Machine Learning Applications to Vibration Problems

A special issue of Vibration (ISSN 2571-631X).

Deadline for manuscript submissions: 20 March 2025 | Viewed by 56

Special Issue Editor


E-Mail Website
Guest Editor
Department of Aerospace Engineering, San Jose State University, San Jose, CA 95192, USA
Interests: finite elements; machine learning; mobile sensors; response monitoring; stress reconstruction; safety; structural health monitoring

Special Issue Information

Dear Colleagues,

Machine learning and data-driven algorithms are promising approaches in analysing the dynamic behaviour of a mechanical system. These algorithms have the ability to automatically generate a model using data from past experiences; the number of applications is extensive and includes self-driving cars, high-frequency trading, house price estimation, search engines, bioinformatics, chemistry, and material science, for which large amounts of data are available. Cases involving large amounts of variables, high levels of uncertainty, and rapid changes in behaviour are among the typical scenarios. Although machine learning algorithms date back to the 1950s, their application for analysing the mechanical behaviour of dynamic systems has only been the focus of research for the past 10 years and is now progressing very quickly.

This Special Issue aims to collect the latest research findings in the field and invites the submission of articles related (but not limited) to the following topics:

  • Surrogate machine learning approaches for the stress analysis of vibrating systems;
  • Data-driven approaches for structural health monitoring;
  • Machine learning approaches for sensor optimization in vibration analysis;
  • Data-driven real-time stress predictions;
  • Machine learning applications in relation to finite element analysis for vibrating systems;
  • Uncertainty quantification in the stress analysis of machine learning modelling;
  • Data-driven modal analysis;
  • Physics-informed machine learning approaches for vibrating systems.

Dr. Maria Chierichetti
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Vibration is an international peer-reviewed open access quarterly 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 1600 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

  • machine learning approaches
  • data-driven modelling
  • stress analysis
  • surrogate models
  • structural health monitoring
  • finite elements
  • modal analysis

Published Papers

This special issue is now open for submission.
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