Browse Topic: Acoustics
For analysing flow and acoustic induced structural vibration, a fully run time coupled framework combining a hybrid CFD-CAA approach with a modal response simulation was validated and presented at the ISVNH 2022 (SAE Technical Paper 2022-01-0938). In this paper i We apply this CFD–CAA–modal coupling method to a series-representative bonnet geometry and demonstrate its capability to capture flow and aeroacoustically driven vibration with two-way coupling. ii We analyse the modal properties of the bonnet and show that confined air volumes beneath the bonnet can introduce significant fluid loading effects, which are already embedded in experimentally validated FE modal models and must therefore be treated carefully in two-way coupled simulations. iii We validate the fully coupled aeroelastic simulation against wind-tunnel measurements with undisturbed inflow, show close agreement with the measured vibration response and analyse that the dominant excitation is in this case from below the bonnet due to acoustic pressure fluctuations.
Noise, Vibration, and Harshness (NVH) performance is critical in the automotive development process, yet identifying the true root causes of unwanted dynamic behavior remains a challenge in full vehicle or system-level finite element (FEM) models. This work demonstrates how Frequency Based Substructuring (FBS) provides an efficient framework for understanding NVH phenomena and facilitates new root cause analysis (RCA) types and processes. To begin, we prove the numerical accuracy of the FBS algorithm deployed in the presented investigation by comparing its results with those obtained with superelements and without substructuring. We point out that because the used FBS process starts with a modal representation of the components rather than their frequency response functions (FRF) a different class of RCA type becomes available. Then we introduce new RCA types starting with an analysis named Modal Influence (MI) that reveals the effect of the modes of any component on a certain response. Its key characteristic is that MI analysis is not restricted to the response component opposite to the well-known modal participation factors. Finally, a second novel analysis type is introduced, an advanced variant of Transfer Path Analysis (TPA). While standard TPA assesses the paths between only two system components, the new Expanding TPA is a multi-step process that identifies the most critical path across all components in a fully automated way.
As acoustic requirements for NVH trim components become increasingly constrained by mass, cost, and sustainability targets, traditional approaches to inner dash design based on spatially averaged Transmission Loss (TL) metrics are reaching their practical limits. In fully built vehicles, the acoustic performance of the inner dash is governed by its global insulation capability but also by strong spatial heterogeneity and its interaction with spatially distributed noise sources such as the power unit, gearbox, and tyre-road excitation. This paper presents a test-based methodology for the spatial optimisation of inner dash acoustic performance using reciprocal holography. By applying a calibrated sound power source within the vehicle cabin and measuring the reciprocal response in the engine bay and wheel-arch regions, a high-resolution spatial Transmission Loss “hologram” of the inner dash is obtained under in-situ conditions. The resulting spatial data enables the identification of localised acoustic weak points that are not observable using conventional testing methods. To bridge the gap between passive component characterisation and real-world vehicle operation, the spatial TL hologram is subsequently evaluated using representative operational source sound power data to prioritise acoustically relevant regions. This enables the transmitted acoustic energy to be evaluated under realistic driving conditions. The holographic data is then coupled with a parametric acoustic model of the inner dash system, allowing localised mass redistribution to be optimised using a genetic algorithm while respecting packaging and manufacturing constraints.
In this study, we propose a methodology for predicting the acoustic modes and natural frequencies of a sedan using artificial intelligence and demonstrate the feasibility of controlling its acoustic characteristics by modifying the hole distribution of the package tray. In typical sedan structures, the cabin cavity and trunk cavity are acoustically coupled through holes in the package tray. The distribution of these holes significantly affects the natural acoustic modes and frequencies of the vehicle. However, once the exterior shape of the vehicle is finalized during the design stage, options for structural modifications to mitigate noise issues caused by these modes become extremely limited. To address this challenge efficiently, we develop a deep learning-based neural network model trained on data derived from a simplified acoustic analysis model of a sedan that includes a package tray. Finite element analysis is performed to generate acoustic modes and natural frequencies, which serve as training data, for various hole distributions. The trained model is then used to predict acoustic natural modes and natural frequencies from unseen input images representing different hole configurations in the package tray. These predictions are made in a fraction of the time required for traditional simulation methods, thereby validating the model’s effectiveness. Furthermore, we demonstrate that the latent variables embedded in the trained model can be manipulated to control the acoustic modes and natural frequencies of the sedan. This indicates the potential for artificial intelligence-driven acoustic design optimization in early-stage vehicle development, offering both time efficiency and design flexibility without physical prototyping or extensive simulations.
