Ultrasound-generated bubbles enhance osteogenic differentiation of mesenchymal stromal cells in composite collagen hydrogels.

Hydrogels can improve the delivery of mesenchymal stromal cells (MSCs) by providing crucial biophysical cues that mimic the extracellular matrix. The differentiation of MSCs is dependent on biophysical cues like stiffness and viscoelasticity, yet conventional hydrogels cannot be dynamically altered after fabrication and implantation to actively direct differentiation. We developed a composite hydrogel, consisting of type I collagen and phase-shift emulsion, where osteogenic differentiation of MSCs can be non-invasively modulated using ultrasound. When exposed to ultrasound, the emulsion within the hydrogel was non-thermally vaporized into bubbles, which locally compacted and stiffened the collagen matrix surrounding each bubble. Bubble growth and matrix compaction were correlated, with collagen regions proximal (i.e., ≤ ∼60 µm) to the bubble displaying a 2.5-fold increase in Young's modulus compared to distal regions (i.e., > ∼60 µm). The viability and proliferation of MSCs, which were encapsulated within the composite hydrogel, were not impacted by bubble formation. In vitro and in vivo studies revealed encapsulated MSCs exhibited significantly elevated levels of RUNX2 and osteocalcin, markers of osteogenic differentiation, in collagen regions proximal to the bubble compared to distal regions. Additionally, alkaline phosphatase activity and calcium deposition were enhanced adjacent to the bubble. An opposite trend was observed for CD90, a marker of MSC stemness. Following subcutaneous implantation, bubbles persisted in the hydrogels for two weeks, which led to localized collagen alignment and increases in nuclear asymmetry. These results are a significant step toward controlling the 3D differentiation of MSCs in a non-invasive and on-demand manner.

Effect of Acoustically Responsive Droplet-based Low-intensity Histotripsy on Canine Prostate.

OBJECTIVE: Low-intensity histotripsy (LIH) is a novel and safe technique for tissue ablation. This study aimed to explore the effects of LIH on canine prostate tissue and identify the degree of acute injury to the gland. METHODS: We constructed and evaluated two types of acoustically responsive droplet (ARD) emulsions using either perfluoropentane (PFP) with a lipid shell or perfluoromethyl-cyclopentane (PFMCP) with lauromacrogol (L) injection. Twenty beagles were assigned to four experimental groups: ultrasound (US) + PFP (n = 6), US + PFMCP-L (n = 6), PFMCP-L (n = 5) and PFP (n = 3). The ARDs were injected transcutaneously and transabdominally into normal canine prostates under US-guided imaging. Subsequently, focused therapeutic US was employed to induce acoustic droplet vaporization and bubble cloud cavitation. The mechanical damage to canine prostate tissue was evaluated using gross and histological examination. RESULTS: Gross specimens showed that the injured area was dark brown. Hematoxylin and eosin-stained tissue sections of the damage zone showed significant cavity formation and interstitial edema. The total tissue damage scores in the US + PFP group were compared to those of the other three experimental groups. No statistically significant differences were observed in the extent of tissue damage and total scores among the US + PFMCP-L, PFMCP-L and PFP groups. CONCLUSION: We achieved significant mechanical tissue damage in the canine prostate using PFP ARD-based LIH that proved to be superior to that using PFMCP ARDs with LIH.

Acoustic Analysis of Mandarin-Speaking Transgender Women.

