In 1992, the author proposed a generalization of the Sabine formula that develops reverberation time over a series of powers of the reflection coefficient on the boundaries. Some years later, he reduced the development to just two terms that made it possible to monitor reverberation times up to large absorptions. The present paper revisits this development and justifies it with the help of free path statistics in ergodic 2D and 3D circular and rectangular enclosures. It proves that Kuttruff's reverberation formula is a special case of the general formula, but diverges for large absorption. Reverting to Kuttruff's original integration process leads to a formula that does not diverge. The paper further explains the difference between Eyring-type reverberation times that vanish for total absorption, and Sabine-type reverberation times that never vanish even for total absorption, and proposes a simple scheme for evaluating the asymptotic free path statistics and thus improving reverberation time prediction. Lastly, the approach is extended to non-ergodic enclosures.
Acoustics in engineering. Acoustical engineering, Acoustics. Sound
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Abstract Hearable devices, equipped with one or more microphones, can be used to capture the user’s own voice in noisy environments. In such environments, an own voice reconstruction (OVR) system is needed to enhance the quality and intelligibility of the recorded own voice. In this work, we aim to estimate clean broadband speech from a microphone at the outer face of the hearable and an in-ear microphone, which captures the own voice at a higher signal-to-noise ratio than the outer microphone, but with a limited bandwidth and additive body-produced noise. Training a supervised deep learning-based OVR system requires a substantial amount of own voice signals as training data. Such training data can be collected by recording many utterances from different talkers wearing the hearable, which is costly, or generated by augmenting existing clean speech datasets. In this paper, we investigate several data augmentation techniques to simulate a large amount of in-ear own voice signals from a limited amount of recorded own voice signals. More specifically, we consider different models for the own voice transfer characteristics between the outer microphone and the in-ear microphone, ranging from a fixed talker-averaged relative transfer function to a phoneme-dependent individual model. We investigate the influence of the amount of recorded own voice signals on the performance of an OVR system based on the FT-JNF architecture, either by directly using the recorded signals for training or by using the recorded signals to generate augmented data for training (with and without fine-tuning with recorded signals). Experimental results show that training using the proposed speech-dependent individual data augmentation technique and additional fine-tuning with recorded signals yields the best performance in terms of objective metrics, even when only few recorded own voice signals are available.
Topological physics has been driving exciting progress in the area of condensed matter physics, with findings that have recently spilled over into the field of metamaterials research inspiring the design of structured materials that can govern in new ways the flow of light and sound. While so far these advances have been driven by fundamental curiosity-driven explorations, without a focused interest on their technological implications, opportunities to translate these findings into applied research have started to emerge, in particular in the context of sound control. Our team has been leading a highly collaborative research effort on advancing the field of topological acoustics, dubbed ‘New Frontiers of Sound’ and connecting it to technological opportunities for computing, communications, energy and sensing. In this comment, we outline our vision towards the future of topological sound, and its translation towards industry-relevant functionalities and operations based on extreme control of acoustic and phononic waves.
Shane Zhang, Shirui Peng, Haakon L. L. Ervik
et al.
Earthquakes excite sound waves along continental margins, T waves, that can propagate for thousands of kilometers in the ocean. The complex T waveforms are shaped by the extended region of seismic-to-acoustic conversion. Because the conversion has a width comparable to ocean eddies, T waveforms can be modified substantially by the subsequent propagation through eddies. Sound speed anomalies associated with eddies shift arrival times, so waves arriving from different azimuths can have experienced different phase shifts, making the recorded waveform an eddy-dependent interference pattern. Leveraging this multipath propagation can improve the spatial resolution of deep-ocean temperature change estimated with T waves.