Recent studies indicate that the door system plays a significant role in the interior noise levels of newly developed vehicles. This research investigates the noise transmission paths through the door system and identifies effective strategies for improvement through a combination of door buck testing and simulation. Specifically, in this study, the finite element method (FEM) was employed for door buck simulation, and the model was validated against vibration test results. Subsequently, acoustic analysis tools were utilized to correlate with noise testing, thereby establishing a process to ensure simulation accuracy. The sound insulation performance for the main areas of the door was experimentally evaluated, and a simulation model with good correlation to these test results was developed. By utilizing both experimental and simulation results, the principal transmission paths were identified, and appropriate improvement strategies for these paths were investigated. The validated improvement strategies are intended to be applied in the development of next-generation vehicles.
The payload fairing of a launch vehicle is subjected to extremely high acoustic loads, with peak levels occurring during lift-off and transonic aerodynamic regimes. The external acoustic field penetrates the fairing, producing intense internal sound pressure levels that can challenge the integrity of spacecraft components. Accurate characterization of the vibroacoustic behavior of the payload fairing and its enclosed cavity is therefore essential to ensure spacecraft survivability. The internal acoustic field is governed by the coupled dynamics of the fairing structure and the spacecraft configuration, making it critical to quantify the acoustic environment for different payload arrangements. This study presents a detailed vibroacoustic analysis of a payload fairing with multiple spacecraft configurations to evaluate the resulting internal sound pressure distribution. Vibroacoustic finite element analysis is employed in the low frequency range, while statistical energy analysis is utilized for mid and high frequency ranges. Representative models are developed, and the predicted structural and acoustic responses are validated against experimental acoustic test measurements. The validated models are subsequently extended to other spacecraft configurations to perform sensitivity studies. The influence of various parameters on the internal sound pressure levels is assessed, and the resulting perturbations across frequency bands are quantified. The outcome of this study provides a comprehensive understanding of the internal acoustic environment within payload fairing, aiding in the specification of qualification acoustic test level for spacecraft.
This paper presents a study of gunshot acoustic signal detectability in the near field of propeller noise, with a focus on the isolation of external gunshot signatures masked by propeller-induced noise. Controlled measurements were conducted in a Recirculation Delayed Anechoic Chamber (RDAC), where acoustic data were collected across varying rotor speeds, source locations, and propagation distances. Propeller noise characteristics were verified using UCD-QuietFly. The recorded signals were analyzed for the acoustic pressure, sound pressure level, and overall sound pressure level directivity to quantify masking effects. Results show that RPM is the dominant factor governing signal detectability. At 3000 RPM, the gunshot signal remains clearly identifiable within the low frequency range of 200–2000 Hz. At 4000 RPM, the signal becomes partially masked, while at 5000 RPM, propeller noise fully dominates and the gunshot signal becomes undetectable. Detectability is further reduced with increasing propagation distance. In-plane microphone locations provide improved detectability. A machine learning-based spectral separation framework was developed to suppress propeller noise and enhance the visibility of impulsive gunshot signatures in multichannel spectrograms. Experimental results show that learning-based denoising is effective at lower RPMs where the signal-to-noise ratio remains favorable, but performance degrades as broadband masking intensifies at higher rotor speeds.
Metal-elastomer bonded components can suffer from manufacturing defects such as porosity and bond-line voids. Nondestructive evaluation (NDE) methods can replace or supplement existing destructive tests; however, implementation can be challenging for manufacturers due to the initial equipment cost, time required per test, and imaging quality. These criteria were used to evaluate shearography, high-resolution ultrasound testing (UT), 2D projection X-ray, computed tomography (CT), and acoustic emission (AE) testing, culminating in trade studies for different sample part types. Experimental work was performed on three samples of varying geometries and sizes with seeded defects, applying feasible NDE methods to each. Shearography succeeded in detecting void defects and flow fronts. X-ray and CT failed to detect flaws in 2 out of 3 part types due to energy and time constraints. UT could not reliably detect defects in parts with complex geometries because of scatter. Acoustic emission reliably detected a seeded knit-line defect.
