Changhong Guo

The deflector jet servo valve is a key component in servo systems, and the performance of its deflector jet hydraulic amplifier is closely associated with the overall system characteristics. This study uses central composite design to construct a sample space covering different structural parameters and service conditions, and conducts numerical simulations using a method that combines the low-Reynolds-number turbulence model with the multiphase flow model. Using the sample data, surrogate models for performance prediction are developed based on response surface methodology (RSM) and a residual multilayer perceptron (Res-MLP). Analysis of variance is conducted on the RSM model to quantify the weight contribution of each factor to performance. The comparison shows that the Res-MLP model outperforms the RSM model in predictive capability, with the correlation coefficient R of 0.995 and the mean absolute error Δ of 7.29%. For unknown samples, the Res-MLP model demonstrates stronger generalization ability than the RSM model, with a Δ value of 4.24%. The differential evolution algorithm is introduced into the Res-MLP model to optimize the key structural dimensions, and the obtained results are consistent with those of the RSM model. The optimized structure increases the pressure gain by 34.6% compared with the initial structure. Finally, particle image velocimetry is used to obtain the internal flow field characteristics and validate the accuracy of the turbulence model. Meanwhile, load pressure tests are conducted on test specimens designed according to the similarity principle, and the experimental results are compared with the numerical simulations, yielding a maximum error of 7.98%.

The structure of the deflector jet hydraulic amplifier is intricate and involves various dimensional size factors. The internal flow field undergoes intricate physical processes with multiple energy conversion stages, leading to insufficient research on the mechanism of the internal flow field and its static characteristics. This paper considers boundary layer effects and momentum loss, proposing a calculation method where the isovelocity contours of the jet cross section exhibit an arch shape. The velocity distribution within the jet space is derived, and a three-dimensional nonlinear velocity diffusion model for the deflector jet hydraulic amplifier is established. Based on this, theoretical and numerical models of the static pressure characteristics of the receiver port are established, aiming to narrow the gap between conventional theory and actual system behavior. To verify the model, the pressure characteristics of the deflector jet hydraulic amplifier are evaluated through performance testing. The results show that the three-dimensional theoretical data are in good agreement with the experimental data, with a maximum deviation of 6%. The numerical simulation combining the Yang-Shih low-Reynolds number model and multiphase flow model exhibits a maximum deviation of 8% from experimental data. The two-dimensional theoretical model, which neglects momentum loss along the thickness direction, results in calculated values higher than those of the three-dimensional model, and exhibits a maximum deviation of 14% from experimental data. Additionally, this study employs theoretical and numerical methods to analyze the influence of refined characteristic parameters on pressure performance, providing theoretical and numerical guidance for servo valve design and performance improvement.

During the closure of a specific aircraft canopy, oil leakage occurs from the pressure tank’s overflow port in the gas–liquid control system. This issue often occurs during closure, potentially leading to reduced system oil and impacting the normal operation of the canopy. Firstly, we analyzed canopy actuation principles to identify the return stroke pressure impact transmission path and derive its mathematical model. Secondly, the gas–liquid control system simulation model was constructed to replicate the oil overflow fault in the pressure tank digitally. Finally, specific improvement measures were developed based on fault mechanism analysis and simulation results to optimize the system’s design. After optimization, the peak pressure in the pressure tank’s oil chamber was reduced by 91.58%, eliminating overflow. This solution was validated by the manufacturer and implemented in production.

This paper conducts theoretical and experimental research on the docking lock of the space station docking mechanism, aiming to predict its long-term service life. By analyzing the working principle and load transmission path of the docking lock, a theoretical model based on the material performance degradation mechanism is established, and the life degradation equation of key components under service conditions is derived. Additionally, accelerated performance degradation tests with temperature as the accelerated stress were conducted to validate the accuracy of the theoretical model. The results show that the life prediction error of the theoretical model is less than 5%, demonstrating that the docking lock can operate safely for over 15 years. Through stress relaxation and creep tests, relevant parameters were fitted, and numerical calculations and experimental verification confirmed that when the initial load is 37 kN, the attenuation value of the locking force after 15 years of service is less than 10%, and the remaining locking force still meets the safety service requirements. These findings provide crucial insights into the design and optimization of docking locks, providing technical support for the design of docking mechanisms for future space stations and other spacecraft, and have important engineering application value.

