Energy saving is the theme of automobile development, and intelligence and networking are the inevitable trend of automobile technology development. Aiming at the influence of traffic information on vehicle energy consumption, an economic speed planning method for intelligent connected vehicles based on interval analysis is proposed. Firstly, based on cellular automata and confidence interval theory, traffic information rules are introduced, and a road speed interval extraction method considering traffic density and traffic signal phase information is established. Secondly, according to the vehicle driving energy consumption model, the objective function of economic speed planning is established, and the traffic speed interval under different driving conditions is taken as the dynamic constraint condition, and the optimal control problem model of vehicle economic speed planning under urban road conditions is established; Then, the optimal control problem of vehicle economic speed is transformed into a model predictive control problem, and the DP algorithm is used to solve the optimal control sequence in each predictive domain, and the optimal speed sequence is planned by cyclic rolling optimization. Finally, through simulation and experimental verification, the results show that the method proposed in this paper can not only achieve all-green traffic at signal intersections, but also achieve good energy-saving effect, and the planning algorithm has fast calculation speed.
Although the porosity in Al/SiC metal matrix composites can be reduced, its presence is inevitable. This study aims to investigate the influence of porosity and pore size on the performance of SiC reinforced aluminum matrix composites that contain porosity. To achieve this, we consider both constant and variable diameters of pores, assuming a circular shape while maintaining the same volume fraction. Finite element analysis is conducted on a square matrix reinforced with nine particles subjected to a tensile test. The simulation employs a two-dimensional plane stress model along with square, hexagonal, and random distributions of multiple particles. The results indicate that, despite the presence of pores, the stress transfer from the softer matrix to the reinforcement remains effective. Moreover, the properties of the composite are found to be increasingly sensitive to porosity and pore size, particularly when the pore diameter increases and the distance to the particles decreases.
Based on computer-aided ergonomics the paper proposes a hip joint rehabilitation exoskeleton utilizing a adjustable spherical parallel mechanism, specifically designed for rehabilitation training of individuals with impaired hip joint movement function. Initially, the screw theory is employed to determine the degrees of freedom of the parallel mechanism, revealing that it possesses three rotational degrees of freedom, enabling sagittal plane movements, frontal plane movements and transverse plane movements at the hip joint. The closed vector method is utilized to derive the inverse position solution, and the velocity Jacobian matrix is solved. Leveraging the inverse position solution and the constraint relationships between mechanisms, the reachable workspace of the mechanism is obtained using MATLAB software programming. Utilizing screw theory and velocity Jacobian matrix, the dexterity of the mechanism is analyzed. Ultimately, a human-robot integrated system is established in AnyBody software to verify its capability to achieve certain rehabilitation effects on human muscle groups. Research demonstrated that the hip joint parallel mechanism exhibits good stability and can effectively assist individuals with hip joint dysfunction in rehabilitation training.
The prompt and efficient diagnosis of anti-friction bearing faults is crucial for the proper functioning of rotating machinery. In this paper, a novel approach to anti-friction bearing fault diagnosis utilizing Bi-dimensional extensive empirical wavelet decomposition combined with optimized incremental RVM is presented. As an enhanced version of ensemble empirical wavelet decomposition, Bi-dimensional extensive empirical wavelet decomposition extends its application from 1D to 2D signal processing, enabling the extraction of more comprehensive anti-friction bearing features. Additionally, the optimized incremental RVM is employed for fault diagnosis of anti-friction bearings. The experimental findings indicate that Bi-dimensional extensive empirical wavelet decomposition surpasses Bi-dimensional empirical wavelet decomposition, and optimized incremental RVM outperforms traditional RVM. The proposed method incorporating Bi-dimensional extensive empirical wavelet decomposition and optimized incremental RVM proves to be highly effective for anti-friction bearing fault diagnosis.
