To address the issue of gearboxes’ vibration and noise, multi-objective topology optimization was adopted to optimize the box structure.First, a combination weighting method known as game theory comprehensive analytic hierarchy process and grey correlation was proposed to allocate optimal weight values to sub-objectives. At the same time, the iterative curves of the optimization results of the three weighting methods were compared to verify the advantages of the combination weighting method.Then, the compromise programming method was used to normalize the sub objectives to obtain the comprehensive objective function.Finally, based on the topology optimization results, stress displacement nephogram, and modal shapes, the box structure was improved.Compared with the original box, the improved box reduces the mass by 11.2%,the maximum stress of the box decreases by 39.6%, the displacement decreases by 5.1%, the node displacement amplitude response decreases by 82.8%, and the all first four-order frequencies increase.The proposed weight allocation method improves the disadvantages of low reliability of sub objective weight value allocation and ignoring subjective judgment,realizes the lightweight of the box. After the improvement of the box structure, the static and dynamic performances are significantly improved.

The traditional Markov chain Monte Carlo (MCMC) simulation method is inefficient and difficult to converge in high dimensional problems and complicated posterior probability density.In order to overcome these shortcomings, a Bayesian finite element model updating algorithm based on Markov chain population competition was proposed. First, the differential evolution algorithm was introduced in the traditional method of Metropolis-Hastings (MH) random walk algorithm.Based on the interaction of different information carried by Markov chains in the population, optimization suggestions were obtained to approach the objective function quickly. It solves the defect of sampling retention in the updating process of high-dimensional parameter model. Then, the competition algorithm was introduced, which has constant competitive incentives and a built-in mechanism for losers to learn from winners. Higher precision was obtained by using fewer Markov chains, which improves the efficiency and precision of model updating. Finally, a numerical example of finite element model updating of a truss structure was used to verify the proposed algorithm.Compared with the results of standard MH algorithm, the proposed algorithm can quickly update the high-dimensional parameter model with high accuracy and good robustness to random noise. It provides a stable and effective method for finite element model updating of large-scale structure considering uncertainty.

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.

Octet-truss lattice structure is one of the preferred materials in engineering field with light, high strength and high toughness properties.Three-point bending experiments were carried out on Ti6Al4V Octet-truss lattice structure with shallow pre-crack, and the fracture process was observed by digital image correlation (DIC) technique.To further study the fracture toughness of Octet-truss lattice structure, the fracture behavior of the structure under three-point bending load was analyzed by finite element method.The mechanical response of the truss member for the structure was characterized by the isotropic elastoplastic mechanical model.The validity of the finite element model was verified by experiments.Based on the elastic-plastic fracture behavior of the structure, the J-integral method was used to calculate the fracture toughness of the Octet-truss lattice structures.The results show that the fracture toughness of the Octet-truss lattice structure increases linearly with the relative density and the square root of the truss length.For the truss member at the crack tip, truss in different planes have different stress states and deformation modes with the same cross-sectional size.According to the failure mode of the structure,the stress state of truss from different planes is balanced by optimizing the proportion of the cross-section size, which can optimize toughness of the lattice structure with same relative density.

Considering the uncertainty associated with structural boundary conditions, a method for modifying the boundary constraint static model of beam structures was proposed based on the homotopy stochastic finite element method.The overall modification of both the beam body elements and boundary elements was achieved using uncertain static measurement data. By employing the static condensation method, computational degrees of freedom were ensured to match measured degrees of freedom. Regularization methods were applied to mitigate ill-conditioned solutions in modification equations for stochastic models. The probabilistic residual minimization method enables optimal selection of homotopy coefficients, ensured accurate identification of boundary constraints and precise overall modification. Finally, simulations on variable-section concrete beams and static loading tests on aluminum alloy beams were conducted to verify the effectiveness of this approach.

