Search Results (56)

As the primary load-bearing structure of deployable mesh antenna reflectors, the surface accuracy of cable-net structures directly determines the performance of cable-net antennas. To meet surface accuracy requirements, installed cable-net antennas must undergo surface adjustments, making the measurement of cable tension very important. However, constrained by measurement capabilities and conditions, large-scale cable tension measurement is highly challenging. To address this issue, this paper proposes a piezoelectric-integrated cable-net structure. By embedding piezoelectric patches at the nodes of the cable-net structure, the deformation of crimp terminals is converted into voltage signals via the direct piezoelectric effect. Furthermore, a cable force prediction method based on a BP neural network is introduced for piezoelectric-integrated cable-net structures. This method uses piezoelectric voltage values as the input layer and self-stress equilibrium factors of the cable-net as the output layer, thereby reducing the complexity of cable force prediction. Building on this, the influence of the quantity and placement of piezoelectric patches on the accuracy of the cable force prediction model is investigated. The study demonstrates that accurate prediction can be achieved when the number of piezoelectric patches is greater than or equal to the number of self-stress equilibrium factors. Additional piezoelectric patches and asymmetric placement can further enhance the prediction model’s accuracy. Finally, the predictive model was validated in triangular, quadrilateral, and tensegrity cable-net structures, demonstrating the validity of the cable force prediction method based on the backpropagation neural network. This work leverages neural networks to provide a new approach and solution for predicting cable forces in piezoelectric-integrated cable-net structures. Full article

To address the issue of cable force optimization during the cantilever casting stage of reinforced concrete arch bridge construction, this study proposes a cable force optimization method based on an Improved Whale Optimization Algorithm (IWOA) combined with a Support Vector Machine (SVM) model. First, the standard Whale Optimization Algorithm is enhanced through Tent chaotic mapping, a nonlinear iterative control parameter, adaptive weight factors, and adaptive threshold strategies. The improved algorithm is then used to optimize key parameters (C, g) in the SVM model, constructing a parameter-optimized cable force combination-structure response prediction model for the arch bridge. Next, with the average tensile stress of the arch ring’s top and bottom slabs during construction and the bending strain energy after bridge completion as target variables, a multi-objective optimization mathematical model for cable forces during the construction stage of reinforced concrete arch bridges based on IWOA-SVM was established. Finally, the feasibility of the method was validated using the Shatuo Bridge project as a case study. The results indicate that compared to the finite element optimization method, the IWOA-SVM cable force optimization method significantly improved computational efficiency while ensuring optimization effectiveness. After optimization, the peak tensile stress and vertical displacement of each arch segment were significantly reduced, leading to improved internal force distribution and alignment, thereby enhancing the overall structural safety and reliability of reinforced concrete arch bridges. Full article

Temperature-induced expansion and contraction of the upper highway steel girder can modify the force distribution in the vertical hanger cables and thereby influence the response of the lower railway deck in highway–railway steel composite bridges. This study analyzes three years (2019–2021) of field monitoring data to quantify the relationships among member temperature, highway expansion-joint displacement, and inner/outer cable tensions. Linear temperature-based prediction equations were developed using daily-averaged records and validated against independently estimated cable tensions from vibration-based identification (n = 24 tests; 8 cables × 3 campaigns). The prediction showed mean deviations below 5% and a maximum absolute deviation of 8.4%. A supporting ANSYS model reproduced the first-mode frequencies within 4%. The proposed framework provides practical equations for operational monitoring and maintenance planning within the monitored temperature range. Full article

Submarine power cables for offshore wind farms experience continuous cyclic loading from environmental forces and floating-platform motions, making fatigue performance a critical design factor. This study combined global and local analyses to investigate the fatigue behavior of a 66 kV dry-type submarine cable installed using a flexible pull-in installation system. A global dynamic analysis using site-specific meteorological and oceanographic data provided time-series displacement responses that were used to evaluate the fatigue damage to the metallic components of the cable. The results indicated that the minimum fatigue life of 8.71 × 10⁴ cycles occurred at the upper metallic sheath near the fixed end, with a corresponding cumulative damage of 1.147 × 10⁻⁵. Fatigue accumulation was predominantly governed by lateral (y-direction) displacement, while axial and vertical displacement components contributed minimally. Furthermore, the predicted fatigue life of the metallic sheath varied by a factor of up to 3.6 depending on the selected curve, comparing the cyclic stress amplitude and number of cycles to failure (S–N curve), highlighting the importance of accurate material fatigue data. These findings emphasize the need for careful evaluation of the environmental loading and sheath fatigue properties in flexible pull-in installation system-based submarine cable system designs. Full article

