Structural optimization in shipbuilding represents a significant research focus within the fields of naval architecture and marine engineering. This study investigates multi-condition topological optimization for the deck pillar region of a transport ship's sectional structure. A mechanical model incorporating six typical load conditions was developed, and the Analytical Hierarchy Process (AHP) was employed to quantify the weighting coefficients for each condition. This enabled multi-condition collaborative topological optimization of the pillar layout. The optimized configuration underwent model reconstruction and finite element verification. Results demonstrate that the proposed multi-condition collaborative topology optimization method effectively balances structural performance and weight reduction requirements while satisfying strength specifications. This method yields optimal pillar layouts meeting multi-condition constraints, providing a reference for multi-condition topology optimization studies in ship structures.
To enable more natural motion mapping between the human arm and a robotic counterpart while reducing control complexity, this paper presents a novel seven-degree-of-freedom (7-DoF) bionic robotic arm with hybrid pneumatic–electric actuation in an antagonistic configuration inspired by the skeletal structure and muscular actuation of the human upper limb. The design combines the high power density and intrinsic compliance of pneumatic artificial muscles with the precision and stability of electric motors, improving motion adaptability and payload-to-weight performance. Kinematic feasibility and motion smoothness for human-like waving are validated via forward kinematics and redundancy-resolved inverse kinematics, together with trajectory simulations. To quantitatively evaluate dexterity and operational range, Monte Carlo sampling is used to generate reachable postures across the workspace, producing a wrist activity map that characterizes attainable orientations and maneuverability. A prototype testbed is built to verify physical performance. Joint-angle tracking experiments for the wrist and elbow, as well as whole-arm coordinated-motion tests, demonstrate accurate trajectory tracking, smooth transitions, and stable motion. These results confirm the mechanical soundness and effectiveness of the proposed hybrid antagonistic actuation scheme. This work provides a practical basis for advanced control development and offers insights into hybrid actuation design for bionic robotic systems.
This paper presents an Energy-Balanced Splitting Factor Method (EBSFM) for nonconforming generalized mixed finite elements to enhance accuracy and stability under mesh distortion. The splitting factor significantly influences the numerical solutions. Traditional approaches employ a uniform splitting factor for all elements, neglecting their distinct characteristics and boundary conditions. Wang's geometry-based Stiffness–Compliance Splitting Factor Method (SCSFM) is adopted to obtain element-wise initial values. Building upon SCSFM, the proposed EBSFM optimizes the splitting factor through an energy balance criterion that minimizes the deviation between mixed energy and generalized strain energy, thereby improving the physical consistency of the finite element model. The method establishes an approximate mapping relationship between unknown variables and splitting factors via matrix decomposition and reconstruction techniques, enabling element-wise adaptive optimization. The EBSFM demonstrates consistent superiority in terms of displacement accuracy, stress accuracy, and energy balance.
Wind turbines equipped with large blades significantly enhance power generation efficiency. For large turbines reaching 150 meters in height, concrete towers offer an effective means of cost savings. Nevertheless, the stability of such structures must be carefully considered, given that wind perturbations are amplified with increased height. In this study, we aim to develop a numerical approach for conducting fluid-structure interaction (FSI) analysis on a 150-meter wind turbine concrete tower. A two-way FSI analysis method has been developed using the immersed boundary method, effectively addressing the coupling effects between the structural and fluid models without the need for body-fitted meshing. Our numerical results demonstrate that the proposed method achieves stable convergence and accurately captures dynamic structural responses under high-speed wind conditions. This method will contribute to the numerical design and safety validation of wind turbine infrastructure in engineering projects.