As miniaturized ultrasonic transducers with sophisticated structure have become increasingly demanded, the vibrating bodies made by conventional metals face the problem of fabricating difficulty and high expenses. The 3D printing metals are prospective materials for their flexibility in forming complicated configurations, but their mechanical-loss properties need clarification as they greatly affect the vibration properties. As a pilot trail, first, an approach to measure the attention coefficients according to the distributions of the vibration velocity and the phase was developed to evaluate their dependence on the strain and the frequency. Then, an aluminum alloy via 3D printing (AlSi10Mg) was employed as the vibrating bodies to form the ultrasonic transducers, whose performance, e.g., vibration properties, temperature rise, and sound pressure level (SPL) in water, was assessed and compared with conventional aluminum alloy (7075). As typical results, AlSi10Mg’s damping coefficient is 1.16 times that of 7075 at 33 kHz frequency; this implies the 3D printing process does not deteriorate the aluminum alloy’s mechanical-loss property. Meanwhile, AlSi10Mg’s damping coefficient reaches 2.19 × 10-4 at the laser power of 350 W, relatively small compared to the values corresponding to other laser powers; this indicates the capability to reduce the mechanical loss by adjusting the parameters during 3D printing possesses. Moreover, the maximum vibration velocity and the SPL of the AlSi10Mg transducer are 1.13 and 1.11 times those of the 7075 transducer that has the same configuration and operates in the same vibration modes. This study enriches the candidate materials as the vibrating bodies of ultrasonic transducers, which potentially meet the demands in wider ultrasonic application fields.
Underwater acoustics has been implemented mostly in the field of sound navigation and ranging (SONAR) procedures for submarine communication, the examination of maritime assets and environment surveying, target and object recognition, and measurement and study of acoustic sources in the underwater atmosphere. With the rapid development in science and technology, the advancement in sonar systems has increased, resulting in a decrement in underwater casualties. The sonar signal processing and automatic target recognition using sonar signals or imagery is itself a challenging process. Meanwhile, highly advanced data-driven machine-learning and deep learning-based methods are being implemented for acquiring several types of information from underwater sound data. This paper reviews the recent sonar automatic target recognition, tracking, or detection works using deep learning algorithms. A thorough study of the available works is done, and the operating procedure, results, and other necessary details regarding the data acquisition process, the dataset used, and the information regarding hyper-parameters is presented in this article. This paper will be of great assistance for upcoming scholars to start their work on sonar automatic target recognition.
We report the experimental realization of an acoustic Chern insulator (ACI), by using an angular-momentum-biased resonator array with the broken Lorentz reciprocity. High Q-factor resonance of the constituent rotors is leveraged to reduce the required rotation speed. ACI is a new topological acoustic system analogous to the electronic quantum Hall insulator, based on an effective magnetic field. Experimental results show that the ACI featured with a stable and uniform metafluid flow bias supports one-way nonreciprocal transport of sound at its edges, which is topologically immune to various types of defects. Our work opens up opportunities for exploring unique observable topological phases and developing topological-insulator-based nonreciprocal devices in acoustics.
Metamaterials are attracting increasing interest in the field of acoustics due to their sound insulation effects. By periodically arranged structures, acoustic metamaterials can influence the way sound propagates in acoustic media. To date, the design of acoustic metamaterials relies primarily on the expertise of specialists since most effects are based on localized solutions and interference. This paper outlines a deep learning-based approach to extend current knowledge of metamaterial design in acoustics. We develop a design method by using conditional generative adversarial networks. The generative network proposes a cell candidate regarding a desired transmission behavior of the metamaterial. To validate our method, numerical simulations with the finite element method are performed. Our study reveals considerable insight into design strategies for sound insulation tasks. By providing design directives for acoustic metamaterials, cell candidates can be inspected and tailored to achieve desirable transmission characteristics.
Antonio Bevilacqua, Barbara Speranza, Daniela Campaniello
et al.
While probiotics have a wide range of beneficial properties, they can also negatively affect the taste or aroma of foods products by resulting in the phenomenon of post-acidification. Ultrasound (US) is a tool to modulate the metabolism of probiotic bacteria, counteracting post-acidification and improving the performance and functional properties of microorganisms without affecting their viability. The purpose of this paper was to evaluate the effect of 10 different combinations of power (20 and 40 %) and duration (2, 4, 6, 8 and 10 min) of US treatment on two functional strains of Lactiplantibacillus plantarum (c16 and c19) isolated from table olives, with the aim of understanding how, some of the main functional and technological traits (viability, acidification, growth profile under different conditions, antibiotic resistance, viability at pH 2.0 and 0.3 % bile salts), were affected. It was found that the effects were strain dependent, and the best results were obtained for strain c19 in the combinations at 20 % for 8 and 10 min and 40 % for 2 min, where an improvement in functional characteristics was found, with some effects on biofilm stability, inhibition of acidification, without adverse results on some technological properties.
