In recent years, the automotive industry has increasingly adopted large displays to replace physical buttons, drawing attention to touch and haptic technologies. While low-frequency haptic technologies, particularly those based on the bending wave principle, are widely used, they have been criticized for generating noise. This noise arises because vibrations from the display radiate sound, causing discomfort. In this study, we explored a method to implement haptic feedback through vibration motors upon touch, maximizing vibration at the touch point while minimizing overall noise. To achieve this, we defined anew index called the Haptic Noise Index (HNI) to select optimal frequencies, identifying the frequency with the lowest HNI. The HNI is defined as the ratio of vibration at the touch point to the Equivalent Radiated Power (ERP). Additionally, we adjusted the phase of the vibration motors, treated each motor's vibration contribution as a design variable, and used HNI as the objective function for optimization. By applying this approach, we successfully reduced noise at specific touch locations. The optimization was performed using an Sequential Quadratic Programming (SQP) algorithm. As a result, we achieved noise reduction of over 10 dB to without the of this method.
Towed linear array sensors offer excellent long-range, low-frequency underwater detection performance but generate hydrodynamic drag during towing, which reduces platform maneuverability. For small platforms such as unmanned underwater or surface vehicles, minimizing drag requires ultra-slim array structures. Achieving such miniaturization demands high-density circuit design, compact component integration, and reduced signal interference and cabling, all of which introduce significant engineering challenges. In this study, we developed ultra-miniature signal transmission nodes that can be placed within a diameter of 30 mm, applying a build-up Printed Circuit Board (PCB) process for circuit integration and adopting a multi-hop network architecture to reduce internal wiring. These techniques enabled efficient spatial utilization within the constrained diameter of the array module, and the ultra-miniature signal transmission nodes were evaluated through electrical performance tests to verify performance optimization and confirm its practical applicability.
This study aims to provide data for establishing acoustic standards in Korean school classrooms by analyzing the results of an acoustic survey conducted in 49 classrooms and lecture rooms across elementary, junior high, high schools, and universities, totaling 106 active classes. The findings indicate that in spaces where speech intelligibility is critical, acoustic design should not be limited to unoccupied room conditions but must incorporate occupied conditions reflecting students and teaching activities to ensure adequate speech intelligibility. Based on the acoustic measurement results of classrooms and lecture rooms, the recommended reverberation time for spaces with a volume of 250 m(3) or less is 0.60 s at 125 Hz-4 kHz, with a range of 0.48 s to 0.72 s depending on the number of people in the room. To enable teachers to maintain an appropriate Speech to Noise Ratio (SNR) value without unnecessarily raising their voice levels during class, the maximum noise level in an unoccupied room is L-Aeq <= 40 dBA (the air conditioner is running). To minimize noise from adjacent classrooms during class activities, the wall's sound insulation performance should be STC >= 50 for adjacent classrooms and STC >= 45 for adjacent corridors. In areas where speech privacy is important, such as in a combined wall with a corridor, the STC should be >= 50. To achieve a speech intelligibility of Speech Transmission Index (STI) >= 0.60 and U-50 >= 4.1 dB, the recommended SNR value of >= 15 dBA, and a C-50 of >= 4 dB should be met. In this study, only 5 % of the 106 classrooms were from special schools. Therefore, when establishing acoustic standards for educational facilities,it is necessary to consider not only general schools, but also special schools that require acoustic support.
This study numerically investigates the frequency-dependent propagation behavior of operational underwater noise from offshore wind turbines using a coupled vibro-acoustic framework. Structural excitation induced by aerodynamic loads was defined, and the dynamic responses obtained from finite element analysis were linked to an acoustic model representing the surrounding marine environment. Transmission Loss (TL) was evaluated over the frequency range of 10 Hz-200 Hz, and variations in propagation characteristics associated with substructure configurations and frequency bands were examined. In addition, spatial sound field distributions were analyzed to explore factors influencing the observed propagation trends. The results highlight the importance of incorporating both structural and frequency-dependent features in predicting underwater noise from operating wind turbines and provide useful information for future large-scale wind farm assessments.
