Advanced Structural Assessment: From Computational Mechanics to AI-Enabled Digital Twins

Dear Colleagues,

We are pleased to invite submissions to a forthcoming Special Issue of Buildings, entitled “Advanced Structural Assessment: From Computational Mechanics to AI-Enabled Digital Twins”.

The increasing use of hybrid materials in buildings and infrastructure—including combinations of concrete, steel, timber, fibre-reinforced polymers and other advanced materials—has created new opportunities and challenges for structural assessment, monitoring and maintenance. AI-enabled digital twins offer powerful tools for integrating structural health monitoring data, numerical modelling, artificial intelligence and predictive analytics to support more accurate, efficient and reliable decision-making throughout the asset lifecycle.

This Special Issue aims to bring together recent advances in the development and application of digital twin technologies for the assessment of structures incorporating hybrid materials. Contributions are welcome from researchers and practitioners working across structural engineering, materials science, artificial intelligence, sensing technologies, and digital construction.

Topics of interest include, but are not limited to, the following:

• AI-enabled assessment
• Structural health monitoring and sensor technologies
• Machine learning and deep learning for damage detection and prediction
• Digital modelling and simulation of multi-material structural systems
• Reliability assessment, uncertainty quantification and risk-informed decision-making
• Life-cycle assessment, durability and performance prediction
• Structural deterioration, damage diagnosis and remaining-life estimation
• Data assimilation and real-time condition assessment
• Physics-informed machine learning and hybrid modelling approaches
• BIM, IoT and cloud-based platforms for structural digital twins
• Experimental validation, case studies and field applications
• Resilience, sustainability and maintenance optimization of hybrid structures

We invite researchers, academics, engineers and industry professionals to submit original research articles, review papers and technical contributions that address the theory, methodology, development or practical application of AI-enabled digital twins for hybrid-material structures. Further information regarding the submission deadline, manuscript preparation requirements and submission process will be provided through the official Buildings journal platform.

We would be grateful if you could share this call with relevant colleagues and research networks. We look forward to receiving your valuable contributions.

Dr. Jianhu Shen
Dr. Tolga Yilmaz
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings 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.