Search Results (3,849)

The empirical calibration of remote microphone probes, used to acquire unsteady pressure fluctuations in a wide range of fluid-dynamic applications, often introduces spurious resonance into the estimated frequency response, i.e., the transfer function, of the probe over the multiple steps it requires. To prevent this spurious resonance from affecting the unsteady pressure measurements, the transfer functions tend to be manually post-processed. Yet, such a procedure can constitute an additional source of uncertainty that hampers the accuracy of the results. A semi-empirical calibration method based on Bayesian inference was previously developed to tackle this problem: ASSIST (BAyesian proceSsing of SpurIous reSonance in calibraTion data). Through this technique, spurious resonance is removed and replaced with a physically correct alternative in a much less operator-reliant manner. However, its application requires a thorough understanding of the model and the related assumptions. This paper provides the knowledge required to apply ASSIST to the calibration of remote microphone probes. It covers the acquisition of the calibration data, the set-up of the method, the analysis of the results, and the iterative tuning of the input parameters to achieve the optimal fit. These steps are demonstrated on an open-source acoustic finite-element method simulation dataset, allowing the analytic line-cavity model to be compared with a 3D model and the impact of the relevant parameters constituting the method to be discussed. This framework is finally used to propose a novel development of the technique that reduces the calibration process of remote microphone probes to one single step, removing the source of the spurious resonance and enabling their in-situ calibration on non-sealing surfaces. Full article

The quest for a theoretical framework and ingredients that capture our current understanding of the cosmos has motivated the design of a large number of highly informative experiments, generating an abundant flow of data. Given this quantity of data and the need for thorough analysis, the main aim of this work is to present and assess the Particle Swarm Optimization (PSO) algorithm as a complementary tool to conventional cosmological data analysis techniques. PSO is one of the most representative bio-inspired algorithms, offering good robustness for high-dimensional or complex problems while remaining relatively simple to implement and requiring only a few hyperparameters. In this study, we employ two standard variants of the canonical PSO algorithm—global best and local best—to investigate dark energy models using measurements of Type Ia Supernovae and Baryon Acoustic Oscillations, focusing in particular on the DESI and DESI + Union3 datasets. Our findings demonstrate that PSO effectively recovers the best-fit parameters from observational data and show that, under suitable conditions, PSO can achieve results comparable to those of traditional MCMC techniques, but in a significantly reduced computation time. Moreover, the solutions obtained with PSO can be used as high-quality initial conditions for MCMC analyses, thereby accelerating their convergence. Full article

Shell-and-tube heat exchangers often operate under harsh conditions that induce fouling, leading to loss of thermal efficiency, production downtime, and increased maintenance costs. Conventional cleaning procedures generally require scheduled or unscheduled shutdowns, with direct operational and financial impacts. In this context, ultrasonic cavitation has been investigated as a strategy for fouling prevention and equipment cleaning, with the potential to reduce cleaning downtime or support in-service mitigation strategies. This work presents the development of an acquisition platform based on a miniaturized, waterproof acoustic probe designed for operation inside 8 mm tubes under cavitating ultrasonic fields, with the goal of experimentally mapping the relative acoustic response amplitude and dominant frequency in U-tube heat exchangers. The system integrates a piezoelectric sensing element embedded in protective encapsulation, signal-conditioning electronics, and a high-sampling-rate acquisition module. Experiments were conducted in a reduced-scale exchanger comprising 90 access ports and measurement depths up to 775 mm, using 28 kHz ultrasonic transducers. The probe successfully captured both the spectral content and the spatial variation of the voltage-based acoustic response along the tube bundle, revealing position-dependent amplitude variations and dominant-frequency measurements concentrated around the imposed excitation frequency. The analysis supported the definition of a reduced set of representative sampling locations, decreasing acquisition time while preserving the main spatial trends relevant to the objectives of this study. The procedures established here provide an experimental basis for future studies on the application of ultrasound to fouling-mitigation strategies in industrial thermal systems. Full article

