An experimental method to obtain the hard alpha anomaly distribution for titanium alloy aeroengine disks

A probability-based damage tolerance methodology has been proposed to improve the recognition of material anomalies, especially hard alpha (TiN) anomalies for aeroengine rotor disks. A key input to this method is hard alpha anomaly distribution, which reflects the occurrence rate and size of anomalies present in the finished part material of titanium rotors. Since anomalies rarely occur naturally, an experimental method is proposed to obtain the anomaly distribution for titanium alloy aeroengine disks to reflect and equivalently replace the manufacturing development in titanium industry. In general, the anomaly distribution information can be divided into two parts: the Probability of Detection (POD) curve and the detected anomaly distribution, which contains the size and frequency data of the detected anomalies. The distribution can be established based on several appropriate assumptions and derivation steps with different confidence levels of POD curves and detected anomaly distributions. In this case, the distribution can be obtained in a relatively short time as a key input to the probability-based damage tolerance methodology. Then the Probability of Failure (POF) can be calculated, and the value is found to vary with different confidence levels. On this basis, the conservative estimated POF can be obtained in conjunction with confidence levels.     

Imaginary filtered hindsight experience replay for UAV tracking dynamic targets in large-scale unknown environments

As an advanced combat weapon, Unmanned Aerial Vehicles (UAVs) have been widely used in military wars. In this paper, we formulated the Autonomous Navigation Control (ANC) problem of UAVs as a Markov Decision Process (MDP) and proposed a novel Deep Reinforcement Learning (DRL) method to allow UAVs to perform dynamic target tracking tasks in large-scale unknown environments. To solve the problem of limited training experience, the proposed Imaginary Filtered Hindsight Experience Replay (IFHER) generates successful episodes by reasonably imagining the target trajectory in the failed episode to augment the experiences. The well-designed goal, episode, and quality filtering strategies ensure that only high-quality augmented experiences can be stored, while the sampling filtering strategy of IFHER ensures that these stored augmented experiences can be fully learned according to their high priorities. By training in a complex environment constructed based on the parameters of a real UAV, the proposed IFHER algorithm improves the convergence speed by 28.99% and the convergence result by 11.57% compared to the state-of-the-art Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The testing experiments carried out in environments with different complexities demonstrate the strong robustness and generalization ability of the IFHER agent. Moreover, the flight trajectory of the IFHER agent shows the superiority of the learned policy and the practical application value of the algorithm.     

Review on ultra-lightweight flapping-wing nano air vehicles:Artificial muscles,flight control mechanism,and biomimetic wings

Flying insects are capable of flapping their wings to provide the required power and control forces for flight. A coordinated organizational system including muscles, wings, and control architecture plays a significant role, which provides the sources of inspiration for designing flapping-wing vehicles. In recent years, due to the development of micro-and meso-scale manufacturing technologies, advances in components technologies have directly led to a progress of smaller Flapping-Wing Nano Air V...     

A new accelerating technique for low speed flow: pseudo high speed method

This paper proposes a new accelerating technique for simulating low speed flows, termed as pSeudo High Speed method (SHS), which uses governing equations and numerical methods of compressible flows. SHS method has advantages of simple formula, easy manipulation, and only need to modify flux of Euler equations. It can directly employ the existing well-developed schemes of hyperbolic conservation laws. To verify the technique, several numerical experiments are performed, such as: flow past airfoils and flow past a cylinder. Analysis of SHS method and comparisons with some precondition methods are made numerically. All tests show that SHS method can greatly improve the efficiency of compressible method simulating low speed flow fields, which exhibits in accelerating the convergence rate and increasing the accuracy of the numerical results.     

An automatic isotropic/anisotropic hybrid grid generation technique for viscous flow simulations based on an artificial neural network

Based on the author’s previous research, a novel hybrid grid generation technique is developed by introducing an Artificial Neural Network(ANN) approach for realistic viscous flow simulations. An initial hybrid grid over a typical geometry with anisotropic quadrilaterals in the boundary layer and isotropic triangles in the off-body region is generated by the classical mesh generation method to train two ANNs on how to predict the advancing direction of the new point and to control the grid size....     

