Young Editorial Board

Zheren Cai
School of Optoelectronic Engineering, Chongqing University, Chongqing, China.
Interests: Acoustic metamaterials; Underwater detection and sensing; Advanced smart sensing systems

Geng Chen
School of Energy and Environment, Southeast University, Nanjing, Jiangsu, China.
Interests: Thermoacoustics; Energy harvesting; Nonlinear acoustics

Xiaodong Cui
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, Shandong, China.
Interests: Acoustic seabed sediment classification; Benthic habitat interpretation; Underwater target recognition; Applications of multibeam bathymetry systems; Sonar image processing

Hongqing Dai
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China.
Interests: Acoustic metamaterials; Acoustic tweezers; Acoustic manufacturing

Xiaofei Du
School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu, China.
Interests: Mechanical vibration; Acoustic black hole; Structural optimization design

Shiwang Fan
Department of Engineering Mechanics, Shijiazhuang Tiedao University, Shijiazhuang, Hebei, China.
Interests: Wave control; Acoustic and elastic metasurfaces; Ventilated sound insulation; Mechanical vibration; Metastructural optimization design

Cong Gao
School of Naval Architecture & Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China.
Interests: Structural vibration; Acoustic; Experiment; Dynamic analysis

Wenbo Han
Marine Engineering College, Dalian Maritime University, Dalian, Liaoning, China.
Interests: Surface acoustic wave; Microfluidics; Fluid mechanics; Acoustic particle manipulation; Fault diagnosis for marine and offshore equipment

Chenxue Hou
State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau; Institute of Microelectronics, University of Macau, Macau, China.
Interests: Piezoelectric transducer; Impedance matching; Ultrasonic energy transfer circuits and applications

Xudong Li
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang, China.
Interests: Underwater noise; Electromagnetic noise; Acoustic boundary element method; Vibro-acoustic coupling

Zhaoxi Li
Faculty of Integrated Circuits, Xidian University, Xi'an, Shaanxi, China.
Interests: Ultrasonic field control and acoustic wave propagation; Acoustic metasurfaces and acoustic holography; Piezoelectric ultrasonic transducers and arrays; Ultrasonic sensing, measurement, and imaging; Ultrasonic wireless power transfer and acoustic communication

Linda Liang
School of Civil Engineering and Architecture, Guangxi University, Nanning, Guangxi, China.
Interests: Architectural acoustics; Psychoacoustics; Automotive acoustics; Numerical simulation; Speech intelligibility

Jingui Qian
School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei, Anhui, China.
Interests: Acoustic MEMS; Acoustofluidics; Flexible ultrasonic

Hao Sun
College of Artificial Intelligence, Nankai University, Tianjin, China.
Interests: Acoustic manipulation; Chladni plate-based acoustic manipulation; Robotics

Xinhao Sun
The Shaanxi Key Laboratory of Integrated Circuits and System, Faculty of Integrated Circuit, Xidian University, Xi'an, Shaanxi, China.
Interests: Piezoelectric composites; High-temperature piezoelectric ultrasonic transducers; Array ultrasonic transducers for medical applications and non-destructive testing

Zhaoyong Sun
School of Mechanical and Electrical Engineering, Beijing Institute of Graphic Communication, Beijing, China.
Interests: Acoustic metamaterials; Vibration and noise control; Flexural wave; Ultrasonic transducer; Ultrasonic imaging; Air coupled ultrasonics

Tianquan Tang
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Interests: Computational acoustics and wave propagation in complex media; Acoustic radiation forces and torques, and particle dynamics; Ultrasonic acoustic tweezers and intelligent particle manipulation; Machine learning for acoustic design and noise control

Zhiwei Wan
School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Interests: Vibration control; Acoustic black hole; Model updating

Xingyuan Wang
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, Heilongjiang, China.
Interests: Underwater operation equipment; Ultrasonic measurement of contact conditions; Development of ultrasonic measurement instruments

Tao Yang
Chair of Vibroacoustics of Vehicles and Machines, Department of Engineering Physics and Computation, TUM School of Engineering and Design, Technical University of Munich, Boltzmannstrasse 15, 85748 Garching, Germany.
Interests: Acoustic metamaterials and metasurfaces; Porous and fibrous acoustic materials; Sound absorption and noise control; Acoustic material characterization and modeling; Machine learning for acoustic material design and optimization

Yuchen Zang
Institute of Acoustics, School of Physics and Technology, Nanjing Normal University, Nanjing, Jiangsu, China.
Interests: Acoustic manipulation and analysis of acoustic radiation force and torque; Acoustic levitation and analysis of dynamics for suspended particles; Acoustic cavitation and analysis of bubble dynamics in liquids; Reciprocity theorems in acoustics and relevant applications

Dadi Zhang
Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Interests: Indoor environmental quality (IEQ); Acoustic comfort & occupant behavior; Personalized control and occupant-centric building design; Healthy & sustainable educational buildings

