A review of topology optimization for additive manufacturing: Status and challenges

Topology optimization was developed as an advanced structural design methodology to generate innovative lightweight and high-performance configurations that are difficult to obtain with conventional ideas. Additive manufacturing is an advanced manufacturing technique building as-designed structures via layer-by-layer joining material, providing an alternative pattern for complex components. The integration of topology optimization and additive manufacturing can make the most of their advantages and potentials, and has wide application prospects in modern manufacturing. This article reviews the main content and applications of the research on the integration of topology optimization and additive manufacturing in recent years, including multi-scale or hierarchical structural optimization design and topology optimization considering additive manufacturing constraints. Meanwhile, some challenges of structural design approaches for additive manufacturing are discussed, such as the performance characterization and scale effects of additively manufactured lattice structures, the anisotropy and fatigue performance of additively manufactured material, and additively manufactured functionally graded material issues, etc. It is shown that in the research of topology optimization for additive manufacturing, the integration of material, structure, process and performance is important to pursue high-performance, multi-functional and lightweight production. This article provides a reference for further related research and aerospace applications.     

多变量全局寻优与智能优化在星座组网中的应用

顶层任务规划通常与星座组网紧密结合,小卫星分散灵活的特性尤其适用于星群规模化在轨运行。针对热点区域覆盖和全球覆盖的不同任务需求,提出了对构型多变量进行全局寻优和利用智能优化技术进行星座构型优化的方法,两种优化方法可分别获得小规模星群最优效能与超大型星群的较优效能。优化方法不受轨道类型和任务目标分布的约束,具有良好的鲁棒性。     

100 kWe级空间快堆核电源系统仿真平台开发与应用

空间核反应堆电源作为一种具有竞争力的空间电源方案,正逐渐受到关注及应用。本文针对一个100 kWe级锂冷快堆耦合布雷顿循环的空间堆核动力系统方案,修改了RELAP5程序中的物性程序、换热模型,程序中的中子动力学模块使用蒙特卡洛方法计算快堆物理参数与堆芯控制调节参数,由此集成并建立一个空间快堆核动力系统综合仿真平台,应用该平台对100 kWe级空间堆核动力系统进行了稳态模拟与事故分析。结果表明:在瞬态发生后系统各参数变化符合预期,验证了各部件及控制系统的功能性及有效性;同时,还初步进行了仿真平台用于100 kWe级空间反应堆核动力系统设备的设计优化的实践,为空间快堆设计与安全分析提供了技术储备。     

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.     

基于Optistruct的结构静动力拓扑优化设计

基于Optistruct平台,研究了二维平面薄板及三维结构的静力、动力以及静动力联合的拓扑优化,给出了典型结构的算例,对比了优化参数取值不同时所对应的优化结果,探讨了优化过程中的网格依赖性以及拓扑优化的效率等问题.     

ORB-SLAM系统优化框架分析概述

首先阐述了ORB-SLAM系统的核心思想和基本框架,介绍了SLAM系统中光束平差法的应用实现,然后针对视觉里程计部分不同的关键帧位姿优化过程分别进行了详细阐述,并利用KITTI数据集的不同序列的实验结果进行比较研究,给出了核心的光束平差法在ORB-SLAM中的具体工作方式及性能分析,最后讨论和分析了ORB-SLAM的优势和不足。     

智能方法在惯性系统误差参数辨识中的应用

总结了目前我国提高惯性系统导航精度的技术途径,阐述了国内外惯性系统误差参数辨识方法的研究现状,介绍了当前滤波算法、智能优化算法和人工神经网络方法在惯性系统导航领域的应用情况以及存在的不足。最后,分析了空间飞行器惯性系统误差参数辨识技术的未来研究方向,即智能优化算法和人工神经网络方法等智能方法将在惯性系统误差参数辨识中发挥越来越重要的作用,通过将误差系数标定问题转换为参数辨识问题,采用智能方法在庞大的解空间内实现对惯性系统误差参数的快速辨识。     

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。     

一种未来大型天地往返运输系统平台气动方案

针对未来低运行成本、可直接水平起降、重复使用的大型天地往返运输系统平台飞行器研制所需重点解决的全速域气动力性能需求与气动热防护匹配等难题,分析了典型航天飞机方案所存在的能量运行缺陷等主要问题及可能的改善方案。基于放宽气动热防护设计、涡轮/冲压/火箭发动机三动力组合、嵌套式旋转机翼全速域变体、在爬升阶段将飞行动能转化为高度势能以及再入阶段“跳跃式”盘旋减速飞行轨迹控制等设计思想,从能量损失速率控制和回收利用等角度出发,开展了一种新型大型天地往返运输系统平台气动布局概念设计研究。全速域气动力/热性能工程估算以及内/外流整体气动效能初步分析结果表明,该方案可有效满足整个飞行包线内的升重平衡需求,相比航天飞机方案具有显著的整体气动效能优势,值得进一步开展深入研究。     

基于欠采样的零阶优化算法

非平衡学习吸引了许多研究者的关注。一般情况下,少数类是更值得关注的,并且其误分类代价要远高于多数类。由于非平衡数据分布的非均衡性,标准的分类算法将难以适用。为了解决非平衡数据分类问题,给出了基于欠采样的零阶优化算法。首先,为了降低数据非平衡分布的影响,针对不同非平衡比的数据集给出了不同的两种采样策略。然后,采用了一种引入间隔均值项的支持向量机(Support vector machine,SVM)优化模型进行分类,并使用带有方差减小的零阶随机梯度下降算法进行求解,提高了算法的精度。在非平衡数据上进行了对比实验,实验证明提出的方法有效提高了非平衡数据的分类效果。