AI-Driven Wind Engineering for Sustainable and Resilient Buildings
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".
Deadline for manuscript submissions: 30 April 2026
Special Issue Editors
Interests: AI in wind engineering; wind speed forecasting; wind-structure interaction
Interests: artificial intelligence technologies; wind tunnel testing; computational fluid dynamics
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; civil and structural engineering; risk assessment; surrogate modeling; uncertainty quantification and analysis
Special Issue Information
Dear Colleagues,
Thanks to the rapid development of artificial intelligence (AI) technologies, wind engineering for sustainable and resilient buildings has received significant global attention in recent years. AI-driven approaches have shown great potential in enhancing the analysis, design, and performance assessment of structures subjected to wind effects. Existing engineering applications have proven that integrating AI into wind engineering can provide powerful tools for high-rise, long-span, and other wind-sensitive structures.
To make full use of AI capabilities and improve the efficiency, safety, and sustainability of building design, it is both reliable and efficient to combine AI techniques with experimental, numerical, and data-driven wind engineering methods. Continuous innovative studies on AI-driven wind engineering are necessary to improve predictive accuracy, structural resilience, long-term performance, energy efficiency, and adaptability under extreme climate events.
This Special Issue will showcase high-quality original research articles on the latest developments of AI-driven wind engineering for sustainable and resilient buildings. The scope of the Special Issue includes (but is not limited to) AI-based wind load prediction, structural response modeling, data-driven optimization, digital twin applications, AI-enhanced wind tunnel testing, and machine learning integration for design and safety assessment. In addition, this Special Issue also provides space for review papers to provide insights into research status and development tendencies. We are pleased to invite you to contribute your invaluable articles to our Special Issue.
Dr. Dongqin Zhang
Prof. Dr. Gang Hu
Dr. Jize Zhang
Dr. Pengfei Lin
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. 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
- artificial intelligence
- data-driven modelling
- sustainable building design
- structural resilience
- wind-structure interaction
- smart cities
- urban wind environment
- extreme wind events
- computational fluid dynamics
- wind tunnel tests
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