Search Results (805)

Background: Prolonged exposure to moderate and loud noise is known to impair hearing; however, the safety of long-duration exposure to low-level sound, such as that encountered during everyday conversation, remains unclear. This study aimed to determine the effect of continuous exposure to sound at a 65 dB sound pressure level (SPL) on auditory processing. Methods: Auditory brainstem responses (ABRs) were recorded in C57BL/6 mice before and after a 1 h exposure to a continuous pure tone at 65 dB SPL. Changes in ABR thresholds, wave amplitudes, and latencies were analyzed across frequencies and time points. Correlations between amplitude and latency changes across ABR waves were also assessed. Results: Tone exposure induced a significant, frequency-specific increase in ABR thresholds, with a mean elevation of approximately 6 dB and a maximum shift of 15 dB. Significant reductions in amplitudes and prolongations of latencies were observed in Waves I–III, while Wave V amplitude remained relatively stable. A strong negative correlation between amplitude reduction and latency increase was found in Wave I, which progressively weakened from Wave II to Wave V. These functional changes persisted for up to three hours following exposure before gradually returning to baseline. Conclusions: Prolonged exposure to low-level sound at intensities typical of conversational speech can transiently impair auditory function and alter early neural processing in the auditory pathway. These findings suggest that sound levels commonly considered safe may still pose a risk when exposure is sustained, with implications for understanding hidden hearing loss and improving early diagnostic approaches. Full article

Road traffic noise in urban streets is shaped not only by traffic sources but also by sound propagation through the surrounding street geometry. Existing prediction methods are still largely source-oriented, and receptor-specific models that rely on street morphology alone remain uncommon. We developed and compared interpretable machine-learning models to predict a cyclist-side sound pressure level (SPL) under fixed source conditions, using 12 spatial parameters extracted from 5060 street sections on 195 streets in Harbin, China. Acoustic simulations were performed in ODEON under fixed source-power conditions, and four models—Linear Regression, support vector regression (SVR), extreme gradient boosting (XGBoost), and Random Forest (RF)—were evaluated through an illustrative 80/20 split, 20 repeated random 80/20 splits, and 20 road-name-based grouped holdout repetitions. The nonlinear models consistently outperformed the linear baseline. Under grouped holdout validation, XGBoost achieved the highest predictive accuracy (R² = 0.953 ± 0.018, RMSE = 0.583 ± 0.119 dB, MAE = 0.418 ± 0.082 dB). RF reached comparable accuracy (R² = 0.938 ± 0.041, RMSE = 0.662 ± 0.210 dB, MAE = 0.453 ± 0.128 dB) and was retained for the interpretation of feature importance and marginal response patterns. A computation-time comparison based on 93 representative ODEON simulations showed that ODEON required a median of 2 min 33 s per street section, whereas the trained models predicted all 5060 sections in 0.013 s with XGBoost and 0.143 s with RF. The RF-based interpretation identified vehicle-lane width, sidewalk width, and near-zone cross-sectional enclosure degree as the most influential variables. Width-related parameters dominated cyclist-side SPL prediction, while enclosure-related parameters became more relevant mainly under narrower width conditions. The framework is therefore intended as a comparative morphology-screening tool under fixed source conditions, not as a predictor of real-world traffic noise under varying traffic states. Full article

