Machine Learning Applications in the Design and Analysis of Composite Materials
A special issue of Journal of Composites Science (ISSN 2504-477X). This special issue belongs to the section "Composites Modelling and Characterization".
Deadline for manuscript submissions: 10 March 2026 | Viewed by 19
Special Issue Editor
Special Issue Information
Dear Colleagues,
You are invited to contribute to this upcoming Special Issue of the Journal of Composites Science, titled “Machine Learning Applications in the Design and Analysis of Composite Materials”. This Special Issue aims to gather original research and review articles focused on the integration of machine learning techniques with theoretical, numerical, and experimental approaches in the field of composite materials. Topics may include, but are not limited to, property prediction, damage detection, optimization, and performance enhancement of fiber-reinforced and novel composite structures.
As composite materials continue to play a pivotal role in aerospace, automotive, civil, and biomedical engineering, there is a growing need for intelligent, data-driven approaches to accurately characterize, predict, and optimize their behavior. The integration of machine learning with computational mechanics, material modeling, and experimental data offers a powerful framework to revolutionize composite analysis and design. This Special Issue aims to achieve the following: (1) develop machine learning models for accurate prediction of mechanical properties of composite materials; (2) investigate and classify failure mechanisms through data-driven techniques; (3) apply intelligent algorithms for damage detection and health monitoring; and (4) explore optimization strategies for material architecture and performance enhancement. Contributions that demonstrate practical, interpretable, and reliable machine learning solutions for these aims are especially encouraged. Through this Special Issue, we seek to advance the role of artificial intelligence in the modeling, failure analysis, and performance optimization of composite materials, paving the way for more efficient and innovative engineering solutions.
We look forward to receiving your valuable contributions to this Special Issue.
Dr. Gyula Varga
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. Journal of Composites Science is an international peer-reviewed open access monthly 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 1800 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
- composite materials
- machine learning
- mechanical properties prediction
- structural damage detection
- optimization
- fatigue life prediction and analysis
- data-driven design
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