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.     

Collaborative image compression and classification with multi-task learning for visual Internet of Things

Widespread deployment of the Internet of Things(Io T) has changed the way that network services are developed, deployed, and operated. Most onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io T. Typically, the sender would compress images, and then through the communication network, the receiver would decode images, and then analyze the images for applications. However, image compression and semantic inference are generally conducted separately, and t...     

光波纳米推进技术中的表面等离激元增益光镊作用机理

为研究天线不同结构对表面等离激元（SPP）增益光镊作用的影响,建立天线-基底的电磁波传输耦合激元电场触发光梯度力的数值模型,并利用数值模型分析天线不同结构对SPP电场的影响规律,同时,这种电场变化规律对光镊增益有直接的数学关系,基于上述物理机制,获得不同天线结构对光梯度力产生的优化策略。为验证上述物理机制与优化策略的有效性,开展纳米颗粒的粒子图像测速（PIV）试验,天线材料为银,基底为二氧化硅,纳米颗粒为银,试验能够完好地观测到纳米颗粒在天线通道的运动情况。结果表明,光梯度力的增益机制在于激元电场强度和梯度两方面因素,前者随天线不对称性增强而先增大后减小,后者呈现一直增大趋势;纳米颗粒推动作用力的计算误差约为5.5%~13.8%,且试验值与计算值的趋势相符,一方面验证本文研究机理及优化策略的有效性,另一方面证明PFP技术的原理可行。     

燃油喷嘴雾化特性试验研究

为了检验某型航空发动机燃油喷嘴改进设计效果,利用相位多普勒粒子分析仪对燃油喷嘴的雾化性能参数进行试验研究。得到雾化液滴的索太尔平均直径的空间分布、轴向平均速度、脉动速度及其湍流度的分布情况。结果表明:轴向平均速度呈凹盆状分布,脉动速度呈双峰状分布;喷雾中心湍流度大,喷雾边缘湍流度小。随着供油压力增大,在相同测试截面上,喷雾的范围和中心区域粒径变大,边缘位置粒径变小。在相同供油压力下,随着与喷嘴距离的增加,喷雾范围增大,喷雾的轴向平均速度和脉动速度减小,轴向速度的湍流度波动幅度减小。     

日球层内外能量中性原子的探测

能量中性原子(Energetic Neutral Atoms, ENA, 简称能原子)是指在日球层内外空间, 拥有>0.1keV动能的原子.在此空间领域并没有温度>106K的中性气体, 但却充满动能>0.1keV的正离子.因此能原子A应该是A+离子与原地稀薄气体B原子或分子交换电荷所产生的, 即A++B→A+B+. 电荷交换涉及极小的动能变化, 新生的能原子A和离子B+基本上各自保持原有动能. 离子B+随即被当地磁场俘获, 能原子A则脱离磁场约束并携带其原属离子群的成分和能量信息而直线运动, 成为遥测空间等离子体的有效媒介. 美国人造卫星 IBEX (Interstellar Boundary Explorer) 直接探测得到来自日球层以外星际空间的能原子, 大幅延伸了利用能原子遥测空间等离子体的领域. 本文据此论述了空间能原子的发现, 综述了探测空间能原子的基本概念与实例、取得的主要成果、仪器设计和研制进展以及未来空间利用能原子遥测的发展趋势.      

一种融合MRF分割与数学形态学的道路提取算法

针对高分辨率合成孔径雷达（Synthetic Aperture Radar, SAR）图像中道路目标难以有效提取的问题,提出一种融合马尔可夫随机场（Markov Random Field, MRF）分割与数学形态学处理的高分辨率SAR图像道路提取算法。该算法首先利用直方图均衡化和增强Lee滤波对SAR图像进行预处理,实现道路的边缘增强,抑制相干斑噪声;进而利用基于条件迭代模式（Iterated Conditional Mode, ICM）的MRF对SAR图像中的道路目标进行初分割;再用数学形态学填充空洞,平滑道路边缘;最后,基于道路的几何特征,使用偏心率、矩阵度、复杂度等因子去除虚警,从而提取出道路目标。利用该文算法对两块实际高分辨率SAR图像进行道路目标提取,均可以取得90%以上的正确道路提取率,表明本文算法具有较高的道路提取精度。     