With the development of autonomous driving and intelligent connected vehicle technologies, the vehicle cabin is shifting from a simple transportation space to an intelligent mobile space integrating infotainment, interaction, and rest, and passenger comfort has gradually become an important factor affecting user experience, system trust, and perceived safety. Focusing on three categories of cabin environmental factors, namely the acoustic, optical, and thermal environments, this study develops an experimental design and comprehensive modeling method for passenger comfort evaluation. First, controlled single-factor experiments were conducted to establish quantitative mapping relationships between physical environmental parameters and subjective comfort ratings. The analytic hierarchy process (AHP) was then used to determine the weights of each indicator, and a penalty-based aggregation mechanism was introduced to construct a comprehensive comfort evaluation model. Finally, external validation was performed on an independent vehicle platform to examine the model’s applicability and consistency. The results show that acoustic comfort decreases as the sound pressure level increases, whereas optical and thermal comfort exhibit nonlinear behavior with optimal intervals. AHP weight results show that the thermal environment has the highest weight (0.4280), followed by the acoustic environment (0.3305) and the optical environment (0.2415). The external validation results indicate that the proposed model exhibits good predictive consistency across three steady-state operating conditions, with a mean absolute error of 0.122, a root-mean-square error of 0.150, and a Pearson correlation coefficient of 0.960. The findings show that the penalty-based aggregation model can effectively characterize the limiting-factor effect under the joint action of multiple environmental factors, providing a computable and interpretable evaluation framework for intelligent cockpit environmental control and automotive engineering experimental teaching. The conclusions of this study are mainly applicable to the current experimental platform and steady-state operating conditions, and further validation is still required with more vehicle models, dynamic road scenarios, and complex multi-environment factor disturbances. Full article

Wind is a significant contributor to global energy requirement, with technological advancements in this industry enabling its rapid growth over the last few decades. The rise in demand for clean energy provides the driving factor to make wind more efficient and widespread. One such solution involves mitigating the aerodynamic noise of wind turbine rotors to harness untapped energy and improve turbine efficiency. Quieter wind turbines gain community acceptance, promoting their widespread application. This article explores passive compliant coatings applied to a flat plate under fully turbulent conditions through Computational Fluid Dynamics (CFD) and wind tunnel testing. It extends prior flat plate investigations by evaluating the noise mitigation potential of passive compliant coatings in the context of wind turbine trailing edge (TE) noise. Two coatings with distinct material properties were investigated through Computational Aeroacoustics Analysis (CAA) and Fluid–Structure Interaction (FSI). While coating-1 (Dow Corning Silastic S-2) increased the overall sound pressure level (OASPL) by 2.89 dB, coating-2 (Dow Corning Sylgard 184) reduced TE noise by 2–4 dB/Hz between 600 and 1575 Hz and lowered the OASPL by 1.85 dB. Within the two configurations investigated, the differences in noise mitigation characteristics may be attributed to variations in coating stiffness and geometric compliance. Based on these simulations, wind tunnel tests were conducted to record noise measurements using coating-2 which revealed a 3.23 dB OASPL reduction, suggesting its suitability for wind turbine noise mitigation applications. Full article

The nonlinear dynamic response of aerospace thin-walled structures in a post-buckling state under thermo-acoustic loads is critical for their design. This study investigates this phenomenon through integrated experimental and numerical approaches. Acoustic tests on thermally stressed flat plates yielded results in close agreement with finite element and reduced-order modal (FEM/ROM) simulations, with first-order frequency deviations within ±2 Hz and strain values of the same order of magnitude (10.7 µε vs. 9.5 µε at 50 °C). A key observation is the non-monotonic variation in the thermal modal frequency, which initially decreases then increases with the buckling coefficient, while dynamic strain data further validate the computational model. Comparative analysis of three Haynes 188 alloy geometries—flat plates, cylindrical shells, and spherical shells—reveals distinct behaviors rooted in their critical buckling temperatures (68.46 °C, 151.20 °C, and 698.28 °C, respectively): flat plates exhibit softening–hardening transitions with a frequency range of 491–624 Hz; cylindrical shells show irregular responses with a dramatic frequency drop from 1120 Hz to 360 Hz; and spherical shells maintain the highest stability and frequency range (1913–2109 Hz), governed by the buckling coefficient’s linear effect. Time-domain and probability density function (PDF) analyses elucidate the snap-through phenomena and the modulating roles of the buckling coefficient and sound pressure level (SPL). These findings underscore that geometric configuration and inherent stiffness are critical to post-buckling performance, providing a theoretical basis for designing aerospace components in extreme environments. Full article