This study proposes a physics-informed graph convolutional reduced-order model, namely Phys-GCN, for high-fidelity and computationally efficient prediction of steady incompressible flow fields. In Phys-GCN, the incompressible Navier–Stokes equations are embedded into the loss function via residual constraints, such that the spatial feature extraction of graph convolutional networks is integrated with the physics-constrained learning strategy of physics-informed neural networks. This mixed design enables the model to capture complex nonlinear flow features while maintaining a clear level of physical interpretability. Benefiting from the node-edge encoding inherent to graph neural networks, Phys-GCN operates directly on unstructured CFD meshes to learn flow features from graph representations constructed using node attributes and adjacency relationships. In doing so, Phys-GCN dispenses with voxelization or SDF preprocessing and fully preserves the local geometric and topological characteristics of the flow domain. The proposed model is systematically evaluated on steady flows past circular and elliptical cylinders, where the predicted velocity and pressure fields are compared against reference CFD solutions in both interpolation and extrapolation scenarios. Results show that, for all physical quantities, the reconstructed steady flow fields achieve mean relative errors below 5%, exhibiting excellent agreement with the CFD benchmark solutions. After offline training, Phys-GCN achieves inference times that are several orders of magnitude faster than conventional CFD solvers, while maintaining comparable predictive accuracy. These findings demonstrate that Phys-GCN provides an accurate and efficient graph-based and physics-informed surrogate for steady flow-field reconstruction on non-uniform, unstructured meshes, thereby laying a solid foundation for future extensions to more complex three-dimensional and compressible flow configurations.
The helicopters conducting carrier deck operations and performing maritime rescue missions experience significant impacts from the downwash generated by their rotors, affecting both landing performance and the surrounding environment. Addressing the unclear mechanisms of downwash effects during water rescue operations, this study employed Computational Fluid Dynamics (CFD) methods, including overlapping grids, to investigate the operational characteristics of helicopter rotor airflow. Numerical simulations were conducted under various operating conditions, including different inflow velocities and rotor speeds. Based on the calculation results, the implementation process of helicopter rescue operations is proposed. These findings provided valuable guidance for helicopter water rescue operations. The results showed that as the rotor speed of the rescue helicopter gradually increased, the force of the rotor downwash flow on the water surface was greater. Moreover, when the rescue helicopter had an incoming flow velocity, the interference of the rotor downwash flow on the water force could be reduced accordingly.
In the electrochemical machining (ECM) process of the M50 bearing raceway, the oxide layer’s corrosion resistance exerts a notable impact on the machining efficiency. To achieve high-efficiency ECM of M50 bearing raceways, the electrochemical impedance spectroscopy (EIS) testing technique was adopted to conduct systematic research on the anti-corrosion performance of the oxide layer on M50 bearing raceways under different ECM processing parameters (polarization voltage, polarization time, inter-electrode gap). Then, the impact of different processing parameters on the oxide layer’s corrosion resistance was revealed. The results show that the corrosion resistance of the oxide layer decreases with the increase of the polarization voltage and polarization time, and increases with the increase of the interelectrode gap. Based on this law, in the actual ECM process, the rapid formation of oxide layer can be promoted by adjusting the polarization time, increasing the polarization voltage and reducing the interelectrode gap, and finally, the efficiency of ECM can be improved.
The geometrical and velocity scaling behavior of levitation and dragging forces in Electrodynamic suspension (EDS) systems was studied by both analytical and numerical methods, to provide comparisons between designs for both on-board and ground-mounted magnetic components. Effects of system dimension, levitation gap, magnetic field dependence of critical current density, and vehicle velocity were studied. The lift-to-self-weight ratio of two realistic EDS systems and their geometrical scaling were studied numerically.
Accurate evaluation of measurement uncertainty is crucial for precision manufacturing. This paper proposes a two-stage Bayesian-Monte Carlo method for assessing roundness measurement uncertainty in online inspection. The method separates machining errors from measurement system errors by first establishing a prior distribution via calibration with a standard artifact and then updating it with workpiece measurements. To validate the method, measurements were conducted on a certified roundness standard, showing close agreement with the reference value. The method demonstrates effective uncertainty quantification with small sample sizes and provides a foundation for intelligent evaluation in dimensional metrology.
Aluminum alloy thin-walled tubular parts play an important role in the energy absorbing elements of automotive passive safety. The number of geometry-trigger based notches is a factor in alleviate the initial force peak and shift the progressive buckling mode. However, until now, only limited work has been reported considering multiple notches. It is hard to clearly understand the impacts of the number of triggers on the buckling behavior and thresholds. Here, a mixture of quasi-static axial compression testing with high-fidelity finite element simulations is used to explore the influence of elliptical perforation number on AA6061-T6 tube crushing behaviour. For the first time, it is demonstrated that increasing the perforations leads to non-monotonic buckling evolution: from symmetry increasing → asymmetrical instability → optimal re-symmetrization → excessive weakening. We observe this transition from isolated holes to a collective “weakening hoop” controlling symmetric buckling as the number of holes increases. Our results give optima for separate objectives; T6 offers the best overall crashworthiness (45.2% less maximum force), with the other measures showing T4 with the best stiffness. We determine quantitative relationships between the number of holes and corresponding performance metrics. This gives practical design criteria for the design of energy absorbers.