As vehicle electrification enhances the demand for quietness, the Noise, Vibration, and Harshness (NVH) performance of Pressure Relief Valves (PRV) in air suspension systems has become critical. This study develops an integrated flow-vibroacoustic analysis framework to predict Fluid-Borne Vibration (FBV) and radiated noise induced by unsteady compressible flow inside a PRV. Wall-pressure fluctuations are computed using 3D unsteady compressible Large Eddy Simulation (LES) and mapped onto a structural model for frequency-response and structural-acoustic coupled analysis. Short-Time Fourier Transform (STFT) is employed to characterize the time-varying spectral features of the discharge process. The predicted acceleration and sound pressure spectra show good agreement with experimental data, specifically capturing the broadband and quasi-tonal components during the initial transient phase. The proposed framework provides an effective tool for predicting and optimizing the NVH performance of electronic air suspension systems at the early design stage.
This study proposes a numerical optimization framework to improve the oxygen delivery and flow performance for a ventilation system integrated into a vehicle seat. Computational Fluid Dynamics (CFD) simulations based on the multi-species incompressible Reynolds-Averaged Navier-Stokes (RANS) equations were performed, and the volume-averaged oxygen mole fraction in the breathing zone was used as the performance metric. The vertical and horizontal discharge angles were selected as design variables, and the optimal angles maximizing the breathing-zone oxygen mole fraction were determined using the Response Surface Method (RSM). In addition, adjoint-based sensitivity analysis was applied to optimize the flow path geometry for pressure-loss reduction. Numerical results show that the breathing-zone oxygen concentration increases by approximately 0.126 % compared with the baseline configuration when the optimal discharge angles are applied. Furthermore, the pressure loss is reduced by approximately 44.24 % through flow path shape optimization. Based on the fan affinity law, this pressure-loss reduction corresponds to an estimated fan noise reduction of approximately 6.33 dB under the same flow-rate condition. The proposed integrated framework demonstrates the feasibility of improving both oxygen delivery and flow efficiency and can be applied to the design of high-performance and low-noise automotive ventilation systems.
Polymers, along with metals, are most widely used as structural materials for air conditioners. Polymers are lightweight and have low thermal conductivity, so they are used to protect customers from hot or cold surfaces, reduce weight, and improve appearance. However, structural properties such as the Young's modulus of the polymer are temperature dependent, which changes significantly as it approaches the melting point or glass transition temperature. Operating the air conditioner for winter heating can heat-deform the polymer and cause loud squeaking noise due to friction deformation motion. To solve this problem, Young's modulus, which depends on temperature, is expressed as a simplified function and a topology optimization model using it is proposed. In addition, the usefulness is demonstrated by performing structural phase optimization for static and dynamic problems and multi objective problems with both items using this model.
This paper experimentally investigates a sub-100 W class Flow-Induced Motion (FIM) energy converter prototype for low-velocity marine currents using towing-tank tests. Two drivetrain configurations (Inner and Outer) and two cylinder aspect ratios were evaluated under identical conditions by measuring cross-flow vibration response, mechanical power, and conversion efficiency. In the Vortex-Induced Vibration (VIV) regime within the target operating range, the larger aspect-ratio cylinder generally produced higher mean power and efficiency, suggesting that an increased effective span enhances hydrodynamic performance. The two configurations showed different efficiency trends in VIV, while a clear difference in absolute power output was observed in the galloping regime. Overall, drivetrain-related response stability and dynamic characteristics directly influenced power generation and efficiency. These results provide practical guidelines for configuration selection and design of Flow-Induced Motion (FIM) based energy converters in low-speed tidal-current environments.
