Search Results (60)

Low solution accuracy and efficiency are two bottleneck problems in the existing models and methodologies for spatial distance calculations to verify the minimal electrical clearance of overhead transmission lines if a dynamic windage yaw is considered. To address these two issues, the accurate numerical models and the corresponding efficient solution methodologies tailored for different scenarios are proposed. First, a conductor windage yaw surface model incorporating a horizontal specific load coefficient is established, transforming the wire-to-wire minimal distance determination into a multi-dimensional nonlinear constrained optimization problem. An improved gradient-guided crossover genetic algorithm (GGA) is subsequently developed to solve this optimization problem. By integrating the gradient information to guide the crossover operator and combining an adaptive mutation with a dimension mutation strategy, the solution efficiency is enhanced. For the wire-to-tower minimal distance determination, a simplified tower model and a hybrid optimization methodology combining an oriented octree with the GGA are proposed. Numerical results on typical case studies show that, for a wire-to-wire minimal distance calculation, the GGA outperforms both the basic genetic algorithm and particle swarm optimization in terms of both convergence speed and solution accuracy. For a wire-to-tower minimal distance calculation, the oriented octree improves the spatial utilization, and the proposed hybrid methodology substantially improves the computational performance. Full article

With the rapid development of high-speed railways, the dynamic performance of the pantograph–catenary system plays a crucial role in ensuring the safe and stable operation of trains. This study investigates the effect of the structural parameters of the pantograph–catenary system to achieve good dynamic interaction performance under high-speed conditions. A finite element model of the catenary system, incorporating nonlinear cable and truss elements, and a lumped mass model of the pantograph are developed. The penalty function method is employed to simulate the pantograph–catenary interaction. A total of 2187 dynamic simulations are performed, with seven variables—pantograph parameters, span length, contact wire tension, messenger wire tension, number of droppers, stitch wire length, and stitch wire tension. The comprehensive effect of these parameters is evaluated based on dynamic performance indicators, such as pantograph–catenary contact force, pantograph head lift, and support point lift. The results indicate that increasing the number of droppers, contact wire tension, and messenger wire tension enhances dynamic performance, while an increase in span length negatively affects performance. Stitch wire tension has little to no effect. Full article

Accurate reproduction of deterministic gusts in wind tunnels is essential for studying unsteady aerodynamics and aeroelastic response in aircraft, uninhabited aerial vehicles, and wind turbines. This work presents the design, experimental characterization, and numerical modelling of a low-speed gust generator based on oscillating vanes, capable of producing high-amplitude gusts in strongly unsteady flow regimes. Cross-flow hot-wire measurements are combined with time-accurate computational fluid dynamics simulations to analyze gust formation and propagation. Classical ‘1-cos’ gusts are shown to exhibit pronounced negative velocity peaks associated with start–stop vortex shedding. A modified vane motion protocol is proposed that significantly reduces the negative peak factor while preserving a substantial gust ratio over a wide range of reduced frequencies. Measurements are supplemented with computational fluid dynamics (CFD) simulations. The CFD study included 2D and 3D URANS as well as higher fidelity DES simulations. Flow-field analysis reveals that secondary variations in gust angle arise from nonlinear interactions between vortices shed by adjacent vanes and are influenced by wind-tunnel confinement. The results provide physical insight into the limitations of oscillating-vane gust generators and guidance for the design of high-fidelity gust-generation systems. Full article

To address the increasing demands for faster response and higher control accuracy in the braking systems of electric and intelligent vehicles, a novel brake-by-wire actuation unit and its braking force control methods are proposed. The braking unit employs a permanent-magnet linear motor as the driving actuator and utilizes the lever-based force-amplification mechanism to directly generate the caliper force. Compared with the “rotary motor and motion conversion mechanism” configuration in other electromechanical braking systems, the proposed scheme significantly simplifies the force-transmission path, reduces friction and structural complexity, thereby enhancing the overall dynamic response and control accuracy. Due to the strong nonlinearity, time-varying parameters, and significant thermal effects of the linear motor, the braking force is prone to drift. As a result, achieving accurate force control becomes challenging. This paper proposes a model-free adaptive control method based on compact-form dynamic linearization. This method does not require an accurate mathematical model. It achieves dynamic linearization and direct control of complex nonlinear systems by online estimation of pseudo partial derivatives. Finally, the proposed control method is validated through comparative simulations and experiments against the fuzzy PID controller. The results show that the model-free adaptive control method exhibits significantly faster braking force response, smaller steady-state error, and stronger robustness against external disturbances. It enables faster dynamic response and higher braking force tracking accuracy. The study demonstrates that the proposed brake-by-wire scheme and its control method provide a potentially new approach for next-generation high-performance brake-by-wire systems. 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