Transmission tower guy wires are critical flexible tension members ensuring the stability and safe operation of overhead power transmission networks. However, these components are vulnerable to external impacts from falling rocks, ice masses, and other natural hazards, which can cause excessive deformation, anchorage loosening, and catastrophic failure. Current design standards primarily consider static loads, lacking comprehensive models for predicting dynamic impact responses. This study presents a theoretical model for predicting the peak impact response of guy wires by modeling the impact process as a point mass impacting a nonlinear spring system. Using an energy-based elastic potential method combined with cable theory, analytical solutions for axial force, displacement, and peak impact force are derived. Newton–Cotes numerical integration solves the implicit function to obtain closed-form solutions for efficient prediction. Validated through finite element simulations, deviations of peak displacement, peak impact force, and peak axial force between theoretical and numerical results are within ±4%, ±18%, and ±4%, respectively. Using the validated model, parametric studies show that increasing the inclination angle from 15° to 55° slightly reduces peak displacement by 2–4%, impact force by 1–13%, and axial force by 1–10%. Higher prestress (100–300 MPa) decreases displacement and impact force but increases axial force. Longer lengths (15–55 m) cause linear displacement growth and nonlinear force reduction. Impacts near anchorage points help control displacement risks, and impact velocity generally has a more significant influence on response characteristics than impactor mass. This model provides a scientific basis for impact-resistant design of power grid infrastructure and guidance for optimizing de-icing strategies, enhancing transmission system safety and reliability. Full article

The wave glider is an unmanned marine observation platform propelled by wave energy. Accurate prediction of its motion performance is crucial for structural design and motion control. This paper presents a four-degree-of-freedom nonlinear coupled dynamic model for wave gliders in complex marine environments, developed using a separated-body modeling approach. The model incorporates the torsional properties of the umbilical cable and includes coupled environmental forces that account for wave–current interactions. Simulation results demonstrate that the proposed model agrees well with existing studies. Based on the model, experimental analyses were conducted to investigate the turning and heading tracking performance under various operational conditions. The findings reveal that the rudder angle determines the radius and direction. The significant wave height influences the longitudinal velocity and turning rate; the average longitudinal velocity increases from $0.15\mathrm{m}/\mathrm{s}$ (at $0.5\mathrm{m}$ wave height) to $0.3\mathrm{m}/\mathrm{s}$ (at $1.25\mathrm{m}$ wave height), leading to a notable increase in turning cycles per unit time. Current disturbances cause trajectory drift, the pattern of which depends on the wave–current angle, exhibiting a distinct $\eta$-direction offset under ${90}^{\circ }$ conditions. A conventional PID controller fails to achieve precise heading maintenance under second-order wave forces. The surface float exhibits more pronounced oscillations than the submerged glider, and the heading deviation becomes more severe at a wave height of $1.25\mathrm{m}$. Full article

The upper-limb exoskeleton is ergonomically designed to align with human arm motion and can be configured for deployment as a master tool manipulator (MTM) in teleoperation systems. However, existing teleoperated exoskeletons are limited by excessive weight and inadequate force feedback. This study proposes a novel lightweight exoskeleton with optimized shoulder and wrist joint structure, enabling full arm mobility and sufficient force feedback. In practical applications, gravitational forces can lead to muscle fatigue and degrade teleoperation performance, making compensation essential for ergonomic and safety. However, unknown system disturbance caused by unmodeled dynamics (such as internal compliance and cables) pose challenges for compensation precision. A theoretical dynamics model and a Bayesian neural network (BNN) trained on separate datasets to predict joint torques and their corresponding uncertainties were independently developed. Then a Bayesian fusion method was employed to combine model-based and data-driven estimates, using predicted standard deviations to assign fusion weights and produce a refined torque output. Compared to relying solely on the CAD model, the proposed fusion framework combines the physical consistency of model-based approaches with the adaptability of data-driven methods. Experiments ultimately demonstrate that the proposed algorithm effectively reduces modeling errors and enhances the accuracy and robustness of gravity compensation. Full article

Tunnel anchorages are critical components in long-span suspension bridges, transferring immense cable forces into the surrounding rock mass. Although previous studies have advanced the understanding of their pullout behavior through field tests, laboratory models, numerical simulations, and theoretical analyses, significant challenges remain in predicting their performance in complex geological conditions. This study investigates the pullout failure mechanism and bearing behavior of tunnel anchorages situated in heterogeneous conglomerate rock, with application to the Wujiagang Yangtze River Bridge in China to employ a tunnel anchorage in such strata. An integrated research methodology is adopted, combining in situ and laboratory geotechnical testing, a highly instrumented 1:12 scaled field model test, and detailed three-dimensional numerical modeling. The experimental program characterizes the strength and deformation properties of the rock, while the field test captures the mechanical response under design, overload, and ultimate failure conditions. Numerical models, calibrated against experimental results, are employed to analyze the influence of key parameters such as burial depth, inclination, and overburden strength. Furthermore, the long-term stability and creep behavior of the anchorage are evaluated. The results reveal the deformation characteristics, failure mode, and ultimate pullout capacity specific to weakly cemented and stratified rock. The study provides novel insights into the rock–anchorage interaction mechanism under these challenging conditions and validates the feasibility of tunnel anchorages in complex geology. The findings offer practical guidance for the design and construction of future tunnel anchorages in similar settings, ensuring both safety and economic efficiency. Full article