This work focuses on the dynamic load identification motivated by Newmark-(3 Method and regularization strategy. Given the ill-posed nature of load identification, an improved hybrid LSQR regularization strategy is proposed, which incorporates an adaptive correction mechanism by iteratively comparing the computed response with the measured response. For load identification problems with prior conditions, an augmented hybrid LSQR regularization strategy is further developed, which expands the Krylov subspace with prior information and combines the improved hybrid LSQR regularization strategies to ensure stable iteration. Simulation examples using a simply supported beam as a representative structure of continuous systems, involving different load types and noise levels, validate the stability and accuracy of the two methods. The results show that the improved hybrid LSQR algorithm exhibits superior stability and accuracy compared to the conventional LSQR algorithm and yields relatively favorable identification results. Moreover, the superposition load identification simulation indicates that the augmented hybrid LSQR algorithm further improves the accuracy of load identification when prior knowledge of the load is available.
Based on the kinematics theory of multibody systems, this paper investigates the error compensation problem of CNC machine tools. By abstracting the true of the CNC machine tool as a multibody system composed of kinematic pairs and components, a complete spatial error model from drive input to tool execution is constructed using homogeneous coordinate transformation MCS, and the generation, accumulation, and coupling mechanisms of various geometric errors are analyzed. The paper details the establishment of coordinate systems in multibody systems, the homogeneous coordinate method for and vectors, and the construction of zero-order motion equations. On this basis, a universal geometric error model with dual branches of "workpiece-tool" and "tool-machine tool" is established, expressions for position and orientation errors are derived, and error compensation condition equations for achieving precision machining are proposed. In preliminary experimental verification, the errors of the Z-axis of a VMC-500 machine tool were measured and compensated using a Renishaw ML10 dual-frequency laser interferometer. The results indicate that the compensated error variance decreased from 6.4534 and 5.8352 to 3.061, the fluctuation range of the error was narrowed, and the method demonstrated potential effectiveness and engineering applicability.
This review has examined recent advancements, underlying mechanisms, and performance characteristics of FSAM, with particular emphasis on its application to both similar and dissimilar aluminium composites. FSAM demonstrates significant potential in addressing the limitations of conventional fusion-based additive manufacturing, offering enhanced mechanical properties, refined microstructures, and superior interfacial bonding. A systematic evaluation of key process parameters such as tool geometry, rotational speed, and traverse speed reveals their critical role in defect mitigation and structural optimization. Furthermore, the incorporation of reinforcement particles illustrates FSAM’s ability to fabricate composite materials with tailored properties for high-performance applications. Owing to its versatility and capability to fabricate complex, multi-material structures, FSAM stands out as a promising solution for sectors including aerospace, automotive, and biomedical industries. Overall, this study not only consolidates current knowledge but also lays a foundation for continued innovation and optimization in solid-state additive manufacturing technologies.
This study compares MPC with PI and PID controllers for temperature control. While PI and PID are effective for simple and stable systems, MPC shows better performance in complex and dynamic conditions. Laboratory experiments confirm that MPC handles disturbances, airflow variations, and setpoint changes more accurately, with improved stability and reduced overshoot. The results highlight MPC as a more efficient and reliable solution for advanced temperature control applications, with strong potential for use in larger industrial systems.
Cylindrical tubes are fundamental structural components across many engineering fields, particularly for bearing external loads. In pressurized water reactors (PWR), the metal cladding tube acts as the first safety barrier, containing radioactive materials under extreme conditions of external pressure, high temperature, and intense fast neutron flux. Accurate prediction of its creep deformation remains a critical challenge in nuclear engineering. This study analyzes the coupled thermal and irradiation creep behavior of cladding tubes using the commercial finite element code ABAQUS and its user subroutine CREEP. The results demonstrate that creep deformation mode and magnitude are highly sensitive to geometric and mechanical factors. Specifically, longer axial lengths correlate positively with greater creep deformation, while increased wall thickness reduces it. Cladding tubes with length-to-diameter ratios exceeding 21 can be treated as infinitely long structures. Furthermore, relaxed boundary conditions have an effect equivalent to increasing the tube’s effective length, thereby amplifying creep deformation. These insights are important for evaluating cladding performance and structural safety under long-term creep deformation.
