Asymmetric acoustic wave propagation is important for control and manipulation of the acoustic wave signals in various devices. However, previous approach to find optimal asymmetric acoustic transmission (AAT) is through repeatedly adjusting the geometrical parameters, thus causing time-consuming. Here we propose a study on the multi-objective optimization of the AAT, aiming to achieve the widest working frequency range (fr) and the highest transmittance peak (η) with regard to the design variables. For this purpose, the Radial Basis Function (RBF) neural work and finite element (FE) method are applied to obtain the valuable data in the procedure. Furthermore, local sensitivity analysis of design parameters on the fr and η are analyzed. Ultimately, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is adapted for getting the Pareto-optimal solutions. The optimization results show great improvement for the overall performance of the AAT, which could be potentially significant in designing various sound devices.
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Sci Rep
January 2025
Physics Department, Faculty of Science, TH-PPM Group, Beni-Suef University, Beni Suef, 62514, Egypt.
In this paper, the transfer matrix method is used to study the dispersion of acoustic waves in a finite periodic expansion chambers system with a defect. Two kinds of structures are studied. The first one is formed by expansion chambers, which are symmetrical concerning a defect, and the second one is asymmetrical with a defect.
View Article and Find Full Text PDFLight Sci Appl
January 2025
Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, 19716, USA.
Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity.
View Article and Find Full Text PDFJ Acoust Soc Am
December 2024
Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Ministry of Education, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361005, China.
Although air sinuses are prevalent in odontocetes and are an integral component of their sound reception system, the acoustic function of these air-filled structures remains largely unknown. To address this, we developed a numerical model using computed tomography data from a Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) to investigate the role of the air sinuses in sound reception. By comparing sound reception characteristics between model cases with and without the air sinuses, we found that the air sinuses improved sound reception directivity.
View Article and Find Full Text PDFMicrosyst Nanoeng
December 2024
Key Laboratory of MEMS of the Ministry of Education, Southeast University, Nanjing, 210096, China.
Piezoelectric resonance sensors are essential to many diverse applications associated with chemical and biological sensing. In general, they rely on continuously detecting the resonant frequency shift of piezoelectric resonators due to analytes accreting on their surfaces in vacuum, gas or fluid. Resolving the small analyte changes requires the resonators with a high quality factor.
View Article and Find Full Text PDFEur J Neurosci
January 2025
Experimental Otorhinolaryngology, Department of Neurosciences, KU Leuven - University of Leuven, Leuven, Belgium.
Binaural unmasking is a remarkable phenomenon that it is substantially easier to detect a signal in noise when the interaural parameters of the signal are different from those of the noise - a useful mechanism in so-called cocktail party scenarios. In this study, we investigated the effect of binaural unmasking on neural tracking of the speech envelope. We measured EEG in 8 participants who listened to speech in noise at a fixed signal-to-noise ratio, in two conditions: one where speech and noise had the same interaural phase difference (both speech and noise having an opposite waveform across ears, SπNπ), and one where the interaural phase difference of the speech was different from that of the noise (only the speech having an opposite waveform across ears, SπN).
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