A 2D numerical model for viscous flow is established in OpenFOAM version 10 to analyze the hydrodynamic response of submarine power cables for offshore wind turbines under combined wave–current conditions. It focuses on analyzing the effect of the cable suspension ratio e/D and the current-to-wave velocity ratio U_c/U_m on the Morison coefficient of the suspended cable. The results indicate that for the cable suspension ratio e/D of less than 0.5, the strength of the dependence of both the drag coefficient C_d and inertia coefficient C_M on the cable suspension ratio e/D is significantly influenced by the current-wave-ratio U_c/U_m, while this dependence becomes less pronounced for e/D greater than 0.5. And the inertia force coefficient C_M decreases monotonically with the current-to-wave velocity ratio U_c/U_m, while the drag force coefficient C_d demonstrates a more complex, non-monotonic relationship with it. Based on the simulation results in this paper, a quantitative relationship between C_d, C_M, and the key governing parameters is established using a two-layer feedforward neural network model, providing a method for predicting wave–current forces on subsea suspended cables. Full article

During the operation of steel cable-driven radiation-resistant robots in nuclear industrial environments, the tensile force of a steel cable is influenced by temperature variations, which can cause significant detection errors. To address this problem, this study proposes a temperature-compensated axial force characterization method for steel cables based on the magnetoelastic effect, aiming to ensure the measurement accuracy of magnetoelastic sensors. The principle of the magnetoelastic measurement method involves magnetizing the steel cable. When subjected to tensile forces, the magnetization characteristics of the steel cable change, thereby altering the detection signal of the magnetoelastic sensor. By analyzing the relationship between steel cable tension and variations in the detection signal, effective force measurement can be achieved. First, experiments are conducted to investigate the influence of temperature on the detection signals of a magnetoelastic sensor under zero-load conditions. Then, additional tests are performed to examine the combined effects of a tensile force and temperature on the sensor’s signals. Finally, based on the experimental data, axial force prediction models are constructed using both surface fitting and a backpropagation neural network (BPNN). The results demonstrate that, compared to the resistance values, inductance exhibits superior stability under temperature variations. In the temperature range of 20–50 °C, the inductance variation is approximately 0.15 μH, which indicates improved suitability for characterizing the axial force of steel cables. It is also shown that under isothermal conditions, the inductance increases linearly with the applied tensile force, exhibiting a slope of approximately 0.025 μH/kN. Both the surface fitting-based and BPNN-based axial force prediction models demonstrate high accuracy, with absolute prediction errors consistently below 5% compared to actual data. Full article

Cable force distribution in cable-stayed bridges critically impacts structural safety and efficiency, yet traditional optimization methods struggle with unconventional designs due to nonlinear mechanics and computational inefficiency. This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization (MOPSO) to overcome these challenges. RSM constructs surrogate models for strain energy and mid-span displacement, reducing reliance on finite element analysis, while MOPSO optimizes Pareto solution sets for rapid cable force adjustment. Validated through an engineering case, the method reduces the main girder’s max bending moment by 8.7%, mid-span displacement by 31.2%, and strain energy by 7.1%, improving stiffness and mitigating stress concentrations. The response surface model demonstrates prediction errors of 0.35% for strain energy and 5.1% for maximum vertical mid-span deflection. By synergizing explicit modeling with intelligent algorithms, this methodology effectively resolves the longstanding efficiency–accuracy trade-off in cable force optimization for cable-stayed bridges. It achieves over 80% reduction in computational costs while enhancing critical structural performance metrics. Engineers are thereby equipped with a rapid and reliable optimization framework for geometrically complex cable-stayed bridges, delivering significant improvements in structural safety and construction feasibility. Ultimately, this approach establishes both theoretical substantiation and practical engineering benchmarks for designing non-conventional cable-stayed bridge configurations. Full article