In this paper, a semi-active nonlinear artificial intelligence compound controller for marine engines was developed to improve vibration reduction characteristics across a wide frequency range. A mathematical model was developed and investigated for two-stage vibration isolation systems (Virgin IslandsS) considering vertical, roll, and pitch motion. The passive mathematical model of the magnetorheological damper was also developed and integrated with the two-stage VIS. The passive numerical analysis was validated through the experimental investigation. Force transmitted from the engine to the base was evaluated on the validated model using four different strategies, that is, conventional passive, semi-active low, semi-active high, and semi-active controlled damper. In a semi-active–controlled damper, a mathematical model is developed for controlling the force by developing a nonlinear artificial intelligent compound controller (NAICC) using the algorithm of chaotic fruit fly and fuzzy logic control. The results show that the application of NAICC has a better isolating effect than the passive VIS over a broad spectrum of frequencies. By strengthening the control effect in the low-frequency resonance zone, marine engine vibration reduction performance was significantly enhanced.
Control engineering systems. Automatic machinery (General), Acoustics. Sound
Locust protein hydrolysates (LoProHs) pre-processed with microwave and ultrasonication were developed and evaluated for their potential for enhancing the quality of the stored meat emulsion (MEmul). Locust protein (LoPro) samples pre-processed with ultrasonication (Ult) or microwave (Mic) or with no treatment (Not) were hydrolysed with alcalase enzyme (3%). The microwave pre-processed (Mic-LoProHs) and ultrasonicated (Ult-LoProHs) hydrolysates showed significantly (P < 0.05) higher antioxidant [FRAP (ferric reducing antioxidant power) and ABTS and DPPH radical scavenging activities] and antimicrobial [minimum inhibitory concentration (MIC) and inhibitory halos (mm)] potential. The MEmul samples incorporated with Mic-LoProHs and Ult-LoProHs at the maximum level of 1.5% exhibited significantly (P < 0.05) improved results for all the quality parameters such as antioxidant potential (FRAP, ABTS and DPPH), protein oxidation (total carbonyl content), lipid stability, and microbial quality during refrigerated storage (4 ± 1 °C) of two-weeks compared to the control MEmul without any LoProHs. A positive (P < 0.05) impact of the LoProHs was found on the sensory quality of MEmul samples after one week of storage. The digestion simulation improved (P < 0.05) the antioxidant potential of the MEmul samples.
Varaha P. Sarvothaman, Vijay K. Velisoju, Janardhanraj Subburaj
et al.
Phenols are recalcitrant compounds that constitute the majority of organic contaminants in industrial wastewaters. Their removal at large scales require a combination of various processes to reach the desired discharge quality. An extensive body of work has already been published in the area of phenol removal from wastewater, however none of them have focussed on a truly ‘sensible’ approach for coupling advanced oxidation processes (AOPs). Rather, a higher removal efficiency was targeted by unduly complicating the process by combining multiple AOPs. The most influential AOP as the primary method typically driven by the nature of the pollutant should form the basis for a hybrid AOP followed by a complementary AOP to intensify the oxidation process. This strategy is lacking in current literature. We address this knowledge gap directly by systematically identifying the best hybrid process for ZnO mediated photocatalysis of phenol. Either a cavitation mediated pre-treatment of ZnO or cavitation-photocatalysis-peroxide based hybrid AOP was investigated. While the pre-treatment approach led to >25% increase in phenol oxidation compared to bare ZnO photocatalysis, the hydrodynamic cavitation-photocatalysis-peroxide based system was found to have a cavitational yield 5 times higher than its acoustic cavitation counterpart. A new phenomenon known as the ‘pseudo staggered effect’ was also observed and established in hydrodynamic cavitation mediated photocatalysis-peroxide hybrid process for the first time. While we demonstrated that cavitation is a truly ‘sensible’ choice to enhance photocatalysis, the nature of the pollutant under investigation must always be the key driver when designing such hybrid AOPs.