In high-temperature testing scenarios that rely on contact, fine-wire thermocouples demonstrate commendable dynamic performance. Nonetheless, their thermal inertia leads to notable dynamic nonlinear inaccuracies, including response delays and amplitude reduction. To mitigate these challenges, a novel dynamic error correction approach is introduced, which combines a Continuous Restricted Boltzmann Machine, Deep Belief Network, and Physics-Informed Neural Network (CDBN-PINN). The unique heat transfer properties of the thermocouple’s bimetallic structure are represented through an Inverse Heat Conduction Equation (IHCP). An analysis is conducted to explore the connection between the analytical solution’s ill-posed nature and the thermocouple’s dynamic errors. The transient temperature response’s nonlinear characteristics are captured using CRBM-DBN. To maintain physical validity and minimize noise amplification, filtered kernel regularization is applied as a constraint within the PINN framework. This approach was tested and confirmed through laser pulse calibration on thermocouples with butt-welded and ball-welded configurations of 0.25 mm and 0.38 mm. Findings reveal that the proposed method achieved a peak relative error of merely 0.83%, superior to Tikhonov regularization by −2.2%, Wiener deconvolution by 20.40%, FBPINNs by 1.40%, and the ablation technique by 2.05%. In detonation tests, the corrected temperature peak reached 1045.7 °C, with the relative error decreasing from 77.7% to 5.1%. Additionally, this method improves response times, with the rise time in laser calibration enhanced by up to 31 ms and in explosion testing by 26 ms. By merging physical constraints with data-driven methodologies, this technique successfully corrected dynamic errors even with limited sample sizes. Full article

Wire-rope isolators (WRIs) are widely used in vibration and seismic protection due to their multidirectional flexibility and amplitude-dependent hysteretic damping. However, their complex nonlinear behavior, especially under inclined and combined-mode loading, poses challenges for predictive modeling. This study presents a simplified finite-element modeling framework using constant-property Timoshenko beam elements with tuned Rayleigh damping to simulate WRI behavior across various configurations. Benchmark validation against analytical ring deformation confirmed the model’s ability to capture geometric nonlinearities. The framework was extended to five WRI types, with effective cross-sectional properties calibrated against vendor-supplied quasi-static data. Dynamic simulations under sinusoidal excitation demonstrated strong agreement with experimental force-displacement loops in pure modes and showed moderate accuracy (within 29%) in inclined configurations. System-level validation using a rocking-control platform with four inclined WRIs showed that the model reliably predicts global stiffness and energy dissipation under base accelerations. While the model does not capture localized nonlinearities such as pinched hysteresis due to interstrand friction, it offers a computationally efficient tool for engineering design. The proposed method enables rapid evaluation of WRI performance in complex scenarios, supporting broader integration into performance-based seismic mitigation strategies. Full article

As a high-frequency and essential type of special electromechanical equipment, a vertical elevator has a significant societal implication for their safe operation. The load-weighing module, serving as the core component for overload warning, is susceptible to precision degradation due to the nonlinear deformation of rubber buffers installed at the base of the elevator car. This deformation arises from the coupled effects of environmental factors such as temperature, humidity, and material aging, leading to potential safety risks including missed overload alarms and false empty status detections. To address the issue of accuracy deterioration in elevator load-weighing systems, this study proposes an online self-calibration method based on multimodal information fusion. A reference detection model is first constructed to map the relationship between applied load and the corresponding relative compression of the rubber buffers. Subsequently, displacement data from a draw-wire sensor are integrated with target detection model outputs, enabling real-time extraction of dynamic rubber buffers’ deformation characteristics under empty conditions. Based on the above, a displacement-based compensation term is derived to enhance the accuracy of load estimation. This is further supported by a dynamic error compensation mechanism and an online computation framework, allowing the system to self-calibrate without manual intervention. The proposed approach eliminates the dependency on manual tuning inherent in traditional methods and forms a highly robust solution for load monitoring. Field experiments demonstrate the effectiveness of the proposed method and the stability of the prototype system. The results confirm that the synergistic integration of multimodal perception and adaptive calibration technologies effectively resolves the challenge of load-weighing precision degradation under complex operating conditions, offering a novel technical paradigm for elevator safety monitoring. Full article