This study investigates the acoustic performance of a single rotor representative of those seen on multi-passenger UAM-sized vehicles, focusing on the effects of blade count, disk loading, solidity, and tip Mach number in both hover and propeller operating conditions. Using PSU-WOPWOP and ANOPP2, unweighted and A-weighted overall sound pressure levels (OASPL) are computed in-plane for 2- and 5-bladed rotors across a range of design parameters and operating conditions. Unweighted results show that reducing blade count significantly increases total noise levels (14.1 dB on average) and reduces sensitivity to design parameters. In contrast, A-weighted results demonstrate that broadband noise dominates perceived acoustic performance and shows a decreased sensitivity to blade count (1.9 dBA average difference). Minimum noise levels occur at tip Mach numbers ranging from 0.35-0.45 for unweighted results and 0.4-0.5 for A-weighted results, and are primarily governed by broadband noise sensitivity to disk loading and solidity. The rotor in propeller mode, with axial flow and reduced disk loading, showed less sensitivity to variation in disk loading and solidity than the rotor in hover, indicating weaker acoustic dependence in cruise conditions.
This study investigates the use of the Overset mesh method for propeller simulations in OpenFOAM and compares it with the Arbitrary Mesh Interface (AMI) approach. While AMI is well validated for rotor aeroacoustics, it is limited in handling large relative motions and complex component interactions. In contrast, the Overset method enables flexible simulation of transition kinematics using overlapping grids, though its aeroacoustic capability in OpenFOAM has not been well established. A comparative analysis was conducted on a Joby-scale five-bladed propeller at an 80° tilt angle without a fairing, representing a transition-flight condition. Aerodynamic and acoustic predictions were obtained using hybrid DDES coupled with the Ffowcs Williams–Hawkings method. Results show that the Overset method provides improved agreement with experimental thrust and torque and captures stronger leading-edge vortices than AMI. Both methods resolve blade-vortex and blade-wake interactions. However, the Overset approach produces higher broadband noise due to stronger vortices and interpolation effects, while AMI yields smoother pressure fields and clearer tonal content. In the far field, AMI better matches experimental SPL trends. Overset shows larger first-BPF SPL errors (up to 22.5 dB vs. 5.7 dB for AMI), though OASPL differences remain small. Overall, Overset is less reliable for noise prediction and more computationally expensive.
This study highlights that rotor-rotor interactions can significantly modify both tonal and broadband noise characteristics. Continued investigation into these mechanisms is vital to developing reliable noise prediction methodologies and establishing design strategies that balance propulsion efficiency with acoustic acceptability for AAM vehicles. This work sought to answer what physical mechanisms contribute to the increased dominance of broadband noise in eVTOL-scale rotors. By characterizing the tip vortex of a single rotor, it was found that rotor-rotor interaction is highly dependent on two factors: Blade-vortex phasing and interaction duration. Characteristic vortex time scales can be correlated with increased noise. Interactions that generate increased noise have a non-linear relationship with rotor positioning. The interaction-generated noise is highly directive. This work aims to elucidate the dominant source noise mechanisms of rotor-rotor interaction noise by characterizing blade tip vortices using PIV.
The Audio system is an important part of the design of a vehicle cabin. In the vehicle development process, the audio system needs to be tuned for optimal acoustic performance. Traditionally, this process is performed physically on vehicles. In this paper, a methodology is developed to numerically simulate the acoustic performance of the audio system across the full audible frequency range. To provide validation of the method, the p/v acoustic transfer functions (ie., the sound pressure p at the passengers’ ears divided by the voltage inputs v) are measured for different speakers in a production vehicle. As the sound perceived by the passengers depends on both the source and the path, the method development is split into two parts: (a) characterization of parameters that describe the loudspeaker as a source and (b) representation of the vehicle cabin as a path. The speaker parameters are characterized from sound radiation data measured in a 2pi chamber. To represent the vehicle cabin, a hybrid BEM-SEA model is utilized in which the cabin is fully deterministic below 1kHz and is statistical between 1 kHz and 20 kHz. The speaker model is then integrated into the cabin model in order to predict the acoustic transfer functions. This model accounts for two-way coupling between the speakers and the cabin. The results show that the predicted transfer functions are in very good agreement with the data from acoustic measurements. Therefore, performing the audio tuning virtually by numerical simulation is a feasible solution for the industry.