In historic districts, the audiovisual environment plays an important role in shaping both cultural expression and spatial experience. However, the influence of acoustic and visual environmental factors on perceived street vitality remains insufficiently understood. Taking the Shangxiahang Historic District in Fuzhou as a case study, this paper employs on-site sound pressure level measurements, panoramic visual data collection, questionnaire surveys, principal component analysis, correlation analysis, and multiple regression analysis to systematically examine the effects of acoustic and visual environmental factors on perceived street vitality. The results indicate that traditional cultural sounds and natural sounds have a significant positive impact on perceived street vitality, while construction noise and tour guide’s horn sound exhibit negative effects. Regarding the visual environment, street and alley spaces, traditional architecture, greenery, and the sky are all important factors in promoting perceived street vitality. Further regression analysis reveals that the perception rate of street and alley spaces has the strongest influence, followed by the perception rate of traditional architecture, the perceived frequency of folk activity sounds, preference for greenery, and the perception rate of the sky. These findings demonstrate that perceived street vitality in historic districts does not depend on a single environmental factor but rather arises from synergistic interaction between culturally meaningful acoustic cues and legible spatial forms. These results offer practical implications for multisensory design and vitality-oriented regeneration in historic districts. Full article

This paper addresses the challenge of accurately measuring liquid level interfaces in multiphase mixed media by proposing a detection method based on ultrasonic transmission. First, a mathematical model of the ultrasonic measurement system was established, and the acoustic field characteristics of transducers with different frequencies and diameters in slurry were simulated and analyzed to determine the optimal excitation frequency and probe diameter. On this basis, an echo sound pressure calculation model based on the side-incidence method was constructed, and a formula for calculating the liquid level interface height was derived. Finally, an experimental test platform with a multi-layer steel container was built to measure the propagation velocity, attenuation coefficient, and acoustic impedance coefficient of ultrasound in the slurry, verifying the feasibility of the liquid level interface measurement method. Full article

This paper examines the subjective annoyance associated with shared-bike electronic alert sounds (SBeASs), an emerging urban noise source. A study was conducted by employing extensive questionnaire surveys and psychoacoustic experiments. A preliminary survey (N = 1340) indicated that 90.6% of participants reported being impacted by SBeASs, with pronounced effects on nighttime rest and daytime work efficiency. In this study, SBeAS samples were taken from three prominent Chinese bike-sharing brands: Hello Bike, Meituan Bike, and DiDi Bike. Under laboratory conditions, subjective annoyance assessments (N = 28) for SBeASs were conducted at controlled sound pressure levels (SPLs) ranging from 45 to 65 dBA, with occurrence frequencies of 1, 3, and 5 s. Simultaneously, annoyance assessments were also conducted for two reference noise types: traffic noise and street noise. The results indicated a notable increase in annoyance levels related to SBeASs with rising SPL and increased occurrence frequency. Minor variations in annoyance were identified among different bike-sharing brands, which can be attributed to their distinct acoustic features. When the SPL was above 55 dBA, the DiDi Bike SBeASs produced considerably higher annoyance than those of other brands. This can be attributed to its elevated low-frequency energy, loudness, and roughness. Moreover, individuals exhibiting increased sensitivity to noise reported notably higher annoyance ratings on the SBeAS scale (p = 0.019). Under low-SPL conditions (45–55 dBA), the annoyance attributed to frequent SBeASs can exceed that caused by traffic noise and street noise at comparable SPLs, highlighting the distinct disruptive impact of abrupt sound sources. Full article

Drone noise-induced human annoyance is emerging as one of the main barriers to socially acceptable large-scale urban air mobility (UAM) operations, which have the potential to revolutionize urban transportation systems in the next few decades. This paper investigates the state-of-the-art technology in the assessment of drone noise and its impact on individuals, focusing on measurement and evaluation methodologies, as well as subjective evaluations. Various acoustic metrics are reviewed to characterize drone noise, including sound pressure levels, spectral analysis, and psychoacoustic parameters such as loudness and annoyance. Preliminary experimental investigations to identify key frequencies and tonal components that significantly contribute to drone noise-induced public annoyance are also discussed. Interdisciplinary approaches integrating pure technical acoustics, human perception, and subjectivity emerge as promising solutions for a comprehensive understanding of drone noise effects. Finally, a preliminary framework for drone noise assessment towards noise-aware UAM operations is proposed. Full article

