Theory and Applications of Engineering Materials in Advanced Engineering
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".
Deadline for manuscript submissions: 20 September 2026 | Viewed by 23
Special Issue Editors
Interests: structural dynamics; seismic design; smart materials; structural experiments; numerical analysis; structural optimization; urban road-to-freeway interchange; navigation map
Special Issues, Collections and Topics in MDPI journals
Interests: structural dynamics; damping models; seismic analysis; multifunctional materials; numerical analysis; structural optimization and performance evaluation
Special Issue Information
Dear Colleagues,
A synergistic integration of data-driven Artificial Intelligence/Machine Learning (AI/ML) and physics-based mechanics models is catalyzing a paradigm shift in modeling, assessing, and optimizing performance of modern materials and structures. By combining the powerful learning capabilities of the former with the solid theoretical foundation of the latter, this integrated strategy enables more accurate predictions, smarter designs, and more efficient operations. This Special Issue focuses on applications and innovations of these cutting-edge technologies in the fundamental theory, numerical computation, and experimental investigation of engineering materials and structures.
The scope and topics of this Issue may include, but are not limited to, the following: machine learning; deep learning; structural dynamic models; seismic analysis; structural performance prediction and optimization; the damping characteristics of multifunctional materials; the fatigue performance of structures; structural design and optimization; the experimental and numerical analysis of modal parameter identification; and the uncertainty quantification of dynamic performance.
We welcome original research papers, review articles with new insights and perspectives on pioneering developments and their applications, including case studies in civil engineering. Authors who are experts in these fields of study are invited and encouraged to submit their contributions to this Special Issue.
Prof. Dr. Dongwei Wang
Dr. Panxu Sun
Guest Editors
Dr. Zhiju Chen
Guest Editor Assistant
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. Materials 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 2600 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
- structural dynamics
- seismic performance of engineering structures
- damping characteristics of materials
- multifunctional materials
- fatigue performance of structures
- structural design and optimization
- machine learning
- structural performance prediction and optimization
- modal parameter identification
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