OBJECTIVES: This study aims to investigate the speech characteristics and assess the potential risk of voice fatigue and voice disorders in Chinese transgender women (TW). METHODS: A case-control study was conducted involving TW recruited in Shanghai, China. The participants included 15 TW, 20 cisgender men (CISM), and 20 cisgender women (CISW). Acoustic parameters including formants (F1, F2, F3, F4), cepstral peak prominence (CPP), jitter, shimmer, harmonic-to-noise ratio (HNR), noise-to-harmonics (NHR), fundamental frequency (f0), and intensity, across vowels, passages, and free talking. Additionally, the Voice Handicap Index-10 (VHI-10) and the Voice Fatigue Index were administered to evaluate voice-related concerns. RESULTS: (1) The F1 of TW was significantly higher than that of CISW for the vowels /i/ and /u/, and significantly higher than that of CISM for the vowels /a/, /i/, and /u/. The F2 of TW was significantly lower than CISW for the vowels /i/, significantly higher than CISW for the vowels /u/, and significantly higher than CISM for the vowels /a/ and /u/. F3 was significantly lower in TW than in CISW for the vowels /a/ and /i/. The F4 formant was significantly lower in TW than in CISW for the vowels /a/ and /i/, but significantly higher than in CISM for the vowel /u/. (2) The f0 of TW was significantly lower than that of CISW for the vowels /a/, /i/, /u/, during passage reading, and in free speech, but was significantly higher than CISM during passage reading and free talking. Additionally, TW exhibited significantly higher intensity compared with CISW for the vowel /a/ and during passage reading. (3) Jitter in TW was significantly higher than in CISW for the vowels /i/ and /u/, and significantly lower than in CISM during passage reading and free talking. Shimmer was significantly higher in TW compared with both CISW and CISM across the vowels /a/, /i/, during passage reading, and in free talking. The HNR in TW was significantly lower than in both CISW and CISM across all vowels, during passage reading, and in free talking. The NHR was significantly higher in TW than in CISW across all vowels, during passage reading, and in free talking, and significantly higher than in CISM for the vowels /a/, /i/, during passage reading, and in free talking. The CPP in TW was significantly lower than in CISW during passage reading and free talking, and significantly lower than in CISM across all vowels, during passage reading, and in free speech. (4) The VHI-10 scores were significantly higher in TW compared with both CISM and CISW. CONCLUSIONS: TW exhibit certain acoustic parameters, such as f0 and some of the formants, that fall between those of CISW and CISM without undergoing phonosurgery or voice training. The findings suggest a potential risk for voice fatigue and the development of voice disorders as TW try to modify their vocal characteristics to align with their gender identity.

Reconfigurable ultrasound focusing effect through acoustic barriers.

The low transmission efficiency of ultrasonic waves in waveguides of a high acoustic impedance (referred to as dense materials), due to the impedance mismatch between the background media and the dense materials, poses a significant obstacle to practical applications of high-intensity focused ultrasound (HIFU) such as ultrasound therapy or medical imaging. To address this challenge, we present an inverse optimization scheme for fabrication of novel acoustic meta-lenses, enabling strengthened penetration and enhanced focusing of ultrasonic waves when the waves traverse barriers. Both simulation and experiment validate the effectiveness of the developed meta-lenses which are annexed to hemispherical plates, and demonstrate an enhanced transmission of the sound power by an order of magnitude compared to a scenario without the use of the meta-lens. The focal distance is reconfigurable by adjusting the geometric parameters of the meta-lenses. The proposed design philosophy is not restricted by the complexity of the target structures, and it allows the ultrasonic waves to pass through acoustic barriers with a non-uniform thickness yet maintaining efficient wave focusing. This study holds appealing applications in HIFU-enabled ultrasound imaging and therapy.

Rapid detection of depression by volatile organic compounds from exhalation.

