This study develops an enhanced surrogate modeling method integrating back propagation neural network (BPNN) with an improved sparrow search algorithm (SSA) reinforced by reinforcement learning (ISSA-RL). The SSA algorithm is substantially modified through Tent chaotic mapping for population initialization to improve distribution uniformity, combined with a nonlinear adaptive weighting strategy to better balance global and local search capabilities. A multi-agent reinforcement learning framework based on Q-learning is incorporated to dynamically adjust search strategies according to prediction error and population diversity metrics. The proposed method demonstrates high predictive accuracy, which is rigorously validated through benchmark functions and engineering applications. The BPNN-based surrogate model effectively replaces computationally expensive finite element analyses, while uncertainty quantification techniques enhance model robustness against material property fluctuations and loading variations. To determine the optimal configuration of a framed body-in-white (BIW), a structural optimization considering four types of discrete design variables is formulated and optimized by the proposed method. The results show that a 29.2% mass reduction and higher computational efficiency are achieved. The integration of multi-variable optimization with enhanced neural network training and intelligent search algorithms significantly improves both design quality and computational efficiency for complex BIW structures.

Geogrid reinforcement is a feasible technique for improving the mechanical and deformation behaviors of calcareous gravelly sand that is predominantly distributed in reclaimed foundations as construction materials. However, the shear behavior of geogrid-reinforced calcareous gravelly sand still remains unclear. In this paper, a series of large-scale drained consolidated triaxial compression tests (the specimen 300 mm in diameter by 600 mm in height) were conducted to investigate the effects of confining pressure, moisture content and geogrid inclusion on the mechanical and deformation behaviors of calcareous gravelly sand. The dilation effect, strain-softening behavior, reinforcing effect and particle breakage characteristics of unreinforced and geogrid-reinforced calcareous gravelly sand were comprehensively analyzed and discussed. Additional analysis was also performed from a microscopic perspective using the three-dimensional discrete numerical modelling. The experimental results indicate that calcareous gravelly sand exhibited a greater resistance to strain-softening tendency, and produced a higher susceptibility to crushing under the same input energy than calcareous coarse sand. Geogrid inclusion can effectively mitigate the susceptibility of calcareous gravelly sand to volumetric dilation through constraining the lateral expansion within the reinforced zone, and thus substantially increased the peak shear strength. Moreover, particle breakage appeared to be insensitive to geogrid reinforcement and water content, but increased significantly with increasing confining pressures. The numerical results further indicate that the mechanical response of geogrids was regulated by axial strain and confining pressure. As axial strain was greater than 10%, increased confining pressure resulted in a wider area of stress concentration within the geogrid meshes, and the upper geogrid sustained a greater contact force and tensile strain. The findings in this study are of practical significance for the design and construction of structures in calcareous gravelly sand reinforced with geogrids.

In real life, there are a lot of uncertainties in engineering structure design, and the potential uncertainties will have an important impact on the structural performance responses. Therefore, it is of great significance to consider the uncertainty in the initial stage of structural design to improve product performance. The consensus can be reached that the mechanical structure obtained by the reliability and robustness design optimization method considering uncertainty not only has low failure risk but also has highly stable performance. As a large mechanical system, the uncertainty design optimization of key vehicle structural performances is particularly important. This survey mainly discusses the current situation of the uncertain design optimization framework of automobile structures, and successively summarizes the uncertain design optimization of key automobile structures, uncertainty analysis methods, and multi-objective iterative optimization models. The uncertainty analysis method in the design optimization framework needs to consider the existing limited knowledge and limited test data. The importance of the interval model as a non-probabilistic model in the uncertainty analysis and optimization process is discussed. However, it should be noted that the interval model ignores the actual uncertainty distribution rule, which makes the design scheme still have some limitations. With the further improvement of design requirements, the efficiency, accuracy, and calculation cost of the entire design optimization framework of automobile structures need to be further improved iteratively. This survey will provide useful theoretical guidance for engineers and researchers in the automotive engineering field at the early stage of product development.

To meet the requirements of a specific ship's controllable pitch propeller system in terms of adjustment time, tracking accuracy, and leakage, a servo-valve controlled cylinder hydraulic system with mechanical feedback was designed. System working principle was analyzed, and a simulation model including mechanical linkages, electric cylinder, servo valve and hydraulic cylinder were established based on AMESim to analyze how servo valve underlap value and radial clearance between spool and sleeve, electric cylinder displacement and system working flow rate affect pitching propeller system static and dynamic characteristics, and optimize the above four parameters. Experiment and engineering practice verified that improved system's pitching stroke error was 2.04mm, tracking accuracy error was 0.2s, pitching time was reduced from 10.1s to 5.9s, and valve zero position leakage was less than 2L/min, which met the system working requirements. And simulation results provided a theoretical basis for the improvement and design of similar mechanical hydraulic servo systems.