To address the issues of strong empirical dependence and low computational efficiency in traditional ball mill cylinder design, this study proposes a lightweight design methodology integrating multiple response surface models with finite element parametric simulation technology. Based on the equivalent density method, stress-strain characteristics are obtained through simplified cylinder structural modeling and finite element static analysis. Parametric finite element simulations are employed to generate sample data. The optimal response surface model is determined by comparing the goodness-of-fit (using evaluation metrics such as the coefficient of determination R2, root mean square error RMSE, etc.) among neural network, Kriging, and genetic aggregation methods. Key structural parameters of the cylinder are identified through sensitivity analysis using data generated from the optimal response surface, enabling the construction of a lightweight mathematical model that is solved using a multi-objective genetic algorithm. Experimental validation on ball mill demonstrates that the proposed method achieves 8.04% reduction in cylinder mass and 12.28% decrease in maximum deformation while maintaining equivalent stress within permissible safety limits.
In this paper, the time-dependent flow of a Newtonian fluid generated by a porous disk performing oscillation without torsion and the fluid at infinity rotating about two different axes is considered. As the disk and the fluid at infinity are rotating non-coaxially at the beginning of the oscillation motion, the disk initiates oscillations without torsion within its own plane. The exact solutions for the velocity and shear stresses within the fluid are presented and the influences of the suction and injection are analysed. The results indicate that increasing suction leads to a reduction in the length of the space curves associated with points at which the velocity is purely axial, whereas increasing injection results in an elongation of the curves. The application of suction leads to a decrease in the boundary layer thickness whereas it increases with the implementation of injection. Furthermore, a periodic solution is presented, and the analysis confirms that the time required for the flow to become periodic is shorter for both suction and injection cases.
The environmentally responsible disposal of waste cooking oil is a significant concern for numerous nations. One method to repurpose waste cooking oil is to employ it as diesel fuel. This approach diminishes both the expense of fuel feedstocks and the ecological repercussions of waste cooking oil. In this study, the use of waste cooking oil as fuel was achieved by converting it into biodiesel thru the transesterification method. The negative thermos-physical properties of biodiesel, due to its high density and viscosity, have been improved by increasing the injector injection pressure. Furthermore, the optimal injection advance value for engine torque was established, and combustion properties were enhanced. The impact of varying injection pressures and timings of biodiesel on engine performance, combustion characteristics, and exhaust emission parameters was examined in a three-cylinder, naturally aspirated direct injection diesel engine. Consequently, increasing both injection pressure and advance favorably affected combustion characteristics such as ignition delay, combustion duration, and the crank angle at which maximum pressure was achieved. Thanks to an increase in injection pressure, the specific fuel consumption improved by 6.74% and thermal efficiency by 10.14% compared to using biodiesel into regular engine parameters. The impact of injection advance was more significant in the exhaust emission parameters. Extra reductions of 7.92%, 5.79%, and 3.14% were established for CO, HC, and smoke opacity emissions, respectively. Enhanced combustion efficiency, leading to elevated end of combustion temperatures, resulted in a rise of up to 15.66% in NOX emissions.
Aspherical optical elements have significant advantages over traditional spherical elements, and have become the core technology for high-resolution imaging, intelligent devices, and precision instrument upgrades through optical performance, simplifying system structure, and reducing manufacturing costs. It has gradually promoted the development of optical systems towards high performance, lightweight, and high quality. However, the rapid development of aspheric optical elements is limited by the detection technology of aspheric surface profile. In order to solve the problems of detection principle error, low detection efficiency, expensive detection instruments and poor general performance in the current non-spherical optical elements shape detection technology, a new principle of non-spherical surface shape detection is proposed based on the theory of the closest circle, and the detection numerical model of non-spherical is constructed. At the same time, based on this, the overall structure design of small aperture non-spherical surface shape detection instrument is carried out, and the specific steps of detection instrument to implement small aperture non-spherical surface shape detection are analyzed. In order to further improve the detection accuracy of the small-caliber non-spherical surface profile detector, the detection technology of the geometric error of the is studied. The spatial geometric error detection of the moving axis of the small-caliber non-spherical surface profile detector is carried out by using the laser interferometer, and the compensation scheme of the small-caliber non-spherical surface profile detector is proposed through the analysis of the error compensation logic. In addition, the mathematical model of geometric error is established. The correctness of the research content is effectively verified by carrying out the geometric error compensation experiment on the moving axis of the small-caliber non-spherical surface profile, and the research on the accuracy improvement of the small-caliber non-spherical surface profile detector is completed.