For complex structures, the solution process of existing cable force optimization methods for low-tower cable-stayed bridges is characterized by a significant number of matrix operations, which require substantial computing power and time. As a result, achieving a more accurate solution becomes exceedingly difficult. To tackle this challenge, we propose a new cable force optimization method that enhances the stress distribution of the cable-stayed cables in the completed state of the bridge. This approach minimizes the need for frequent adjustments to cable forces and alterations to the linear elevation of the beam bridge during construction. In this study, the low-tower cable-stayed bridge of the Lanjiang Bridge serves as the engineering background. By integrating finite element analysis with a multi-objective optimization method, we propose an optimization approach for the real-time correction of cable forces during the construction of long-span low-tower cable-stayed bridges. Within this optimization framework, the cable forces during construction are treated as variable parameters, while the linear elevation of the completed bridge is imposed as a constraint. The improved grey wolf algorithm is integrated with the finite element algorithm, and the key parameters of the support vector machine are optimized using this method, resulting in the optimal parameter combination predicted based on the training samples. The results indicate that after optimizing the support vector machine model using the improved grey wolf algorithm, the cable force distribution of the cable-stayed cables becomes more uniform, with a variance of 19.96. Additionally, the maximum displacement change of the main beam under the influence of the dead load is reduced by 33.48%. This method demonstrates high optimization efficiency and produces favorable outcomes, highlighting its value in calculating cable forces and guiding construction processes during the erection of cable-stayed cables for similar bridges. Full article

To investigate the controllability of sensitive cable forces during the construction phase of cable-stayed bridges, a novel optimization method is proposed, based on BP neural networks, which combines Gaussian process prediction with a simulated annealing-optimized particle swarm algorithm to determine the tolerance intervals of construction cable forces. Based on the analysis results of multiple linear regression, the variables for optimization are identified, and a mapping relationship between the sensitive cable forces and displacement values is established using a BP neural network. Subsequently, a Gaussian process model is constructed to delineate the relationship between cable forces and reliability, with a focus on the reliability of displacements during the construction phase of the cross-section, specifically targeting sensitive cable forces. Finally, a combination of the simulated annealing algorithm and the particle swarm algorithm is employed to optimize the tolerance intervals of the cable forces. To validate the effectiveness of the proposed optimization method, a case study is conducted on the tolerance interval optimization of cable forces using a three-tower steel box girder cable-stayed bridge. In this study, the construction cable forces are treated as optimization variables, while the reliability of displacements at both the main girder section and the tower’s top section serve as the optimization objectives and constraint conditions. Under the premise of ensuring structural reliability, the accurate tolerance range for the stay cable forces during the construction phase of the cable-stayed bridge is obtained. The results indicate that the traditional PSO algorithm stabilizes after 26 iterations, whereas the hybrid intelligent algorithm reaches stability after just 13 iterations. In addition, the hybrid algorithm shows a significant increase in the objective function value during early iterations, demonstrating stronger optimization capability. This indicates that the optimization method exhibits better convergence and superior global optimization capability. It effectively improves the compatibility and controllability of the cable-stayed bridge construction process while simplifying the computational process. Full article

This paper investigates the stability issues of the Unmanned Surface Vehicle (USV)–Unmanned Underwater Vehicle (ROV) system induced by cable loads under real marine conditions and high-speed operation. This study focuses on the dynamic coupling characteristics of cable forces affecting the unmanned platform and outlines the variation patterns of these forces under different operational scenarios. By developing the dynamic models of the USV, UC, and UUV, a comprehensive system model for the unmanned marine platform is constructed. The accuracy of the cable model is validated through experimental results, and the coupling interference effects of the cable during collaborative operations are systematically analyzed from multiple perspectives. Additionally, the cable tension and force behaviors under high-speed cruising conditions are thoroughly examined. The results provide a solid foundation for the development of cable load prediction models for collaborative marine unmanned platforms, and offer both theoretical and numerical insights for dynamic control strategies based on cable force adjustments. Full article

Most theoretical models of shallow anchor cables do not take the effect of anchor inclination into consideration, which is an important factor influencing load distribution, stress concentration, and failure mechanisms. In this paper, a modified bearing capacity was developed for a single anchor cable, taking the anchor inclination into consideration, based on the principle of limit equilibrium. Then, a series of indoor pull-out tests of single anchors with different inclinations were performed, where the effects of the anchor inclination on the bearing capacity and failure mechanisms were carefully analyzed. The experimental bearing capacities were compared to the predicted data of the proposed modified model, as well as other existing experimental results, aiming to verify the applicability and accuracy. The results show that the bearing capacity increases with decreasing anchor inclination because the vertical component of the force acting on the anchor cable increases. The failure models of the anchor cables, pulled out at different angles, exhibit an asymmetric “inverted trumpet” shape, which is caused by the varying stress distributions around the anchor cable during pull-out. In addition, the bearing capacities of the theory differ very little from the experimental and previous results, with a max error of nearly 10%. This study confirms that the proposed model reliably captures the effects of anchor inclination, providing valuable insights for designing inclined anchors in engineering practice. Full article