This study investigates how key milling parameters influence both cutting noise and surface quality during the machining of laminated bamboo lumber. Using a multifactorial optimal response surface methodology, the effects of fibre orientation (0–135°), spindle speed (7000–10,000 r/min), feed rate (0.5–2.0 m/min) and milling depth (0.5–2.0 mm) were quantified through 25 experimental runs. Cutting noise, measured as peak sound pressure level (SPL), ranged from 86.8 to 95.2 dB, increasing markedly with fibre angle, feed rate, and milling depth, but exhibiting a non-linear response to spindle speed. Surface roughness (S_a) varied from 2.6 to 11.7 µm and was most strongly governed by milling depth, followed by fibre orientation and feed rate, with a significant interaction between fibre orientation and spindle speed. Quadratic regression models demonstrated strong predictive performance (R² = 0.97 for SPL; R² = 0.85 for S_a). Based on the response surfaces, optimal low-noise, high-quality machining was achieved at moderate spindle speeds, low feed rates, and shallow milling depths. These findings provide a mechanistic basis for understanding noise–roughness coupling in bamboo machining and offer practical guidance for computer numerical control processing, tool selection, and industrial noise reduction strategies in bamboo manufacturing. Full article

Existing studies of street-related emotional perception mainly rely on static scene evaluations, which cannot capture the cumulative effects of environmental exposure during continuous walking. To address this limitation, this study proposes a method for predicting pedestrian physiological responses in sequential audiovisual street environments. Four real-world walking routes were selected, with outbound and return directions treated as independent paths, yielding eight paths and 32 valid samples. EEG, ECG, sound pressure level, first-person video, and GPS data were synchronously collected to construct a 1 s multimodal time-series dataset. Pearson correlation, Kendall correlation, and mutual information analyses were used to examine linear, monotonic, and nonlinear relationships between environmental variables and physiological indicators, and the resulting weights were incorporated into a Long Short-Term Memory (LSTM) model for multi-step prediction. Visual elements and noise exposure were the main factors influencing physiological responses. Among the models, the mutual-information-weighted LSTM performed best, achieving an R² of 0.77 for heart rate variability (RMSSD), whereas prediction of the EEG ratio (β/α and θ/β) remained limited. An additional independent street sample outside the training set was then used to generate a dual-dimensional EEG-ECG physiological response map, demonstrating the model’s potential for identifying emotional risk segments and supporting street-level micro-renewal. Full article

With the growing demand for hybrid and electric vehicles, the accurate prediction of NVH (Noise, Vibration, and Harshness) behavior in Permanent Magnet Synchronous Machines (PMSMs) has become a critical aspect of electric motor design. This paper presents a detailed modeling approach for electromagnetic-induced noise and vibrations in PMSMs, integrating both analytical and numerical methods. The model focuses on quantifying the contributions of radial and tangential electromagnetic forces, which are key drivers of vibro-acoustic responses. The analytical part employs curved beam theory and a simplified acoustic model, offering rapid insights during early design stages. In parallel, a detailed numerical model based on finite element analysis is developed using a physics-based approach that accounts for the actual geometry and material properties of the PMSM prototype. This allows for enhanced accuracy without relying on experimental material parameter identification. Moreover, the detailed model includes the fluid–structure interaction introduced by the channels of the cooling fluid of the electric machine, which, although poorly addressed by the existing literature, was found to play a key role in driving the vibrational behaviour of the structure. By combining analytical speed with numerical precision, the proposed approach enables consistent and physically-based NVH predictions across various design phases, ultimately supporting improved electric machine performance and reducing development time and costs. Validation against experimental data confirms the ability of the model to accurately predict both sound pressure levels and housing surface vibrations. The novelty of this work lies in its integration of fluid–structure interaction and material modeling without the need for empirical parameter tuning, offering a robust tool for NVH design in electric vehicle applications. Full article

