Computational Intelligence and Optimization for Structural Health Monitoring
A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".
Deadline for manuscript submissions: 31 August 2027 | Viewed by 31
Special Issue Editors
Interests: structural health monitoring; damage identification; optimization algorithms; computer vision
Interests: structural health monitoring and safety assessment; structural disaster prevention and mitigation; intelligent operation and maintenance of engineering structures
Special Issues, Collections and Topics in MDPI journals
Interests: structural health monitoring; big data mining and analysis of infrastructure monitoring; artificial intelligence algorithms
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Structural health monitoring (SHM) has become an essential component in ensuring the safety, resilience and serviceability of critical infrastructure systems, including bridges, railways, buildings, tunnels and offshore platforms. With the increasing demand for intelligent infrastructure and lifecycle management, traditional SHM approaches are facing limitations in handling large-scale sensing data, complex structural behaviors and uncertain environmental and operational conditions. In particular, challenges arise in extracting reliable damage-sensitive features, establishing robust condition assessment models and achieving accurate prognosis under limited or noisy data. Recent advances in computational intelligence and optimization techniques, such as machine learning, deep learning and evolutionary algorithms, effectively support automated damage detection, localization, quantification and the predictive maintenance of structures.
This Special Issue aims to provide a platform for presenting recent developments in computational intelligence and optimization methods tailored for SHM applications. Contributions are expected to address theoretical developments, methodological innovations and practical implementations that improve the accuracy, robustness and efficiency of SHM systems.
Specific methods and fields of applications include, but are not limited to, the following:
- Data-driven and physics-informed machine learning for structural damage detection and assessment
- Optimization methods for sensor placement, model updating and parameter identification
- Signal processing and feature extraction using computational intelligence techniques
- Multi-source data fusion and heterogeneous sensing integration
- Autonomous inspection systems (e.g., UAVs, robotics) combined with intelligent algorithms
- SHM applications in bridges, railways, tunnels, buildings and energy infrastructure
- Uncertainty quantification and probabilistic approaches in SHM
- Edge computing and real-time monitoring systems for large-scale infrastructure
Dr. Guangcai Zhang
Dr. Chunfeng Wan
Dr. Zhenwei Zhou
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. Computation is an international peer-reviewed open access monthly 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 1800 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
- damage detection
- model updating
- computational intelligence techniques
- data fusion
- optimization algorithms
- digital twin
- uncertainty quantification
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