Body centered cubic (BCC) structure has excellent mechanical properties, but the stress concentration phenomenon at the nodes limits its further development in mechanical properties. At present, the method of adding spherical nodes or variable cross-section pillars is commonly used to alleviate stress concentration at nodes and achieve strengthening design of lattice structures, but there is a lack of research on the influence of the volume ratio of nodes to pillars on the strengthening effect. A new type of variable cross-section pillar based on trigonometric function reduction is designed, and a variable cross-section body centered cubic lattice (VC-BCC) lattice is designed. Dynamic node design is achieved by directly connecting the pillars to explore the optimal node to pillar volume ratio. Theoretical formula estimation of the volume of VC-BCC lattice is carried out, and based on the Timoshenko beam model, the equivalent elastic modulus of VC-BCC lattice is theoretically analyzed. A simplified model is established using the method of equivalent cross-section. Finite element simulation analysis was conducted on VC-BCC lattice with different proportions of node pillars, and lattice specimens were manufactured using selective laser melting technology for quasi-static compression testing. The experimental results show that there is little difference between theoretical calculations and simulation analysis. The maximum stress of the VC-BCC lattice structure is significantly reduced, and the equivalent yield strength is significantly improved. In all analyses, the VC-BCC lattice structure with a variable cross-sectional parameter of 0.6 exhibited excellent performance and had the best overall mechanical properties.

In order to improve the traditional design concept and the lack of optimization of genetic algorithm, and promote the development and innovation of the shape optimization of truss structure, according to the basic principles of harmony search algorithm and genetic algorithm, a new hybrid genetic algorithm-harmony search genetic algorithm was proposed (the mixing of genetic algorithm and harmony search algorithm is to embed the harmony search operator after the operation of the genetic algorithm), and at the same time the cross-variation in the genetic algorithm was adaptively improved in three situations, and elitism and other improvement measures were introduced. In addition, the harmonious search algorithm is processed with mixed variables of discrete variables and continuous variables, and a truss structure shape optimization method based on the harmonic search hybrid genetic algorithm was established. In the optimization process, the two different types of design variables of node coordinates and cross-section area were considered uniformly, which solves the problem of difficulty in coupling of the two types of variables. Through the analysis of two typical examples, the results show that the harmonic search genetic algorithm (HS-GA) has efficient convergence speed and strong global ability. Compared with genetic algorithm (GA), heuristic particle swarm optimization (HPSO) and other optimization algorithms, the optimization effect is obvious, and it is a method suitable for the shape optimization of truss structure.

Considering cracks of various length and depth (various constraints) on the nuclear power main pipeline as the research object, through the mass acceleration application method, applying vertical load of 5 earthquake intensities and 3 real earthquakes to the nuclear power main pipeline under varying constraints respectively, and based on a method to determine the constraint related to fracture toughness of the actual structure, the calculation of constraint related fracture toughness was performed, the various constraint under various vertical earthquake loads related crack toughness was systematically studied.The results show that under the same constraint, the crack opening force curve shifts to the left with the increase of earthquake intensity, and the constraint related fracture toughness decreases gradually.With an increased crack length, the effect of earthquake intensity on constraint related fracture toughness becomes more obvious.With an increased crack depth, the effect of earthquake load on constraint related fracture toughness firstly becomes obvious, and then becomes insignificant.Under different constraints, the influence trend of the real earthquake load on constraint related fracture toughness is the same as that of the earthquake intensity, and has a certain relation with the magnitude and earthquake acceleration time history curve.

Accurately predicting the fatigue life of products plays an important role in the structural strength design and reliability design of key components of electric vehicles.Starting from the measured road load spectrum of the reinforced road,a method for data processing and analysis of measured load spectrum was proposed, based on the Miner criterion, the load data of the vehicle under no-load, half-load and full load were obtained, and the key data for vibration simulation analysis and indoor bench test were obtained through time-domain frequency domain processing and damage equivalent treatment.A parallel-shaft electric drive axle was designed and developed, the statics analysis and modal analysis were carried out for key components such as the bridge shell, and the results concluded that the bridge shell would not have torsion and bending caused by road surface excitation.Based on nCode DesignLife simulation analysis software, the fatigue life and damage value distribution of the bridge shell were obtained, and the accuracy of the simulation analysis was verified by the bridge shell durability test.Based on the measured road load spectrum of the reinforced road, a 15 000 km vehicle vibration test was carried out on the vehicle vibration test bench for the electric drive axle.The test shows that the overall life and reliability of the electric drive axle meet the design requirements, and the reliability of the analysis method is verified.