This study investigates the aerodynamic, aeroacoustic, and psychoacoustic behaviour of a side-by-side twin-propeller Unmanned Aerial Vehicle (UAV) system operating under both static and forward-flight conditions, with particular focus on the effects of asynchronous rotational speeds. Experiments were conducted using two identical five-bladed constant pitch propellers with a diameter of 9 in (228.6 mm) and a pitch to diameter ratio of 1. Rotational speed differences between 0 and 300 rpm were examined in 50 rpm increments at inflow velocities of 0 m/s, 14 m/s and 24 m/s. The results show that variations in rotational speed have a significant influence on both acoustic levels and perceived annoyance. Asynchronous operation causes the dominant tonal peak at the blade passing frequency to split into two components, reducing tonal reinforcement. This produces noise level reductions of approximately 2 dB in static and high advance ratio conditions, increasing to about 5 dB reduction at low advance ratios. Psychoacoustic metrics show greater sensitivity to tonal structure than to overall sound pressure level, with annoyance reductions of about 5% in static conditions and up to 15% at low advance ratios. A modest aerodynamic penalty of about 5% at $\Delta N=50$ rpm is observed, increasing with larger speed mismatches. Full article

The present study investigates the influence of geometric parameters on the vibro-acoustic performance of piezoelectric speakers, with the objective of establishing quantitative design guidelines for resonance tuning and sound pressure level (SPL) enhancement. Understanding the dimension-dependent behavior of such devices is essential for the development of compact and efficient acoustic transducers. To this end, a fully coupled electromechanical–acoustic finite element model is developed in the frequency domain, incorporating linear piezoelectric constitutive relations, structural dynamics, and an external acoustic air domain. The model systematically examines the effects of variations in piezoelectric disc thickness, brass diaphragm thickness, and diaphragm radius. The results demonstrate that increasing the piezoelectric disc thickness leads to a noticeable increase in resonance frequency and a measurable enhancement in SPL due to strengthened electromechanical coupling. In contrast, reducing the brass membrane thickness primarily shifts the resonance frequency to lower values, while producing negligible changes in SPL amplitude. Furthermore, enlarging the diaphragm radius significantly decreases the fundamental resonance frequency, confirming its dominant influence on stiffness-controlled vibration behavior. These findings quantitatively establish the relationship between geometric design parameters and acoustic response, providing a predictive framework for performance optimization. The proposed modeling approach offers an effective and reliable tool for the design and refinement of high-performance piezoelectric speaker systems. Full article

Detectability of auditory signals in built environments is a critical issue in architectural acoustics, particularly in public spaces where notification sounds must be perceived reliably under background noise. This study investigated reaction times (RTs) to amplitude-modulated pure tones under silent, white noise, and bandpass-noise conditions. Twenty young and twenty elderly participants responded to 1 and 2 kHz tones with flat, gentle, and steep onset envelopes. To describe perceptual detection in physically interpretable terms, a time-integrated sound-exposure level model, $L_{AE}\left(t\right)$, was applied. RT was defined as the moment when cumulative acoustic energy exceeded a criterion value relative to the hearing threshold. In silent conditions, RTs were accurately predicted by $L_{AE}\left(t\right)$, with onset-envelope shape influencing early energy accumulation. In noise conditions, RTs increased systematically with spectral proximity between target and masker, consistent with auditory filter theory. When spectral separation exceeded approximately four ERB numbers, masking effects were minimal, and RT approached silent-condition values. These findings demonstrate that perceptual detection timing is governed by cumulative acoustic energy and spectral masking rather than instantaneous sound pressure level. The $L_{AE}\left(t\right)$ model provides a detection-oriented metric that complements conventional room-acoustic parameters and may support evidence-based design of perceptually robust auditory signals in architectural environments. Full article