Straw is one of the major biomass energy sources. It has low economic benefits by conventional disposal methods, such as returning to the field, using as feed, pressing into block fuel, gasification power generation, papermaking, and manufacturing building materials. With the surplus of crop straw, a large amount of straw resources will be burned, resulting in severe resource waste, soil structure damage, and air pollution. Straw carbonization technology and equipment are effective measures to solve the problem of straw surplus. This paper proposes a mobile straw carbonization technology, studies the principles and processes of straw carbonization, and designs a high-efficiency mobile carbonization equipment that can be used in the field to reduce the costs of straw collection, transportation, and storage and realize the transformation of straw from waste to valuable resources. A mathematical model for the pyrolysis process of straw pellets was established. The structure of the mobile straw carbonization equipment was designed based on the research on the mechanism of straw pyrolysis and carbonization. A multi-layer sleeve rotary structure of the reactor is adopted, and the furnace body solves the problem of uneven heating of carbonization with a mixed feeding design of screws and scrapers. Simulation and experiments were conducted using corn straw as the raw material to analyze the variation law of temperature inside the furnace and verify the feasibility of the equipment designed for straw carbonization.
The folding wing mechanism is widely used in aircraft design. Whether the folding wing surface can unfold smoothly determines whether the aircraft can fly normally. Therefore, studying the aerodynamic loads and structural deformations during the unfolding process of folded wing surfaces is very important. The motion process of a folded wing mechanism is a typical fluid-structure interaction (FSI) process. During deployment, the wing surface moves under the combined action of the actuator’s pull and the aerodynamic loads from the incoming flow, while the large deformation of the wing surface during its movement, in turn, affects the aerodynamic loads on the mechanism from the flow field. Considering the FSI effects during the unfolded motion process of the folded wing, simulation was conducted using the ALE algorithm in LS-DYNA to obtain the kinematic and dynamic parameters in the unfolded motion process, and also to get the aerodynamic torque on the wing under different angles and angular velocities. In practical engineering applications, the actuation force of the deployment mechanism can vary due to factors such as the amount and performance of the pyrotechnic material. Consequently, the final velocity and the whole motion process of the wing mechanism will also change. For the calculation of aerodynamic external loads under multiple operating conditions, using the ALE algorithm will consume a large amount of computational time and cost. Given the high computational cost and long computation time of finite element simulations, a BP neural network was established to calculate the aerodynamic loads on the wing surface under different actuation forces. This allows for a rapid assessment of whether significant deformation or damage will occur to the folding mechanism or nearby components during the deployment process.
This paper establishes a joint simulation model for landing gear vibration problems. Based on the model, the influence laws of different braking control methods, different runway conditions, and different positions of the rear strut on the main landing gear vibration are compared and analyzed. The results show that the runway conditions have a certain influence on the landing gear braking performance and heading vibration; the rear strut landing gear has better vibration response, and the vibration displacement is reduced by 10–20% in all simulation conditions compared with the strut in front.
The marine propulsion shafting system serves as the core component of ship power transmission, wherein torsional vibrations can easily lead to shaft cracking and failure. Thus, avoiding shafting resonance is vital for ship safety. Previous research primarily focuses on a single vibration mechanism of diesel engine propulsion shafting systems, lacking a comprehensive analysis of modal characteristics, frequency, and transient responses. This paper systematically investigates the torsional vibration characteristics of shafting systems, constructs a mathematical model for torsional vibrations, deduces a method for solving natural frequencies, and establishes a frequency-domain transfer function matrix using the Laplace Transform to theoretically derive the transient response of damped forced vibrations. Taking the propulsion shafting system of a low-speed diesel engine in a 10,000-ton oil tanker as an example, a multi-condition analysis based on a simplified shafting model is conducted. This includes modal solution analysis, 0–2000 Hz frequency sweep tests, and comparative experiments on transient responses under different excitation frequencies with a 1000 Nm torque. The study reveals the influence mechanism of the coupling between excitation frequency and natural frequency on the dynamic characteristics of the shafting system. By investigating torsional vibration patterns, this research provides a theoretical basis for vibration reduction design and resonance avoidance in marine propulsion shafting systems.
