AI-Driven and Data-Driven Modelling in Acoustics and Vibration
A special issue of Modelling (ISSN 2673-3951).
Deadline for manuscript submissions: 30 June 2026 | Viewed by 182
Special Issue Editor
Interests: machine learning for modal analysis; surrogate modelling for vibro-acoustic simulations; AI-enhanced sensor fusion; hybrid physics-informed neural networks; applications in automotive, aerospace, civil, marine, biomedical and industrial domains
Special Issue Information
Dear Colleagues,
The integration of Artificial Intelligence into computational modeling is proving to revolutionize the field of Acoustics and Vibrations. The present Special Issue for the Modelling Journal aims at inviting cutting-edge contributions that would explore how AI-driven and data-driven approaches can reshape the analysis and prediction, but also the control of vibrational and acoustic phenomena in engineering systems. This Special Issue will aim at showcasing the transformative potential of intelligent modeling, from deep learning models that can include complex nonlinear dynamics to data-driven techniques that would enhance real-time diagnostics and noise mitigation.
We welcome original research, review articles, and case studies that demonstrate rigor and innovative applications across automotive, aerospace, civil, and industrial domains. Topics of interest include machine learning for modal analysis, surrogate modeling for vibro-acoustic simulations, AI-enhanced sensor fusion, and hybrid physics-informed neural networks.
This Special Issue will serve as a valuable resource for researchers, engineers, and practitioners seeking to harness AI and data science for smarter, more efficient acoustic and vibration solutions. All submissions will undergo a thorough peer-review process to ensure scientific quality and impact.
Join us in shaping the future of intelligent modeling and submit your work and contribute to this vibrant and rapidly evolving field.
Dr. Rostand B. Tayong
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Modelling is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence in acoustics
- data-driven vibration analysis
- machine learning for vibro-acoustics
- physics-informed neural networks
- surrogate modeling
- deep learning for structural dynamics
- hybrid modeling techniques
- AI-enhanced noise and vibration control
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