To address the issues of low calibration accuracy, complex system structure, and cumbersome detection processes in traditional angular measurement equipment, this study proposes an innovative Opto-Mechanical coupled high-precision angular measurement turntable solution based on the principle of reciprocal angular displacement measurement. By systematically analyzing the structural characteristics and error distribution patterns of the turntable, a comprehensive error mathematical model based on relative pose matrices was established, enabling quantitative characterization of the error characteristics in the high-precision angular measurement turntable system. The threepoint reverse decoupling algorithm, combined with a systematic continuous error compensation strategy, effectively suppresses installation errors of the components under test on the turntable. Furthermore, by optimizing BP neural network parameters using an improved particle swarm optimization algorithm, the system's error compensation performance was significantly enhanced. Experimental results demonstrate that the compensated system achieves a calibration accuracy of 0.38 '', meeting the sub-arc-second precision calibration requirement. The post-compensation overall error distribution remains within +/- 0.5 '', and the reliability and accuracy of the turntable system were thoroughly validated through multiple comparative experiments. This study provides a novel technical approach for high-precision angular measurement.
The pressure-driven flow of methane in silicon nano slits is analytically studied by using Zhang's multiscale scheme (to handle the hybrid continuum and non-continuum flow) for the wide channel heights ranging between 8.6 nm and 1444 nm when there is the intermediate (continuum or quasi-continuum) fluid film between the two non-continuum adsorbed layers and no wall slippage occurs. Zhang's multiscale scheme for nanochannel flow well matches full molecular dynamics simulation with a good accuracy of the calculated total flow rate through the nanochannel. The values of the characteristic parameters of the adsorbed layer required by Zhang's approach were found from molecular dynamics simulation, and they are considered as independent on the channel height. According to the calculation results, the adsorbed layer encumbers the flow in the whole channel especially for the low channel heights which give the ratio of the thickness (hbf) of the adsorbed layer to the thickness (h) of the intermediate continuum fluid film no less than 0.1, and this makes the total volume flow rate through the channel about 35% smaller than the classical Hagen-Poiseuille equation calculation. The flow is not sensitive to the variation of the value of the ratio (q0) of the neighboring fluid molecule separations across the adsorbed layer thickness once the thickness of the adsorbed layer is fixed. With the increase of the channel height, the effect of the adsorbed layer is weakened. When hbf/ h < 0.01, the reduction of the total flow rate through the channel owing to the adsorbed layer is no more than 5.5% and the effect of the adsorbed layer can be considered as negligible. These disciplines of the Poiseuille flow in nanochannels renders the great application values of the adsorbed layer in improving the load-carrying capacity of micro bearings with very low clearances.
To address the lack of research on the dynamic characteristics of asymmetric helical gears, this study systematically investigates their time-varying meshing stiffness and meshing impact characteristics based on the lumped-parameter method and nonlinear dynamic theory. An eight-degree-of-freedom dimensionless dynamic model is developed. Using the pressure angle on the driving side as the main variable, the dynamic characteristics of asymmetric and symmetric helical gears are compared, and the effects of different pressure angles on time-varying meshing stiffness, time histories, phase portraits, and Poincar & eacute; maps are analyzed. The results show that the asymmetric helical gear exhibits higher average meshing stiffness, smaller vibration amplitudes, and smoother responses than the symmetric gear. Within a driving-side pressure angle range of 30 to 35 degrees, the system achieves the best stability and periodicity, and the meshing impact amplitude is effectively suppressed. However, excessively small or large pressure angles lead to reduced system stability. This work clarifies the dynamic behavior of asymmetric helical gears and provides a theoretical basis for parameter design and high-performance transmission optimization.