Particle accelerator laboratories, which enable world-class research across many scientific fields, depend on the magnets used to manipulate their particle beams for successful operation. The community employs various techniques, typically based on Hall probes and induction sensors/coils, to verify the performance of these accelerator magnets. When the transverse access around a magnet is restricted, conventional Hall probe systems cannot be deployed or require significant modification, while moving wire/coil systems tend to provide information only on the magnetic field’s integral. This research builds upon a vibrating wire setup first commissioned to locate the magnetic center of quadrupole magnets. Scans up to the n = 200 wire harmonic (∼10 kHz drive frequency) were measured to reconstruct the magnetic field across a wire strung through a test magnet. New software was developed to systematically process the many frequency response scans needed for a detailed field reconstruction. This research investigated the speed and precision of the measurement, identifying limitations due to both instrumentation and nonlinear wire behavior. The vibrating wire data agreed with a reference Hall probe scan on the order of 6%; roughly 0.7% RMS error persisted after calibrating the vibrating wire data to the reference scan via scaling factor. Full article

This study investigates the influence of electrical actuation parameters on the performance of a morphing composite aerodynamic profile actuated by Shape Memory Alloy (SMA) wires. A fully coupled electro-thermo-mechanical finite element model has been developed to simulate the transient response of NiTi SMA, capturing the nonlinear interplay between temperature evolution, phase transformation, and mechanical deformation under Joule heating. The model incorporates phase-dependent material properties, heat effects, and geometric constraints, enabling accurate prediction of actuation dynamics. To validate the model, a morphing spoiler prototype has been fabricated using high-performance additive manufacturing with a carbon fibre-reinforced polymer. The SMA wires have been pretensioned and electrically actuated at different current levels (3 A and 6 A), and the resulting deformation has been recorded through video analysis with embedded timers. Experimental measurements confirmed the model’s ability to predict both actuation time and displacement, with maximum deflections of 33 mm and 40 mm corresponding to different current inputs. This integrated approach demonstrates an efficient and compact solution for active aerodynamic surfaces without the need for mechanical linkages, enabling future developments in adaptive structures for automotive and aerospace applications. Full article

During the winding process of a coil winding machine, excessive tension can cause wire deformation, over-stretching, or breakage, while insufficient tension may lead to slackness, accumulation, and wrinkling. The magnitude of winding tension directly affects product quality and operational performance. This paper addresses the challenges of inadequate constant-tension control accuracy and excessive fluctuations in the unwind system of winding machines under disturbances. By integrating specific operational scenarios, a fuzzy PID control strategy suitable for actual production environments is designed. Based on an established coupling model relating unwind tension to roll diameter, unwind speed, and moment of inertia, conventional PID and fuzzy PID control simulation models are developed in the MATLAB/Simulink platform. These models evaluate both control strategies under noise disturbances and abrupt tension changes. A systematic comparative analysis examines the dynamic response characteristics, steady-state accuracy, and anti-interference capabilities. Results demonstrate that the fuzzy PID control, integrated with actual winding machine conditions, effectively suppresses tension fluctuations induced by nonlinear disturbances, reducing adjustment time by 3 s compared to conventional PID control. This indicates that the production-condition-integrated fuzzy PID control exhibits smaller overshoot, enhanced robustness, and superior dynamic response and better meets precision requirements for wire winding tension control. Full article

The remarkable success of autoregressive Large Language Models (LLMs) is predicated on the causal attention mechanism, which enforces a static and rigid form of informational asymmetry by permitting each token to attend only to its predecessors. While effective for sequential generation, this hard-coded unidirectional constraint fails to capture the more complex, dynamic, and nonlinear dependencies inherent in sophisticated reasoning, logical inference, and discourse. In this paper, we challenge this paradigm by introducing Dynamic Asymmetric Attention (DAA), a novel mechanism that replaces the static causal mask with a learnable context-aware guidance module. DAA dynamically generates a continuous-valued attention bias for each query–key pair, effectively learning a “soft” information flow policy that guides rather than merely restricts the model’s focus. Trained end-to-end, our DAA-augmented models demonstrate significant performance gains on a suite of benchmarks, including improvements in perplexity on language modeling and notable accuracy boosts on complex reasoning tasks such as code generation (HumanEval) and mathematical problem-solving (GSM8k). Crucially, DAA provides a new lens for model interpretability. By visualizing the learned asymmetric attention patterns, it is possible to uncover the implicit information flow graphs that the model constructs during inference. These visualizations reveal how the model dynamically prioritizes evidence and forges directed logical links in chain-of-thought reasoning, making its decision-making process more transparent. Our work demonstrates that transitioning from a static hard-wired asymmetry to a learned and dynamic one not only enhances model performance but also paves the way for a new class of more capable and profoundly more explainable LLMs. Full article