An experimental investigation was conducted to explore the loads, acoustics, and tip vortex trajectories of coaxial counter-rotating (CCR) rotor with unequal upper and lower radii. The upper and lower rotor radii were tested both at the nominal radius of 1.108 m, and also with a lower rotor radius of 90% nominal radius, for a constant rotor speed of 1180 RPM and a constant inter-rotor spacing of z/R = 0.108. Rotors were torque balanced and tested for a range of upper rotor collective pitch from -2◦ to 10◦ . The power required for both CCR systems was within 0.9% for most trim conditions, and equal thrust was produced at upper rotor collectives of 6◦ and 8◦ (within 1.0%). At low loading conditions the unequal radii configuration produced more thrust for the same power due to a reduction in profile drag. The overall sound pressure level (OASPL) was lower for the CCR rotor with shortened lower rotor blades at all angles of elevation. Larger reductions in A-weighted OASPL(A) were observed, due to a larger contribution of broadband noise to the total OASPL(A).
This study examines the capability of medium-fidelity comprehensive analysis models to predict the acoustics for manned and unmanned rotorcraft configurations. Using the automated tool NDARC2RCAS developed at DEVCOM Army Research Laboratory, multiple configurations including a single main rotor, tilt rotor, coaxial and pusher, quadcopter, and hexacopter are evaluated at various mission segments including hover, advancing climb, and forward flight. Each configuration and condition is evaluated using a range of aerodynamic models from lower to higher fidelity, including uniform inflow, dynamic inflow, prescribed wake, free wake, and viscous vortex particle method (VVPM). These evaluations are then used with another automated tool, RCAS Acoustics, to predict noise on a Voronoi observer sphere. A comparison of the results for the single main showed good agreement between all of the aerodynamic models except VVPM. For the tilt rotor in forward flight, the higher-fidelity models produced changes in rotor loads due to the interaction with the wing. With prescribed and free wake models, this change in load is sharp and causes noise increases of up to 40 dB in front of and behind the vehicle, while the VVPM model produced a smoother change that results in a smaller, 20 dB increase in noise. The quadcopter and hexacopter show similar in-plane noise levels for all models, with alternating cancellation and amplification patterns due to rotor phasing, while out-of-plane noise is increased on the hexacopter when using the higher fidelity models.
In pursuit of a distinct sporty interior sound character, the present study explores an innovative strategy for designing intake systems in passenger vehicles. While most existing literature primarily emphasizes exhaust system tuning for enhancing vehicle sound quality, the current work shifts the focus toward the intake system’s critical role in shaping the perceived acoustic signature within the vehicle cabin. In this research work, target cascading and settings were derived through a combination of benchmark and structured subjective evaluation study and aligning with literature review. Quantitative targets for intake orifice noise was defined to achieve the desired sporty character inside cabin. Intake orifice targets were engineered based on signature and sound quality parameter required at cabin. Systems were designed by using advanced NVH techniques, Specific identified acoustic orders were enhanced in the intake system to reinforce the required signature in acceleration as well as in cruising mode. A novel decomposition method was developed to identify exact contribution of intake system’s noise from overall in cab noise. Based on advanced NVH analysis and sound diagnosis a precise identification of intake system contributions during both acceleration and cruising conditions was carried out. Furthermore, sound design strategy was developed which targets a dual-mode acoustic profile. The developed design strategy was validated at vehicle level, confirming that the intake system design met both subjective and objective targets. This integrated approach provides a repeatable framework for intake sound design, offering OEMs a robust pathway to differentiate sporty vehicle character through intelligent intake acoustics. This work not only demonstrates the critical role of intake design in vehicle sound signature development but also proposes a systematic methodology for future vehicle sound engineering.