Abstract： Background: Depression is a pervasive and often undetected mental health condition, which poses significant challenges for early diagnosis due to its silent and subtle nature. OBJECTIVE: To evaluate exhaled volatile organic compounds (VOCs) as non-invasive biomarkers for the detection of depression using a virtual surface acoustic wave sensors array (VSAW-SA). METHODS: A total of 245 participants were recruited from the Hangzhou Community Health Service Center, including 38 individuals diagnosed with depression and 207 control subjects. Breath samples were collected from all participants and subjected to analysis using VSAW-SA. Univariate and multivariate analyses were employed to assess the relationship between volatile organic compounds (VOCs) and depression. The findings revealed that the responses of virtual sensor ID 14, 44, 59, and 176, which corresponded respectively to ethanol, trichloroethylene or isoleucine, octanoic acid or lysine, and an unidentified compound, were sensitive to depression. Taking into account potential confounders, these sensor responses were utilized to calculate a depression detection indicator. RESULTS: It has a sensitivity of 81.6% and a specificity of 81.6%, with an area under the curve (AUC) of 0.870 (95% CI=0.816-0.923). CONCLUSIONS: Exhaled VOCs as non-invasive biomarkers of depression could be detected by a VSAW-SA. Large-scale cohort studies should be conducted to confirm the potential ability of the VSAW-SA to diagnose depression. .

Making Patterned Single Defects in MoS2 Thermally with the MoS2/Au Moiré Interface.

Normally, it is hard to regulate thermal defects precisely in their host lattice due to the stochastic nature of thermal activation. Here, we demonstrate a thermal annealing way to create patterned single sulfur vacancy (VS) defects in monolayer molybdenum disulfide (MoS2) with about 2 nm separations at subnanometer accuracy. Theoretically, we reveal that the S-Au interface coupling reduces the energy barriers in forming VS defects and that explains the overwhelming formation of interface VS defects. We also discover a phonon regulation mechanism by the moiré interface that effectively condenses the Γ-point out-of-plane acoustic phonons of monolayer MoS2 to its TOP moiré sites, which has been proposed to trigger moiré-patterned thermal VS formation. The high-throughput nanoscale patterned defects presented here may contribute to building scalable defect-based quantum systems.

Pathogenesis and New Pharmacological Approaches to Noise-Induced Hearing Loss: A Systematic Review.

Noise-induced hearing loss (NIHL) is responsible for significant adverse effects on cognition, quality of life and work, social relationships, motor skills, and other psychological aspects. The severity of NIHL depends on individual patient characteristics, sound intensity, and mainly the duration of sound exposure. NIHL leads to the production of a reactive oxygen (ROS) inflammatory response and the activation of apoptotic pathways, DNA fragmentation, and cell death. In this situation, antioxidants can interact with free radicals as well as anti-apoptotics or anti-inflammatory substances and stop the reaction before vital molecules are damaged. Therefore, the aim of this study was to analyze the effects of different pharmacological treatments, focusing on exogenous antioxidants, anti-inflammatories, and anti-apoptotics to reduce the cellular damage caused by acoustic trauma in the inner ear. Experimental animal studies using these molecules have shown that they protect hair cells and reduce hearing loss due to acoustic trauma. However, there is a need for more conclusive evidence demonstrating the protective effects of antioxidant/anti-inflammatory or anti-apoptotic drugs' administration, the timeline in which they exert their pharmacological action, and the dose in which they should be used in order to consider them as therapeutic drugs. Further studies are needed to fully understand the potential of these drugs as they may be a promising option to prevent and treat noise-induced hearing loss.

Low-Frequency Sound-Insulation Performance of Labyrinth-Type Helmholtz and Thin-Film Compound Acoustic Metamaterial.

This paper presents a type of acoustic metamaterial that combines a labyrinth channel with a Helmholtz cavity and a thin film. The labyrinth-opening design and thin-film combination contribute to the metamaterial's exceptional sound-insulation performance. After comprehensive research, it is observed that in the frequency range of 20-1200 Hz, this acoustic metamaterial exhibits multiple sound-insulation peaks, showing a high overall sound-insulation quality. Specifically, the first sound-insulation peak is 26.3 Hz, with a bandwidth of 13 Hz and giving a transmission loss of 56.5 dB, showing excellent low-frequency sound-insulation performance. To further understand the low-frequency sound-insulation mechanism, this paper uses the equivalent model method to conduct an acoustic-electrical analogy, construct an equivalent model of the acoustic metamaterial, and delve into the sound-insulation mechanism at the first sound-insulation peak. To confirm the validity of the theoretical calculations, physical experiments are carried out by 3D printing experimental samples. The analysis of the experimental data has yielded results that are consistent with the simulation data, providing empirical evidence for the accuracy of the theoretical model. The material has significant practical application value. Finally, various factors are studied in depth based on the established equivalent model, which can provide valuable insights for the design and practical engineering application of acoustic metamaterials.

