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.

The non-isothermal complex flow caused by fluid impacting obstacles is very important to the industrial processes such as nuclear energy utilization. Through coupling various numerical techniques such as the density diffusive term, artificial viscous term, particle shifting technique, a stable and accurate non-isothermal smoothed particle hydrodynamics (SPH) scheme is established, and accurate simulation of non-isothermal complex flow caused by fluid impacting obstacles is realized. Based on the simulation for the non-isothermal flow past a heated cylinder, the non-isothermal dam break past single/multiple obstacles, it is demonstrated that: (1) the developed non-isothermal SPH scheme can not only compute a smooth pressure field and avoid the spurious oscillation of numerical solutions, but also predict accurately the temperature field and the key physical quantities; (2) this SPH scheme can also accurately show the interaction between the heat conduction process and the complex free-surface evolution, and has the capability to simulate non-isothermal complex flows past multiple obstacles.

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.

Using fractional derivatives to modify the Zener standard rheological solid model and considering the instantaneous rheological effect of the soil around the pile, a vertical coupled vibration model of the pile-soil system is constructed. The frequency-domain analytical solution of the system dynamic control equation is derived using Laplace transform and potential function decomposition methods. The time domain response under instantaneous excitation at the pile top is obtained through numerical Laplace inversion. Then, numerical examples are used to analyze the frequency domain characteristics of displacement and dynamic stiffness, and dynamic damping of end-bearing pile vertical vibration in a rheological clay layer, as well as the wave response under instantaneous excitation at the pile top. Research has found that the rheological effect of soil reduces the amplitude of pile top displacement and dynamic stiffness and the rheological effect of soil causes a decrease in the amplitude of the pile top response and a weakening of the reflected wave signal under instantaneous excitation.

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.

To investigate the evolution of dimpling and the mechanism of interface separation in bimetal clad pipes under external mechanical loading, a stress model was established. The study analyzed the effects of the ratio of diameter to thickness for the inner and outer pipes, forming pressure, initial forming clearance, and operational internal pressure on dent formation and interface separation. Results indicate that interface separation distance and rebound rate correlate positively with the ratio of diameter to thickness for the inner pipes, forming pressure, and initial forming clearance, and negatively with the ratio of diameter to thickness for the outer pipes. Higher operational internal pressure reduces interface separation but increases rebound rate. Internal pressurization of dented pipes decreases interface separation; for instance, under 2-MPa operating pressure, interface separation is 5% less compared with conditions under 2-MPa pressurization. Additionally, the difference in separation between these conditions decreases with increasing pressure. Adjacent dimpling results in increased interface separation in intermediate pipe segments, causing a broader interface separation area compared with isolated dimpling.

The computation mechanism of the calculation method for the completed state of existing suspension bridges is unclear, and the target state is unreasonable. A reasonable numerical analysis algorithm is proposed for bridge formation state. The cable theory consisting of the initial end angle and horizontal cable force is validated based on the relationship between the initial end angle and cable force in the theory of catenary equations. A system of bridge state analytical equations are constructed based on the optimization principle of the target parameters of each component of the suspension bridge. The calculation equation for the main cable configuration based on the geometric closure conditions of the suspension bridge's main cable. The mechanical equilibrium equations are constructed for each component based on the mechanical equilibrium conditions of the suspension cables and stiffening beams. Based on the principle of minimizing the bending moment of the stiffening beam components and the principle of uniform cable force of the suspension cable components in the completed state of the suspension bridge, a calculation equation system for the stiffening beam and suspension cable is established. The intelligent algorithm GRG is used to optimize the numerical solution of the objective function of the completed state of a suspension bridge. A case study of a kilometer-long level suspension bridge project. The derived analytical algorithm is compared with the calculation results of the finite element model and rigid supported continuous beam algorithm. The results show that the difference between the analytical algorithm and the finite element model calculation is relatively small in terms of force of main cable, shape-finding of main cable, and the bending moment of the stiffening beam. Compared with the rigid support continuous beam algorithm, the analytical algorithm has computational advantages in ensuring the uniformity of cable forces in bridge suspension cables and the extreme bending moment of stiffening beams.

In computational fluid dynamics, mesh quality greatly affects the accuracy and computational efficiency of numerical simulation results. The Bubble does not require the consideration of intersection judgments and has a relatively simple data structure, which has significant advantages in mesh generation efficiency and quality. The process of improving the mesh quality by moving nodes based on the traditional Bubble is optimized in this article, and we define it as the Bubble-Opt method. In this method, a bubble radius selection method combined with neural networks is used to generate the initial bubbles, and an improved bubble dynamic movement technique is used to adjust the bubbles to the appropriate position. The Delaunay method is used to connect the center of bubbles to form the final optimized mesh. Then, the optimization effects of different bubble radius selection methods and Bubble-Opt methods are compared under different process parameters. Taking the flow around a 2D cylinder as an example, the geometric quality and transition ratio of the mesh before and after optimization are tested. For this example, there is a set of optimal parameters and a radius selection method that achieve the best mesh quality optimization effect. The average transition ratio can be improved by about 17.37%, the average mesh quality can be improved by about 13.60%, and the minimum transition ratio and minimum mesh quality can be significantly improved. Finally, under the radius selection method and process parameters, taking two-dimensional cylindrical flow and NACA0012 airfoil flow as examples, the numerical simulation results are compared with experimental data from both qualitative and quantitative perspectives, indicating a significant improvement in the overall grid quality.

This paper presents an analytical method, namely interface stiffness transfer method, for evaluating the responses of multilayered elastic structures. Based on the Love function and general solutions, the stiffness matrix relationship of the displacement-stress state vectors is introduced to obtain the interface stiffness transfer matrix equation between adjacent layers, which satisfies an algebraic Riccati matrix equation. When the elastic layer is a half-space, an explicit solution is obtained directly for the interface stiffness matrix. The interface stiffness transfer matrix method starts from the bottom layer with a known stiffness, and then deals with one layer at a time until the uppermost layer is reached, obtaining the interface stiffness of the multilayered structure. Finally, by solving the symmetric equilibrium equations of the boundary conditions, the displacement-stress state vector of an arbitrary layer is obtained. This method keeps the advantages of the classical transfer matrix method, but naturally excludes its exponential growth terms. In particular, the proposed method is a powerful candidate for efficiently solving the algebraic Riccati equation for the optimal control problems. Numerical examples show the properties of the interface stiffness transfer method.

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.