Multi-scale design and optimization for solid-lattice hybrid structures and their application to aerospace vehicle components

By integrating topology optimization and lattice-based optimization, a novel multi-scale design method is proposed to create solid-lattice hybrid structures and thus to improve the mechanical performance as well as reduce the structural weight. To achieve this purpose, a two-step procedure is developed to design and optimize the innovative structures. Initially, the classical topology optimization is utilized to find the optimal material layout and primary load carrying paths. Afterwards, the solid-lattice hybrid structures are reconstructed using the finite element mesh based modeling method. And lattice-based optimization is performed to obtain the optimal cross-section area of the lattice structures. Finally, two typical aerospace structures are optimized to demonstrate the effectiveness of the proposed optimization framework. The numerical results are quite encouraging since the solid-lattice hybrid structures obtained by the presented approach show remarkably improved performance when compared with traditional designs.     

Applications of structural efficiency assessment method on structural-mechanical characteristics integrated design in aero-engines

In the design process of advanced aero-engines, it is necessary to carry out an effective analysis method between structural features and mechanical characteristics for a better structural optimization. Based on the structural composition and functions of aero-engines, the concept and contents of structural efficiency can reflect the relation between structural features and mechanical characteristics. In order to achieve the integrated design of structural and mechanical characteristics, one quantitative analysis method called Structural Efficiency Assessment Method (SEAM) was put forward. The structural efficiency coefficient was obtained by synthesizing the parameters to quantitatively evaluate the aero-engine structure design level. Parameterization method to evaluate structural design quality was realized. After analyzing the structural features of an actual dual-rotor system in typical high bypass ratio turbofan engines, the mechanical characteristics and structural efficiency coefficient were calculated. Structural efficiency coefficient of high-pressure rotor (0.43) is higher than that of low-pressure rotor (0.29), which directly shows the performance of the former is better, there is room for improvement in structural design of the low-pressure rotor. Thus the direction of structural optimization was pointed out. The applications of SEAM shows that the method is operational and effective in the evaluation and improvement of structural design.     

Inverse identification of constitutive parameters of Ti2AlNb intermetallic alloys based on cooperative particle swarm optimization

Ti₂AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.     

基于DDPG算法的无人机集群追击任务

无人机的集群化应用技术是近年来的研究热点，随着无人机自主智能的不断提高，无人机集群技术必将成为未来无人机发展的主要趋势之一。针对无人机集群协同执行对敌方来袭目标的追击任务，构建了典型的任务场景，基于深度确定性策略梯度网络（DDPG）算法，设计了一种引导型回报函数有效解决了深度强化学习在长周期任务下的稀疏回报问题，通过引入基于滑动平均值的软更新策略减少了DDPG算法中Eval网络和Target网络在训练过程中的参数震荡，提高了算法的训练效率。仿真结果表明，训练完成后的无人机集群能够较好地执行对敌方来袭目标的追击任务，任务成功率达到95%。可以说无人机集群技术作为一种全新概念的作战模式在军事领域具有潜在的应用价值，人工智能算法在无人机集群的自主决策智能化发展方向上具有一定的应用前景。     

Investigating the Coronal Mass Ejections associated with DH type-II radio bursts and solar flares during the ascending phase of the solar cycle 24

We studied a set of 74 CMEs, with shedding the light on the halo-CMEs (HCMEs), that are associated with decametric – hectometric (DH) type-II radio bursts (1–16?MHz) and solar flares during the period 2008–2014. The events were classified into 3 groups (disk, intermediate, and limb events) based on their longitudinal distribution.We found that the events are mostly distributed around 15.32° and 15.97° at the northern and southern solar hemispheres, respectively. We found that there is a clear dependence between the longitude and the CME’s width, speed, acceleration, mass, and kinetic energy. For the CMEs’ widths, most of the events were HCMEs (～62%), while the partial HCMEs comprised ～35% and the rest of events were CMEs with widths less than 120°. For the CMEs’ speeds, masses, and kinetic energies, the mean values showed a direct proportionality with the longitude, in which the limb events had the highest speeds, the largest masses, and the highest kinetic energies. The mean peak flux of the solar flares for different longitudes was comparable, but the disk flares were more energetic. The intermediate flares were considered as gradual flares since they tended to last longer, while the limb flares were considered as impulsive flares since they tended to last shorter.A weak correlation (R?=?0.32) between the kinetic energy of the CMEs and the duration of the associated flares has been noticed, while there was a good correlation (R?=?0.76) between the kinetic energy of the CMEs and the peak flux of the associated flares. We found a fair correlation (R?=?0.58) between the kinetic energy of the CMEs and the duration of the associated DH type-II radio bursts.     