Spatial-Dependent Spectral Response of Acousto-Optic Tunable Filters with Inhomogeneous Acoustic Distribution.

The spectral response of an acousto-optic tunable filter (AOTF) is crucial for an AOTF based spectral imaging system. The acousto-optic (AO) interaction within the spatial-distributed area of the acoustic field determines the spectral response of the light incidence. Assuming an ideally uniform acoustic field distribution, phase-matching geometries can be applied to calculate the anisotropic Bragg diffraction in AO interactions, determining the wavelength and direction of the diffracted light. In this ideal scenario, the wavelength of the diffracted light depends solely on the direction of the incident light. However, due to the non-ideal nature of the acoustic field, the wavelength of the diffracted light exhibits slight variations with incident position. In this paper, an analytical model is proposed to calculate the spatial-dependent spectral response of the diffracted light under non-uniform acoustic field distribution. The study computes the variation pattern of the diffracted light amplitude caused by the inhomogeneous acoustic distribution. The theoretical considerations and computational model are confirmed by AOTF frequency scanning experiments. The study demonstrates that the distribution of the acoustic field leads to non-uniform spatial-spectral response in the AOTF, and the spatial AO interaction computational model can provide data support for calibrating AOTF systems in imaging applications.

CO2 induced phase transition on a self-standing droplet studied by X-ray scattering and magnetic resonance.

HYPOTHESIS: Acoustic levitation is a suitable approach for studying processes occurring at the gas-liquid interfaces, as it allows its investigation in a contact-free manner while providing control over the gas phase. Here, we hypothesize that phase transitions induced by a CO2 rich atmosphere can be examined, at different length scales, in a contact-free manner. EXPERIMENTAL: A system consisting of 12-hydroxysteric acid (HSA) soaps mixed with different ratios of monoethanolamine (MEA) and choline hydroxide, was prepared. Microliter droplets of the samples were acoustically levitated and monitored with a camera, while exposed to CO2 to modify the pH through diffusion at the air-liquid interface and inside the droplet. The phase transition and water mobility in the levitated droplets were evaluated through X-ray scattering (SAXS/WAXS) and magnetic resonance studies, in real-time. Finally, the droplets were collected and examined under the microscope. FINDINGS: The introduction of CO2 gas induced a phase transition from micelles to multi-lamellar tubes, resulting in a gel-like behavior both in the bulk and at the interface. The high stability of the acoustic levitator allowed the investigation of this dynamic phenomenon, in real-time, in a contact-free environment. This study showcases the suitability of acoustic levitation as a tool to investigate complex chemical processes at interfaces.

The influence of surface properties on the cooperative behavior of powdered milks.

This study comprehensively analyses various powdered milk samples to elucidate their structural, surface, and mechanical properties. Through detailed examination, diverse characteristics among the samples were observed, shedding light on their behavior under different conditions. Notably, findings reveal intriguing insights into surface energy profiles, Harkins spreading coefficient, powder rheological properties, and sound absorption efficiency of the powdered milk samples. The intricate relationship between surface properties and bulk characteristics influenced the cooperative behavior of freely poured and consolidated milk powder beds, resulting in varying flowability from free-flowing to cohesive. Surface energy played a significant role in cohesiveness and dispersibility, with milk fat acting as a key mediator leading to changes in bulk dynamic-mechanical stiffness. These findings hold practical implications for formulating innovative aerosol-based dairy and cosmetic products, thereby enhancing everyday experiences.

Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: a comparative case study.