Stress corrosion behavior of 2195-T8 Al-Li alloy with an artificial pit exposed to a 30vol% HNO3 solution

This paper experimentally studied the stress corrosion behavior of 2195-T8 Al-Li alloys with prefabricated pits in 30vol% HNO₃. The microstructure was observed and determined by the scanning electron microscopy and the transmission electron microscopy. The typical corrosion features, i.e., regular or irregular corrosion pits and sub/intergranular corrosion, were investigated, and the role of stress were analyzed. The statistical results of the number and area of corrosion pits in various sizes were studied using an improved image processing method. Experimental results demonstrate that stress affects the intergranular corrosion or sub-intergranular corrosion of the alloy most, and promotes them to evolve into cracks under stress corrosion. Stress also plays a role in accelerating corrosion severity of certain corrosion feature. The number of corrosion pits with an area of 0–50 μm² can be seen as an index to reflect the degree of corrosion. Besides, a corrosion phenomenon, i.e., the pit bottom in the site with the maximum stress locally suffering from no severe corrosion, was observed and discussed.     

Formation flying for magnetic sails around artificial equilibrium points

This paper investigates the problem of magnetic sail-based spacecraft formation control around the artificial equilibrium points (AEPs), which can eliminate the requirement of the propellant. The thrusts are achieved by utilizing the interaction between the solar wind and the artificial magnetosphere generated by superconducting current coil onboard. The circular restricted three-body problem (CRTBP) of magnetic sail is discussed including the allowed regions and linear stability of AEPs, the locations of collinear AEPs and the possibility of existence of periodic orbits around the collinear AEPs. Next, the dynamical models of magnetic sail formation around the collinear AEPs are established. A novel fast fixed-time nonsingular terminal sliding mode controller (FFNTSM) based on fixed-time disturbance observer (FTDO) is developed to account for external disturbances. Several numerical simulations are conducted to substantiate that spacecraft formation can be precisely controlled by the proposed propellantless propulsion method in the presence of external disturbances.     

武器装备智能保障系统建模与效能分析

为实现信息化作战保障条件下的装备保障能力建设和提升，面向装备OODA闭环提出装备智能保障系统，建立基于DoDAF的智能保障系统结构模型，并基于网络分析法对装备智能保障系统和传统装备保障系统的效能进行了对比评估。在总结当前装备效能评估领域国内外研究现状的基础上，以OODA全流程闭环为目标，分析装备保障的现存问题和装备智能保障模式的特点，并构建武器装备智能保障系统模型。通过系统高层概念、能力、任务活动等要素建模，构建武器装备智能保障系统效能模型并基于网络分析法开展效能评估，通过装备训练保障、维修保障、信息支援和行动支持等维度对比了传统装备保障系统与智能保障系统的效能差异，提出智能保障技术的发展建议，为装备保障的智能化发展提供理论参考。     

Finite time non-singular sliding mode control for spinning tether system with prescribed performance under artificial gravity mission

In this paper, the spinning tether system (STS) is applied to produce the artificial gravity overload with a proposed spin-up scheme in elliptical transfer orbits. To improve the comfort of the astronauts during spinning, the combined control scheme with tension and thrust is designed for spin-up. Then, based on the novel performance function and sliding mode technology, a finite time prescribed performance controller is proposed to track angular velocity for the desired artificial gravity overload. Compared with the existing works, the tracking error is controlled within the preset transient performance and converged to the origin within finite time even in the presence of unknown external disturbance. The stability of closed-loop tracking system is proved by Lyapunov theorem. Finally, the numerical simulations are given to demonstrate the effectiveness and robustness of the proposed controllers in the artificial gravity mission.     

增强神经网络辨识模型泛化能力的研究

神经网络(Artificial Neural Network,ANN)辨识模型的泛化能力是其最主要的性能之一,增强ANN模型的泛化能力也是近年来国内外有关专家学者研究的重点问题。大量研究表明,ANN模型泛化能力的改善与很多因素相关联,其中恰当的性能指标函数设计是一个重要影响因素。文中在分析常见的基于均方误差最小原则的性能指标函数基础上,通过加入ANN辨识模型权值间的延迟信息,进而获得一种改进型性能指标函数。通过仿真,验证了所设计的改进型性能指标函数对增强ANN辨识模型的泛化能力是有效的。