This study experimentally examines turbulent flow structures induced by the coupled interaction of transverse bank slope, rigid vegetation, and bed roughness heterogeneity in a compound channel. Three-dimensional velocity components were measured using Acoustic Doppler Velocimetry (ADV) in a 13 m long flume under three transverse bank slopes (0°, 10°, and 25°), both with and without submerged rigid vegetation. Quantitatively, the presence of vegetation on the sloped bank reduced local flow velocity by 40–50% due to drag caused by vegetation canopy, while the accelerating flow in the main channel reduced by 25–35%. The combined effect of a steep 25° slope and vegetation amplified the turbulent kinetic energy (TKE) by ~55% and maximum Reynolds shear stress (RSS) by 50–70% at the sand–gravel interface compared to bare-bed conditions, generating a rigorous lateral shear layer. These quantitative insights provide critical design guidance for river restoration, bank protection, and flood management. The identified interactions between bank slope and vegetation establish a predictive framework for mitigating localized scour and bank erosion while optimizing channel conveyance capacity in ecologically managed river systems. Full article

Traditional interferometric optical hydrophones typically employ narrow-linewidth lasers. Although their long coherence length facilitates interference, it also makes the system highly susceptible to spurious interference and phase noise. Low-coherence sources can effectively suppress such parasitic noise; however, their extremely short coherence length imposes stringent stability requirements on the optical path difference (OPD). In underwater environments, ambient disturbances easily cause OPD drift beyond the coherence length, resulting in loss of interference. To address this issue, we propose and experimentally demonstrate a closed-loop hydrophone system that combines low-coherence interferometry with dynamic OPD compensation using a programmable fiber delay line (FDL). Numerical simulations and experiments confirm that the closed-loop compensation algorithm maintains the OPD within the coherence length under environmental perturbations, thereby ensuring long-term stable interference. The prototype achieves a sensitivity of −117.82 dB re rad/µPa at 171 Hz, a noise-equivalent sound pressure spectral density of 8.69 dB re 1 µPa/√Hz, a measured peak phase amplitude of 130 rad, a minimum detectable phase of 14 µrad, and a corresponding logarithmic dynamic range of 139 dB. These results verify the feasibility of integrating low-coherence interferometry with active OPD compensation for low-frequency underwater acoustic detection, under laboratory quasi-static environmental conditions, the proposed closed-loop compensation maintained stable interference throughout a continuous 1.5-h experiment, presenting a differentiated and worthy-of-further-engineering-exploration technical path for high-sensitivity and low-noise optical hydrophones. Full article

Ultrasonic anemometers are widely used for wind measurement owing to their fast response, high temporal resolution, and long operational lifetime with minimal recalibration requirements. However, most configurations suffer from transducer shadowing, where cylindrical probes disrupt local airflow and introduce systematic errors in time-of-flight (TOF) measurements. While prior computational fluid dynamics (CFD)-based investigations have characterized this effect, their analyses remain confined to low wind speeds, and no existing study has explicitly proposed a method to mitigate shadowing-induced bias. This paper presents a coupled CFD and acoustic propagation framework to analyze wake-induced velocity deficits and their effects on TOF measurements for a three-transducer ultrasonic anemometer, with simulations spanning 5 to 75 m/s over the full 360° range. The results show that shadowing distortions are strongly direction-dependent, peaked within approximately ±5° angular sectors, with a near-constant velocity deficit of approximately 40% along affected paths. A shadowing-aware acoustic path selection method is then proposed that selectively excludes corrupted acoustic paths, reducing the average velocity root-mean-square error (RMSE) to 0.349 m/s and the directional RMSE to 1.14°, representing improvements of more than an order of magnitude over shadow-unaware methods. These findings provide a physically grounded, simulation-based framework for shadowing-aware wind measurement using ultrasonic anemometers. Full article

