Abstract
As the span of the suspension bridge becomes increasingly long, the tower tops are subject to enormous unbalanced horizontal forces under the live load. A novel type of cable-tower restraint system, known as the main cable's self-balanced system, has been proposed to mitigate the above problem. In this restraint system, the main saddle is designed with self-balanced rollers to adjust the geometrical shape of the main cable on the two sides through the limited slip of the main saddle. Thus, the rollers maintain the self-balance between the unbalanced horizontal forces in the main cable, the longitudinal component of support forces imposed by the towers on the main saddle, and the longitudinal component of rolling friction on the saddle under the load. This study proposes an analytical method for solving the internal forces and deformations of the suspension bridge with a self-balanced system of the main cable under any uniformly distributed live load. The proposed algorithm considers various factors, which makes the estimation of structural deformation more reasonable, including the slip and friction between the saddle and tower top, stiffness contribution of the stiffening girder, compression and bending deformation of the tower (the second-order effect included), hanger inclination and elongation, and longitudinal displacement of the stiffening girder. With the parameters already known under the dead load, the force states and deformations of the main cable, stiffening girder, and towers are studied. Next, equations are built based on conditions such as the conservation of unstressed lengths of main cable segments and the closure of span length between the main cables in different spans, which are converted into one objective function. Solutions are found by programming, and the structure's live load response is estimated. Finally, the proposed analytical method is validated against finite element method (FEM) results for a suspension bridge with a 2300 m main span and a self-balanced main cable system. The comparison demonstrates excellent agreement, with a maximum relative error within 3%, confirming the high accuracy and wide applicability of the method.
Key Words
analytical method; finite element analysis (FEA); friction; live load; main cable's self-balanced system; suspension bridge
Address
Wen-ming Zhang: Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing, 210096, China; State Key Laboratory of Safety, Durability and Healthy Operation of Long Span Bridges, Southeast University, Nanjing, 210096, China
Zi-xu Wang: Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing, 210096, China
Xing-hang Shen: Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing, 210096, China
Abstract
This paper presents an extensive investigation of bi-directional functionally graded (BFG) deep circular nanobeam's free vibration behaviour. BFG deep circular nanobeam's displacement field is expressed in accordance with Timoshenko beam theory. To obtain the governing equations in canonical form, Lagrangian equations are first implemented, and the resulting expressions are then converted into a canonical equation set utilizing the conjugate momentums and their associated derivatives. In addition, nanoscale impacts are incorporated into the analyses utilizing Eringen's approach. In accordance with this procedure, an algorithm is established and its accuracy is verified by solving a benchmark free vibration example from literature and comparing the corresponding results. Finally, an extensive parametric study is realized, in which the impacts of nanoscale, boundary condition, bidirectional material gradation, and different geometric characteristics on BFG deep circular nanobeams' fundamental frequencies are evaluated.
Key Words
bi-directional functionally graded materials; conjugate momentums; deep circular nanobeam; free vibration analysis; Lagrangian equations
Address
Faruk Firat Calim, Mehmet Bugra Özbey: Department of Civil Engineering, Adana Alparslan Turkes Science and Technology University, Adana, Türkiye
Abstract
This study investigates the dynamic behaviour of rotating axially functionally graded (AFG) beams, both uniform and non-uniform, using the Meshless Local Petrov-Galerkin (MLPG) method. AFG beam composed of aluminium and zirconia is considered, with aluminium distributed at the left end and zirconia at the right end of the beam. For the accuracy first- five natural frequencies, minimum seven nodes are required in one sub domain. For numerical integration 10-point Gauss-Legendre integration scheme are used for one sub-domain. Chebyshev orthogonal polynomials have been employed as the basis functions in the present MLPG formulation. The effect of rotational speed on natural frequencies is analysed, revealing that increasing rotational speed leads to higher frequencies due to centrifugal stiffening. Non-uniform beams exhibit slightly higher natural frequencies than uniform beams due to their varying mass and stiffness distributions. The study further explores material gradation through exponential and power-law functions. Additionally, effects of tapering and boundary conditions on the natural frequencies are also examined, with C-C beams exhibiting the highest frequencies, while H-H and C-F beams show comparatively lower values. Mode shape analysis highlights asymmetric bending in C-F beams and symmetric deformation in C-C beams, while simply supported beams (H-H) display classical sinusoidal patterns. The effect of material non-homogeneity on natural frequencies is also examined for various boundary conditions, for C-F conditions increasing non-homogeneity parameter (n) from 0 to 2 results in increase in lower mode frequencies whereas for C-C, H-H, C-H conditions the natural frequency decreased with increasing non-homogeneity. Results
are verified from existing literature.