Accurate reservoir characterization is necessary to effectively monitor, manage, and increase production. A seismic inversion methodology using a genetic algorithm (GA) and particle swarm optimization (PSO) technique is proposed in this study to characterize the reservoir both qualitatively and quantitatively. It is usually difficult and expensive to map deeper reservoirs in exploratory operations when using conventional approaches for reservoir characterization hence inversion based on advanced technique (GA and PSO) is proposed in this study. The main goal is to use GA and PSO to significantly lower the fitness (error) function between real seismic data and modeled synthetic data, which will allow us to estimate subsurface properties and accurately characterize the reservoir. Both techniques estimate subsurface properties in a comparable manner. Consequently, a qualitative and quantitative comparison is conducted between these two algorithms. Using two synthetic data and one real data from the Blackfoot field in Canada, the study examined subsurface acoustic impedance and porosity in the inter-well zone. Porosity and acoustic impedance are layer features, but seismic data is an interface property, hence these characteristics provide more useful and applicable reservoir information. The inverted results aid in the understanding of seismic data by providing incredibly high-resolution images of the subsurface. Both the GA and the PSO algorithms deliver outstanding results for both simulated and real data. The inverted section accurately delineated a high porosity zone ( > 20 % ) that supported the high seismic amplitude anomaly by having a low acoustic impedance (6000-8500 m/s ∗ g/cc). This unusual zone is categorized as a reservoir (sand channel) and is located in the 1040-1065 ms time range. In this inversion process, after 400 iterations, the fitness error falls from 1 to 0.88 using GA optimization, compared to 1 to 0.25 using PSO. The convergence time for GA is 670,680 s, but the convergence time for PSO optimization is 356,400 s, showing that the former requires 88 % more time than the latter.

Parametric Synthesis of Single-Stage Lattice-Type Acoustic Wave Filters and Extended Multi-Stage Design.

This study proposes a single-stage lattice-type acoustic filter using an analytical solution method for either a narrow passband filter or a wider passband filter using two kinds of parameter assignments in the Butterworth-Van Dyke (BVD) model. To achieve the goal of a large bandwidth or high return loss, two first-order all-pass conditions are used. For multi-stage lattice-type filters, the cost function is defined and design parameters are extracted by using pattern search, while the initial values are provided through single-stage design to shorten optimization time and allow convergence to a better solution. This method provides the S-parameter frequency response for the filter on the YX 42° cut angle of lithium tantalate (electromechanical coupling coefficient of about 6%) that can meet the system specifications as much as possible. Finally, the three-stage lattice-type was applied to various 5G bands with a fractional bandwidth of 2-5%, resulting in a passband return loss of 10 dB and an out-of-band rejection of 40 dB or more.

Acoustic Transmission Measurements for Extracting the Mechanical Properties of Complex 3D MEMS Transducers.

Recent publications on acoustic MEMS transducers present a new three-dimensional folded diaphragm that utilizes buried in-plane vibrating structures to increase the active area from a small chip volume. Characterization of the mechanical properties plays a key role in the development of new MEMS transducers, whereby established measurement methods are usually tailored to structures close to the sample surface. In order to access the lateral vibrations, extensive and destructive sample preparation is required. This work presents a new passive measurement technique that combines acoustic transmission measurements and lumped-element modelling. For diaphragms of different lengths, compliances between 0.08 × 10-15 and 1.04 × 10-15 m3/Pa are determined without using destructive or complex preparations. In particular, for lengths above 1000 µm, the results differ from numerical simulations by only 4% or less.

Development of a High-Sensitivity Acoustic Sensor Based on Grating Interferometer Combined with Glass Diaphragm.