This paper presents an analytical study on the axisymmetric vibration characteristics of barrel-type cylindrical shells. Assuming that the shell thickness is sufficiently small compared to its length, the torsional motion is neglected and two displacement components-normal displacement along the meridional curvature and tangential displacement along the meridian-are considered. The coupled governing equations are derived from the Lagrangian formulation and expressed as a set of ordinary differential equations. A power series expansion with respect to the angular coordinate is introduced to obtain general solutions, which are classified according to the parity of the displacement functions. Resonance conditions are derived in determinant form for clamped-clamped and simply supported boundary conditions. Natural frequencies and corresponding mode shapes are calculated, and the validity of the proposed analytical method is verified through comparison with finite element analysis. The results show good agreement overall. Furthermore, the effects of the surface curvature radius on resonance frequencies are investigated, revealing that the natural frequencies increase as the curvature radius increases for all vibration modes.
Recent demand for indoor autonomous navigation of drones has increased, drawing attention to ultrasonic-based obstacle detection. This paper experimentally investigates how motor-output-dependent noise characteristics and call-sound design affect ultrasonic detection performance in a drone environment, and provides guidelines for signal processing and call-sound design. Bat-inspired call sounds are designed, and echoes from a transparent reflector are recorded under a medium-size drone with 0.18 m propellers. Data are collected by varying the motor output (20 %, 40 %, 50 %) and the reflector distance(0.5 m-2.0 m). Echoes are detected using matched filtering and adaptive thresholding, and detection performance is evaluated. The results show that concentrating signal energy on the second frequency-modulated component achieves about 80 % detection accuracy at 2.0 m under the 40 % motor-output condition. As motor output increases, broadband noise becomes stronger and degrades echo detectability, leading to limited detection at high output. These findings indicate that allocating signal energy to avoid harmonic noise bands and adopting flight-condition-dependent ultrasonic sensing are important for robust operation.
The shell horn for automobiles is a multiphysics system in which the electromagnetic, mechanical, and acoustic domains interact, and its operating frequency and sound pressure characteristics are highly sensitive to design parameters. Previous studies approximated the horn dynamics using simple linear spring models or focused on predicting the fundamental operating frequency, without providing a systematic analysis of the diaphragm's nonlinear stiffness. This study aims to characterize the nonlinear mechanical behavior of the diaphragm and to propose an enhanced Lumped Parameter Model (LPM) that incorporates this nonlinearity. Static Force-Displacement (FD) curves were obtained through finite element analysis and universal testing machine measurements, confirming the geometric nonlinear stiffening as displacement increased. Dynamic force-displacement measurements using an impedance sensor further revealed nonlinear responses and hysteresis behavior. These static and dynamic characteristics were integrated into the lumped parameter model to compute the electromagnetic-mechanical-acoustic responses. Surface velocity measurement of the armature, conducted without the acoustic shell under a 12 V Direct Current (DC), showed good agreement with the proposed model, accurately predicting not only the fundamental frequency but also higher-order harmonics. The proposed nonlinear stiffness-based model is expected to serve as a useful foundation for future design and performance optimization of the shell horns.
In this paper, experimental and numerical investigations were conducted to explain the generation mechanism of two phase flow-induced noise occurring in the transient section during the drain operation of a bidirectional pump used in washing machines. First, Short Time Fourier Transform (STFT) Diagram analysis of noise measurements and flow visualization experiments confirmed that air inflow into the housing is the primary cause of flow noise generation in the transient section. To numerically simulate this phenomenon, the Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations were selected as the governing equations, and a Volume of Fluid (VoF) model based on the homogeneous mixture model was applied to precisely simulate the two-phase flow within the pump housing. The numerical results revealed that the inflow of air into the bidirectional pump housing reduces the fluid torque load on the impeller. This reduction in torque was confirmed to induce rotational noise by causing r/min fluctuations in the transient section due to the motor's control characteristics. Furthermore, it was elucidated that the perturbation of water within the drain pipe induces strong pressure fluctuations on the housing wall, thereby generating two phase flow noise.
