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.     

Influence of pre-tension on ballistic impact performance of multi-layer Kevlar 49 woven fabrics for gas turbine engine containment systems

In this paper, ballistic impact tests on wrapped multi-layer Kevlar 49 woven fabric systems were carried out with a flat blade projectile to investigate the impact response during a fan blade out event. The influences of the number of Kevlar layers and pre-tension were discussed particularly. Test results were used to analyze failure modes and energy absorption characteristics of multi-ply Kevlar fabrics. Results show that there are two kinds of impact damage for fabrics: global deformation mainly involving stretching of yarns in the impact region and fabric wrinkle from both sides to the impact zone, and local damage characterized by yarn fracture, yarn pull-out, and yarn unraveling. The energy absorption capability of Kevlar 49 woven fabrics improves with the number of fabric layers. The energy absorbed by multi-layer fabrics increases slightly at the beginning and then decreases substantially with pre-tension. The work in this paper can provide guidance for designing light-weight multi-layer fabrics containment systems.     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.     

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...     

着陆缓冲装置特性分析及控制方法研究

着陆缓冲技术在航天器回收系统中的应用日益广泛,文章对着陆缓冲过程所使用的两种发动机推力制度进行了比较;分析了着陆缓冲过程中影响系统最终性能的因素。认为影响最大的因素是初始条件和环境条件的改变,对此提出了一种较为实用的控制方法。应用这一方法,可以最大限度地消除初始条件和环境条件的改变对着陆缓冲装置性能的影响。     

混杂复合材料层合板抗冲击性能研究

为了探究复合材料层合板在实际应用中因承受冲击载荷而造成的结构安全问题,本研究采用实验和仿真相结合的方法,首先探究冲头形状对复合材料层合板损伤机理的影响,然后结合不同冲击能进一步揭示层合板的承载力和能量吸收变化规律。结果表明,相同冲击能下,层合板的损伤范围和承载力随着圆锥头、半球头、平头依次增加;相应的层合板的临界穿透能量随着圆锥头、半球头、平头依次增大;冲头形状和冲击能对层合板的吸能能力有较大的影响。     

电推进羽流粒子束溅射的蒙特卡罗模拟

为了研究电推进羽流对推力器及航天器造成的溅射腐蚀作用,采用蒙特卡罗方法对羽流等离子体对材料的溅射进行模拟,研究了溅射的级联碰撞机理,并开展了Xe离子正入射、斜入射Cu材料的溅射率、溅射产物的能量分布以及空间角分布的研究.结果显示,蒙特卡罗方法对溅射率和能量分布的计算结果与试验结果吻合较好,误差<30％,但是斜入射溅射率...     

我国深空探测领域防热材料的进展与需求

我国深空探测任务的不断发展对航天器的防热技术提出了更高的要求,而先进的防热材料是防热技术发展的重要支撑。本文主要针对月球探测返回任务和火星探测任务,重点介绍了我国在防热材料领域所取得的研究进展,并对未来以火星与小天体探测返回、火星大气制动、以及近日探测为代表的深空探测任务中防热材料的发展和需求进行了展望。     

脉冲展宽对深空激光通信的影响与补偿研究

深空激光通信系统下行链路的脉冲位置调制PPM（Pulse Position Modulation）信号在经过大气信道传输和单光子探测器接收时,将出现脉冲展宽效应,引起通信系统性能下降。分析了大气信道中的淡积云云层散射、大气湍流与气溶胶散射和单光子探测器的抖动特性所引起的脉冲展宽效应。在此基础上,仿真分析了淡积云云层物理厚度对不同PPM调制阶数下通信速率的影响,并研究了单光子探测器引起的脉冲展宽产生的抖动损失。为补偿脉冲展宽的影响,提出了一种基于时隙似然比解调的补偿方法,通过仿真验证了该方法能够有效降低深空PPM激光通信链路中脉冲展宽对通信误码率的影响。该研究对分析和提升深空PPM激光通信系统的链路性能具有一定的参考意义。     

基于改进Johnson-Cook模型的5083P-0铝合金动态本构关系研究

为研究5083P-0铝合金在高应变率下的力学行为及本构模型,通过RPL100材料试验机和分离结果显示随着应变率的增加,5083P-0铝合金的屈服强度、流动应力增加,应变硬化率减小,具有应变硬化效应,正应变率效应以及热软化效应。对其塑性变形原理进行分析发现,滑移系的作用导致材料发生较大的塑性变形,同时由于绝热温升的产生,材料表现出应变硬化与热软化机制相竞争的情况。在Johnson-Cook模型率效应并能准确地描述其流动应力。最后采用新的应变率进行补充实验,通过对比验证了模型的合理性。