Yongou Zhang
School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan, Hubei, China.
Interests: Hydrodynamic noise and noise control; Flow-acoustic coupling; Computational methods; Underwater sound propagation and scattering

Rui Zhong
College of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan, China.
Interests: Nonlinear structural dynamics; Vibro-acoustic analysis and control of composite structures; Structural vibration control and optimization

Fulin Zhou
School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Interests: Underwater acoustics; Vibration and noise engineering

Editor-in-Chief

Prof. Jun Yang

Institute of Acoustics, Chinese Academy of Sciences, China

ISSN

1541-0161 (Print)

2693-1443 (Online)

Publication Frequency

Bi-monthly

Indexing

Web of Science Coverage

Emerging Sources Citation Index (IF 4.2, Q1)

Elsevier Solutions

Scopus (2025 CiteScore 2.0);

Portico, etc.

About the Publisher

Academic Publishing insists on taking academic exchange and publication as the main line, carrying out comprehensive management based on science and technology, and fully exploring excellent international publishing resources. Within 5 years, it will form a strategic framework and scale with science (S), technology (T), medicine (M), education (E), and humanities and arts (H) as the main publishing fields. Academic Publishing is headquartered in Singapore and based in Malaysia, with the United States and China providing the main scientific and academic resources. At the same time, it has established long-term good cooperative relations with other publishing companies, scientific research communities, and academic organizations in more than a dozen countries and regions. Academic Publishing uses English and Chinese as its main publishing languages, mainly publishing books, journals, and conference papers in print and online. The vast majority of publications follow the international open access policy, providing stable and long-term quality and professional publications. With the joint efforts of the expert team and our professional editorial team, our publications will gradually be indexed by international databases in stages to provide convenient and professional retrieval for various scholars. At the same time, manuscripts we accept will be subject to the peer review principle, and cutting-edge and innovative research articles will be preferentially accepted for peer reference and discussion. All kinds of our publications are welcome for peer to contribute, access, and download.

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Volume Arrangement

Featured Articles

New scaling of critical damping and reduced frequency for mechanically excited systems

This paper introduces a universal framework for understanding the vibration responses of systems subjected to harmonic excitation. By examining a simplified cylinder-spring-damper model, the study refurbishes traditional scaling methods for the excitation frequency ratio and critical damping ratio. The findings indicate that in damped systems, the maximum amplitude of vibration does not align with the natural frequency. This observation leads to the introduction of a new scaling method for reduced frequency. This new approach aligns resonance peaks at the new reduced velocity of 1.0 across different damping ratios, providing a consistent characterization of vibration behavior. A new critical damping ratio of 0.707 is identified for an excited system as opposed to the traditional damping ratio of 1.0 for an unexcited system. Key properties such as maximum amplitude, phase lag, bandwidth, and quality factor are analyzed, demonstrating that the proposed reduced frequency and critical damping ratio effectively capture the dynamics of both damped and undamped excited systems. The findings offer significant insights for practical applications in engineering and various scientific fields.

Ultrasonic wave velocity as a universal metric for defect detection in timber structures: A case study on Japanese cedar wood (Cryptomeria japonica)

This study makes significant contributions to the field of ultrasonic testing (UT) by offering a novel approach to the identification of artificially introduced defects within Japanese cedar wood (Cryptomeria japonica). The findings are of particular relevance for the heritage conservation and construction sectors, where non-invasive defect detection is paramount. The study establishes a robust framework for assessing the structural integrity of timber by correlating ultrasonic wave velocity reductions with defect size and distribution. Big-sized defects led to more substantial decreases in wave velocity. The study establishes a robust framework for assessing the structural integrity of historical timber by correlating ultrasonic wave velocity reductions with defect size and distribution. This framework has the potential to be applicable to diverse wood species and defect types.

Vehicle structural road noise prediction based on an improved Long Short-Term Memory method

The control of vehicle interior noise has become a critical metric for assessing noise, vibration, and harshness (NVH) in vehicles. During the initial phases of vehicle development, accurately predicting the impact of road noise on interior noise is essential for reducing noise levels and expediting the product development cycle. In recent years, data-driven methods based on machine learning have gained significant attention due to their robust capability in navigating complex data mapping relationships. Notably, surrogate models have demonstrated exceptional performance in this domain. Numerous researchers have integrated diverse intelligent algorithms into the study of vehicle noise, leveraging advantages such as the elimination of precise modeling requirements, extensive solution space exploration, continuous learning from data, and robust algorithmic versatility. However, in NVH engineering applications, data-driven models face inherent limitations, particularly in interpretability and stability. To address these issues, this paper introduces an improved Long Short-Term Memory (LSTM) network that combines knowledge and data. Inspired by the physical information neural network concept, this approach incorporates values calculated through empirical formulas into the neural network as constraints. Comparative assessments with traditional LSTM networks highlight the advantages of this deep learning model. By integrating empirical formulas constraints, the model not only enhances interpretability but also achieves robust generalization with fewer data samples. The proposed method is validated on a specific vehicle model, showing significant improvements in prediction accuracy and efficiency.