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 structure of the manipulator has the characteristics of high nonlinearity and strong coupling, and high-precision motion control is a hot topic of concern for scholars.The AR4 manipulator was used as the research object to systematically analyze the forward and inverse kinematics that greatly impact the control of the manipulator, determining the manipulator’s corresponding structural parameters.And the D-H method was used to solve the numerical calculation model of the manipulator forward and inverse kinematics.The cubic spline interpolation algorithm was used to optimize the manipulator's jitter phenomenon in the joint space.In Cartesian space planning, the linear interpolation method was used to reduce the end effector’s motion distance.The specific planning points were obtained by Matlab simulation, meeting the design requirements.Finally, the SolidWorks was used to establish a three-dimensional model of the manipulator and generate an unified robot description formatc (URDF) model.The actual trajectory of the manipulator in joint and Cartesian space was planned according to MoveIt, and through RViz, the movement process was displayed.The results show that after adding the cubic spline interpolation algorithm, the joint motors of the manipulator can maintain stable operation, and the joint trajectory curvature is respectively reduced by 15.4%, 35.6%, 21.3%, 26.8%, 18.98% and 45.7%, which effectively solves the jitter vibration problem during joint movement and achieves smooth motion of the manipulator.

Reinforced shell structure is widely used in aerospace load-bearing structures because its high specific stiffness and specific strength.By considering the uncertainty and risk factors in the structural parameters, the reliability-based design optimization (RBDO) can avoid the overly conservative design of the structure and ensure its reliability and safety.An efficient RBDO method based on adaptive surrogate model was proposed to solve the problem of lightweight design of reinforced shell structure under buckling reliability constraints.The adaptive addition of sample points was implemented through the expected feasibility function criterion, and the discrete variables was continued by constructing piecewise functions.This increases optimization efficiency while ensuring the reliability of design results.Finally, the effectiveness of the proposed method is verified by comparing the RBDO results with the deterministic optimization results.

Aiming at the issues of under-maintenance or over-maintenance in preventive maintenance of DSA200 type pantograph, a method was proposed to optimize inspection and maintenance parameters by using pantograph failure data.Firstly, the failure datas of the pantograph components were analyzed by using graph parameter method, which failure time distribution models were fitted.The failure datas were preliminarily determined to obey the exponential distribution, and the Bartlett value method was further used to verify the validity of the failure data obey exponential distribution.Secondly, based on the structure and working characteristics of pantographs, a reliability block diagram model with pantograph components in series was constructed.According to the characteristics of constant failure rate of pantograph components, the failure rate of pantographs was obtained.Thirdly, the minimum cost model of preventive maintenance and replacement of pantographs was established, and the optimal preventive maintenance interval and the optimal number of spare parts were obtained.Finally, the structure importance, probability importance and critical importance of pantograph components were analyzed by using fault tree analysis method, and the failure probability of pantograph and the key components in inspection and maintenance were obtained.The optimized pantograph inspection and maintenance parameters can provide scientific reference for maintenance personnel to improve their maintenance level and reduce maintenance costs.

During the operation of the BV500 type controlled seismic source vibrator in Sichuan and Chongqing areas,due to the improper plate design, the vibration energy down-transfer rate is low and the excitation signal distortion is serious.Therefore, the continuum topology optimization method was introduced, and a variable density method of the solid isotropic material with penalization (SIMP) model was used to optimize the design of BV500 controlled seismic source vibrator plate from two aspects — reducing mass and increasing stiffness, and an “octagonal I-steel-20a” plate was innovatively developed.After optimization, the mass of the plate was reduced by 45.29%, and the stiffness of the plate was increased by 79.92%, the vibration performance of the plate before and after optimization is studied.The simulation results show that compared with the original aluminum alloy plate, the energy down-transfer rate of the “octagonal I-steel-20a” plate increases by 15.11%, the displacement amplitude of the ground surface contact center point increases by 43.74%, and the amplitude of the interaction force increases by 40.56%.The field experiment shows that when the “octagonal I-beam-20a” plate is excited, the effective value of the average vibration velocity of the near-field signal of the detector is increased by 22.23%, and the effective value of the average vibration velocity of the far-field signal of the detector is increased by 39%, the law is consistent with the numerical simulation conclusion of controlled seismic source road excitation.The excitation performance of the “octagonal I-beam-20a” plate is better than that of the original aluminum alloy integral plate, which effectively improves the road excitation effect of BV500 type controlled seismic source in Sichuan and Chongqing areas.