, according to the Just Noticeable Difference JND. Results confirm the utility of the suggested fly tower model, which does not require any set definition. Full article

The acoustic environment of dental clinics plays a critical role in shaping patient experience, staff performance, and overall clinical effectiveness. This comprehensive review, supported by systematic search procedures, investigates how soundscapes in dental settings influence psychological, physiological, and operational outcomes. A total of 60 peer-reviewed studies were analyzed across dental, healthcare, architectural, and environmental psychology disciplines. Findings indicate that mechanical noise from dental instruments, ambient reverberation, and inadequate acoustic zoning contribute significantly to patient anxiety and professional fatigue. The review identifies emerging strategies for acoustic optimization, including biophilic and sustainable design principles, sound-masking systems, and adaptive sound environments informed by artificial intelligence. Special attention is given to the integration of lean management and circular economy practices for sustainable dental architecture. A design checklist and practical framework are proposed for use by dental professionals, architects, and healthcare planners. Although limited by the predominance of observational studies and geographic bias in the existing literature, this review offers a comprehensive, interdisciplinary synthesis. It highlights the need for future clinical trials, real-time acoustic assessments, and participatory co-design methods to enhance acoustic quality in dental settings. Overall, the study positions sound design as a foundational element in creating patient-centered, ecologically responsible dental environments. Full article

Light alloy wheel rims, despite their widespread use, remain vulnerable to fatigue-related defects and mechanical damage. This study presents a method for assessing their technical condition based on acoustic parameter analysis and classification using a deep neural network. Diagnostic data were collected using a custom-developed ADF (Acoustic Diagnostic Features) system, incorporating the reverberation time (T₆₀), sound absorption coefficient (α), and acoustic energy (E). These parameters were measured during laboratory fatigue testing on a Wheel Resistance Test Rig (WRTR) and from used rims obtained under real-world operating conditions. The neural network was trained on WRTR data and subsequently employed to classify field samples as either “serviceable” or “unserviceable”. Results confirmed the high effectiveness of the proposed method, including its robustness in detecting borderline cases, as demonstrated in a case study involving a mechanically damaged rim. The developed approach offers potential support for diagnostic decision-making in workshop settings and may, in the future, serve as a foundation for sensor-based real-time rim condition monitoring. Full article

The architecture of contemporary museums often emphasizes visual aesthetics, such as large volumes, open-plan layouts, and highly reflective finishes, resulting in acoustic challenges, such as excessive reverberation, poor speech intelligibility, elevated background noise, and reduced privacy. This study quantified the impact of surface—specific absorption treatments on acoustic metrics across eight gallery spaces. Room impulse responses calibrated virtual models, which simulated nine absorption scenarios (low, medium, and high on ceilings, floors, and walls) and evaluated reverberation time (T₂₀), speech transmission index (STI), clarity (C₅₀), distraction distance (r_D), Spatial Decay Rate of Speech (D_2,S), and Speech Level at 4 m (L_p,A,S,4m). The results indicate that going from concrete to a wooden floor yields the most rapid T₂₀ reductions (up to −1.75 s), ceiling treatments deliver the greatest STI and C₅₀ gains (e.g., STI increases of +0.16), and high-absorption walls maximize privacy metrics (D_2,S and L_p,A,S,4m). A linear regression model further predicted the STI from T₂₀, total absorption (Sabins), and room volume, with an 84.9% conditional R², enabling ±0.03 accuracy without specialized testing. These findings provide empirically derived, surface-specific “first-move” guidelines for architects and acousticians, underscoring the necessity of integrating acoustics early in museum design to balance auditory and visual objectives and enhance the visitor experience. Full article

