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.     

GEO/IGSO混合区域导航星座的设计与优化算法

区域导航星座能够以较低成本和较短时间获得目标区域导航能力，且地球同步轨道是构建非极区区域导航星座的重要轨道类型。提出一种基于GEO（地球静止轨道）和IGSO（倾斜地球同步轨道）的区域导航星座设计方法。基于星下点轨迹特性构造对称星座设计参数和优化参数集，并考虑地球扁率长期摄动影响，计算星座轨道参数。以导航服务区的统计GDOP（几何精度因子）为目标函数，利用差分进化算法构建星座优化模型。以印度IRNSS的7星星座为例，仿真检验了设计和优化算法的正确性，讨论了IRNSS星座优化构型和轨道类型选取。本方法采用的对称星座设计参数少，能够提升GEO/IGSO混合区域导航星座的全局优化效率，为后续非对称星座快速提供最佳星数和构型设计。     

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.     

基于代理模型全局优化的自适应参数化方法

对于翼型气动隐身设计问题，设计变量的配置对设计结果影响很大，而简单地增加设计变量不能保证得到理想的结果。提出一种适用于代理模型全局优化的自适应参数化方法：利用全局敏感性分析方法——基本效应法，得到设计空间关于目标函数的敏感区域信息，并以此为根据增加设计变量；利用节点插入算法将低维样本在高维空间内进行重构，避免了重新取样的工作量。相对于传统固定设计空间维度方法，自适应参数化方法在设计空间的敏感区域扩展维度，能够更加精准地描述外形并反映目标的变化趋势。通过飞翼布局翼型的气动隐身优化算例，证实自适应参数化方法可以大幅提高优化设计质量和效率。     

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.     

高速开关阀控电液位置伺服系统自适应鲁棒控制

为研究高精度的液压缸位置跟踪控制问题，设计了高速开关阀和换向阀组合控制液压缸的结构方案，并通过实验分析了高速开关阀的静态流量特性。建立了液压缸的连续可微摩擦模型，利用粒子群优化算法对其参数进行辨识。建立了系统的非线性数学模型，基于非连续参数映射和反步法设计了直接自适应鲁棒控制器，通过参数在线自适应调节来更新估计值和鲁棒反馈项支配参数不确定性，实验结果表明:在跟踪幅值为5mm，频率为0.4Hz的正弦信号时，最后一个周期的最大跟踪误差、平均跟踪误差及其标准差分别为0.638、0.25mm和0.405mm，与传统PID控制器相比，控制精度显著提升，旨在为实现高精度的数字阀控位置伺服技术提供有价值的参考。      

可靠性设计优化的球空间设计法

可靠性设计优化（RBDO）在航空航天等领域已经被广泛应用，具有显著提高可靠性的效果；然而它包含两个迭代循环-总体优化循环和可靠性分析循环，双循环求解方法效率低下甚至难以承受。本文提出一种可以提高可靠性设计优化求解效率的方法-球空间设计法，该方法可以方便地表达搜索区域，最大可能失效点可以从极值点处精确获取；同时，该方法可以将总体优化以及可靠性分析同步进行。本文所提出的球空间法的有效性将通过2个算例进行测试，测试结果表明该方法不仅精度与同类方法持平，求解效率有明显提升，它将会对提高航空航天装备如卫星、火箭、飞行器等产品的可靠性提供更为有效的方法和技术支持。     

运载火箭主动段自适应增广控制

针对运载火箭上升段在复杂飞行环境、大不确定性干扰和振动等因素的影响下，传统PID控制方法难以满足高品质控制需求的问题，进行了自适应增广控制(AAC)方法研究，以实现对运载火箭姿态的精确控制。在深入分析自适应增广控制系统整体构架的基础上，通过标称PID控制器设计与基于粒子群优化(PSO)的数字滤波器设计实现了刚体控制及对弹性振动的抑制；继而针对大范围干扰、不确定性和由于滤波器切换产生的弹性振动影响，设计了在线调整算法自适应调节PID控制增益，并对其工作机理与参数设计原则进行研究；然后设计干扰补偿回路和主动减载回路以减小内外扰动、弹性振动和风载荷影响；最后在弹性振动、风干扰和参数不确定性等因素同时作用的状态下进行仿真分析，验证了自适应增广控制系统能够有效应对运载火箭主动段复杂飞行环境的影响，大幅度提升综合控制性能，具有理论研究意义与工程应用价值。     

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.     

Which way is the bookstore? A closer look at the judgments of relative directions task

We present a detailed analysis of a widely used assay in human spatial cognition, the judgments of relative direction (JRD) task. We conducted three experiments involving virtual navigation interspersed with the JRD task, and included confidence judgments and map drawing as additional metrics. We also present a technique for assessing the similarity of the cognitive representations underlying performance on the JRD and map-drawing tasks. Our results support the construct validity of the JRD task and its connection to allocentric representation. Additionally, we found that chance performance on the JRD task depends on the distribution of the angles of participants’ responses, rather than being constant and 90 degrees. Accordingly, we present a method for better determining chance performance.