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The problems of the uneven strip shape and low efficiency of tea de-enzyming and carding machines in the working process were addressed by analyzing the trajectory of tea particles and establishing a force model diagram of tea particles in the pot slot. The three-dimensional geometric model of the tea de-enzyming and carding machine was drawn using UG software, and the simulation model of tea particles was established using EDEM software. The work efficiency of the tea de-enzyming and carding machine was improved, and the rate of broken tea was reduced using the EDEM software to simulate the movement of tea particles in the pot slot under different heights of the convex bar, pot slot angle of inclination, and number of slots. The average velocity and interaction force curve of tea particles were obtained. The influence of the number of slots, the inclination angle of the slot, and the height of the convex bar on the effect of tea into strips were verified using a scheme design based on the quadratic regression orthogonal combination rotation test, and experimental research based on three factors and three levels was carried out. Design-Expert 11 software (Stat-Ease, Minneapolis, MN, USA) was used to optimize the response surface and analyze the regression model of the relevant test data. The 6CSL-800 tea de-enzyming (Anji Yuanfeng Tea Machinery Co., Ltd., Huzhou, China) and carding machine (Anji Yuanfeng Tea Machinery Co., Ltd., Huzhou, China) was used as the verification test prototype, six sets of verification tests were carried out, and the test results showed that the maximum value of the strip rate index and the minimum value of the broken tea rate index were obtained. The order of the indicators affecting the bar-type rate and broken tea rate of the de-enzyming and carding machine from high to low is as follows: the height of the convex bar, the inclination angle of the slot body, and the number of slots bodies. When the height of the convex bar was 10 mm, the inclination angle of the slot was 90°, the number of slots was 12, the bar-type rate was 89.45%, and the broken tea rate was 1.63%. The prediction results of the regression model of the bar-type rate and broken tea rate of the tea de-enzyming and carding machine were verified by employing six sets of control tests with the 6CSL-800 tea de-enzyming and carding machine as the validation test prototype. The actual values of the bar-type rate obtained from the six sets of control tests were 88.19%, 90.37%, and 87.33% (1,2,3 group), and the actual values of the broken tea rate were 1.66%, 1.69%, and 1.61% (4,5,6 group), with average values of 88.63% and 1.65%. The control test was basically consistent with the results of parameter optimization. The processed finished tea has good quality, which can provide theoretical reference for the optimization and design of tea de-enzyming and carding machines and similar tea machines in the future.

A single-arm pantograph of metro train was studied in this work. The mathematical model of a single-arm pantograph was first established and an optimal design method to obtain the geometric parameters of the pantograph was proposed. The 3D model for the pantograph was then built and the simulation was performed by using virtual prototyping technology to ensure superior performance of the optimized pantograph. The fatigue test of pantograph-insulator system was performed under two operating conditions: Electric pantograph lifting and real train operation. Fatigue test results validated the stability of the optimized pantograph system.

In order to increase wosrkspace and carrying capacity of leg mechanism and improve popularity and adaptability of leg mechanism, a novel mechanism is proposed which has three branches of 6-DOF, which used 3-UPS parallel mechanism as the prototype of the mechanism. The static performance of the leg mechanism is analyzed and the structure parameters are designed. First, the static transmission equation of the leg mechanism is established by using the principle of virtual works which simplifies the calculation process of the leg mechanism. Further, the static performance evaluation index and the global torque performance evaluation index are defined, and the performance atlas of the static performance evaluation index is plotted at the work spaces of the leg mechanism. Moreover, by using of the space model theory, the structural dimensions parameters are optimized of the leg mechanism. Finally, using a set of optimal structural dimensions parameters and the virtual prototype of leg mechanism is designed. The research provides a theoretical basis for further investigation on leg mechanism.

Excessive swing of the cantilevered conveyor trough is a key issue restricting the working efficiency and operational stability of combine harvesters. To suppress its swing, this study established a dynamic model of the conveyor trough to reveal the influence mechanisms of the initial angle, overall length, and cylinder pivot length on its swing characteristics. Orthogonal experimental design and multi-factor analysis of variance were employed to systematically analyze the significance of these three factors on swing amplitude, identifying cylinder pivot length as the most dominant factor. Optimization results determined the optimal parameter combination as an initial angle of 48.33°, an overall length of 1.45 m, and a cylinder pivot length of 1.1 m. Field tests verified that this optimized scheme reduces the swing amplitude by 11.62%, with a minimal error of 0.57% between theoretical and measured values, providing a reliable theoretical and experimental basis for the low-vibration design of combine harvester conveying mechanisms.

Mathematical modeling of unitized regenerative fuel cells (URFCs) faces significant challenges in reconciling parameter conflicts between fuel cell (FC) and electrolysis cell (EC) modes. This study establishes a COMSOL-based multi-physics framework coupling water–gas–heat–electric transport for both operational states. The critical factors associated with the model were identified through a systematic sensitivity analysis of structural and operational parameters, including temperature, exchange current density, conductivity, porosity, and flow rates. FC modes exhibited strong sensitivity to exchange current density (27.8–40.5% performance variation) and conductivity of membrane (10.1–35.6%), while temperature degraded performance (−4.2% to −4.0%). Spatial analysis revealed temperature-induced membrane dehydration and accelerated gas depletion at electrodes, thus explaining the negative correlation. EC modes were dominantly governed by temperature (8.6–9.4%), exchange current density (13.0–16.4%), and conductivity (2.5–13.3%). Channel simulations revealed that elevated temperature contributed to enhanced liquid water fluidity, while high flow rates had a relatively limited effect on mitigating species concentration gradients. Parameter optimization guided by sensitivity thresholds (e.g., porosity > 0.4 in FC GDLs, conductivity > 222 S/m in EC modes) enabled dual-mode calibration. The model achieved <4% error in polarization curve validation under experimental conditions, demonstrating robust prediction of voltage–current dynamics. This work resolves key conflicts of URFC modeling through physics-informed parameterization to provide a foundation for efficient dual-mode system design.

