International Journal of Mechanical and Electrical Engineering

Abstract: To meet the requirements for rapid construction and commissioning verification of multi-process machining production lines for valve components, this study investigates the digital modeling and virtual commissioning of a ball valve body machining production line. Considering the complex structure of the ball valve body, the strong correlation among the three internal-hole machining processes, and the difficulty of verifying coordinated equipment operation at the production-line level, an integrated modeling procedure combining process analysis, computer numerical control (CNC) machining simulation, and production-line virtual commissioning is established. First, according to the structural characteristics and technical requirements of the ball valve body, the machining features of the large-end hole, octagonal-end hole, and side hole are analyzed, and the corresponding machining process and CNC programs are developed. Second, a virtual machining environment consisting of a CNC lathe, blank, cutting tools, and machining programs is constructed in Vericut to simulate and verify the three internal-hole machining processes, thereby evaluating the feasibility of the machining programs and the safety of the machining process. Finally, three-dimensional models of machine tools, industrial robots, conveying devices, and auxiliary mechanisms are developed in SolidWorks and imported into the Visual Engineering and Education (VE2) platform to complete the layout modeling, equipment logic configuration, and robotic operation process simulation of the machining production line. The results show that the proposed modeling and virtual commissioning procedure can realize visual verification of both the ball valve body machining process and production-line operation process, providing a reference for process scheme optimization, equipment coordination configuration, and on-site commissioning risk control of valve machining production lines. Read More

Abstract: The growing waste crisis in the world at large requires automated sorting to improve on recycling efficiency and advance the application of the circular economy. In the paper, the developed intelligent waste-sorting robot combines the deep learning-based on YOLOv8 with robot manipulation systems to classify waste and sort it automatically. The given system is implemented with the usage of an RGB-D camera to obtain images, noise reduction and normalization preprocessing algorithms, and a YOLOv8 neural network to detect multiple classes of objects in 9 categories of waste. A 6-DOF collaborative robotic arm with adaptive gripper performs physical sorting tasks computed on the basis of the 3D coordinates and motion planning algorithms. Using an experimental dataset of 8,500 annotated images, the 94.3% mAP at 0.5 detect rate, 92.5% precision, 91.1% recall, and 8.7 ms inference time are achieved, which makes it possible to process images at 115 frames per second in real-time. Robotic manipulation module has 92.3 percent grasping success and the system throughput is 445 objects/hour that is impressive when compared to manual sorting techniques. The findings confirm the feasibility of the system in practice in two areas: municipal recycling centers and industrial waste management and also in niche applications such as e-waste processing. Read More

Abstract: Fretting fatigue is a special fatigue failure mode induced by the coupling of micro-amplitude relative slip and multi-axial cyclic loads on contact pairs of mechanical structures. Its crack initiation is characterized by concealment, randomness and severe damage, serving as a core trigger for the failure of key structures in aerospace, rail transit, energy equipment and other fields. Traditional uniaxial fretting fatigue life prediction models fail to account for the coupling effect of multi-axial stress and strain as well as the synergistic damage mechanism of fretting wear and contact slip, suffering from low prediction accuracy and limited applicable scenarios. Based on the critical plane fatigue theory and combined with the damage characteristics of fretting contact, this paper introduces three correction parameters, namely relative slip amplitude, contact stress gradient and surface wear damage, to establish a multi-axial fretting fatigue crack initiation life prediction model. The model is verified via finite element simulation and classical fretting fatigue test data. The results show that the modified model can effectively characterize the evolution law of composite damage in fretting contact zones under multi-axial loads. Compared with the traditional FS critical plane model and Ruiz damage model, the life prediction error is controlled within 15%, which greatly improves the prediction accuracy of fretting fatigue crack initiation life under complex working conditions. The proposed model can provide theoretical support for fatigue life evaluation and structural optimization design of precision mechanical contact structures. Read More

Abstract: Coiled tubing fishing operation is a major technical challenge in petroleum engineering. Especially for high-strength materials such as N80, conventional direct pulling is often limited by the bearing capacity limit of the tubing. In this study, an innovative fishing process combining perforation weakening and axial fracture is proposed. Based on the finite element method of ANSYS software, the influence of tool geometry on perforation load and residual strength of tubing string is systematically investigated. The explicit dynamics method is adopted to simulate the dynamic process of the punch piercing the pipe wall and fracturing the tubing. Meanwhile, the Johnson-Cook damage model is introduced to characterize the failure behavior of N80 material under complex stress triaxiality. The results show that compared with the circular cutter head, the optimized diamond cutter head reduces the piercing load by approximately 45.3% and the fracture load by about 23%, and induces obvious stress concentration zones on the pipe wall. This research provides a theoretical basis for the design of downhole perforation fishing tools. Read More

Abstract: The paper explores the use of a combined approach of computational fluid dynamics and genetic algorithm in improving the performance of airfoils in subsonic sub-flows to achieve high lift and low-drag ratios. Airfoil shapes are modeled with the use of PARSEC geometric parameterization with eleven design variables, which allows exploring the design space systematically and with physical realizations. Simulations of Reynolds-Averaged Navier-Stokes with Spalart-Allmaras turbulence models offer aerodynamic performance analysis at Reynolds number at Re = 3×10⁶ over angles of attack between -4° to 16°. The genetic algorithm optimization model, which uses tournament selection, simulated binary crossover, and polynomial mutation operators, used populations of 50 individuals which evolved over 100 generations to maximize the lift-to-drag ratio at cruise conditions (α = 4°). The findings show that peak L/D = 98.5, which is equivalent to an increase of 26.5% over NACA 2412 base level and 38.7% over NACA 0012. The streamlined design has lift coefficient Cₗ = 0.52 and drag coefficient Cⴅ = 0.00528 by optimized pressure distribution with increased suction peak and better aft pressure recovery. The results of the computational predictions are in great agreement with the experimental validation data with mean absolute error of 2.8% and 4.2% mean error of lift coefficient and drag coefficient respectively, as well as correlation coefficients higher than R² = 0.99. The study lays down systematic optimization procedures that can be used in the design of unmanned aerial vehicles, general aviation purposes, and wind turbine blades to give the aerospace engineers a solid computational foundation of aerodynamic performance improvements Read More