Sound event localization and detection (SELD) is a fundamental task in spatial audio processing that involves identifying both the type and location of sound events in acoustic scenes. Current SELD models often struggle with low signal-to-noise ratios (SNRs) and high reverberation. This article addresses SELD by reformulating direction of arrival (DOA) estimation as a multi-class classification task, leveraging deep convolutional recurrent neural networks (CRNNs). We propose and evaluate two modified architectures: M-DOAnet, an optimized version of DOAnet for localization and tracking, and M-SELDnet, a modified version of SELDnet, which has been designed for joint SELD. Both modified models were rigorously evaluated on the STARSS23 dataset, which comprises 13-class, real-world indoor scenes totaling over 7 h of audio, using spectrograms and acoustic intensity maps from first-order Ambisonics (FOA) signals. M-DOAnet achieved exceptional localization (6.00° DOA error, 72.8% F1-score) and perfect tracking (100% MOTA with zero identity switches). It also demonstrated high computational efficiency, training in 4.5 h (164 s/epoch). In contrast, M-SELDnet delivered strong overall SELD performance (0.32 rad DOA error, 0.75 F1-score, 0.38 error rate, 0.20 SELD score), but with significantly higher resource demands, training in 45 h (1620 s/epoch). Our findings underscore a clear trade-off between model specialization and multifunctionality, providing practical insights for designing SELD systems in real-time and computationally constrained environments. Full article

Studies underscore the significance of coir fibers as a sustainable building material. Based on these insights, this research aims to evaluate coir fiber composite panels of various thicknesses as eco-friendly sound absorbing alternatives to synthetic construction materials like rockwool and fiberglass, aligning its use with the United Nations Sustainable Development Goals. Acoustic absorption was quantified with an impedance tube, and subsequent simulations compared the performance of coir composite panels with that of conventional materials, which constitutes an underexplored evaluation. Using 10 receiver points, the simulations reproduced the acoustic conditions of a multipurpose auditorium before and after the coir covering of parts of the rear and posterior walls. The results indicate that when coir coverings account for approximately 10% of the auditorium surface, reverberation times at 250, 500, 2000, and 4000 Hz are reduced by roughly 1 s. Furthermore, the outcomes reveal that early reflections occur more rapidly in the coir-enhanced model, while the values of the early decay time parameter decrease across all receiver points. Although the original configuration had poor speech clarity, the modified model achieved optimal values at all the measurement locations. These findings underscore the potential of coir fiber panels in enhancing acoustic performance while fostering sustainable construction practices. Full article

Churches are spaces designed with a unique acoustic identity, which is intimately connected to the oratory and musical needs of the historical period in which they were built. For instance, their typically long reverberation time is appropriate to specific uses, such as liturgical functions and choral music performances, but it may impair the repurposing of the space for other functions. Indeed, an acoustic environment suitable for choral or sacred music may not be compatible with other musical genres such as chamber music, solo performances, or small instrumental ensembles, which require greater clarity and frequency-balanced acoustic properties. In such cases, careful analysis of the environment and specific acoustic conditioning become essential steps to enable the space to be used for novel purposes, without compromising its artistic and historical integrity. In this work, we analyze and improve the acoustics of the church of Saints Marcellino and Pietro through space-time acoustic measurements and simulations. After developing and validating our model, we propose various solutions to optimize the church acoustics, transforming it into a functional concert hall while preserving its original identity and artistic grandeur. Full article

As a fundamental technology in environmental perception, sound source localization (SSL) plays a critical role in public safety, marine exploration, and smart home systems. However, traditional methods such as beamforming and time-delay estimation rely on manually designed physical models and idealized assumptions, which struggle to meet practical demands in dynamic and complex scenarios. Recent advancements in deep learning have revolutionized SSL by leveraging its end-to-end feature adaptability, cross-scenario generalization capabilities, and data-driven modeling, significantly enhancing localization robustness and accuracy in challenging environments. This review systematically examines the progress of deep learning-based SSL across three critical domains: marine environments, indoor reverberant spaces, and unmanned aerial vehicle (UAV) monitoring. In marine scenarios, complex-valued convolutional networks combined with adversarial transfer learning mitigate environmental mismatch and multipath interference through phase information fusion and domain adaptation strategies. For indoor high-reverberation conditions, attention mechanisms and multimodal fusion architectures achieve precise localization under low signal-to-noise ratios by adaptively weighting critical acoustic features. In UAV surveillance, lightweight models integrated with spatiotemporal Transformers address dynamic modeling of non-stationary noise spectra and edge computing efficiency constraints. Despite these advancements, current approaches face three core challenges: the insufficient integration of physical principles, prohibitive data annotation costs, and the trade-off between real-time performance and accuracy. Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. These directions aim to propel SSL toward intelligent systems characterized by high precision, strong robustness, and low power consumption. This work provides both theoretical foundations and technical references for algorithm selection and practical implementation in complex real-world scenarios. Full article