Digital Twins for Civil and Industrial Structures: Data-Physics Fusion-Driven Methods for Hazard Risk Management
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 148
Special Issue Editors
Interests: damage mechanics; material degradation; NDT; concrete structure; acoustic emission; elastic wave theory; 3D image analysis; deep learning
Interests: NDT of civil infrastructure; acoustic emission; ultrasonic; impact-echo; infrared thermography testing; damage detection and evaluation in concrete structures; structural monitoring
Special Issue Information
Dear Colleagues,
The damage management of aging civil and architectural structures requires innovative approaches that integrate real-world monitoring with virtual simulations. Digital Twin (DT) technology, combining physics-based models with data-driven approaches, offers transformative solutions for in-service structures throughout their lifecycle-from normal operation to disaster response and recovery. This Special Issue explores comprehensive applications of DT technology: (1) 3D shape reconstruction and internal condition detection integrating visible and invisible infrastructure domains using advanced NDT methods including satellite remote sensing, UAV-LiDAR, acoustic techniques, and underwater sensing; (2) physics-based structural simulation and seismic analysis coupled with real situation for performance assessment; (3) hydraulic performance evaluation including flow analysis, leakage detection of pipeline water level management, and flood simulation for pump stations; (4) machine learning and AI for predictive maintenance, anomaly detection, knowledge discovery, and automated decision-making; (5) disaster management systems integrating rapid damage assessment, traffic management for emergency response, and recovery planning. We welcome original research, comprehensive reviews, and case studies demonstrating practical implementations in civil, architectural and industrial structures, such as buildings, bridges, roads, dams, headworks, channels, pipelines, and pump stations, etc. This Special Issue aims to establish DT as an essential framework for sustainable and resilient infrastructure management.
Prof. Dr. Tetsuya Suzuki
Prof. Dr. Ninel Alver
Dr. Kentaro Ohno
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
- digital twin
- civil, architectural, and industrial structures
- data-driven
- seismic analysis
- damage evaluation
- artificial intelligence
- non-destructive testing
- automation
- physical-based approach
- operation and maintenance
- post-disaster
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