The sealing performance of a reciprocating seal degrades during service. The analyses developed based on the initial state of a seal cannot express the performance degradation due to seal wear in detail. In this research, the Archard model in dry friction is extended to mixed lubrication by introducing the lubrication coefficient verified by an experiment. The nonlinear adaptive meshing technique is used in finite element analysis (FEA) to simulate the material removal to obtain the static contact pressure during the wear process. Hence, a sealing performance degradation analysis method is proposed based on the modified Archard model for reciprocating seals under mixed lubricating conditions. This method can be used to analyse the sealing, lubrication, and wear characteristics of seals at any service time. The simulation results indicate that the static pressure becomes more uniform with the occurrence of seal wear, and the lubricating property of the oil film reduces the seal wear. The variation trends of the sealing performance parameters such as contact pressure, friction, and net leakage at different service times under specific operating conditions are obtained.

This paper proposes a new fully automatic computational framework from continuum structural topology optimization to beam structure design. Firstly, the continuum structural topology optimization is performed to find the optimal material distribution. The centers of the elements (i.e., vertices) in the final topology are considered as the original model of the skeleton extraction. Secondly, the Floyd-Warshall algorithm is used to calculate the geodesic distances between vertices. By combining the geodesic distance-based mapping function and a coarse-to-fine partition scheme, the original model is partitioned into regular components. The skeleton can be extracted by using edges to link the barycenter of the components and decomposed into branches by identified joint vertices. Each branch is normalized into a straight line. After mesh generation, a beam finite element model is established. Compared to other methods in the literature, the beam structures reconstructed by the proposed method have a desirable centeredness and keep the homotopy properties of the original models. Finally, the cross-sectional areas of members in the beam structure are considered as the design variables, and the sizing optimization is performed. Four numerical examples, both 2D and 3D, are employed to demonstrate the validity of the automatic computational framework. The proposed method extracts a parameterized beam finite element model from the topology optimization result that bridges the gap between the topology optimization of continuum structures and the subsequent optimization or design that enables a fully automatic design of beam-like structures.

The reliability of stern shaft sealing in large ships is affected by the large pressure fluctuation caused by changes in immersion depth. To investigate the dynamic performance of the pressure adjustable air seal system for stern shaft, a mathematical model is established by segmenting the system according to the position of valves and chambers, and a constant pressure difference control strategy is devised. The simulation results reveal the effects of various factors on system response. The results indicate that the sealing flow rate decreases by 2.5 g/s for every 5 μm decrease in the width of lip seal gaps; The overshoot of intake flow is influenced by both the change rate of immersion depth and the volume of air chambers; The maximum overshoot flow rate increases by 2.1 g/s for every 1 m/s increase in the depth change rate, and by 0.05~0.1 g/s for every 0.001 m 3 increase in chamber volume; The rapid change rate of immersion depth can prolong the pressure response time, which extends by 0.4~0.5 seconds at 4 m/s, and by 2 seconds at 6 m/s. Based on the findings, the required widths of the lip seal gaps to achieve rapid pressure relief at different depth change rates are summarized, providing references for the design and engineering practice.

This study proposes a multi-objective optimization (MOO) strategy with an improved constraint-handling technique to improve the crashworthiness of an excavator rollover protective structure (ROPS). First, the experimental test under the ISO 12117 criteria is conducted and the developed numerical model is verified. Then, the amounts of energy absorption and the cross-sectional forces of components in the ROPS are analyzed. The main energy absorbing and load carrying components are identified. Finally, the thicknesses of the identified components are considered as the design variables. A multi-objective crashworthiness optimization process aims at improving the safety distance and reducing the total mass is designed by the finite element analysis-based surrogate model technique and a modified MOO algorithm. The proposed algorithm modifies the objective function values of an individual with its constraint violations and the true objective function values, of which adaptive penalty weights fed back from the constraint violations are used to keep the balance. Compared with the existing methods, it is found that the optimal solutions obtained by the proposed algorithm show superiority on convergence rate and diversity of distribution. The optimal results show that the safety distance is 27.42% higher while the total mass is 7.06% lower than those of the baseline design when it meets the requirements of ISO 12117. This study provides an alternative crashworthiness design route for the ROPS of the construction machines.