This research explores the application of NiTiNOL-steel (NiTi–ST) wire ropes as nonlinear damping devices for mitigating vibrations in composite stiffened panels. A dynamic model is formulated by coupling the composite panel with a modified Bouc–Wen hysteresis representation and employing the first-order shear deformation theory (FSDT), based on Hamilton’s principle. Using the Galerkin truncation method (GTM), the model is converted into a system of nonlinear ordinary differential equations. The dynamic response to axial harmonic excitations is analyzed, emphasizing the vibration reduction provided by the embedded NiTi–ST ropes. Finite element analysis (FEA) validates the model by comparing natural frequencies and force responses with and without ropes. A newly developed experimental apparatus demonstrates that NiTi–ST cables provide outstanding vibration damping while barely affecting the system’s inherent frequency. The N3a configuration of NiTi–ST ropes demonstrates optimal vibration reduction, influenced by excitation frequency, amplitude, length-to-width ratio, and composite layering. Full article

This paper focused on the motion control of an underwater vehicle installed on a linear guide system, which is driven by two electric winches with wire ropes. The vehicle is subject to complex nonlinear time-varying disturbances and actuator input saturation effects during motion. A coupled dynamic model, incorporating an underwater vehicle, winches, and wire ropes, was established. Particular attention was paid to the nonlinear time-varying hydrodynamic disturbances acting on the underwater vehicle. The Kelvin–Voigt model was introduced to characterize the nonlinear dynamic behavior of the wire ropes, enabling the model to capture the dynamic response characteristics of traction forces. To tackle cross-coupling within the towing system, a differential tension coordination control method was proposed that simultaneously regulates system tension during motion control. For the vehicle dynamics model, a nonsingular fast-terminal sliding-mode (NFTSM) controller was designed to achieve high-precision position tracking control. An auxiliary dynamic compensator was incorporated to mitigate the impact of actuator input saturation. To handle time-varying disturbances, a fuzzy adaptive nonlinear disturbance observer (FANDO) is developed to perform feedforward compensation. Stability proof of the proposed algorithms was provided. Extensive numerical simulations demonstrate the effectiveness of the control strategies. Compared to the NFTSM without the disturbance observer the absolute mean value of the tracking error decreased by 76%, the absolute maximum value of the tracking error decreased by 67%, and the mean square error decreased by 93.5%. Full article

Addressing the shortcoming that steer-by-wire (SBW) system cannot directly transmit road feel, this study investigates a SBW system dynamics model, steering angle tracking control, and road feel simulation algorithm design. This study proposes a high-precision observer-based road feel simulation method that achieves road feel feedback torque design through the real-time estimation of system disturbance torque based on accurate front-wheel angle tracking. The methodology employs an improved nonlinear second-order sliding mode observer (INSOSMO) to estimate the system disturbance torque. This observer incorporates proportional–integral terms into the super-twisting algorithm to enhance dynamic response, replaces the sign function with a Sigmoid function to eliminate chattering, and utilizes the sparrow search algorithm (SSA) for global parameter optimization. Meanwhile, a two-stage filter combining a strong tracking Kalman filter (STKF) and first-order low-pass filtering processes the observer values to generate road feel feedback torque. Additionally, for the active return control of the steering wheel, a backstepping sliding mode control (BSSMC) integrated with an extended state observer (ESO) is employed, where the ESO enhances the robustness of BSSMC through real-time nonlinear disturbance estimation and compensation. MATLAB/Simulink-CarSim co-simulation demonstrates that, under sinusoidal testing, the INSOSMO reduces mean absolute error (MAE) by 34.7%, 62.5%, and 60.1% compared to the ESO, Kalman filter observer (KFO), and conventional sliding mode observer (SMO), respectively. The designed road feel feedback torque meets operational requirements. The active return controller maintains accurate steering wheel repositioning across various speed ranges. Full article