基于粒子群算法的电帆轨迹优化设计

电帆是一种利用太阳风动量的新颖的无工质空间推进系统,文章研究了以电帆为对象的行星际转移轨迹优化问题。以地球轨道转移到火星、金星轨道为任务对象,采用连续推力模型,研究极坐标系下最小时间转移轨迹优化设计问题。提出了两种基于粒子群算法(PSO)的直接优化方法,避免对协态变量初值敏感的两点边值问题（TPBVP）求解。方法一是通过打靶法直接离散化控制量输入,将最优控制问题转化为非线性规划参数优化问题,采用PSO算法寻优,获得近似最优的转移轨迹。方法二是针对任何连续控制律曲线都能以一定精度的多项式函数进行曲线拟合的特性,设计逼近最优转移轨迹控制律的多项式函数,通过PSO算法优化多项式函数参数获得逼近最优解的转移轨迹。仿真结果表明采用上述两种方法进行转移轨迹优化设计,具有随机猜测初值、全局收敛、鲁棒性强的特点。     

Hypersonic reentry trajectory planning by using hybrid fractional-order particle swarm optimization and gravitational search algorithm

This paper proposes a novel hybrid algorithm called Fractional-order Particle Swarm optimization Gravitational Search Algorithm (FPSOGSA) and applies it to the trajectory planning of the hypersonic lifting reentry flight vehicles. The proposed method is used to calculate the control profiles to achieve the two objectives, namely a smoother trajectory and enforcement of the path constraints with terminal accuracy. The smoothness of the trajectory is achieved by scheduling the bank angle with the aid of a modified scheme known as a Quasi-Equilibrium Glide (QEG) scheme. The aerodynamic load factor and the dynamic pressure path constraints are enforced by further planning of the bank angle with the help of a constraint enforcement scheme. The maximum heating rate path constraint is enforced through the angle of attack parameterization. The Common Aero Vehicle (CAV) flight vehicle is used for the simulation purpose to test and compare the proposed method with that of the standard Particle Swarm Optimization (PSO) method and the standard Gravitational Search Algorithm (GSA). The simulation results confirm the efficiency of the proposed FPSOGSA method over the standard PSO and the GSA methods by showing its better convergence and computation efficiency.     

Effect of scavenge port angles on flow distribution and performance of swirl-loop scavenging in 2-stroke aircraft diesel engine

Swirl-Loop Scavenging (SLS) improves the performance of 2-stroke aircraft diesel engine because the involved swirl may not only benefit the scavenging process, but also facilitate the fuel atomization and combustion. The arrangement of scavenge port angles greatly influences in-cylinder flow distribution and swirl intensity, as well as the performance of the SLS engine. However, the mechanism of the effect and visualization experiment are rarely mentioned in the literature. To further investigate the SLS, Particle Image Velocimetry (PIV) experiment and Computational Fluid Dynamics (CFD) simulation are adopted to obtain its swirl distribution characteristics, and the effect of port angles on scavenging performance is discussed based on engine fired cycle simulation. The results illustrate that Reynolds Stress Turbulence model is accurate enough for in-cylinder flow simulation. Tangential and axial velocity distribution of the flow, as well as the scavenging performance, are mainly determined by geometric scavenge port angles α_geom and β_geom. For reinforcement of scavenging on cross-sections and meridian planes, α_geom value of 27° and β_geom value of 60° are preferred, under which the scavenging efficiency reaches as high as 73.7%. Excessive swirl intensity has a negative effect on SLS performance, which should be controlled to a proper extent.     

Simple method for performance evaluation of multistage rockets

Multistage rockets are commonly employed to place spacecraft and satellites in their operational orbits. Performance evaluation of multistage rockets is aimed at defining the maximum payload mass at orbit injection, for specified structural, propulsive, and aerodynamic data of the launch vehicle. This work proposes a simple method for a fast performance evaluation of multistage rockets. The technique at hand is based on three steps: (i) the flight-path angle at each stage separation is guessed, (ii) the spacecraft velocity is maximized at the first and second stage separation, and (iii) for the last stage the thrust direction is obtained through the particle swarm optimization technique, in conjunction with the use of the Euler–Lagrange equations and the Pontryagin minimum principle. The coast duration at the second stage separation is optimized as well. The method at hand is extremely simple and easy-to-implement, but nevertheless it proves to be capable of yielding near-optimal ascending trajectories for a multistage launch vehicle with realistic structural, propulsive, and aerodynamic characteristics. The solutions found with the technique under consideration can be employed either for a rapid evaluation of the multistage rocket performance or as guesses for more refined optimization algorithms.