The simulation of the hot stamping process for the rear windshield lower crossbeam in aluminum alloy automobiles was carried out. Contrasted with the one-step forming process, the maximum thickness increase rate was lowered by 6.1% and the maximum thinning rate was decreased by 24.8% using the two-step forming process. Under identical process parameters, the minimum thickness of two-step formed parts was greater than that of one-step formed parts. The forming experiment was conducted by employing the self-developed modular hot stamping die. A gradient boosting regression tree machine learning model for the maximum thickening rate and the maximum reduction rate of the parts was established, and the optimal process parameters matching for the hot stamping of the rear windshield lower crossbeam were obtained based on the NSGA-II multi-objective optimization algorithm, namely, forming temperature 570 degrees C, friction coefficient 0.15, stamping speed 450 mm/s and die clearance 1.05t.
Fault diagnosis method for rolling bearings by using entropy-weighted distance-based local tangent space alignment and Weighted Gaussian Kernel extreme learning machine with Circle chaotic mapping-based grey wolf optimization (ELTSA-CGWGKELM) is presented in this paper. This study introduces two innovative methodologies for rolling bearing fault diagnosis. First, an entropy-weighted distance-based local tangent space alignment (ELTSA) technique is developed to address feature dimensionality reduction in rolling bearing data. This approach effectively resolves limitations associated with conventional Euclidean distance measurement while significantly enhancing critical data information preservation capabilities. Secondly, a weighted Gaussian kernel extreme learning machine optimized through circle chaotic mapping-enhanced grey wolf optimization (CGWGKELM) is proposed for fault classification. The Gaussian kernel implementation substantially improves nonlinear processing performance and robustness compared to traditional weighted ELM architectures. The circle chaotic mapping strategy integrated into the grey wolf optimization algorithm (CGWO) enables superior optimization of the weighted Gaussian kernel ELM training parameters, ensuring enhanced global search capability and convergence efficiency. The experimental results indicate the following fault diagnosis accuracy rates for rolling bearings: ELTSA-CGWGKELM achieves 99.5%, LTSA-WGKELM attains 95.5%, LTSA-ELM reaches 94%, and PCA-ELM attains 92%.It can be seen that ELTSA-CGWGKELM is the better fault diagnosis ability for rolling bearings than LTSA-WGKELM, LTSA-WGKELM, and PCA-ELM.
The areas of application of carbon dioxide lasers in the printing industry are given. A technological process for laser engraving of packaging made of wood-fiber materials has been developed. Experimental studies of the influence of the parameters of CO2 laser radiation on the engraving process of HDF material, which is widely used in the packaging industry, have been conducted. The dependence of the engraving depth on changes in the speed and power of laser radiation has been studied. Based on the experimental studies conducted, the main operating, technological and operational factors affecting the quality of engraving have been identified.
This paper presents an experimental investigation into the use of water, ethanol, and acetone using the suspended droplet method. The influence of atmospheric air temperatures on droplets in the transient phase change is analysed. Experimental results are presented, including thermograms that characterise the droplet's thermal state and diameter monograms that define the variation in droplet size. These data are processed according to the droplet liquid volume change rate parameter. The experimental results confirm that the airflow temperature leads to intensified heat exchange and phase change processes during the droplet transition stages, resulting in the droplet's heating to a higher thermal equilibrium evaporation state. For all the fluids studied, the impact of airflow temperature on the droplet temperature and liquid volume change rate of different liquids is qualitatively similar. Still, the strength of the influence varies depending on the nature and properties of the liquid. In heated air up to 50 °C, the droplet equilibrium temperatures are approximately 8.5 °C for acetone, 22.2 °C for ethanol and 28.3 °C for water. In 100 °C air, these values become approximately 17.8 °C, 32.3 °C and 43.4 °C, respectively. The estimated volume change in the liquid droplet's size shows that acetone, which has the most volatile properties and lowest boiling temperature, evaporates most intensely from the liquids tested in the initial stage.
