Year: 2025
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Application of unsupervised AI-assisted acoustic wave sound analysis for non-destructive detection of steel corrosion induced deterioration
Reinforced concrete structures require reliable monitoring to ensure safety and efficient maintenance. Non-destructive testing methods such as tapping sound inspection are widely applied. However, the diagnosis results often depend on technical expert skill and experience. This study proposes an easy-to-use, AI-based evaluation method for tapping sounds using unsupervised deep learning. Laboratory tests were carried out on reinforced concrete beams with simulated steel bar corrosion. The method proposes an anomaly index that reflects corrosion progress and surface cracking. The results demonstrate that acoustic inspection with AI can support early damage detection and improve condition assessment of concrete structures.
Nopphanan Phannakham, Katsufumi Hashimoto, Yasuhiko Sato, and Naoshi Ueda
A multi-module deep learning framework with graph-based network and crack attention for tunnel lining crack segmentation from LiDAR point cloud
Cracks in railway tunnels threaten safety and require efficient monitoring. This study introduces PointCrackNet, a deep learning method that detects tunnel lining cracks directly from LiDAR point clouds. By combining graph-based convolution, attention mechanisms, and a crack-enhancement module, the model accurately captures fine crack details while maintaining global structural context. A tailored loss function addresses class imbalance and improves crack continuity. Tested on a large-scale LiDAR dataset from a real railway tunnel, PointCrackNet outperformed existing methods. The approach enables automated tunnel inspection and supports smart, data-driven infrastructure maintenance.
Shanpeng Liu, Koichi Isobe, Junling Si, Diyuan Li, and Daoju Ren
Construction and Building Materials Volume 494, 2025, 143383
Effects of Combined Deterioration of Steel Corrosion and Freeze-thaw Cycles on the Pull-out Behavior of Deformed Bars in Concrete
This study is the first to systematically investigate how loading sequence and cracking history affect the bond performance of deformed bars under the combined deterioration caused by steel corrosion and freeze–thaw action, a serious problem in concrete structures in cold regions. Through controlled experiments simulating realistic deterioration paths, the study clarified the influence of damage sequence on structural performance. In particular, it demonstrated that pre-existing cracks significantly accelerate deterioration by promoting moisture ingress and freeze–thaw damage. These findings highlight that considering damage history is essential for reliable durability assessment and long-term maintenance planning of aging reinforced concrete infrastructure.
Muhmudul Hasan Mizan, Ryuhei Hayakawa, and Koji Matsumoto
Mesoscale modeling of anisotropic compressive behavior and pull-out performance of 3D printed concrete with steel bars using 3D RBSM
This study uses a 3D Rigid Body Spring Model (RBSM) to analyze the anisotropic behavior of 3D-printed concrete (3DPC) with steel reinforcement. Validated by experiments, the research highlights how the mesoscale structure—specifically porous interlayer interfaces—affects performance. Results indicate that specimens loaded parallel to the printing direction exhibit superior compressive strength and bond performance. Conversely, loading perpendicular to the layers leads to stress concentrations and weaker bonds due to interfacial zones. Overall, this research provides a predictive framework for optimizing the structural integrity of 3DPC through mesoscale modeling.
Jiaxu Yao, Jie Luo, Minghong Qiu, and Kohei Nagai
Evaluation of Phosphorus Release from Lake Sediments Using Passive Sampling and Phosphate Oxygen Isotope Analysis
In eutrophic lakes, the persistent high phosphorus concentration in lake water poses a significant problem. This study employs passive sampling techniques and phosphorus oxygen isotope analysis to identify the sources supplying phosphorus to the lake water. This approach will also reveal contributions from lake sediments, which have not been evaluated previously. This research is expected to contribute to the assessment and conservation of lake water environments.
Akira Hafuka, Takuya Ishida, and Kazuto Sano
The Sumitomo Foundation, Grant for Environmental Research Projects 2025.11.01～2026.11.30
Development of Ethical Mining Technologies to Achieve Responsible Mineral Sourcing: The Future of Mining Development Enabled by Blockchain
Assistant Professor Okada of Hokkaido University, with support from the JST Sakura Science Program, will invite eight faculty members and students from Aksum University in Ethiopia. Using blockchain and GIS, they will examine new technological frameworks for ensuring transparency in responsible mineral sourcing and for environmentally conscious resource development through joint research, practical exercises, and presentations of results.
Sakura Science Exchange Program 2026.2.4~2026.2.18
Characterizing the Settlement of Activated Sludge Based on AI-Assisted Analysis of Moving and Still Images
In the final process of wastewater treatment, the settleability of activated sludge, a mass of microorganisms responsible for the adsorption and decomposition of pollutants, is important. In order to contribute to the improvement of the efficiency of wastewater treatment plants in rural areas and developing countries, which have problems in terms of economical human resources, this study proposed a low-cost settleability diagnosis method that uses AI-based technology to analyze still images of activated sludge using inexpensive digital microscopes and moving images of activated sludge settling using smartphone camera functions.
Yuki Nakaya, Kai Sugino, Shota Ishizaki, Reiko Hirano, Shuhei Noda, Shinobu Moniwa, Yukio Hiraoka, and Hisashi Satoh
Protium enrichment by polymer electrolyte fuel cell with hydrogen gas circulation
A polymer electrolyte fuel cell (PEFC) equipped with a gas recirculation system was employed for deuterium separation. Incorporating a hydrogen gas tank into the gas recirculation line achieved significant hydrogen concentration. During fuel cell operation, hydrogen concentration in the gas increased, yielding a high separation factor. This improvement in separation efficiency is thought to result from enhanced separation efficiency via gas-phase chemical exchange reactions.
Toranosuke Nago, Mikito Ueda, and Hisayoshi Matsushima
SH wave scattering in Eringen’s nonlocal elastic solid using the method of fundamental solutions
Eringen’s nonlocal elastic solid is a mechanical model that enables the analysis of phenomena difficult to describe using classical elasticity. This study analyzed wave scattering in nonlocal elastic solids using the method of fundamental solutions, a meshfree numerical method. An analytical representation of the traction operator specific to nonlocal elasticity was derived, and scattering characteristics relevant to ultrasonic nondestructive testing were evaluated.
Akira Furukawa, Taizo Maruyama, Takahiro Saitoh, Sohichi Hirose, Davinder Kumar, Dilbag Singh, and Sushil K. Tomar
Self-organized luminous pattern formation observed above the anode surface of a DC glow discharge in pure He
To elucidate the mechanism of self-organization phenomena in luminescence observed on the anode surface during atmospheric pressure direct current glow discharge generation, we investigated luminescence patterns while varying pressure in a pure He environment. The results revealed that luminescence patterns appear when the product of pressure p and electrode distance d (pd) is high. Moving forward, we will connect this to reaction-diffusion systems, a method used in mathematics to obtain self-organization phenomena.
Toshiaki Miyazaki, Jan Kuhfeld, Koichi Sasaki, and Naoki Shirai