In this study, based on the principle of grating interferometer-based acoustic sensors, design guidelines for the grating interferometric module were obtained and analyzed considering various factors in order to obtain high sensitivity, and a glass-based grating interference component and its acoustic sensor device were developed. The key parameters of the grating interference structure were extracted, and their effects on the acoustic response sensitivity were quantified for multiple mechanisms. For the development of the acoustic sensor, the grating-on-convex-platform structure and the micromachining processes of the glass-based components were designed and developed. The developed acoustic sensor samples achieved high sensitivity. In particular, the sample suitable for low-frequency application obtained a sensitivity of 0.776 V/Pa @ 1 kHz, and the spectrum of its sensitivity was flat from 50 Hz to 8 Hz with a deviation less than 1.5 dB and a sensitivity of 0.408 V/Pa @ 20 Hz.

Research on On-Line Monitoring of Grinding Wheel Wear Based on Multi-Sensor Fusion.

The state of a grinding wheel directly affects the surface quality of the workpiece. The monitoring of grinding wheel wear state can allow one to efficiently identify grinding wheel wear information and to timely and effectively trim the grinding wheel. At present, on-line monitoring technology using specific sensor signals can detect abnormal grinding wheel wear in a timely manner. However, due to the non-linearity and complexity of the grinding wheel wear process, as well as the interference and noise of the sensor signal, the accuracy and reliability of on-line monitoring technology still need to be improved. In this paper, an intelligent monitoring system based on multi-sensor fusion is established, and this system can be used for precise grinding wheel wear monitoring. The proposed system focuses on titanium alloy, a typical difficult-to-process aerospace material, and addresses the issue of low on-line monitoring accuracy found in traditional single-sensor systems. Additionally, a multi-eigenvalue fusion algorithm based on an improved support vector machine (SVM) is proposed. In this study, the mean square value of the wavelet packet decomposition coefficient of the acoustic emission signal, the grinding force ratio of the force signal, and the effective value of the vibration signal were taken as inputs for the improved support vector machine, and the recognition strategy was adjusted using the entropy weight evaluation method. A high-precision grinding machine was used to carry out multiple sets of grinding wheel wear experiments. After being processed by the multi-sensor integrated precision grinding wheel wear intelligent monitoring system, the collected signals can accurately reflect the grinding wheel wear state, and the monitoring accuracy can reach more than 92%.

Design and Evaluation of Real-Time Data Storage and Signal Processing in a Long-Range Distributed Acoustic Sensing (DAS) Using Cloud-Based Services.

In cloud-based Distributed Acoustic Sensing (DAS) sensor data management, we are confronted with two primary challenges. First, the development of efficient storage mechanisms capable of handling the enormous volume of data generated by these sensors poses a challenge. To solve this issue, we propose a method to address the issue of handling the large amount of data involved in DAS by designing and implementing a pipeline system to efficiently send the big data to DynamoDB in order to fully use the low latency of the DynamoDB data storage system for a benchmark DAS scheme for performing continuous monitoring over a 100 km range at a meter-scale spatial resolution. We employ the DynamoDB functionality of Amazon Web Services (AWS), which allows highly expandable storage capacity with latency of access of a few tens of milliseconds. The different stages of DAS data handling are performed in a pipeline, and the scheme is optimized for high overall throughput with reduced latency suitable for concurrent, real-time event extraction as well as the minimal storage of raw and intermediate data. In addition, the scalability of the DynamoDB-based data storage scheme is evaluated for linear and nonlinear variations of number of batches of access and a wide range of data sample sizes corresponding to sensing ranges of 1-110 km. The results show latencies of 40 ms per batch of access with low standard deviations of a few milliseconds, and latency per sample decreases for increasing the sample size, paving the way toward the development of scalable, cloud-based data storage services integrating additional post-processing for more precise feature extraction. The technique greatly simplifies DAS data handling in key application areas requiring continuous, large-scale measurement schemes. In addition, the processing of raw traces in a long-distance DAS for real-time monitoring requires the careful design of computational resources to guarantee requisite dynamic performance. Now, we will focus on the design of a system for the performance evaluation of cloud computing systems for diverse computations on DAS data. This system is aimed at unveiling valuable insights into performance metrics and operational efficiencies of computations on the data in the cloud, which will provide a deeper understanding of the system's performance, identify potential bottlenecks, and suggest areas for improvement. To achieve this, we employ the CloudSim framework. The analysis reveals that the virtual machine (VM) performance decreases significantly the processing time with more capable VMs, influenced by Processing Elements (PEs) and Million Instructions Per Second (MIPS). The results also reflect that, although a larger number of computations is required as the fiber length increases, with the subsequent increase in processing time, the overall speed of computation is still suitable for continuous real-time monitoring. We also see that VMs with lower performance in terms of processing speed and number of CPUs have more inconsistent processing times compared to those with higher performance, while not incurring significantly higher prices. Additionally, the impact of VM parameters on computation time is explored, highlighting the importance of resource optimization in the DAS system design for efficient performance. The study also observes a notable trend in processing time, showing a significant decrease for every additional 50,000 columns processed as the length of the fiber increases. This finding underscores the efficiency gains achieved with larger computational loads, indicating improved system performance and capacity utilization as the DAS system processes more extensive datasets.