The welded pipeline structure of aircraft fuel is a complex and diverse entity, significantly influenced by fluid–solid coupling. The refined aviation fuel-welded pipeline model plays a pivotal role in the investigation of its fluid–solid coupling mechanical properties. However, the mechanical analyses of pipelines with welded structures frequently simplify or ignore the influence of the weld zone (WZ). Consequently, these analyses fail to reveal the complex interactions between different weld zones in detail. In this study, a comprehensive and precise fuel-welded pipeline refinement model is developed through the acquisition of microstructural dimensions and mechanical parameters of the weld zone via metallographic inspection and microtensile testing. Additionally, the influence of clamps and brackets under airborne conditions is fully considered. Furthermore, the numerical simulation results are compared and verified using modal and random vibration tests. This paper addresses the impact of diverse fluid characteristics on the velocity field, pressure field, and stress in disparate areas, and it also conducts an investigation into the random vibration characteristics of the pipeline. The results demonstrate that the fluid pressure and velocity exert a considerable influence on the fluid flow state and structural stress distribution within the pipeline. An increase in flow velocity and alteration to the pipeline geometry will result in a change to the local velocity distribution, which in turn affects the distribution of the fluid pressure field. The highest stresses are observed in the weld zone, particularly at the junction between the weld zone and the heat-affected zone (HAZ). In contrast, the stresses in the bend region exhibit a corrugated distribution in both the axial and circumferential directions. An increase in fluid pressure has a significant impact on the natural frequency of the pipeline. This study enhances our comprehension of the mechanical properties of aircraft fuel lines with fluid–solid coupling and provides a foundation and guidance for the optimal design of fuel-welded lines.

In this study, a vehicle state joint estimation method based on lateral stiffness was applied to estimate the running states of electric vehicles driven by rear-drive, in-wheel motors. Different from the estimation methods used in other research, the joint estimator designed in this study uses the least-squares (LS) algorithm to estimate the lateral stiffness of the front and rear axles of the vehicle, deploying the high-degree cubature Kalman filter algorithm to estimate the vehicle state. We establish a three-degree-of-freedom nonlinear vehicle model with longitudinal velocity, lateral velocity, and yaw rate, and the lateral stiffness of the front and rear axles as the principal parameters. For the low-speed running state of the vehicle, a linearized magic tire model with high fitting accuracy was used to calculate the lateral force of the entire vehicle. The LS algorithm with a forgetting factor was used to design a lateral stiffness estimator to assess the front-axle and rear-axle lateral stiffness of the entire vehicle. The generalized high-degree cubature Kalman filter (GHCKF) algorithm was used to design the vehicle state estimator and further improve the GHCKF algorithm. A vehicle state estimator, using the square root generalized high-degree cubature Kalman filter (SRGHCKF), was designed. Therefore, the joint estimator, comprising a lateral stiffness estimator and a vehicle state estimator, adopts the LS-GHCKF/SRGHCKF algorithm and enables the estimation of the lateral stiffness, the longitudinal velocity, the lateral velocity, and the yaw rate of the entire vehicle during the driving process. A double lane change and slalom simulation were performed to analyze the feasibility and accuracy of the joint estimation algorithm and verify the results of the LS-GHCKF algorithm and the LS-SRGHCKF algorithm. Further, a low-speed driving experiment was carried out for electric vehicles driven by rear in-wheel motors. The inertial navigation system (INS), the global positioning system (GPS), the real-time kinematic (RTK), and an angle sensor were used to collect real-time vehicle data. The results were compared to verify the feasibility of the joint estimator and the progressiveness of the algorithm. The experimental verification and simulation both show that the vehicle state joint estimator, designed based on the LS-GHCKF/SRGHCKF algorithm, can accurately estimate the real-time state of the vehicle. Additionally, the LS-SRGHCKF algorithm shows better effectiveness and robustness than the LS-GHCKF algorithm.

The hydraulic pipeline vibration noise is one of the main noise sources in submarine stealth conditions. Taking the local hydraulic system of a certain type of submarine as the research object, a model is first developed to simulate water hammer pressures and to study the influence of component parameters on the generation and transmission of water hammers. Then, using the maximum water hammer as the excitation, fluid–structure interaction (FSI) vibration characteristics analysis of the pipeline is carried out. Additionally, the simulation method of clamp bolt pre-tightening is discussed. Finally, the modal test of various specifications of the pipeline is carried out. The results show that the error between the simulation and the test results is within 10%, which verifies the correctness of the model settings. On this basis, with the position of the clamp as the independent variable and the maximum stress of pipelines as the dependent variable, the optimization of pipeline passive vibration control is carried out by genetic algorithm, and the finite element verification shows that the pipeline vibration stress is effectively reduced.