In this investigation, the combinations of exogenous pretreatment (melatonin or vitamin C) and contact ultrasound-assisted air drying were utilized to dry broccoli florets. To understand the influences of the studied dehydration methods on the conversion of glucoraphanin to bioactive sulforaphane in broccoli, various components (like glucoraphanin, sulforaphane, myrosinase, etc.) and factors (temperature and moisture) involved in the metabolism pathway were analyzed. The results showed that compared with direct air drying, the sequential exogenous pretreatment and contact ultrasound drying shortened the drying time by 19.0–22.7%. Meanwhile, contact sonication could promote the degradation of glucoraphanin. Both melatonin pretreatment and vitamin C pretreatment showed protective effects on the sulforaphane content and myrosinase activity during the subsequent drying process. At the end of drying, the sulforaphane content in samples dehydrated by the sequential melatonin (or vitamin C) pretreatment and ultrasound-intensified drying was 14.4% (or 26.5%) higher than only air-dried samples. The correlation analysis revealed that the exogenous pretreatment or ultrasound could affect the enzymatic degradation of glucoraphanin and the generation of sulforaphane through weakening the connections of sulforaphane-myrosinase, sulforaphane-VC, and VC-myrosinase. Overall, the reported results can enrich the biochemistry knowledge about the transformation of glucoraphanin to sulforaphane in cruciferous vegetables during drying, and the combined VC/melatonin pretreatment and ultrasound drying is conducive to protect bioactive sulforaphane in dehydrated broccoli.
Synthetic fiber is still considered the best sound absorptive material. However, due to the health concern of synthetic fiber usage, researchers are trying to find another viable alternative. A microperforated panel (MPP) is a promising alternative that relies on the concept of a Helmholtz resonator for sound absorption. MPP possessed excellent acoustic resistance and a considerable range of absorption bandwidth. In this paper, MPP made of natural fiber composite was fabricated and its acoustic absorption was measured using a two-microphone impedance tube method as per ISO 10534-2 standard. Later, the tensile strength of the fabricated acoustic absorbers was measured using an Instron Universal Testing Machine as per ASTM D638. The idea of employing additive manufacturing, better known as the 3D printing technique, is proposed to produce lightweight MPP. The 3D printing technique provides design freedom and is less tedious in creating complex and light structures. The 3D printing technique has various important parameters, and infill density is one of the parameters. It was found that the reduction of infill density leads to a decrease of the MPP’s mass and thus, slightly affects the resonance frequency of the MPP, still within the mid-frequency spectrum. It was also noted that the increment of air gap thickness leads to the shifting of MPP’s resonance frequency to a lower frequency range. The tensile strength of the 3D printed samples decreases with a decrease in infill density. A sample with an infill density of 100% has the highest tensile strength of 22 MPa, and a sample with an infill density of 20% has the lowest tensile strength of 12 MPa.
Mitra Aliabouzar, Oliver D. Kripfgans, William Y. Wang
et al.
Acoustically-responsive scaffolds (ARSs), which are fibrin hydrogels containing monodispersed perfluorocarbon (PFC) emulsions, respond to ultrasound in an on-demand, spatiotemporally-controlled manner via a mechanism termed acoustic droplet vaporization (ADV). Previously, ADV has been used to control the release of bioactive payloads from ARSs to stimulate regenerative processes. In this study, we used classical nucleation theory (CNT) to predict the nucleation pressure in emulsions of different PFC cores as well as the corresponding condensation pressure of the ADV-generated bubbles. According to CNT, the threshold bubble radii above which ADV-generated bubbles remain stable against condensation were 0.4 µm and 5.2 µm for perfluoropentane (PFP) and perfluorohexane (PFH) bubbles, respectively, while ADV-generated bubbles of any size in perfluorooctane (PFO) condense back to liquid at ambient condition. Additionally, consistent with the CNT findings, stable bubble formation from PFH emulsion was experimentally observed using confocal imaging while PFO emulsion likely underwent repeated vaporization and recondensation during ultrasound pulses. In further experimental studies, we utilized this unique feature of ADV in generating stable or transient bubbles, through tailoring the PFC core and ultrasound parameters (excitation frequency and pulse duration), for sequential delivery of two payloads from PFC emulsions in ARSs. ADV-generated stable bubbles from PFH correlated with complete release of the payload while transient ADV resulted in partial release, where the amount of payload release increased with the number of ultrasound exposure. Overall, these results can be used in developing drug delivery strategies using ARSs.