The structural parameters of the seal directly affect the friction performance of the reciprocating seal and determine the service life of the seal. For the low friction combination seal structure of an aerospace actuator, a two-dimensional model is established by the finite element method to investigate the influence of three structural parameters on the contact stress distribution, which include the pre-compression rate, the upward inclination angle of the wear ring, and the inner surface width of the wear ring. Aimed to reduce the sealing friction, the response surface method is used to optimize the structural parameters in terms of the simulation data. The results show that the friction is much higher in the instroke than in the outstroke. The pre-compression rate of the seal and inner surface width of the wear ring have a greater influence on the instroke friction than the upper inclination angle of the wear ring. Through the response surface method, the optimal dimensional parameters of the seal structure are obtained, and the friction of the optimized seal structure during the instroke is effectively reduced. The research has a certain engineering guiding significance for the optimization design of the aero-actuator seal.

Tractor and earth-moving machine rollover has become one of the leading causes of occupational death in the agricultural/constructional industry. Therefore, these machines need proper protective structures to protect operators. In this study, explicit finite element (FE) analysis is adapted to predict the performance of rollover protective structure (ROPS) of a hydraulic excavator in the early design stage based on ISO 12117-2. The virtual test includes three sequential quasi-static loads applied in side, longitudinal and vertical directions, one at a time. Well-organized load sequence enables the simulation model to take the cumulative deformations caused by the three sequential loads into account and reduce the computational cost. A ROPS prototype is fabricated and tested to validate the FE model. The simulation-based results have a close agreement with the experimental test results. This FE-based safety prediction could be used to assess the new design in the early design stage to save design time and money.

When using the method of matching the resonant cavity eigenfrequency to measure the backscatter coefficient of a laser gyro resonant cavity, the weak backscattered optical signal in the ring resonant cavity excited by the non-uniform loss on the optical path and the non-uniformity of the refractive index is accompanied by strong noise during the measurement, which is difficult to be extracted efficiently by the conventional amplifier, resulting in the low detection accuracy and poor repeatability of the backscatter coefficient by this method. As the Kalman filter is a state-optimal estimation algorithm with good adaptability, in order to further improve the signal-to-noise ratio, it is proposed to use a Kalman filter for secondary filtering after the phase-locked amplification link to further reduce the noise superimposed on the resonant cavity locked frequency signal, thus improving the detection accuracy of the backscatter coefficient. Simulations in Simulink have shown that the output signal volatility of the proposed method is reduced by 33.2% compared with that of a conventional lock-in amplifier for the same input signal; the accuracy of the proposed method is improved by 10.3% compared with the conventional method when measuring the backscattered light of a laser gyro resonant cavity.

This study proposed a discrete structural optimization method for a framed automotive body. Up to four types of discrete design variables are considered simultaneously, that is, the sizing, cross-sectional shape, topology, and material variables. Firstly, to solve the nonconvex and nonlinear optimization problem, the original non-dominated sorting genetic algorithm, the third version (NSGA-III), is adapted. An improved extreme points identification scheme and a new mutation operator are proposed to stabilize the normalization of the population and accommodate the manufacturing constraints, respectively. Two test problems demonstrate that the modified NSGA-III can handle continuous and discontinuous multiple objective optimization. Subsequently, the classical 10-bar truss is used to illustrate the proposed method. A weight reduction of 4.5 kg is achieved as compared to previous optimal designs in the literature. Finally, a framed automotive body is optimized for maximizing the first order natural frequency and minimizing the total mass, the maximum stresses and the maximum displacements in different load cases and the manufacturing cost. The results obtained by different optimization procedures are presented and discussed. The results demonstrate the feasibility and effectiveness of the proposed method. A weight reduction of 17.59% is achieved while other structural performances satisfy the design requirements.

Stress-based topology optimization is one of the most concerns of structural optimization and receives much attention in a wide range of engineering designs.To solve the inherent issues of stress-based topology optimization, many schemes are added to the conventional bi-directional evolutionary structural optimization (BESO) method in the previous studies.However, these schemes degrade the generality of BESO and increase the computational cost.This study proposes an improved topology optimization method for the continuum structures considering stress minimization in the framework of the conventional BESO method.A global stress measure constructed by p-norm function is treated as the objective function.To stabilize the optimization process, both qp-relaxation and sensitivity weight scheme are introduced.Design variables are updated by the conventional BESO method.Several 2D and 3D examples are used to demonstrate the validity of the proposed method.The results show that the optimization process can be stabilized by qp-relaxation.The value of q and p are crucial to reasonable solutions.The proposed sensitivity weight scheme further stabilizes the optimization process and evenly distributes the stress field.The computational efficiency of the proposed method is higher than the previous methods because it keeps the generality of BESO and does not need additional schemes.

