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CONTENTS
Volume 36, Number 6, December 2025
 

Abstract
The present study exhibits the idea, mathematical formulation, and confirmation with machine learning of a smart spherical harvester that is able to harvest efficiently ultra-low-frequency marine vibrational energy. The harvester which is made for ocean applications is spherical in shape which helps it to interact more actively with the low-frequency vibrations that are usually found in the ocean environment. By combining the piezoelectric and electromagnetic methods of harvesting, the harvester is provided with the capacity to fully exploit the energy out of the mechanical vibrations which are very difficult to capture because of their small amplitude and low frequency. During the development of theoretical models, the focus was on aligning the resonant frequency with the environmental marine vibrations in predicting the harvester's efficiency in converting energy. These models take into account the forces caused by the water movement, the properties of the material making up the spherical shell, and the interactions occurring between the components of energy harvesting and the surrounding marine medium. Theoretical predictions are validated through experimental tests performed in a controlled marine environment to assess practical performance. Moreover, deep neural networks (DNNs) are applied to the experimental results verification, which in turn, enhances the accuracy and stability of the performance analysis. The outcomes reveal that the smart spherical harvester can successfully catch and convert very low-frequency vibrations into power, thus producing reasonably high power even in real marine conditions. This proves the harvester's position as a green energy source for very off-grid marine applications, such as sensor and monitoring systems, and even underwater drones. Working smartly on materials and energy harvesting technologies for different functions, this work is helping the incorporation of such devices into marine energy applications.

Key Words
energy harvesting; experimental test; low-frequency vibrations; machine learning validation; marine environments; smart spherical harvester

Address
(1) Xiaojian Mu:
School of Automation and Electrical Engineering, Linyi University, Linyi 276000, Shandong, China;
(2) Hamed Safarpour:
Faculty of Engineering, Department of Mechanics, International University of Imam Khomeini, Qazvin, Iran;
(3) M.A. Ahmed:
Department of Mathematics, College of Science, Majmaah University, Al-Majmaah 11952, Saudi Arabia;
(4) Murat Yaylacı:
Department of Civil Engineering, Recep Tayyip Erdogan University, 53100, Rize, Turkey;
(5) Murat Yaylacı:
Turgut Kiran Maritime Faculty, Recep Tayyip Erdogan University, 53900, Rize, Turkey.

Abstract
The suppression of oscillations in cable-stayed bridges has been a formidable challenge in engineering. Although various types of dampers have been employed in the vibration suppression of cable-stayed bridges, obvious oscillations of cable-stayed bridges still can be observed. The possible reason is dynamic mechanisms of coupling system remain unclear, and the current dynamic theoretical models only consider the damper coupling with a single component (i.e., beam or cable) of cable-stayed bridges. To address this problem, a novel double coupled cable-damper-beam dynamic theoretical model of cable-stayed bridges and its internal resonance analysis is investigated in this paper. There are three innovation points. Firstly, a double coupled cable-damper-beam dynamic theoretical model, involves the direct coupling between the cable and beam ends and the indirect coupling between the cable and beam through dampers, is proposed, which is closer to the real case compared with the non-double coupled model. The geometric nonlinearity of cable and beam is considered in the modeling. Secondly, an important mechanism is revealed, i.e., the stiffness of damper affects the Hopf bifurcation of the model. The increase in damper stiffness enhances the coupling between cable and beam, which lead to the occurrence of the Hopf bifurcation and further induce the large vibration of cables. Thirdly, a very interesting phenomenon is discovered, i.e., reduction in the sag of the cable has almost no effect on its dynamic response, but it leads to a significant increase in the dynamic response of the beam. The phenomenon indicates that the sag of cable has a significant effect on the dynamic mechanism of cable-stayed bridges. Moreover, the proposed model can explore the mechanism of cable-damper-beam more clearly due to its double coupled characteristic, which lays a theoretical foundation for effective vibration suppression and provides the convenience for the optimization design of dampers.

Key Words
cable-damper-beam model; cable-stayed bridges; double coupled structure; nonlinear dynamic

Address
(1) Yonghui An, Houjun Kang, Yunyue Cong:
Guangxi Laboratory of Whole Life Safety for Land-sea Corridor Engineering, Guangxi Key Laboratory of Disaster Prevention and Engineering Safety, State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures (Provincially and Ministerially Co-constructed), Guangxi University, Nanning, Guangxi, China;
(2) Yonghui An:
Department of Civil Engineering, Dalian University of Technology, Dalian, China;
(3) Yunpeng Cai, Houjun Kang, Yunyue Cong:
Scientific Research Center of Engineering Mechanic, School of Civil Engineering and Architecture, Guangxi university, Nanning, China.