Accidental mechanical impacts such as forklifts may lead to serious degradation of the stability of industrial rack uprights.The finite element simulation model of the upright bending damage was established based on the physical test mechanism with five types of common upright in the industry as examples, and the analysis found that even a small impact deformation (1 mm) may lead to a decrease in the ultimate bearing capacity of the upright (maximum about 37%).Compared with other impacted positions, the bending damage at the prism made the upright stability decrease more significantly.Based on this, an intelligent prediction model of the bending damage state of the upright was established by physical simulation and convolutional neural network method.The results show that the residual load capacity values of the damaged upright obtained from the prediction model agree well with the finite element simulation data (the mean absolute percentage error is 5.99%) and can be used for rapid assessment of the bending damage performance of the rack upright.

Based on two basic configurations of hexagonal and inner concave shapes, by utilizing experimental test and finite element simulation method, the crack expansion law of laminated porous structures under three-point bending was studied, the influence of cellular element angle of laying direction on failure mode, load capacity, and deformation of the laminated porous structures was discussed. The results indicate that the crack expansion path in the bilayer model deviates towards the weaker layer with less crack expansion inhibition capability. The weaker side experiences greater deformation,leading to a deviation of the model towards the stronger side. Under certain angle combinations, the bilayer model shows significantly improved load-bearing capacity and toughness compared to the corresponding single-layer model.

In order to investigate the nature and causes of the cracked passage hole of the low-pressure turbine shaft of aero-engine during the high and low circumference compound fatigue test, the low-pressure turbine shaft crack location was examined in appearance, fracture analysis, surface inspection, metallographic organization, finite element analysis and crack expansion simulation.The results show that the low-pressure turbine shaft passage hole crack failure is a fatigue crack, which is caused by the incomplete removal of the remelting layer after the passage hole is cut by electrical discharge machining,resulting in the existence of part of the unremoved remelting layer and visible microcracks on the internal surface, and the fatigue crack sprouted and crack expansion occurred under the action of large high and low circumferential composite load,thus leading to the passage hole crack failure. The initial crack length is estimated to be between 0.2-0.3 mm by the crack expansion simulation analysis. In order to ensure the processing quality of the through oil hole, considering the poor processing accessibility of this location, it is suggested that special tooling can be designed and the machining technology can be used for processing, on the basis of ensuring the processing, fundamental eliminate the influence of the remelting layer.

The research on multiaxial fatigue life prediction of materials is one of the critical elements in ensuring the structural integrity of components. In recent years, machine learning, especially neural networks, has been widely applied in fatigue life prediction. However, the scarcity of fatigue data has limited the further application of neural networks in fatigue prediction. To address this issue, physics-informed neural networks that consider prior physical knowledge of fatigue have gradually gained attention. Firstly, provided an overview of the classification of machine learning algorithms and the application of neural-network models in multiaxial fatigue life prediction. Then, it focused on a deep exploration of the research on material fatigue life prediction based on physics-informed neural networks. Finally, the development of physics-informed neural networks was introduced from three aspects: physics-informed input features, the construction of physics-informed loss functions, and physics-informed network frameworks. Relevant studies show that physics-informed neural networks can exhibit better physical consistency and prediction performance in the process of multiaxial fatigue life prediction of materials.

In order to study the influence of residual stress and hardness on bending fatigue performance of gear, the 20MnCrS5 steel gear with carburizing heat treatment was taken as the research object, and composite small diameter shot peening strengthening treatment was carried out to realize the gear with different hardness and residual stress states of the same material.Based on the maximum principal strain criterion, incorporating separate factors for residual stress influence and residual stress-hardness coupling influence were introduced respectively to establish the fatigue life prediction model.Through shot-peened gear bending fatigue tests, optimal values for both the residual stress influence coefficient and correction coefficient were determined.The two models’ accuracy for life prediction was contrasted, and the accuracy of these models was further verified through unshot peened gear bending fatigue test.The results show that considering only residual stress influence yielded an optimal value of 0.09 for the residual stress influence coefficient, the model achieving high life predictive accuracy.Whereas considering the effects of residual stresses and hardness, it requires a correction coefficient with an optimal value of 0.04, the model achieve even higher predictive accuracy.

For the contact fatigue failure problem of vehicles’ hypoid gears under complex conditions, the rain-flow counting method and Goodman’s average stress equation were used to establish a contact statics model.The load-time history of the contact gear surface was extracted. And the load spectrum of hypoid gears was produced.The research focused on predicting the high-cycling fatigue life of hypoid gears based on the load spectrum.The study also utilized the finite element method to simulate gear teeth’s meshing or contact behaviour under loading conditions. Moreover, the influence mechanism of fatigue damage criterion on the gear fatigue life prediction was revealed.The proposed method is highly significant in assessing and predicting the high-cycling fatigue life of vehicles’ hypoid gears.