The traditional Ant Colony Algorithm has defects such as easy entrapment in local optima due to a simplistic heuristic function and slow convergence due to excessive search directions. A fusion path planning algorithm integrating ant colony optimization and artificial potential field based on a maneuver action library is proposed. Firstly, a mathematical model for UCAV path planning is established. Considering the maneuverability constraints of UCAVs, and drawing on the concept of basic maneuver action libraries for fighter aircraft, an ant colony-potential field fusion path planning algorithm based on a maneuver action library is introduced. Simulation results demonstrate that compared to two other algorithms, the proposed method significantly improves the number of waypoints and planning completion time.
Railway wire harness connectors are critical elements in modern rail transport systems, ensuring reliable signal transmission, power distribution, and communications across the subsystems that govern traction, braking, and passenger information. The progressive deterioration of these connectors under harsh operating conditions, particularly temperature variations encountered during continuous railway operations, poses significant challenges to system reliability and operational safety. This paper presents a hybrid framework integrating an adaptive Wiener process with a deep generative model (DGM) for reliability assessment and remaining useful life (RUL) prediction of railway wire harness connectors under multi-temperature conditions. The proposed methodology combines Arrhenius-based temperature acceleration with a Wiener degradation model that characterizes temperature-dependent degradation kinetics. Specifically, a variational autoencoder (VAE) is employed as the deep generative network to learn the complex nonlinear degradation patterns that conventional parametric models may fail to capture. Furthermore, a particle filter algorithm is incorporated to enable real-time Bayesian parameter updating and state estimation, thereby allowing the model to be refined in an adaptive manner as new monitoring data become available. The effectiveness of the proposed method is validated through accelerated degradation tests on electrical connectors at four temperature levels (25°C, 55°C, 85°C, and 105°C), demonstrating that the RMSE is reduced by 23.5%, 18.2%, and 32.1% compared with the standard Wiener process, LSTM-based approach, and Gaussian process regression, respectively. The analytically derived reliability function and RUL distribution provide comprehensive uncertainty quantification to support maintenance decision-making in railway systems.
The accurate prediction of high-temperature mechanical behavior of GH3230, as a core material for the new generation of combustion chambers in China, is a key technical prerequisite for promoting engineering applications. This article is the first to conduct a systematic study on the tensile properties of the alloy at three typical service temperatures of 200°C, 550°C, and 900°C, combining high- temperature tensile testing with numerical simulation. Through metallographic observation, the excellent microstructure characteristics of the alloy, including no grain boundary defects, inclusion phase size less than 5 μm, and uniform distribution, were clarified. Based on this, a multi-temperature adaptive tensile simulation model was established. Experimental verification showed that the model can accurately reproduce stress-strain tensile curves at different temperatures, with prediction errors controlled within a reasonable range, effectively breaking through the limitations of traditional single-temperature simulation. This study not only provides an efficient and accurate new method for the performance analysis and safety evaluation of GH3230 in a wide temperature range but also provides practical technical means to support the component-level engineering application of this material. At the same time, the research results also provide a reference technical path and research ideas for the multi-temperature mechanical performance prediction of other nickel-based high-temperature alloys.
The issues associated with the traditional single-gimbal control moment gyroscope (SGCMG) driven by electromagnetic motors, such as complex structure, significant gear backlash, weak anti- interference capability, poor adaptability to space environments, and large volume and weight, make it difficult to meet the attitude control requirements of micro/nano satellites. To address these issues, this paper proposes an SGCMG design based on a rotary traveling wave ultrasonic motor (RTWUM) drive. Ultrasonic motors offer advantages including high torque, fast response, self-locking upon power-off, immunity to electromagnetic interference, and simple structure, making them suitable for spacecraft attitude control systems. This paper elaborates on the working principle and structural design of the ultrasonic motor, covering the entire process from stator modal optimization, flywheel and gimbal structural design to system integration and control system implementation. Through finite element analysis and experimental verification, the designed ultrasonic motor-driven SGCMG meets the requirements of micro/nano satellites in terms of output torque, speed control accuracy, and structural compactness, demonstrating the promising application prospects of ultrasonic motors in aerospace attitude control.
