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Advances in Engineering Structure Inspection, Monitoring Technologies, and Post-Disaster Diagnosis, Maintenance, and Operation

This special issue belongs to the section “Building Materials, and Repair & Renovation“.

Special Issue Information

Dear Colleagues,

Presently, next-generation information technologies (artificial intelligence, big data, the Internet of Things, 3D printing) are propelling the structural engineering field towards profound digitalization and intelligent transformation. To accelerate the intelligent development of structural engineering, this Special Issue focuses on three cutting-edge directions: intelligent structural design, intelligent structural monitoring and inspection, and intelligent enhancement of structural disaster prevention and mitigation. It aims to provide an innovative engine for the high-quality development of the civil infrastructure industry and contribute to the construction of an intelligent building ecosystem.

This Special Issue aims to showcase the latest research findings and recent advancements in non-destructive evaluation (NDE) and structural health monitoring (SHM) technologies, alongside intelligent algorithms tailored for structural engineering applications. We cordially invite high-quality original research papers and review articles covering, but not limited to, the following themes:

Intelligent operation, maintenance, and diagnosis of structures

UAV–robot collaborative operations and AI-based damage prediction

Deep-learning-driven damage identification

Digital twins and predictive maintenance

Multi-source information fusion and system integration

Intelligent operation, maintenance, and diagnostics for railway engineering structures

Intelligent structural design and construction

Green buildings and sustainable development

Smart materials and intelligent structural systems

Multi-hazard effects and disaster resilience of structures

Structural seismic isolation, vibration reduction, and control

Digital intelligence empowerment of structural testing and structural digitalization enhancement

Physics-informed neural networks (PINN) for solving structural dynamic responses

Urban renewal

Smart cities

Building operation and maintenance

Living preservation of historic buildings

Others

Dr. Lingkun Chen
Dr. Qing Zeng
Dr. Qikai Sun
Dr. Tao Wang
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

  • structural damage identification
  • physical information data mining
  • computer-vision-based structural health monitoring
  • digital twin
  • multi-source information fusion
  • intelligent operation, maintenance and diagnostics
  • intelligent design and construction
  • disaster resilience
  • UAV-robotics
  • physics-informed neural networks (PINN)
  • operation and maintenance
  • urban renewal
  • green building

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Published Papers

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Buildings - ISSN 2075-5309