This research combines simulation technology, a surrogate model, and a dung beetle optimizer (DBO) to propose a structural optimization design method for lightweight adhesive modules. The structure of the wall-climbing robot is introduced, and its adhesion stability is analyzed. Through simulation comparison of four typical Halbach array magnetic circuit modes, it was determined that the adhesion generated by the three-magnetic circuit structure mode is more advantageous. Determine the parameters that need to be optimized through sensitivity analysis. The Chebyshev model of adhesion force and parameters was established. An optimization model aimed at lightweight and the constraints of adhesion stability and structural parameters was set. The penalty function combined with DBO was used to solve the optimization model. Compared with before optimization, the weight of the adhesive module is reduced by 11.7 %. The experiments verified the adhesive module’s adhesion force and the robot’s load capacity.

It is important to optimize the structure of inlet due to the increasing demand of ram air. In this paper, structural optimization of the submerged inlet is pursued using a hybrid model by integrating least squares support vector machines (LS-SVM) prediction model and improved genetic algorithm-particle swarm optimization (GA-PSO). Inlet shape is controlled by changing three-dimensional geometric parameters. Ramp angle, width to depth ratio and ramp length play significant parts in this optimization process. Ram efficiency and mass flow are the main objectives of the performance evaluation. Results show that the prediction error of the mass flow and ram efficiency is 2.31% and 0.54%, respectively. Comparison with the original geometry is used to prove the optimization capabilities of the proposed optimization method. The mass flow and ram efficiency are increased by 29.2% and 10.0%, respectively. In addition, the characteristics of the optimized submerged inlet geometry are numerically investigated. The numerical results are compared to the optimization results and indicate that this optimization method has high validity. The error of ram efficiency and mass flow is 0.30% and 0.66%, respectively. Consequently, this optimization method can be valuable to aircraft engineers-by providing a novel approach for the design of the submerged inlet.

Symmetrical bearing raceway led to the axial sliding of rolling elements, which is a crucial factor in shortening the operational lifespan. This study addresses this limitation through three-step advancements: first, a parametric equation for logarithmic spiral raceways is developed by analyzing their asymmetric geometric features; second, based on the geometrical model, we systematically investigate the parameters of the logarithmic spiral that affects the bearing performance metrics; and finally, a novel fatigue life prediction framework that integrates static mechanical analysis with raceway parameters establishes the theoretical foundation for optimizing the raceway parameters. The results of the model analysis show that the error of the maximum contact stress verified by the finite element method is less than 8.3%, which verifies the model’s accuracy. Increasing the contact angle α of the outer ring from 82 to 85 can increase fatigue life by 15.6 times while increasing the initial polar radius O of the inner ring from 7.8 mm to 8.1 mm will cause fatigue life to drop by 86.9%. The orthogonal experiment shows that the contact angle α of the outer ring has the most significant influence on the service life, and the optimal parameter combination (clearance δ of 0.02 mm, inner race and outer race strike angles α of 85°, an inner race initial polar radius ro of 7.8 mm, and an outer race initial polar radius ro of 7.9 mm) achieves a 60.7% fatigue life increase. The findings provide theoretical support and parameter guidance for the optimal bearing design with logarithmic spiral raceways.

The downhole engineering parameters measurement sub is a key component of the rotary steerable drilling system. To enable a measurement sub to serve reliably under downhole complex conditions, the structural parameters optimization of its key but weak elastic cell is systematically studied. First, the multiple relations among measurement sensitivities, structural stiffnesses, and strength during structural parameters design are summarized. Second, the selection of the structural parameters of the elastic cell is characterized as a multi-objective optimization model, which is solved using the non-dominated sorting genetic algorithm II (NSGA-II). Furthermore, the finite element method (FEM) is used to verify the measurement performance and static strength of the proposed structure. Finally, transient dynamics analysis is applied to investigate the dynamic strength of the designed structure. The results show that the proposed parameters optimization strategy can quickly obtain the database for the structural parameters design of an elastic cell. The static analysis results based on the FEM further verify the effectiveness of the proposed method. Transient dynamic analysis also reveals the relative rigor of the proposed methodology framework to some extent. This work has practical significance for improving the drilling efficiency and reducing drilling risks. In addition, this proposed methodology has good extensibility.

The current harvesting arms used in harvesting robots are developed based on standard products. Due to design constraints, they are unable to effectively avoid obstacles while harvesting tomatoes in tight spaces. To enhance the robot’s capability in obstacle-avoidance picking of tomato bunches with various postures, this study proposes a geometric parameter optimization method for a 7 degree of freedom (DOF) robotic arm. This method ensures that the robot can reach a predetermined workspace with a more compact arm configuration. The optimal picking posture for the end-effector is determined by analyzing the spatial distribution of tomato bunches, the main stem position, and peduncle posture, enabling a quantitative description of the obstacle-avoidance workspace. The denavit–hartenberg (D-H) model of the harvesting arm and the expected collision-free workspace are set as constraints. The compactness of the arm and the accessibility of the harvesting space serve as the optimization objectives. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective genetic algorithm is employed to optimize the arm length, and the results were validated through a virtual experiment using workspace traversal. The results indicate that the optimized structure of the tomato harvesting arm is compact, with a reachability of 92.88% in the workspace, based on the collision-free harvesting criteria. This study offers a reference for structural parameter optimization of robotic arms specialized in fruit and vegetable harvesting.