Artificial Intelligence in Building Structural Performance and Safety
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 80
Special Issue Editors
Interests: intelligent computing; physical AI; digital twins; AI4S; data fusion; structural optimization; inverse analysis
Interests: intelligent inspection; structural health monitoring; temperature effect; predictive maintenance; digital twins; virtual construction preassembly
Interests: structural health monitoring; bridge inspection; structural performance evaluation; AI‑accelerated simulation and optimization; steel-concrete composite structures
Special Issue Information
Dear Colleagues,
Recent advances in artificial intelligence—spanning machine learning, deep learning, physics‑informed modeling, and probabilistic inference—are reshaping how building structures are designed, analyzed, monitored, and safeguarded across their life cycle. This Special Issue, “Artificial Intelligence in Building Structural Performance and Safety”, invites high‑quality research and reviews that leverage AI to accelerate structural computation and design, enable data‑driven and hybrid modeling, and deliver reliable monitoring, diagnosis, and decision support for safety‑critical applications. Topics include AI‑accelerated simulation and optimization; inverse problems for parameter identification and model updating; structural health monitoring and damage detection with multi‑source sensing; digital twins and real‑time safety assessment; uncertainty quantification, reliability analysis, and risk‑informed decision‑making; predictive maintenance and life‑cycle performance; resilience to extreme events and multi‑hazard scenarios; and explainable, trustworthy AI for code compliance and engineering practice. We particularly encourage contributions presenting benchmarks, open datasets, replicable workflows, and translational case studies that bridge academia and industry. By assembling cutting‑edge methods and practical implementations, this Special Issue aims to chart the state of the art and provide actionable pathways to enhance the performance, robustness, and safety of building structures.
Dr. Chen Wang
Dr. Yufei Liu
Dr. Jing-Lin Xiao
Dr. Linghan Song
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-blind 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.
Keywords
- building structures
- AI‑accelerated simulation and optimization
- structural health monitoring
- digital twins
- physics‑informed machine learning
- inverse analysis
- uncertainty quantification
- risk‑aware decision‑making
- building resilience
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