This paper presents a two-stage training method for speech enhancement that effectively exploits embedding vectors generated by a large Speech Representation Learning (SRL) model. At Stage-1, a DEMUCSbased conditioned model is trained to approach near-ideal performance by using SRL embedding vectors, and at Stage-2, a lightweight model without the SRL model is trained to imitate the target latent vectors obtained from the Stage-1 model. The target latent vector is produced in several ways, and we analyze which approach most effectively improves the final inference performance of the Stage-2 model. The latent vectors to be imitated are initially acquired from the decoder input of the Stage-1 DEMUCS model and processed to be the target latent vector for training. Their values are processed in four ways: 1) using the latent vectors directly as targets; 2) using the latent vectors conditioned by t-SNE processed SRL vectors; 3) using the latent vectors regularized for maximum entropy; and 4) using the latent vectors scaled. Experimental results show that the Stage-2 model that imitated the scaled target latent vectors produces the most consistent performance improvement across five objective evaluation metrics, including Perceptual Evaluation of Speech Quality (PESQ), while incurring negligible additional inference complexity. Although the experiments are limited to DEMUCS as the baseline architecture, the results demonstrate that appropriately adjusting the values of the Stage-1 latent vectors can improve the performance of the Stage-2 model with a negligible increase in inference complexity.
Directional Frequency Analysis and Recording (DIFAR) sonobuoys estimate the direction of arrival of a signal using one omni-directional sensor and two orthogonal directional sensors. When multiple DIFAR sonobuoys are deployed, target localization can be performed by finding the intersections of the bearing lines from each buoy. In underwater environments ambient noise and multipath propagation prevent bearing lines from converging to a single point, leading to the uncertainty of the estimate. To address this problem, this study proposes an ambiguity map-based target localization. The ambiguity map is generated by mapping beamforming output of each sonobuoy onto the X-Y plane and incoherently summing them to generate beam power at each coordinate. The target location is estimated as the maximum value coordinates. Ambiguity map based on Conventional Beamforming (CBF) and Minimum Variance Distortionless Response (MVDR) are implemented, and the target localization performance of proposed method is evaluated in simulated underwater environment considering ambient noise and multipath effect using mean and standard deviation of absolute error.
This study compares the whistle characteristics of false killer whale (Pseudorca crassidens) populations, the Main Hawaiian Islands (MHI), the Northwestern Hawaiian Islands (NWHI) and Pelagic. To accurately identify calls from each population, we utilized the Detection, Classification, Localization, and Density Estimation (DCLDE) 2022 workshop dataset. Whistle contours were manually extracted by tracing time-frequency contours in spectrogram, and each whistle was classified into one of six types based on its time-frequency contour shapes. To assess differences in whistle characteristics among populations, we performed Welch's Anlysis of Variance (ANOVA) and post-hoc pairwise comparisons Games-Howell, which controls the family-wise error rate under unequal variances and unequal number of samples. For each pairwise comparison, we report the mean difference (Delta) and Cohen's d, together with 95 % bootstrap Confidence Interval (CI)s obtained via stratified within-group resampling with 1,000 times. The results suggest that MHI false killer whales generally use higher min-max frequencies than those in the other two regions (pelagic and NWHI). Across five time-frequency contour shapes, the MHI population shows higher mean value in most frequency characteristics than the other two populations.
This study proposes a deep learning-based multi-fidelity optimization design process to improve the aerodynamic performance of a clothes dryer fan system. The optimization targets are the multi-blade centrifugal fan and scroll, which have a dominant influence on drying performance. The design space was expanded by adding the scroll cutoff angle and operating pressure to the impeller inlet and outlet angles. To minimize data generation costs within this expanded design space, transfer learning was employed. First, flow results obtained through 2D Computational Fluid Dynamics (CFD) simulations were used to pre-train the model as low-fidelity data. Subsequently, transfer learning was performed on datasets containing the new variables. Then, an optimal Deep Neural Network (DNN) surrogate model was constructed using Automated Machine Learning (Auto-ML). The results indicate that the proposed model achieved a 35 % reduction in the required training data while maintaining prediction accuracy comparable to conventional multi-fidelity models. Validation using the derived optimal design parameters confirmed that the flow rate improved by approximately 24 % compared to the baseline model. Furthermore, verification via 3D CFD revealed a prediction error of approximately 1.4 %. In conclusion, this study demonstrates that the proposed design process is effective for the aerodynamic optimization of fan systems while reducing data generation costs.
