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| CONTENTS | |
| Volume 37, Number 5, May 2026 |
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- Experimental assessment of dynamic parameters and vibration behaviour of a reduced-scale steel frame system Abderaouf Daci, Nassima Benmansour, Rachid Derbal, Abdellatif Bentifour
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| Abstract; Full Text (5180K) . | pages 347-375. | DOI: 10.12989/sss.2026.37.5.347 |
Abstract
The identification of dynamic parameters and vibration control are fundamental to understanding the dynamic behaviour of civil engineering structures and constructing earthquake-resistant systems. Despite previous research, a critical need remains for a deeper understanding of comprehensively determining these parameters experimentally using Frequency Response Functions (FRFs). Furthermore, there is a lack of studies investigating vibration control in multi-degree-of-freedom (MDOF) structures through the modification of their physical properties, specifically mass. This study aims to experimentally identify dynamic parameters using FRFs and investigate the vibration control performance of a three-story reduced-scale steel portal frame by adding masses to its different stories. The model is excited using a white-noise signal from a shaking table, while responses are recorded at each floor using piezoelectric accelerometers. FRFs are computed from input-output signals using spectral analysis techniques, allowing natural frequency identification from resonance peaks. Damping ratios are estimated via the half-power bandwidth method, and mode shapes are extracted using Singular Value Decomposition (SVD) of the FRF matrix. In the second part, the influence of added masses on the model
Key Words
frequency response function analysis; mass effect; modal identification; numerical model; reduced-scale steel frame; shaking table; vibration signature
Address
(1) Abderaouf Daci, Nassima Benmansour, Rachid Derbal, Abdellatif Bentifour:
RISk Assessment & Management Laboratory (RISAM), University of Tlemcen, P.O. Box 230, Tlemcen, Algeria;
(2) Rachid Derbal:
Department of Civil Engineering and Public Works, University of Ain Temouchent, P.O. Box 284, Ain Temouchent, Algeria.
- A combined piezoelectric active sensing with hybrid 1D CNNLSTM model for damage detection in structural joints of wind energy system Thanh-Truong Nguyen, Jeong-Tae Kim, Ngoc-Lan Pham, Gia Toai Truong, Thanh-Canh Huynh
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| Abstract; Full Text (4661K) . | pages 377-405. | DOI: 10.12989/sss.2026.37.5.377 |
Abstract
Wind tower structures are continuously exposed to dynamic loads and harsh environmental conditions, leading to the gradual degradation of critical tower joints, which compromises structural integrity and operational safety. This study proposes a combined piezoelectric impedance sensing and deep learning approach for low-cost condition monitoring of bolted joints in wind turbine support structures. A hybrid 1D CNN (convolutional neural network) and LSTM (long short-term memory) model is developed to enhance damage detection under operational challenges such as blade rotation, vibrations, and environmental noise. Experimental validation on a wind turbine joint model, where different levels of fastener looseness are systematically introduced, demonstrates the model's effectiveness in detecting subtle changes in joint rigidity under various wind and noise conditions. Comparative analysis with conventional 1D CNN models confirms that the proposed approach significantly improves both accuracy and robustness, enabling reliable real-time monitoring and early damage prediction.
Key Words
active sensing; deep learning; noisy environment; piezoelectric transducers; wind turbine
Address
(1) Thanh-Truong Nguyen:
Faculty of Mechanical Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam;
(2) Thanh-Truong Nguyen:
Vietnam National University Ho Chi Minh City, Linh Xuan Ward, Ho Chi Minh City, Vietnam;
(3) Jeong-Tae Kim:
Department of Ocean Engineering, Pukyong National University, 45 Yongso-ro, Daeyeon 3-dong, Namgu, Busan 48513, Republic of Korea;
(4) Ngoc-Lan Pham:
Faculty of Civil Engineering, Industrial University of Ho Chi Minh City, 12 Nguyen Van Bao, Hanh Thong, Ho Chi Minh City, Vietnam;
(5) Gia Toai Truong:
Faculty of Civil Engineering, Dong A University, Danang 550000, Vietnam;
(6) Thanh-Canh Huynh:
Institute of Research and Development, Duy Tan University, Danang 550000, Vietnam;
(7) Thanh-Canh Huynh:
Faculty of Civil Engineering, Duy Tan University, Danang 550000, Vietnam.
Abstract
This study presents a BIM-integrated automated shape quality control framework for precast concrete elements, designed to enhance accuracy, efficiency, and traceability in industrial inspection processes. The proposed five-stage workflow combines 3D laser scanning, point-cloud preprocessing, two-stage registration (edge-point alignment and Iterative Closest Point refinement), deviation analysis, and BIM-linked reporting. Using a dataset of 820 precast arch segments, the method achieved a mean registration RMSE of 1.58 mm, representing a 43% improvement in dimensional accuracy compared to manual inspection. The fully automated process reduced inspection time by 40% and achieved 100% defect-detection sensitivity while maintaining consistency under variable environmental conditions. Color-coded deviation heatmaps and digital audit reports were automatically linked to BIM object identifiers, ensuring full compliance with ISO 19650 and ISO 9001 standards for information and quality management. The results demonstrate that the proposed method provides a practical foundation for digital transformation in precast production and aligns with the objectives of Smart Structural Systems by establishing a data-driven, ISO-compliant, and scalable framework for automated geometric quality assurance.
Key Words
3D laser scanning; automated quality control; Building Information Modeling (BIM); digital twin; infrastructure lifecycle management; precast concrete inspection; scan-vs-BIM comparison; smart construction
Address
Civil Smart Engineering Team, Civil Engineering Division, DL E&C Co., Ltd, Seoul, Republic of Korea.
- Energy dissipation and operating time analysis of a vibro-impact capsule robot powered by lithium battery under PWM control Ngoc-Hung Chu, Van-Du Nguyen, Quoc-Huy Ngo
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| Abstract; Full Text (3419K) . | pages 429-450. | DOI: 10.12989/sss.2026.37.5.429 |
Abstract
This paper investigates energy dissipation and operating time of a vibro‑impact capsule robot powered by a compact LIR1040 lithium battery under pulse‑width modulation (PWM) excitation. An improved mathematical model incorporating coil inductance and a nonlinear excitation force is developed and validated against experiments. Numerical simulations and laboratory tests quantify losses from viscous damping, Coulomb friction, and impact events, and show their dependence on excitation frequency and duty cycle. Analysis of hysteresis loops of impact force versus relative displacement and relative velocity clarifies how collision dynamics convert mechanical energy into irreversible loss. Higher frequencies generally favor forward locomotion with reduced impact losses, while lower frequencies produce larger instantaneous displacements and faster energy dissipation. Comparison of theoretical operating time based on battery capacity with operating time accounting for voltage decay reveals that voltage drop substantially shortens effective operation. Practical PWM tuning guidelines are provided to balance locomotion efficiency and battery endurance for biomedical and industrial applications.
Key Words
active capsule; energy dissipation; lithium battery endurance; micro‑robotics locomotion; nonlinear dynamics; PWM excitation; vibro-impact
Address
(1) Ngoc-Hung Chu:
Trade Union University, No. 169 Tay Son Street, Kim Lien Ward, Hanoi, Vietnam;
(2) Van-Du Nguyen, Quoc-Huy Ngo:
Department of Mechanical Engineering, Thai Nguyen University of Technology, 3/2 Street, Thai Nguyen City, Viet Nam.
