Damage and fracture are the main causes of structural failure, which have a significant impact on engineering safety. Crack propagation problem is also a fundamental scientific challenge that needs to be solved urgently. In this paper, the relevant theoretical basis for simulating damage and fracture, such as a fracture mechanics model, damage evolution model and numerical calculation methods, such as the finite element method, boundary element method and peridynamics theory, are introduced in the form of literature review. This paper also reviews the commonly used CAE software for structural damage and fracture analysis, including general-purpose finite element programs such as the damage and fracture analysis module that comes with ABAQUS, as well as specialized fracture analysis software, damage tolerance tools, fatigue life analysis tools, etc. The development status of some autonomous CAE software is also discussed. Finally, this paper analyzes some challenges faced by CAE software for damage and fracture simulation, and looks forward to the future development direction of domestic CAE software.

A surrogate model is a new research idea direction of aerodynamic data generation. A traditional surrogate model relies on a large number of high-precision simulation sample points and their responses values to ensure the accuracy of the model. A multi-credibility surrogate model can reduce the computational cost while maintaining a certain accuracy by integrating multi-layer high and low credibility models, which is of great significance for reducing a missile development cycle. In this paper, the influence of different numbers of low-confidence sample points on the multi-confidence model and the optimal ratio of high-low-confidence sample points are studied, and a multi-confidence sampling method suitable for aerodynamics data is proposed. It is applied to the construction of three multi-credibility surrogate models in the prediction of missile aerodynamic data, among which the Co-Kriging model has the best comprehensive prediction effect. The recommended ratio of high and low confidence sample size is between 1: 4 and 1: 3.

In order to investigate the effect of cable damage on in-plane free vibration characteristics of cable-beam composite structures, three dimensionless parameters of cable damage intensity, extent and position are introduced in this paper to establish an in-plane dynamic model of single-cable cantilever beam composite structures with cable damage. The eigenvalue problem of in-plane free vibration of a single cable-cantilever beam model is solved by the method of separation of variables. At the same time, the finite element models under undamaged and damaged conditions of the cable are established for verification, and the results are in good agreement with the theoretical results. The results show that the frequency of the combined structure will decrease obviously only when the sag or damage intensity and extent of the cable are large. When the damage intensity and extent of the cable increase to a certain value, 1∶1 in-mode resonance phenomena tend to appear for high order frequencies. The asymmetric initial configuration caused by damage can increase the frequency of the combined structure, and some mixed modes of the combined structure change to local modes, while some local modes change to mixed modes.

Addressing the challenge of accurately solving unstable stick-slip vibration problems in non-smooth dynamics, this paper proposes a solution algorithm based on Physics-informed Neural Networks (PINN). Firstly, the classical stick-slip vibration problem is dynamically modeled using the linear complementarity theory under unilateral constraints. Then, the linear complementarity relationship is designed as a loss function to guide the training of the neural network, constructing a PINN algorithm for solving multi-point friction-induced stick-slip vibration problems. The accurate simulation of complex responses of multiple sliders'stick-slip vibrations in frictional systems is conducted. By comparing the numerical results with the Switching Model method that includes event detection and the traditional Time-Stepping method without event detection, the accuracy of the PINN algorithm is verified. The proposed PINN algorithm transforms the traditional optimization problem calculation into network training of the machine learning algorithm, making it suitable for stick-slip vibration analysis with multiple contact points. This method achieves accurate nonsmooth state transitions and provides a convenient and easy-to-use new approach for the accurate simulation of complex nonlinear vibration responses in multi-degree-of-freedom frictional systems.

The power battery pack of an electric vehicle is a complex system, whose efficient and high fidelity modeling is an urgent need for solving collision problems. This paper firstly proposes a hybrid reduced order battery pack model, with fine modeling in the central region and centralized mass in other parts through a simple connection contact. Compared with the refined full model, the maximum stress error is relatively small, and the computational efficiency is improved by about 3.5 times. Then, to consider the effect of the boundary further, a centroid module structural model with equivalent contact is proposed. Compared with the hybrid reduced order model, the collision displacement and the maximum stress of the centroid module structure model are much closer to those of the fine full model. Finally, an impact response analysis is conducted on the centroid module structural model and the fine full model, by comparing the behaviors of the collision center point and the impact object. It is found that both models have the similar trend in the response curves with small errors, which verifies the feasibility of the proposed model.

Accurately constructing the nonlinear hysteresis loop model at the bolt connection is crucial for the vibration reduction and safety performance evaluation of a satellite load-carrying structure. Traditional time-domain analysis methods of computational models require substantial time costs, and typical data-driven models struggle to construct high-precision hysteresis models. To address these challenges, a novel Residual Improvement Deep Learning Algorithm (RIDLA) is proposed for constructing the hysteresis loop model of displacement and force at the bolt connection. The algorithm fully leverages the capacity of Long Short-Term Memory (LSTM) neural networks to fit nonlinear relationships in time series. It adopts an innovative approach by creating a multi-level residual improvement deep learning model that iteratively refines predictions based on measured responses, resulting in highly accurate modeling of hysteresis at bolt connections. The performance of the RIDLA method is validated using experimental data from cyclic loading of a subcomponent of a satellite load carrying structure. The findings demonstrate that RIDLA achieves highly accurate predictions of the displacement and force hysteresis loop at the bolt connection. Additionally, the RIDLA method could be applied to predict the dynamic responses of other complex non-linear systems.