A novel framework for liquid propellant engine’s cooling system design by sensitivity analysis based on RSM and multi-objective optimization using PSO

One of the challenges of combustion chamber and nozzle design in a Liquid Propellant Engine (LPE) is to predict the behavior and performance of the cooling system. Therefore, while designing, the optimization of the cooling system is always of great importance. This paper presents the multi-objective optimization of the LPE’s cooling system. To this end, a novel framework has been developed, resulting from the application of the Response Surface Method (RSM) and the correlation coefficients matrix, sensitivity analysis and the The Particle Swarm Optimization (PSO). based on this method, the input variables, constraints, objective functions, and their surfaces were identified. In terms of multi-optimization algorithms, RSM and PSO are utilized to get global optimum. In conclusion, the methodology capability is to optimize the LPE’s cooling system, 6 percentage increase in total heat transfer and 7 bar decrease cooling system pressure loss, which resulted in a 1.2-seconds increase in the specific impulse of the engine.     

Formation flying reconfiguration manoeuvres via environmental forces in highly elliptical orbits

A study on reconfiguration manoevres applied to a tetrahedral formation in highly elliptical orbits is proposed, by using a propellantless solution. The manoeuvring strategy consists in exploiting certain environmental forces, specifically those provided by solar radiation pressure and atmospheric drag, by actively controlling the satellites’ attitudes. Through inverse dynamics particle swarm optimization the optimal attitudes required for the manoeuvres are evaluated, whereas the configuration’s evolution is simulated by a high-fidelity orbital simulator. The goal of the reconfiguration problem is to find an optimal control in order for the four spacecraft to reach a desired configuration in a specified portion of orbit, where the desired configuration is evaluated by a shape and size geometric parameter. By increasing the manoeuvring time and the satellites’ area to mass ratio, all the case studies considered are successfully verified.     

Multiscale topology optimization using feature-driven method

This paper presents a multiscale design method for simultaneous topology optimization of both macrostructures and microstructures. Geometric features are extended as design primitives at both macro and micro scales and represented by Level Set Functions (LSFs). Parameters related to the locations, sizes, and orientations of macro and micro features are considered as design variables and optimized simultaneously. In the overlapping areas of different macro features, embedded microstructures are optimally figured out as the solution of the corresponding sub-optimization problem. In this study, the eXtended Finite Element Method (XFEM) is implemented for structural and sensitivity analyses with respect to design variables. This method has the advantage of using a fixed grid independent of the topology optimization process. The homogenization procedure is applied to calculate the effective properties of considered microstructures in each macro feature. Numerical examples are presented to illustrate the effectiveness of the proposed method. Results depict that the multiscale design cannot obviously improve structural stiffness compared with a solid-material design under the linear elastic condition.     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

激光动态液位测量技术研究

如今,运载火箭大量使用液氧、煤油等液体推进剂,其液位测量技术主要有浮子式、激光式、电容式、雷达式等。介绍并实现了一种激光液位测量系统,该系统体积小、功耗低,可适应多种测量环境,能满足航天燃料液位测量高精度、高动态、连续稳定测量的要求。系统利用相位式激光测距技术,通过测量激光回波信号的相位延迟,计算激光光程从而得到距离数据并通过客户端进行直观展示和数据存储。系统最大测量距离可达100 m,精度为±1 mm。该系统为非接触测量,耐腐蚀,通过加入反射板可实现透明、非透明液体测量。