Personal voice activity detection (PVAD) identifies whether each detected speech frame originates from a designated target speaker. Modern PVAD systems are typically trained offline and then deployed with frozen model parameters and a fixed, pre-enrolled speaker embedding, leaving them unable to adapt to distribution shifts at inference time such as unseen acoustic environments, changing speaking styles, or mismatches between enrollment and test conditions. Test-time training (TTT) and test-time adaptation have shown promise in language, vision, and several speech tasks, yet their behavior on PVAD has not been studied. In this work, we present an empirical study of two complementary test-time adaptation mechanisms built on top of the recently proposed FDE-Mamba backbone. The first is a VAD-gated TTT adapter, which instantiates the TTT-Linear formulation within the personalization pathway and augments it with a VAD-probability gate and exponential moving-average stabilization, adapting an internal weight matrix on the speaker-conditioned feature stream of each test utterance. The second is TEA (Test-time Embedding Adaptation), a scheme that keeps all model parameters frozen and instead adapts the target speaker d-vector itself via self-supervised objectives at inference time, directly targeting enrollment–test mismatch. We evaluate both mechanisms on the LibriSpeech PVAD benchmark across two backbones (LSTM-based FDE-RNN and Mamba-based FDE-Mamba), reporting category-wise average precision, mean average precision (mAP), accuracy, recall, precision, and real-time factor. We further isolate the effect of a post-hoc Gaussian smoothing step and report that, of all the components we examine, this task-agnostic smoothing accounts for the largest single accuracy gain on the FDE-Mamba backbone (accuracy $89.87\%\to 90.47\%$); the test-time adaptation mechanisms contribute a separate, smaller gain that is concentrated on speaker-discrimination metrics (mAP, precision) rather than on accuracy. Overall, the proposed test-time adaptation yields a consistent but modest improvement over the FDE-Mamba baseline (mAP $0.9605\to 0.9641$, precision $0.881\to 0.899$), while slightly reducing recall and increasing inference cost when TEA is enabled. Through ablation studies, we quantify the independent and combined contribution of each component and characterize the recall–precision trade-off introduced by adaptation. These findings, together with a discussion of their limitations and cost–benefit profile, provide a measured baseline and design insights for future work on adaptive PVAD, particularly under stronger acoustic and enrollment mismatches than those captured by the LibriSpeech protocol. Full article

With increasingly strict air quality standards and growing concerns about air pollution, fine and ultrafine particulate matter remains a major challenge for conventional air cleaning technologies. Due to their small size, these particles are difficult to remove using traditional filtration and separation methods. Acoustic agglomeration can be used as a pre-treatment technology to increase particle size in a high-intensity acoustic field and improve the efficiency of particle removal. This study investigates acoustic-induced agglomeration of solid aerosol particles in a dynamic airflow system. The effects of acoustic frequency were evaluated at 3, 5.5, 7.5, and 15 kHz under a sound pressure level of 135 dB and at two airflow velocities: 0.75 m/s and 1.5 m/s. These velocities corresponded to different particle residence times in the acoustic field. Arizona test dust was used as the test aerosol, and particle-number concentration and particle-size distribution were measured before and after the acoustic field. The results showed that acoustic agglomeration of fine and ultrafine particles was strongly affected by both acoustic frequency and particle residence time. The highest agglomeration efficiency, reaching up to 42%, was obtained at 3 kHz, 135 dB, and longer particle residence time. These findings indicate that acoustic agglomeration can promote particle-size redistribution in moving airflow and may be used as a pre-treatment method for improving particulate matter removal in air quality control systems. Full article

To reduce the computational burden of conventional spectral search direction-of-arrival (DOA) estimation algorithms for acoustic vector sensor arrays (AVSAs), this paper proposes a low-complexity DOA estimation method based on semi-real-valued noise power invariance (SR-NPI). The proposed method is developed for centrosymmetric AVSAs under the required steering-vector parity and pressure-channel conjugate-symmetry conditions after pressure–velocity (PV) co-processing. The AVSA measurements are first preprocessed through PV co-processing, and a pseudo-data covariance matrix is then reconstructed by exploiting the complex conjugate relationship between the true DOAs and their symmetric virtual DOAs. By introducing a scanning source into the reconstructed covariance matrix, a DOA-dependent spatial spectrum is constructed according to the eigenvalue-ordering behavior. Since the reconstructed matrix contains both the true DOAs and the symmetric virtual DOAs, the angular search range can be reduced to one half of the original domain. Under the tested configuration, the proposed method reduces the computational cost to approximately 1.92% of that of the original NPI algorithm. Simulation and sea trial results indicate that SR-NPI can maintain competitive estimation accuracy while significantly reducing computational complexity under the centrosymmetric-array conditions. Full article

