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.     

Topology optimization in lightweight design of a 3D-printed flapping-wing micro aerial vehicle

Topology optimization is an effective method to obtain a lightweight structure that meets the requirements of structural strength. Whether the optimization results meet the actual needs mainly depends on the accuracy of the material properties and the boundary conditions, especially for a tiny Flapping-wing Micro Aerial Vehicle (FMAV) transmission system manufactured by 3D printing. In this paper, experimental and numerical computation efforts were undertaken to gain a reliable topology optimization method for the bottom of the transmission system. First, the constitutive behavior of the ultraviolet (UV) curable resin used in fabrication was evaluated. Second, a numerical computation model describing further verified via experiments. Topology optimization modeling considering nonlinear factors, e.g. contact, friction and collision, was presented, and the optimization results were verified by both dynamic simulation and experiments. Finally, detailed discussions on different load cases and constraints were presented to clarify their effect on the optimization. Our methods and results presented in this paper may shed light on the lightweight design of a FMAV.     

An innovative approach for integrated airline network and aircraft family optimization

The determination of optimal aerial transport networks and their associated flight frequencies is crucial for the strategic planning of airlines, as well as for carrying out market research, to establish target markets, and for aircraft and crew rostering. In addition, optimum airplane types for the selected networks are crucial to improve revenue and to provide reduced operating costs. The present study proposes an innovative approach to determine the optimal aerial transport network simultaneously with the determination of the optimum fleet for that network, composed of three types of airplanes (network and vehicle integrated design). The network profit is maximized. The passenger’s demands between the airports are determined via a gravitational model. An embedded linear programming solution is responsible for obtaining potential optimal network configurations. The optimum fleet combination is determined from a database of candidate aircraft designs via genetic algorithm. A truly realistic airplane representation is made possible thanks to accurate surrogate models for engine and aerodynamics is adopted. An accurate engine deck encompassing a compression map and an innovative engine weight calculation besides an aerodynamical artificial neural network module enable a high degree of accuracy for the mission analysis. The proposed methodology is applied to obtain the optimum network comprised of twenty main Brazilian airports and corresponding fleet.     

基于函数链神经网络的深度分类器

目前的宽度学习系统（Broad learning system，BLS）通过所建立的一系列映射节点和增强节点来形成联合节点。因为联合节点与输出层的线性连接，网络权值可以用求解伪逆的方法快速求得，避免了耗时的训练过程，从而成为快速而高效的学习方法。然而在追求高精度结果的过程中，BLS对于增强节点数量的需求过于巨大，容易造成过拟合问题。为此，本文提出了基于函数链神经网络（Functional-link neural network，FLNN）的深度分类器（FLNN based deep classifier，FLNNDC），旨在提供一种更加简单却又不失精度的BLS变体结构。FLNNDC将几个轻量级的BLS子系统堆积成栈式结构，每一个轻量级的BLS子系统随机选择一部分映射节点生成增强节点，而不是全部映射节点。和原宽度结构相比，在几个主流数据集上的实验结果表明本文所提出的FLNNDC分类器具有网络结构更小且学习速度更快的优势。     

基于粒子群算法的多波位高度估计方法

为解决雷达斜视模式下对目标区域的高度估计问题,提出了一种基于粒子群算法的多波位高度估计方法。利用粒子群优化算法建立约束条件和目标函数,通过多次迭代使目标函数趋于一个最优值,同时得到高度的最优解。利用粒子群优化算法求解多波位测高方程组可减小方程组近似处理误差。此外,利用粒子群优化算法可随时更改波位数目,增强了该测高方法使用的灵活性,有效提高了高度估计精度。通过理论仿真和实测数据仿真分析,验证了粒子群优化算法在求解多波位测高方程组时的有效性。结果表明:该方法具有较高的高度估计精度。     

六自由度激励台精密高刚度铰链结构设计与试验应用

精密高刚度铰链作为六自由度并联激励平台中的关键组件,其性能高低对激励台的控制精度有直接影响。针对铰链所需满足的高刚度、高基频和无间隙等要求,文章提出了基于虎克铰结构的铰链设计方法。首先根据铰链所处的工况确定选用圆锥滚子轴承作为旋转支撑部件,并通过对轴承的配置和预紧实现无间隙振动运动的要求,从而确定了铰链结构形式。然后,利用有限元法校核了结构的刚度与基频,进而完成铰链结构方案和样机制造,并将样机集成于激励台中。最后,开展了铰链动态特性试验和激励台振动控制试验,分别获取了铰链的基频和激励台控制响应。结果表明,铰链可满足激励台工作频段内的使用要求,铰链设计合理。     

Influence of TiB2 particles on machinability and machining parameter optimization of TiB2/Al MMCs

In situ formed TiB₂ particle reinforced aluminum matrix composites (TiB₂/Al MMCs) have some extraordinary properties which make them be a promising material for high performance aero-engine blade. Due to the influence of TiB₂ particles, the machinability is still a problem which restricts the application of TiB₂/Al MMCs. In order to meet the industrial requirements, the influence of TiB₂ particles on the machinability of TiB₂/Al MMCs was investigated experimentally. Moreover, the optimal machining conditions for this kind of MMCs were investigated in this study. The major conclusions are: (1) the machining force of TiB₂/Al MMCs is bigger than that of non-reinforced alloy and mainly controlled by feed rate; (2) the residual stress of TiB₂/Al MMCs is compressive while that of non-reinforced alloy is nearly neutral; (3) the surface roughness of TiB₂/Al MMCs is smaller than that of non-reinforced alloy under the same cutting speed, but reverse result was observed when the feed rate increased; (4) a multi-objective optimization model for surface roughness and material removal rate (MRR) was established, and a set of optimal parameter combinations of the machining was obtained. The results show a great difference from SiC particle reinforced MMCs and provide a useful guide for a better control of machining process of this material.     

分析插值误差和斜率的轨迹优化网格细化方法

提出一种基于插值误差和斜率分析的轨迹优化自适应网格细化方法，包括节点插入算法和节点删除算法。节点插入算法分析各个离散节点的控制变量的插值误差。若插值误差较大，则在该节点周围增加节点细化网格；否则，不进行细化。节点删除算法分析各个离散节点处的控制变量斜率。若某个节点的左斜率和右斜率都为零，那么删除该节点；否则，保留该节点。采用三个典型的轨迹优化算例验证了所提出的方法的有效性和特色，并且与其它几种网格细化方法进行了对比。仿真结果表明，本文方法生成的网格规模较小，需要的网格迭代次数较少，能够快速、高精度求解非光滑轨迹优化问题。     

Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

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.