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.     

微等离子体转化二氧化碳发射光谱诊断

火星大气层的主要成分为二氧化碳，如果能够利用低温等离子体方法高效分解二氧化碳，使其转化为氧气和一氧化碳加以利用，可以大幅降低航天员生命保障相关载荷长途运输的成本，进一步提高生命保障能力。低温等离子体放电过程中会产生大量活性组分，可以在数百度温度下实现二氧化碳的高效解离，是具有很大潜力的二氧化碳解离与转化方式。设计了一种尺度在亚毫米级、功率输入为数瓦的直流微槽等离子体反应器，可以在较低气体温度下实现二氧化碳分解。测量了反应器电流、功率等放电参数，采用发射光谱确定了体系中激发态组分，分析了激发态粒子谱线强度随输入电压、稀释气体比例等反应器工作参数变化，利用氮气分子振转谱带测量了等离子体放电区振动温度和气体温度。研究表明，添加氩、氦、氮气均可以增强二氧化碳的分解，添加氦气可以促进二氧化碳的电离过程。稀释气体激发态因具有高能量，可以通过潘宁解离通道增强二氧化碳分解。氦组分激发态的能量高于二氧化碳电离能，可以促进二氧化碳的电离反应。微等离子体内存在强烈的振动 平动非平衡现象：振动温度约为4400~4800K，而气体温度仅为450 ~600K，表明可以通过合理的放电和结构设计，定向将能量注入到振动态，从而进一步促进二氧化碳的振动解离。     

一种减小再入飞行器侧向气动非线性的布局优化方法

为改善升力式再入飞行器在跨声速段出现的侧向气动特性非线性问题,发展了一种基于Kriging代理模型的自适应迭代气动布局优化方法。设计了一种常规升力式再入飞行器布局,计算了该布局在跨声速段的侧向气动力,分析了可能影响侧向气动特性的机翼布局参数。根据气动布局优化流程,计算了气动布局样本气动特性,建立了布局参数到侧向力矩系数导数的代理模型,完成了以减小飞行器侧向非线性为目标的布局优化设计。优化布局的气动特性计算结果表明,所发展的方法是可行和有效的。该项研究为再入飞行器减小侧向气动非线性提供了新的布局设计途径,有利于降低控制系统设计难度,保障飞行安全。     

内装式空射运载火箭重力出舱机箭耦合动力学分析

研究了以运输机为平台的内装式运载火箭空射过程载机和火箭的耦合动力学建模。建模针对两个阶段：第一阶段，火箭固定于载机机舱内，两者构成一个整体，按照普通刚体的力学方法处理；第二阶段，火箭解锁后，沿着舱内的发射筒向外滑行，载机和火箭形成两刚体相互作用的耦合系统，基于牛顿-欧拉法建立系统动力学模型。载机在空射火箭过程中，油门和升降舵满偏，在加速前飞的同时拉大姿态俯仰角，火箭在自身重力分量和惯性力的作用下，沿着机舱内的发射筒加速向外滑行，直至与载机分离。数值仿真分析了空射过程载机的重要力学参数的变化过程，验证了载机操控策略的可行性和安全性，可为未来中国空射运载火箭技术设计提供数据参考。     

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.     

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.     

带攻角约束的高超声速飞行器自适应反步控制器设计

针对带攻角(AOA)约束的高超声速飞行器控制问题，提出一种基于非对称时变障碍函数的非线性自适应反步控制方法。首先，将飞行器模型化为严反馈形式，以反步法为基础进行控制器设计。然后通过光滑饱和函数对名义攻角指令信号进行限幅，并保证限幅信号的可导性，限幅产生的误差通过设计辅助系统进行补偿。进而使用障碍函数对攻角指令跟踪误差进行非对称时变约束。针对不确定性和干扰，设计新型自适应律对集中干扰上界进行估计并补偿。最终通过Lyapunov理论证明了闭环系统状态量一致最终有界并且攻角始终满足时变约束。仿真结果表明，本文方法能够在满足攻角约束基础上保证良好跟踪性能。     

复杂动态环境下无人飞行器动态避障近似最优轨迹规划

针对复杂动态环境下无人飞行器的动态障碍规避问题，基于合理假设建立了无人飞行器和动态障碍的运动学模型，并综合考虑无人飞行器飞行过程中的终端约束、控制输入约束、安全避障约束等，以能量最少为性能指标构建动态避障问题数学描述。之后，针对终端约束和控制输入约束，依据优化模型预测静态规划算法(OMPSP)生成初始轨迹；针对动态避障问题的不等式约束，引入松弛变量并结合滑模变结构控制方法设计松弛变量动力学，实现对一个、多个或同时多个动态障碍的安全规避；最后，依据有限时间微分动态规划(RHDDP)算法进行轨迹优化，获得满足上述各种约束并能规避动态障碍的近似最优轨迹。     

基于时标分解的弹性高超声速飞行器智能控制

考虑弹性高超声速飞行器纵向动力学模型，提出了一种基于时标分解的智能控制方法。考虑刚体状态和弹性模态具有不同的时标特性，采用奇异摄动理论进行快慢时标分解，将模型转换为刚体慢变子系统和弹性快变子系统。针对刚体子系统考虑动力学不确定，基于平行估计模型构造表征不确定逼近效果的预测误差，结合跟踪误差给出复合学习控制策略。针对弹性子系统设计自适应滑模控制稳定弹性模态。通过李雅普诺夫稳定性分析可证系统状态一致终值有界。仿真表明所提出的控制方法能够实现刚弹模态的稳定收敛，且具有更高的跟踪精度、更好的学习性能和更快的收敛速度。     

Six sigma robust design optimization for thermal protection system of hypersonic vehicles based on successive response surface method

Lightweight design is important for the Thermal Protection System(TPS) of hypersonic vehicles in that it protects the inner structure from severe heating environment. However, due to the existence of uncertainties in material properties and geometry, it is imperative to incorporate uncertainty analysis into the design optimization to obtain reliable results. In this paper, a six sigma robust design optimization based on Successive Response Surface Method(SRSM) is established for the TPS to improve the reliability and robustness with considering the uncertainties. The uncertain parameters related to material properties and thicknesses of insulation layers are considered and characterized by random variables following normal distributions. By employing SRSM, the values of objective function and constraints are approximated by the response surfaces to reduce computational cost. The optimization is an iterative process with response surfaces updating to find the true optimal solution. The optimization of the nose cone of hypersonic vehicle cabin is provided as an example to illustrate the feasibility and effectiveness of the proposed method.