Advances and Machine Learning Approaches for the Health Monitoring and Integrity Assessment of Structures
A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Physics and Theory".
Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 1885
Special Issue Editors
Interests: product design; structural health monitoring (SHM); composite materials; finite element analysis (FEA)
Special Issues, Collections and Topics in MDPI journals
Interests: structural health monitoring; finite element analysis; structural behavior; mechanical design; crashworthiness
Special Issues, Collections and Topics in MDPI journals
2. Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology (NTNU), Richard Birkelands vei 2B, 7491 Trondheim, Norway
Interests: Structural Health Monitoring (SHM); composite materials; organic materials; machine learning; conservation and preservation
Interests: Structural Health Monitoring (SHM); composite materials; damage diagnosis; remaining useful life prediction; explainable AI; SHM reliability
Special Issue Information
Dear Colleagues,
Structural Health Monitoring (SHM) and damage diagnosis approaches have widely demonstrated their importance in assessing the integrity of damage-tolerant components. The integration of such technology for engineering structures leads to numerous benefits in terms of maintenance costs, repair operations, and carbon footprint reductions. Nevertheless, the acquired data must be rigorously processed in order to obtain reliable information about the structure’s actual state of health.
This Special Issue will report on the advancements in SHM and machine learning approaches to assess the performance and conditions of engineering structures through monitoring data by taking into account challenging environmental and operational environments, new sensing technologies, and novel data analysis under the theme of Industry 4.0. The results of theoretical, analytical, numerical, or experimental investigation can be presented. Review articles can be also proposed.
The key focus of this Special Issue is on SHM strategies for fibre-reinforced composite materials. Articles on advances and machine learning-based approaches for SHM for other families of materials (smart, organic, additively manufactured, etc.) are also highly appreciated.
Potential topics of interest for this Special Issue include but are not limited to:
- Machine learning algorithms and novel approaches for predicting unknown scenarios;
- Numerical methods for SHM systems simulation;
- Numerical and experimental investigations of damage detection and characterization;
- Novel damage detection and characterization algorithms;
- Novel signal and image processing algorithms for damage diagnosis and prognosis;
- Assessment of load-carrying capacity of pristine and damaged structures;
- Smart methods to enhance the durability of structures;
- Environmental and operational effects on SHM reliability;
- Novel multi-functional sensors for structural health monitoring;
- Structural Health Monitoring-informed maintenance management.
Dr. Donato Perfetto
Dr. America Califano
Dr. Alessandro De Luca
Dr. Nan Yue
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. Polymers 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 2700 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
- SHM systems
- damage detection
- composite materials
- organic materials
- additively manufactured materials
- data analysis
- machine learning
- structural analysis
- finite element modelling
- damage tolerance