Shallow-water underwater acoustic (UWA) communication is strongly affected by long-delay multipath propagation, time-varying Doppler distortion, and the computational burden of coherent demodulation. This paper presents a software-defined, quasi-real-time orthogonal chirp division multiplexing (OCDM) communication prototype implemented on a National Instruments compactRIO heterogeneous platform. The prototype maps previously developed multiplex resampling (MR) and Data Pick-Rake (DP-Rake) algorithms to a hardware–software processing chain, in which the FPGA executes sample-level physical-layer operations, including MR, DP-Rake windowing, OCDM demodulation, and equalization, while the ARM real-time controller performs frame-level control, FEC/CRC processing, and state-machine scheduling. The DMA-based RT–FPGA data exchange achieved a measured throughput of 80–100 MB/s. Under the maximum MR configuration, the FPGA physical-layer processing, DMA transfer, and ARM RT-layer processing required approximately 4.5 ms, 0.5 ms, and 5.0 ms per data block, respectively, resulting in a total receiver-side digital processing latency of approximately 10.0 ms. This corresponds to a 32.6 ms timing margin relative to the shortest acoustic data-block duration. The maximum FPGA resource utilization among the reported resource categories was 56.8%. The prototype was evaluated through replay-based channel emulation, Qiandao Lake mobility experiments, and Xiamen Outer Port sea trials. The replay-based results show that DP-Rake reception reduces the multipath-induced error floor under severe delay-spread conditions. In the Qiandao Lake experiments, dynamic MR branch selection achieved zero packet errors within the tested observation window while reducing the average number of active MR branches by 32.7% compared with the fixed-branch configuration. In the Xiamen Outer Port sea trials, an over 6 km shallow-water link with an approximately 12 ms delay spread was evaluated, and no packet errors were observed within the tested observation window when the measured SNR exceeded 7.9 dB. These results indicate that the implemented MR-DP-Rake OCDM prototype improves robustness over the OFDM-based baseline under the tested doubly spread UWA channel conditions. The main contribution of this work is the end-to-end software-defined implementation and field validation of MR-DP-Rake OCDM, rather than the proposal of new communication-theoretic algorithms. Full article

This study investigates the acoustic emission (AE) characteristics associated with the shear failure mode based on the principles of active waveguide monitoring for the bedding rock slopes. Physical simulation experiments were conducted to assess the AE response during the shear-induced failure process of active waveguide structures. The findings indicate that during the initial loading phase, the scatter points of the signals are concentrated within a relatively narrow range. As the shear stress exceeds 90% of the peak stress and approaches the failure stage, there is a significant increase in the AE count and a rise in the high-frequency signals. Additionally, the distribution range of signals in the parameter correlation plot expands progressively. With increasing shear stress, the AE count, amplitude, and energy also rise gradually. And the emergence of continuous high-frequency signals is noted. During the failure stage, numerous microcracks initiate and propagate within the specimen, with signal amplitudes ranging between 40 and 90 dB. The peak frequency range of the AE signals broadens, with high-frequency components mainly concentrated between 350 and 450 kHz. Loading tests conducted at shear displacement rates of 0.25–1.5 mm/min reveal a strong correlation between the AE count and the shear displacement rate. Furthermore, prior to the shear failure of the active waveguide structures, the AE count shows a positive correlation with shear displacement. After the shear failure of the waveguide structure specimens, the AE count gradually decreases from a higher level to a lower level, demonstrating a negative correlation with shear displacement. The active waveguide structure can monitor the internal deformation conditions of the bedding rock slope so as to provide some reference for the early warning research. In addition, quantitative statistical analysis and curve fitting are conducted on the relationship between AE statistical count and shear displacement under different loading rates. The measured data show good agreement with the fitted curves, and a distinct two-stage evolutionary pattern (positive correlation before peak and negative correlation after peak) is quantitatively identified. These results further enhance the reliability of using AE parameters for quantitative evaluation of shear failure characteristics and displacement rate effects in bedding rock slopes. Full article

Restaurants are a category of commercial buildings highly sensitive to dynamic changes in ambient parameters, such as thermal, internal air quality, luminous, and acoustic conditions. These fluctuations in environmental comfort yield distinct energy, ecological, and economic implications, posing a significant challenge to understanding building behavior, particularly during the cooling season. The subject of this case study is a restaurant building featuring an atrium space located in Kragujevac (Central Serbia). Its unique architectural form, which aligns with national energy efficiency principles, combined with favorable local parameters characteristic of a moderate continental climate, enables the implementation of bioclimatic measures for the passive reduction of final energy consumption during the cooling season. Therefore, using Google SketchUp 8 and EnergyPlus 7.1 software, eight bioclimatic measures, classified into three groups, were investigated: horizontal overhangs, horizontal pergolas, and deciduous plants. The numerical simulations show that using V. coignetiae as a roof covering for restaurant buildings is optimal across all the criteria. It achieves a one-season payback period, with seasonal specific metrics of 58.2 kWh/(m²season) for total final energy consumption, 145.5 kWh/(m²season) for total primary energy consumption, and 77.11 kg/(m²season) for total CO₂ emissions. In addition, a moderate continental climate suits green architecture and passive solar systems. This study confirms that the bioclimatic measures achieve energy, ecological, and economic justification solely through an integrated approach and a detailed analysis. Integrating these measures during architectural design maximizes their positive effects, ensuring optimal building performance throughout its entire operational life. Full article