A Method for the Pattern Recognition of Acoustic Emission Signals Using Blind Source Separation and a CNN for Online Corrosion Monitoring in Pipelines with Interference from Flow-Induced Noise.

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert-Huang transform (HHT) was applied to each source signal to obtain a joint time-frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%.

Investigation of the Reduction in Distributed Acoustic Sensing Signal Due to Perforation Erosion by Using CFD Acoustic Simulation and Lighthill's Acoustic Power Law.

Distributed Acoustic Sensing (DAS), widely adopted in hydraulic fracturing monitoring, continuously measures sound from perforation holes due to fluid flow through the perforation holes during fracturing treatment. DAS has the potential to monitor perforation Tulsa, OK 74136erosion, a phenomenon of increasing perforation size due to sand (referred to as proppant) injection during treatment. Because the sound generated by fluid flow at a perforation hole is negatively related to the perforation diameter, by detecting the decay of the DAS signal, the perforation erosion level can be estimated, which is critical information for fracture design. We used a Computation Fluid Dynamics (CFD) acoustic simulator to calculate the acoustic pressure induced by turbulence inside a wellbore and investigated the relationship between the acoustic response from fluid flow through a perforation and the perforation size by running the simulator for various perforation diameters and flow rates. The results show that if the perforation size is constant, the plot between the calculated sound pressure level and the logarithm of flow rate follows a straight line relationship. However, with different perforation sizes, the intercept of the linear relationship changes, reducing the sound pressure level. Lighthill's power law indicates that the change in intercept corresponds to the logarithm of the ratio of the increased diameter to the original diameter. The reduction in sound pressure level observed in the CFD simulation correlates with the reduction in the DAS signal in field data. The findings of this study help to evaluate perforation diameter growth using DAS and interpret fluid distribution in fracture stimulation.

Underwater Acoustic Orthogonal Frequency-Division Multiplexing Communication Using Deep Neural Network-Based Receiver: River Trial Results.

In this article, a deep neural network (DNN)-based underwater acoustic (UA) communication receiver is proposed. Conventional orthogonal frequency-division multiplexing (OFDM) receivers perform channel estimation using linear interpolation. However, due to the significant delay spread in multipath UA channels, the frequency response often exhibits strong non-linearity between pilot subcarriers. Since the channel delay profile is generally unknown, this non-linearity cannot be modeled precisely. A neural network (NN)-based receiver effectively tackles this challenge by learning and compensating for the non-linearity through NN training. The performance of the DNN-based UA communication receiver was tested recently in river trials in Western Australia. The results obtained from the trials prove that the DNN-based receiver performs better than the conventional least-squares (LS) estimator-based receiver. This paper suggests that UA communication using DNN receivers holds great potential for revolutionizing underwater communication systems, enabling higher data rates, improved reliability, and enhanced adaptability to changing underwater conditions.