To minimise human and property damage caused by the spread of smoke and flames during a fire, it is essential to ensure that fire compartment penetrations are properly sealed and maintained. Although the most reliable method for inspecting fire compartment penetrations is to physically open the installed fire-resistant sealing structure, this approach presents practical difficulties, as the structure must be reconstructed after inspection. Consequently, a non-destructive testing technology for evaluating fire-stopping systems is required. Measurements of airborne sound insulation were conducted on thirteen representative fire compartment systems commonly used in buildings. The results showed a clear distinction between conditions with and without fire-stopping installation. Firestop configurations with integrated pipe fixings and board-type cable penetrations exhibited lower acoustic insulation compared with those using dedicated sealing materials, due to the presence of gaps.For future applications, it is necessary to identify the most appropriate frequency bands that demonstrate significant differences in sound insulation performance, thereby enabling more accurate assessment of fire compartment penetration integrity during both construction and maintenance phases. Furthermore, measurements using an acoustic camera successfully distinguished between installed and non-installed fire-resistant sealing structures.
This study explored the nature and social implications of floor impact noise by analyzing participant questionnaires and interviews conducted after viewing the film 84 Square Meters(English title : Wall to Wall). The ultimate aim was to provide insights into possible solutions to the issue. The film offered a fundamental understanding of the problem, highlighting diverse perspectives on building structural issues, the psychological and emotional distress caused by floor impact noise, varying levels of noise sensitivity, and the escalation of neighbor conflicts driven by mutual distrust. The viewing experience also encouraged a shift in perception and social reflection. It enabled participants to share personal experiences of discomfort and empathy, reconsider the role of government in addressing the issue, reflect on the limitations of current policy measures, and recognize the potential for a community-based response. This study integrated film appreciation with experiential data to examine the underlying nature of inter-floor noise issues and to propose proper directions for the solution. The findings offer foundational insights that may be applicable for future policy discussions and academic discourse.
With the growing demand for real-time monitoring of marine environments, the importance of Marine Sensor Networks (MSNs) has increased significantly, highlighting the need for a reliable underwater communication system. This study proposes a broadband underwater acoustic transmission system capable of transmitting in the 2 kHz to 20 kHz range by repurposing conventional Sound Navigation and Ranging (SONAR) technology-traditionally used for distance measurement-as an acoustic communication medium. The system consists of an Field Programable Gate Array (FPGA)-based digital signal generator, a Class-D power amplifier using SiC MOSFETs, an impedance matching network, and an acoustic transducer. To minimize Total Harmonic Distortion Plus Noise (THD+N), which significantly affects underwater communication quality, precise impedance modeling of the transducer was conducted and the system was simulated using PSpice. Based on this analysis, LC and notch filters were designed and implemented to suppress harmonic boosting in specific frequency bands. Finally, the application of the filter effectively attenuated high-frequency noise in the 40 kHz-70 kHz and 100 kHz-400 kHz bands by 5 dB to as much as 10 dB, thereby improving the sinusoidal characteristics of the output waveform. Applying the power amplifier proposed in this study to underwater communication systems is expected to greatly enhance the quality and reliability of underwater communications.
Indo-Pacific bottlenose dolphins (Tursiops aduncus) rely on whistles for communication and identity signaling. Yet, no systematic repertoire has been reported for the Jeju population. We collected 5,209 h of long-term underwater recordings off Yeongnak-ri, Jeju (2017-2023). A neural-network detector and duplication-handling workflow were applied. From 5,573 whistles, 349 non-duplicated classes were derived, including 120 signature whistles. Acoustic metrics differed with duplication control: start frequency, max frequency, center frequency, and freqeuncy range decreased, while end frequency increased. Signature whistles showed greater max and center frequency, wider frequency range, longer duration than non-signature whistles, but most metrics showed no significant difference. This study provides the first quantitative whistle repertoire of Jeju dolphins and a baseline for future studies on identification, abundance, and noise impact assessment.
