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Application of Nondestructive Testing in the Structural Health Monitoring of Industrial Materials

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Materials Science and Engineering".

Deadline for manuscript submissions: 20 January 2026 | Viewed by 31

Special Issue Editors


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Guest Editor
Department of Engineering, University of Perugia, Polo Scientifico Didattico di Terni, Via di Pentima 4, 05100 Terni, TR, Italy
Interests: nondestructive testing; signal processing; pulse compression; spintronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nondestructive testing (NDT) and structural health monitoring (SHM) are critical for ensuring the integrity, safety, and longevity of industrial materials across sectors such as aerospace, energy, and manufacturing. As aging infrastructure and complex engineering systems demand proactive maintenance, NDT techniques (e.g., ultrasonic testing, thermography, and eddy currents) enable the early detection of defects without compromising material performance. Meanwhile, SHM integrates sensor networks, data analytics, and AI to continuously assess structural conditions, reducing downtime and operational risks. This research area bridges materials science, mechanical engineering, and digital innovation, addressing global challenges in sustainability, safety, and cost efficiency.

We are pleased to invite you to contribute to this Special Issue. This Special Issue seeks to showcase cutting-edge advancements that enhance the reliability and resilience of industrial assets.

This Special Issue aims to foster interdisciplinary dialog by highlighting novel NDT methodologies, SHM systems, and real-world applications. Contributions should emphasize technical innovation, validation using case studies, and alignment with industry standards.

In this Special Issue, original research articles and reviews are welcome. The main focus of the articles includes, but not strictly limited to, the following areas:

  • Advanced NDT techniques for defect characterization (e.g., phased array ultrasonics, infrared thermography);
  • IoT-enabled SHM systems for real-time structural assessments;
  • Machine learning and AI in NDT data interpretation;
  • Hybrid SHM approaches combining NDT and sensor networks;
  • Digital twins for the predictive maintenance of industrial components;
  • NDT for composite materials and additive manufacturing;
  • Standardization and certification in industrial SHM.

Prof. Pietro Burrascano
Dr. Mario Versaci
Guest Editors

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. Applied Sciences 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 2400 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

  • nondestructive testing (NDT)
  • structural health monitoring (SHM)
  • industrial materials
  • machine learning for NDT
  • IoT in SHM
  • composite materials
  • digital twins in SHM

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Published Papers

This special issue is now open for submission.
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