Mesh segmentation is a powerful tool for the management of digital models. Reeb graph based segmentation is robust to the variations of model pose and insensitive to the highly noised model. Thus, in this paper, an improved Reeb graph based mesh segmentation for the topology optimization result is proposed. Generally, the topology optimization result is short of prominent components. Therefore, previous mesh segmentation methods are difficult used for the mesh segmentation of the topology optimization result. By combining methods proposed in literature, a new mapping function is proposed. Firstly, feature points are extracted from the original mesh. Then, the mapping function is defined as the summation of geodesic distances of a generic vertex to all of the feature points. Subsequently, vertices are classified into different patches based on their mapping function values. The aforementioned steps are repeated with each patch considered as the new model until a desirable solution is obtained. To demonstrate the proposed method, two numerical examples are solved by the proposed method and methods presented in literature. The results demonstrate that, for the topology optimization results, the proposed method could generate a better solution which can facilitates the further post-processing of the topology optimization results.

Handle driving forces are the input of the automotive sliding door dynamic system and play an important role for ensuring a smooth closing process during manual sliding door mechanism design. It is important to provide a reliable and accurate input for the manual sliding door mechanism during the design and analysis stage. This paper aims to present an improvedK-medoids clustering algorithm to investigate the characteristic of handle driving forces in manually closing an automotive sliding door based on experimental data. The improvedK-medoids clustering algorithm includes two stages: observation-based clustering stage and traditionalK-medoids clustering stage. In all, 134 subjects have been recruited to manually close the sliding door in the lab and the handle driving force data are collected and processed. The handle driving forces are described in the sliding door coordinate system (XYZ) fixed on the door. This study mainly focuses on the X direction force component clustering analysis. The first stage of the improved algorithm classifies the X direction force components into three clusters based on force curve shapes. Then, each of the above identified three clusters is clustered with the traditionalK-medoids clustering algorithm. Results show that the X direction force component has three different shapes: Shape 1-only one crest in the curve, Shape 2-two crests in the curve, and Shape 3-one crest and one trough in the curve. The forces with three different shapes are finally divided into six clusters and the amplitude and time duration are similar for X direction forces within the same cluster and are different in the different clusters. The medoids of these clusters are the mined representative prototypes. Compared to the pure traditionalK-medoids algorithm, the improved algorithm can provide much better results that give insights on subjects' door closing behaviors.

To reduce the weight and improve the structural performances of a passenger car rear seat frame, this study uses a discrete structural optimization method to design an aluminium alloy seat frame to replace the original steel one. The optimization problem aims to minimize the total mass, manufacturing cost, the maximum displacements and tensile stresses under certain load conditions and maximize the first order natural frequency. The cross-sectional dimensions and material types of members in the seat frame are considered as the design variables. A modified non-dominated sorting genetic algorithm, the third version (mNSGA-III) which is adapted at handling problems with four or more objective functions, is used to solve the optimization problem. To benchmark the performance of the proposed method, a multidisciplinary design optimization (MDO) method is also utilized to solve the optimization problem. The comparison between the solutions obtained by the proposed method and the MDO method shows that the accuracy and the effectiveness of the proposed method are better. A weight saving of 35.1% is achieved by the aluminium alloy seat frame as compared to the original steel seat frame.

Transfer path analysis (TPA) method has been widely used in the frequency-domain applications. However, it is not suitable for transient vibration problems such as the abnormal vibration in the automotive door slamming event. In this paper, two time-domain TPA models are used for the abnormal transient vibration diagnosis in the automotive door slamming event whenever the door glass is located at its lowest location. To obtain the excitation forces, lab experiments have been carried out for the whole vehicle and door system. In the experiment, a door closing velocity device is built to maintain the closing speed (1.5 m/s) to obtain the operational responses of the indicator points on the 1st and 2nd transfer paths, as well as the target points. The frequency response functions (FRFs) for the 1st transfer path are then recorded using the experiment, including the excitation points to its indicator points and the excitation points to the target points. The FRFs for the 2nd transfer path are obtained using the finite element analysis (FEA), including the excitation points to its indicator points and the excitation points to the target points. With the two time-domain TPA models, the contribution of each transfer path can be obtained. The results show that the two time-domain TPA models can predict the transient vibration in the door slamming event. They also show that the main transfer paths of the abnormal vibration are from the upper door frame on the 1st transfer path and the regulator channel on the 2nd transfer path. These results provide insights for the improvement of the regulator channel and glass run channel designs in order to mitigate the abnormal transient vibration in the door slamming event.