Key Words
axially functional graded beam (AFG); exponential law; fundamental frequency; Meshless Petrov-Galerkin method (MLPG); power law; vibration analysis
Address
Abhisar Chouhan, Vijay Panchore, Akhilesh Soni: Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, 462003, India
Abstract
This paper develops a new method for studying the stability of sandwich doubly-curved structures used in advanced mechanical automation systems. The structure analysed has a core made from a functionally graded graphene origami-enabled auxetic metamaterial (FG-GOEAM) with actuation and sensing face sheets to create an intelligent auxetic sandwich structure that can adapt dynamically to changes in load. To achieve this, a comprehensive coupled-field model based on integrating electromechanical constitutive relationships and first-order shear deformation theory (FSDT) that can represent how the system will react under nonlinear loading when operated automatically was created. Additionally, active control algorithms and controllers were also developed that enhance vibration suppression, increase stability margins, and optimize the real-time structural performance of the intelligent auxetic sandwich structure in an automated manufacturing environment. Numerical simulations explain how graphene dispersed within auxetic geometrical parameters (length, width, thickness), degree of curvature, and feedback control gains affect the dynamic stability of the suggested system. A deep neural network (DNN) is introduced for validating the mathematical results from datasets derived from the previous simulations. Comparison shows the suggested system has improved computational accuracy (by an order of magnitude), required fewer resources for construction (due to better structural adaptability), more effectively controlled process flows (due to enhanced intelligent controls), and increased operational reliability for future generations of automated systems. The suggested system has been designed to reduce computational complexity, provide support for predictive maintenance strategies, and efficiently implement scaling up to autonomous robotic platforms.
Key Words
active vibration control; DNN verification; FG-GOEAM; mechanical automation systems; sandwich curved structures
Address
Peng Zeng: School of Intelligent Manufacturing, Yibin Vocational and Technical College, Yibin, Sichuan Province, 644117, China
Mehran Safarpour: Department of Mechanical Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran
Mustafa Bayram: Department of Computer Engineering, Biruni University, Topkapi, 34010, Istanbul, Turkey
Abstract
The care, durability, and endurance of modern bridge structures are vital aspects as they are complex engineered systems involving advanced materials, design, and embedded technologies. Over time, they are exposed to various types of damage, including loosened connections, cracks, and degradation due to various environmental factors. This can lead to a decline in the integrity and serviceability of the infrastructure. For detecting such damage, visual inspection and manual analysis are often labor-intensive and lack various ability to perform in real-time. To address this gap, this research develops a robust, hybrid machine learning model for precise and accurate damage identification as well as localization in the bridge infrastructure. This paper mentions an investigation on a real life KW51 bridge. This paper integrates IoT-enabled vibration data acquisition, denoising through Autoencoders, and feature engineering, followed by a hybrid ML architecture that combines SVM and GNN, optimized using PSO and DANN. Findings demonstrate that the suggested approach acquired 98% accuracy in damage detection and precisely locates the damage on the structure. To successfully differentiate between the normal and damaged condition of the bridge, a unified DI is used. This research concludes a scalable, real-time method for monitoring bridge health. Enhancing the model's generalizability, on-site edge computing, and adoption in infrastructure management can be a focus in the future.
Key Words
damage detection; feature engineering; machine learning; structural health monitoring; vibration analysis
Address
Ashuvendra Singh, Smita Kaloni: Department of Civil Engineering, National Institute of Technology, Uttarakhand, Srinagar, Pauri Garhwal, Uttarakhand, 246174, India
Abstract
In highway reconstruction and expansion projects, pronounced differences in material properties, compaction states, and settlement histories between existing and newly widened subgrades can easily induce differential settlement in the joint area, thereby affecting structural stability and long-term service safety. To address the problems of incomplete geometric models, insufficient spatial representation of settlement monitoring, and inadequate digital twin-based state evaluation in existing studies, this study takes the reconstruction and expansion project of the Tai'an-Zaozhuang section of the Beijing-Taipei Expressway as the research object. A six-dimensional digital twin framework, a geometric hybrid model, and a settlement deformation analysis method for widened subgrades are developed. By integrating terrestrial three-dimensional laser scanning, UAV oblique photogrammetry, precision leveling, and multi-source point cloud registration, a high-precision subgrade point cloud model is established. Furthermore, point cloud completion, parametric model fusion, and complex polygonal hole repair are combined to construct a geometric hybrid model suitable for finite element analysis. The results show that threedimensional laser scanning can effectively characterize the overall surface settlement of the subgrade. The settlements of the three monitoring sections are 0.065 cm, 0.055 cm, and 0.067 cm, respectively, satisfying the specification requirements for measurement error. The installation of four layers of geogrid reduces the maximum settlement from 0.074 m to 0.026 m, corresponding to a settlement reduction rate of approximately 64.9%, while increasing the stability safety factor from 1.233 to 1.264. The findings indicate that the integration of digital twin technology, fine-scale point cloud modeling, and finite element analysis can provide effective support for settlement monitoring, reinforcement optimization, and structural state evaluation of widened subgrades.
Key Words
digital twin; fine-scale hybrid model; point cloud data; settlement analysis; widened subgrade
Address
Miaozhang Yu: School of Transportation Civil Engineering, Shandong Jiaotong University, Jinan, Shandong, 250357, China
Yanru Shi: School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China
Zhiqiang Liu: School of Transportation Civil Engineering, Shandong Jiaotong University, Jinan, Shandong, 250357, China
Nanjie Wu: School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China
Hongqing Li: School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China