Tire noise reduction is important for improving ride comfort, especially in electric vehicle due to lack of engine noise and majority of the noise generated in-cabin is from tire-road interaction. Therefore, the tire tread pattern contribution is one of the important criteria for NVH performance apart from other structurally generated noise and vibration. In this work a GUI-based pitch sequence optimization tool is developed to support tire design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. The key point to be considered in this pitch sequence is that it should be reducing the tonal sound and equally spread i.e., the same pitch cannot be concentrated on one side which may lead to non-uniformity. So, the restriction is that the highest and lowest pitch types cannot occur adjacent to one another. This design rule helps in reducing undesirable pattern non-uniformity and improves both acoustic and structural performance. This tool helps in faster design iteration and integration with downstream development processes. This tool is also validated in current OE projects showing promising improvements in tire noise behavior while maintaining realistic design feasibility.
Noise generated by a vehicle’s HVAC (Heating, Ventilation, and Air Conditioning) system can significantly affect passenger comfort and the overall driving experience. One of the main causes of this noise is resonance, which happens when the operating speed of rotating parts, such as fans or compressors, matches the natural frequency of the ducts or housing. This leads to unwanted noise inside the cabin. A Campbell diagram provides a systematic approach to identifying and analyzing resonance issues. By plotting natural frequencies of system components against their operating speeds, Test engineers can determine the specific points where resonance occurs. Once these points are known, design changes can be made to avoid them—for example, adjusting the blower speed, modifying duct stiffness, or adding damping materials such as foam. In our study, resonance was observed in the HVAC duct at a specific blower speed on the Campbell diagram. To address this, we opted to optimize the duct design instead of changing the blower speed. This approach helped eliminate resonance at that operating point, reducing noise in the cabin. By applying the Campbell diagram tool, HVAC noise can be minimized, resulting in a quieter cabin and an improved driving experience.
To address the growing concern of increasing noise levels in urban areas, modern automotive vehicles need improved engineering solutions. The need for automotive vehicles to have a low acoustic signature is further emphasized by local regulatory requirements, such as the EU's regulation 540/2014, which sets sound level limits for commercial vehicles at 82 dB(A). Moreover, external noise can propagate inside the cabin, reducing the overall comfort of the driver, which can have adverse impact on the driving behavior, making it imperative to mitigate the high noise levels. This study explores the phenomenon of change in acoustic behavior of external tonal noise with minor geometrical changes to the A-pillar turning vane (APTV), identified as the source for the tonal noise generation. An incompressible transient approach with one way coupled Acoustics Wave solver was evaluated, for both the baseline and variant geometries. Comparison of CFD results between baseline and variant showed spectral broadening of critical tone in variant case. Impact of various other simulation parameters like turbulence intensity, turbulence length scale, time-step size and sampling time, on the critical tonal frequency, was also evaluated. Reduction in time step had a significant impact on the acoustic behavior of the APTVs due to spectral broadening & reduction of tonality. Whereas turbulence intensity is observed to have a significant effect on the frequency of the critical tone, the effect of other simulation parameters was not significant. Coherent vortex shedding from the APTV is identified to be the underlying source of the noise, exhibiting a dipole acoustic behavior. Geometric modification to the leading edge of the APTV is observed to reduce the tonal amplitude due to reduced coherence of vortex shedding and weak vortex core. The current method is able to predict the change in acoustic behavior due to geometric modifications for a particular yaw angle, further studies are ongoing to improve accuracy for full yaw sweep.
Animals like bats, whales, and insects have long used acoustic signals for communication and navigation. Now, an international team of scientists have taken a page from nature’s playbook to model micro-sized robots that use sound waves to coordinate into large swarms that exhibit intelligent-like behavior. The robot groups could one day carry out complex tasks like exploring disaster zones, cleaning up pollution, or performing medical treatments from inside the body, according to team lead Igor Aronson, Huck Chair Professor of Biomedical Engineering, Chemistry, and Mathematics at Penn State.
The increased functionality of today’s medical devices is astounding. Optical devices, for example, analyze chemicals, toxins, and biologic specimens. Semiconductor devices sense, analyze, and communicate. Microelectromechanical system (MEMS) devices utilize inertial methods to detect motion, direct light, and move components over short distances. Radiofrequency (RF) devices communicate wirelessly to other devices directly and remotely over the Internet. Handheld acoustic devices scan the body and build a virtual 3D model that shows conditions in the body. The innovation currently happening in the medical device industry is staggering, limited only by imagination and finding technical methods to implement the vision.
Items per page:
50
1 – 50 of 2292