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2. National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China

2. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
Structural Health Monitoring Based on Materials, Mathematical Methods, and Sensing Technology
Topic Information
Dear Colleagues,
Recent advances in materials, mathematical methods, and sensing technology have opened vast possibilities for the development of disruptive innovations in the field of structural health monitoring.
Nowadays, we can find SHM and its applications being used in various structures with very different requirements. The field of SHM involves a wide range of transdisciplinary areas, including various repair and construction materials, embedded and surface sensors and actuators, damage diagnosis and prognosis, signal and image processing, data interpretation, machine learning, data fusion, energy harvesting, etc. There has been a large and increasing volume of research on SHM based on materials, mathematical methods, and sensing technology. Structural health monitoring (SHM) and related research have gained significant importance for civil, mechanical, aerospace, and offshore structures as they present various cutting-edge achievements to share and promote the development and progress of structural health monitoring technology. However, new and advanced materials, mathematical methods, and sensing technology are not currently being presented and studied for discussion when considering present improvements in safety awareness and increased monitoring information. Thus, for the successful development of SHM using new materials for large and complex structures, techniques should be enhanced. In addition, mathematical methods for signal/data processing plays an important role in the implementation of SHM technologies.
Accurate and regionalized sensing technology for the massive amount of data generated through the long-term monitoring of large and complex structures (e.g., dams, bridges, embankments buildings, ships, aircrafts, wind turbines, pipes, etc.) has become an emerging challenge that needs to be addressed by the community. New ideas provide advanced frameworks and algorithms that can help to discover and model the performance and conditions of a structure through deep mining of materials, mathematical methods, and sensing technology. This Special Issue will publish study results and research papers that present innovative uses of materials, mathematical methods, and sensing technology for processing structural health monitoring. Additionally, we also encourage papers that provide comprehensive reviews of the literature on this topic. We cordially invite you to submit your classic and novel research for consideration. Suitable topics include:
- SHM for dams, bridges, embankments, aerospace, offshore infrastructures, etc.;
- Advanced materials for SHM technology in composite, steel, and concrete structures;
- Accurate and regionalized monitoring methods for different structures;
- Localised monitoring and damage detection;
- Various methods for solving the deployment problem of SHM technology;
- New data processing methods for SHM;
- General research for SHM in terms of materials, mathematical methods, and sensing technology;
- Other any relatively valuable researches about SHM.
Prof. Dr. Chongshi Gu
Prof. Dr. Lei Tang
Dr. Meng Yang
Topic Editors
Keywords
- structural health monitoring
- advanced material
- mathematical method
- damage detection
- sensing technology
- embedded and surface sensors and actuators
- composite structures
- steel structures
- reinforced concrete structures
- numerical simulation
- physical model
- optical fiber
Participating Journals
Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC |
---|---|---|---|---|---|
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Applied Sciences
|
2.5 | 5.3 | 2011 | 18.4 Days | CHF 2400 |
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Buildings
|
3.1 | 3.4 | 2011 | 15.3 Days | CHF 2600 |
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CivilEng
|
- | 2.8 | 2020 | 24.4 Days | CHF 1200 |
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Materials
|
3.1 | 5.8 | 2008 | 13.9 Days | CHF 2600 |
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Remote Sensing
|
4.2 | 8.3 | 2009 | 23.9 Days | CHF 2700 |
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Sensors
|
3.4 | 7.3 | 2001 | 18.6 Days | CHF 2600 |
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