Abstract: To reveal the differences in local thermal instability at rough braking interfaces under different load and rotational-speed conditions, a three-dimensional transient thermo-mechanically coupled finite element model was established. A 5×5×1 mm³ single-sided rough surface region containing 496 asperities was used as the computational domain. Temperature, stress, affected depth, energy dissipation, and frequency-domain fluctuations were compared under three operating conditions. The results show that, when the load increases from 12 kN to 16 kN, the maximum temperature rises from 957.03 °C to 993.10 °C, and the plastic-dissipation depth increases from 0.204 mm to 0.300 mm. Under a 16 kN load, reducing the rotational speed from 48 rad/s to 42 rad/s lowers the maximum temperature to 709.20 °C, but increases the root-mean-square stress amplitude to 265.79 MPa. Lowering the rotational speed can alleviate thermal concentration, but it cannot eliminate contact reconstruction and stress fluctuation induced by high load. Braking risk should therefore be evaluated jointly using the dual indicators of temperature concentration and stress fluctuation. Read More

Abstract: To investigate the local flash temperature, stress oscillations, and elastoplastic energy dissipation induced by asperity interactions on both sides of a high-speed train disc brake, a three-dimensional transient thermo-mechanically coupled finite element model of a dual-roughness disc-pad interface was established. A fixed Weierstrass-Mandelbrot fractal morphology was used to evaluate temperature, von Mises stress, thermal penetration depth, thermoelastic power, plastic dissipation, and frequency-domain responses. The peak temperatures of the brake disc and brake pad reached 1409.5 °C and 1571.9 °C, respectively, and the corresponding peak von Mises stresses were 1079.4 MPa and 1024.6 MPa. The dominant stress frequency was 3395.6 Hz, with a relative oscillation amplitude of 312.10%. Plastic power accounted for approximately 32% and 37% of the theoretical input power in the disc and pad, respectively. Misaligned asperity contact and repeated jumps in contact stiffness jointly caused near-surface heat accumulation, high-frequency instability, and synergistic plastic dissipation. Read More

Abstract: High penetration of distributed energy resources (DERs)—photovoltaics, wind, storage, and flexible demand—is reshaping distribution networks. Bidirectional power flows, tighter voltage limits, and higher uncertainty make traditional passive operation inadequate. Flexible distribution systems (FDSs) address this by coordinating flexibility across source–grid–load–storage. This review synthesizes core FDS work through a three-layer lens: (i) structural flexibility (reconfiguration and controllable interconnection) that expands feasibility; (ii) real-time control (local, distributed/hierarchical, and predictive) that enforces constraints; and (iii) multi-timescale scheduling that allocates resources under forecasts and uncertainty. We emphasize cross-layer alignment—structure shapes controllability, and schedules must preserve regulation margins—and summarize open challenges in uncertainty propagation, scalability, and deployable hybrid (model + data) methods. Read More

Abstract: Thermal management of lithium-ion batteries is critical to ensuring their safe and efficient operation. Phase change materials (PCM) and heat transfer enhancement with fins are mainstream technical solutions at present. In this paper, a topology-optimized fin-PCM composite thermal management model is constructed for 2×3 array 18650 lithium-ion batteries. The thermal performance of three PCMs is compared via numerical simulation, and the influences of phase change temperature, latent heat and thermal conductivity on the maximum battery temperature, maximum temperature difference and liquid fraction are analyzed. The results show that PCM 2 achieves the optimal balance among latent heat capacity, phase change temperature and thermal conductivity under 3C and 4C discharge conditions. At the end of discharge, the maximum temperature of PCM 2 is reduced by 2.49% and 6.17% (3C), 8.54% and 6.12% (4C) compared with PCM 1 and PCM 3, respectively. Meanwhile, PCM 2 presents a stable liquid fraction variation and the best thermal buffering effect. This study can provide a reference for material selection and structural design of passive thermal management systems for high-rate lithium-ion batteries. Read More

Abstract: This paper addresses the issue of lateral vibration of high - speed train car bodies caused by random track irregularity excitation and random wind excitation. It proposes an active control method based on the SABO - LQR algorithm and the secondary suspension system to enhance the running stability and safety of high - speed trains by suppressing the lateral vibration of the car body. First, a dynamic model of the cross - wind - vehicle - track system is established, taking into account both random track irregularity excitation and random wind excitation. Second, considering the difficulty in selecting the weight matrices Q and R during the design of the LQR controller, the SABO algorithm is used for iterative optimization to obtain the optimal weight matrices and the controller. Finally, the effectiveness of the proposed method is further verified through simulation. The results show that the proposed active control method based on the SABO - LQR algorithm and the secondary suspension system has the potential to effectively suppress the lateral vibration of the train car body. Compared with the passive suspension method and the LQR control method, this method can reduce the amplitude of the car body's lateral vibration by 67.13% and 50.30% respectively, thus improving the riding comfort and the running stability of high - speed trains. Read More