Abstract
This study investigates impedance monitoring and damage detection in bottom-fixed wind turbine structures, addressing the challenges posed by operational variations such as blade rotation and noise. A novel linear discriminant analysis-based damage classification method is proposed, utilizing a set of selected impedance features extracted from the impedance signals acquired from piezoelectric transducers. Experimental validation on a lab-scaled wind turbine model demonstrates the effectiveness of the proposed method in accurately classifying damage, under varying operational wind conditions and noise effects. The results show that the proposed method can enhance impedance-based damage detection in the wind turbine joints while mitigating the impact of operational variations and noises, providing a robust and efficient tool for health monitoring of wind turbine structures.

Key Words
blade rotation; impedance-based method; LDA; piezoelectric transducers; wind turbine structures

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) Gia Toai Truong:
Faculty of Civil Engineering, Dong A University, 33 Xo Viet Nghe Tinh, Hoa Cuong, Da Nang 550000, Vietnam;
(5) Thanh-Canh Huynh:
Institute of Research and Development, Duy Tan University, Danang 550000, Vietnam;
(6) Thanh-Canh Huynh:
Faculty of Civil Engineering, Duy Tan University, Danang 550000, Vietnam.

Abstract
This research examines the performance optimization of smart energy systems for vibration control and energy harvesting in coal mining components, with a focus on appropriate rock mechanics and dynamic interactions. External mechanical loads are applied to a sandwich plate model with a concrete core and sensor-actuator integrated face sheets to simulate structural elements used in mining applications. The structural formulation applies higher-order shear deformation theory (HSDT) to accurately account for the effects of transverse shear in thick composite laminates. The governing equations of motion are produced from Hamilton's principle, allowing an energy-based formulation to stay consistent with the foundation of the physics involved. Additionally, the generalized differential quadrature (GDQ) method is used for the spatial discretization in addressing the coupled electromechanical response, while the temporal domain is treated analytically with the Laplace transform. Various control strategies are verified (classical, robust, optimal) for their potential to suppress vibrations, while at the same time maximizing energy harvested. The comparative analysis developed was able to identify the most suitable controller to increase the stability of a concrete structure while also increasing the energy conversion efficiency, despite being acted on by both operational and non-operational disturbances. The framework proposed has great potential to enhance the reliability, durability, and self-sustainability of concrete structures. The results and findings of this thesis offer professional implications for understanding how to implement smart materials in combination with modern control algorithms and effective modeling practices for use in the practice of concrete engineering.

Key Words
coal mining components; composite materials; concrete; rock mechanics; smart systems; vibration control

Address
(1) Chunmei Shen:
Henan Quality Institute, Pingdingshan, Henan Province, China;
(2) M.A. Ahmed:
Department of Mathematics, College of Science, Majmaah University, Al-Majmaah 11952, Saudi Arabia;
(3) Arefeh Baniasadi:
Department of Engineering, Imam Khomeini International University, Qazvin, Iran;
(4) Murat Yaylacı:
Department of Civil Engineering, Recep Tayyip Erdogan University, 53100, Rize, Turkey;
(5) Murat Yaylacı:
Turgut Kiran Maritime Faculty, Recep Tayyip Erdogan University, 53900, Rize, Turkey.

Abstract
Structural systems are exposed to a wide range of hazards that can lead to performance degradation or failure. Fragility curves are commonly used to describe how the probability of failure increases with hazard intensity, yet they do not offer a straightforward way to compare the vulnerability of different structures or determine which ones require priority in mitigation planning. This study introduces a global resilience index that reflects how a fragility curve evolves across the full hazard intensity range. The index is formulated from two components: a probabilistic term based on the mean, standard deviation, and coefficient of variation of the cumulative lognormal fragility model, and an amplification factor that represents the portion of the hazard range in which the structure remains in a low-probability-of-failure state. These terms are combined into a normalized value between 0 and 1 that captures both failure likelihood and retained functional capacity. The index is applied to fragility curves from different structural configurations, and in each case it reflects expected trends and distinguishes meaningful differences in vulnerability. Although the method is limited to fragility curves that follow a cumulative lognormal distribution and does not include recovery modeling, it offers a simple and consistent tool for comparing structural performance and supporting hazard-mitigation decisions.

Key Words
fragility curve; fragility quantification; lognormal cumulative distribution; resilience index; structural vulnerability

Address
(1) Mohamed A. Sherif, Amr M. Ghanem, Mostafa H. Abdelhafeez, Do-Soo Moon:
Department of Civil, Environmental and Construction Engineering, University of Hawai'i at Mānoa, Honolulu, Hawaii, United States;
(2) Donghyuk Jung:
School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, Republic of Korea;
(3) Dae-Jin Kim:
Department of Architectural Engineering, Kyung Hee University, Yongin, Gyeonggi, Republic of Korea.

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