Eventfulness is a core dimension of soundscape perception, reflecting cues of activity, social interaction, and dynamic change in the built environment. Although previous studies have examined variables related to eventfulness, evidence remains fragmented across contexts, terminology, and analytical levels, limiting its use in soundscape evaluation and design. This study aims to synthesize and structure the influencing factors of eventfulness perception in built-environment soundscapes. A systematic review was conducted using Web of Science and Scopus, and 79 relevant studies were selected following the PRISMA procedure. Variables, terms, and findings related to eventfulness were extracted and analyzed through grounded theory coding. The results indicate that eventfulness perception is shaped by four core categories: context, sound sources, acoustic environment, and auditory sensation. Over time, research has shifted from sound-related factors toward a broader contextualized understanding, with sound sources remaining the most recurrent explanatory basis and contextual factors expanding markedly but remaining dispersed in evidence. Although variation in contextual definitions, terminology, and measurement protocols limits direct cross-study comparison, the proposed four-category framework provides a coherent structure for organizing existing evidence and highlights the need for more systematic empirical research across diverse built-environment settings. Full article

High-speed railways (HSRs) generate repeatable and spatially extended seismic wavefields, providing useful signals for distributed acoustic sensing (DAS)-based vibration analysis. This study develops an integrated measurement framework for two characteristic frequency eigenquantities in HSR-induced seismic wavefields: train frequency and bridge frequency. Building on established spectral-line, cepstral, and Doppler descriptions of HSR seismic wavefields, we systematize the relevant theoretical expressions, compare frequency-domain correlation and cepstral strategies for train-frequency estimation, and derive a velocity-independent bridge-frequency estimator from paired Doppler-shifted components. DAS data collected along viaduct sections of the Beijing–Guangzhou HSR are used to evaluate the framework across single trains, dense observation traces, and multiple train events. The results show that bridge frequency is more stable than train frequency, with lower measurement variance. The frequency-derived train speeds and carriage lengths fall within typical operating ranges of Chinese HSR trains, and the observed spatial periodicity in frequency measurements is consistent with bridge pier spacing. These findings support accurate frequency measurement and preliminary estimation of train speed, carriage length, and wave velocity from DAS records. Together, they clarify measurable frequency parameters of HSR seismic sources and establish a quantitative source-characterization basis for DAS-based railway vibration analysis and future multi-source monitoring studies. Full article

Despite the rapid expansion of unmanned aerial vehicle (UAV) applications across precision agriculture, logistics, infrastructure inspection, disaster response, and aerial surveying, objective and quantitative hardware evaluation criteria for UAV components remain insufficiently developed. This paper proposes quantitative key performance indicators (KPIs) for thirteen core hardware subsystems, including airframe and propulsion, battery and power supply, flight control, wireless communication, imaging (camera), Global Positioning System (GPS)/Global Navigation Satellite System (GNSS) positioning, thermal management, acoustic and vibration characteristics, AI-based autonomous flight, electromagnetic compatibility (EMC), cybersecurity, and reliability and environmental qualification, together with LiDAR payload evaluation criteria. International standardization activities by 3GPP (Release 15/17), IEEE (1936–1958 series), American society for photogrammetry and remote sensing (ASPRS), and national regulatory frameworks are synthesized to define measurable performance metrics and recommended test methods for each subsystem. An integrated KPI matrix maps application-domain-specific performance targets—encompassing surveying (real-time kinematic (RTK) horizontal accuracy ≤ 2 cm root-mean-square error (RMSE), ground sample distance (GSD) ≤ 2 cm/px), infrastructure inspection (LiDAR payload up to 8 kg, beyond visual line-of-sight (BVLOS) latency ≤ 140 ms), and logistics delivery (payload ≥ 2 kg, precision landing ≤ 50 cm)—demonstrating that no universal platform can simultaneously satisfy all domain requirements. A fuzzy-AHP weighting procedure and inter-subsystem coupling analysis are introduced to address size, weight, and power (SWaP) trade-off relationships that purely additive scoring models cannot capture. The proposed evaluation framework is intended to contribute practically to UAV standardization, certification, and quality management across the full design–procurement–operation lifecycle. Full article