Piezoelectric materials have advantages such as rapid actuation, ease of preparation, and low energy consumption. Using piezoelectric materials for vibration control can improve structural performance. Studies have shown that the distribution of piezoelectric materials can significantly impact control effectiveness. Many researchers use topology optimization techniques to optimize the layout of piezoelectric materials or control voltages. In the topology optimization of piezoelectric intelligent structures, introducing various control coefficients as design variables can achieve a larger design space and further enhance control efficiency. This paper studies the optimal distribution of control coefficients for piezoelectric layers under harmonic excitation based on the Discrete Material Optimization (DMO) method. Using a negative velocity feedback control strategy for active control, dynamic compliance is selected as the objective function to effectively measure the structural vibration level. The design variables are the negative velocity feedback control coefficients for each pair of piezoelectric sensors and actuators. Sensitivity analysis is conducted using the adjoint variable method. Finally, two numerical examples are provided to verify the correctness of the proposed method.

Considering the issue that low frequency and broadband of elastic wave metamaterials cannot coexist, this paper realizes a low-frequency band gap by rotating asymmetric mechanical metamaterials, and further widens the low-frequency bandgap by introducing multiple orders. By utilizing the node rotation and ligament bending deformation characteristics of anti-chiral materials, the vibration body size and ligament stiffness of the anti-tetra chiral unit cell diagonal are gradually adjusted through ligament folding, and the multi-order asymmetric unit cell design is realized. The generation and change mechanism of elastic wave bandgap are explained by analyzing the resonance mode and transmission characteristics of the upper and lower bounds of the bandgap. The study shows that: in the asymmetric mode, the node rotation and ligament bending deformation characteristics of chiral materials are utilized to realize the rotation resonance of the mass block and open the bandgap, and the band gap is widened by the resonant superposition between two pairs of different mass blocks arranged alternately. Finally, the proposed asymmetric mechanical metamaterial is verified by experiments to have to demonstrate improved broadband and low-frequency vibration isolation performance.

Proppant transport in fractures is essentially a dense granular flow in a slot-shaped space. Applying the two-fluid method in numerical simulations of a field-scale particle flow is promising, but existing solid stress models cannot accurately describe the process of proppant accumulation. In this paper, the morphological change of a proppant pack under flow erosion was analyzed experimentally, and the important influence of cohesion on the change of the pack state was pointed out. Then, combined with the simulated results of a proppant transport and the results of a suspension apparent viscosity test, the influence of the particle radial distribution function on the solid kinetic pressure and the change trend of total solid pressure were analyzed, and the change rate of the solid friction pressure with the particle volume fraction was determined. Based on the granular matter theory and results of a direct shear test, the cohesion of the proppant pack was considered in the frictional viscosity model. The results show that the improved solid friction stress model can capture larger angles of the accumulation and settlement profiles, and correctly simulate the process of proppant accumulation.

Accurately simulating the impact characteristics of a dam break is of paramount significance for the prediction and mitigation of dam-break flow disasters. The B-spline material point method (BSMPM), as an improved algorithm of the material point method (MPM), effectively enhances computational accuracy and improves convergence. However, the BSMPM solves the governing equations based on a tensor grid rather than an Eulerian background grid. Moreover, its interpolation shape functions have a larger influence domain. Consequently, when solving problems involving fluid-structure coupling and contact, issues such as premature contact, difficulty in capturing contact interfaces, and challenges in calculating contact forces arise. Within the same tensor grid space of the BSMPM, accurate capture of contact interfaces is achieved based on the relative velocities and unit outward normals of the same nodes; employing the Greville Abscissa enables precise contact of contacting objects, thereby avoiding premature or spurious contact; through the Lagrange multiplier method, interface contact forces are accurately determined, thus constructing a high-precision contact algorithm for fluid-structure strongly coupled problems, facilitating research on the simulation of dam-break fluid impact with rigid and elastic obstacles, and enabling a comparison with existing experimental or simulated results. The results demonstrate that the simulated impact loads and structural deformation evolution patterns correspond well with existing experimental/simulated results. For rigid obstacles, the peak impact pressure exhibits concave parabolic growth and positive correlation exponential function growth with increasing water level and dam-break slope, respectively. For elastic obstacles, the peak impact pressure decreases exponentially with the increase in the height of the probing point. The feasibility and effectiveness of simulating dam-break flow impact problems using the BSMPM contact algorithm are validated, providing a new perspective for simulating dam-break flow impact problems.