Aerodynamic optimization of rotor airfoil based on multi-layer hierarchical constraint method

Rotor airfoil design is investigated in this paper. There are many difficulties for this high-dimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer hierarchical constraint method is proposed by coupling principal component analysis (PCA) dimensionality reduction and e-constraint method to translate the orig-inal high-dimensional problem into a bi-objective problem. This paper selects the main design objectives by conducting PCA to the preliminary solution of original problem with consideration of the priority of design objectives. According to the e-constraint method, the design model is estab-lished by treating the two top-ranking design goals as objective and others as variable constraints. A series of bi-objective Pareto curves will be obtained by changing the variable constraints, and the favorable solution can be obtained by analyzing Pareto curve spectrum. This method is applied to the rotor airfoil design and makes great improvement in aerodynamic performance. It is shown that the method is convenient and efficient, beyond which, it facilitates decision-making of the high-dimensional multi-objective engineering problem.     

大型民用飞机气动外形典型综合设计方法

基于自主研发的飞行器气动外形大规模并行化、分布式综合设计软件AMDEsign，开展了大型民用飞机气动外形多目标综合设计，研究了处理高维目标空间多目标优化问题的有效处理方式，为优化数学模型的合理确定提供数据参考。在此基础之上，基于软件AMDEsign的主分量分析（PCA）、离散伴随方法两个典型模块，对宽体飞机数字化模型开展多目标优化，其中离散伴随方法中引入虚拟可行解集逼近方法，为权系数提供有效的导向性选择；并进一步将结果进行多目标评估分析，设计结果表明，主分量分析能够有效识别目标函数的相关性，虚拟可行解集方法效率较高，充分利用了离散伴随效率高以及导向性权函数预测等优点，多点设计外形在巡航升阻比、抖振特性以及阻力发散等性能上具有明显改善。文中提出的综合设计方法简捷高效且具有较强的工程应用价值。     

基于变精度遗传算法的翼型快速优化设计方法

低碳环保的电动飞机在要求较高升阻比的同时,需要尽量降低成本、缩短研制周期。但高精度的数值模拟时间代价很大,因此针对电动飞机翼型设计中初始翼型较难选取、优化速度较慢的问题,提出了一种基于变精度遗传算法的翼型多点快速优化方法。以常用的 Hicks-Henne 型函数为基础,改进了其对翼型后缘描述不精确的问题。在数值模拟阶段,介绍了一种快速气动参数计算软件XFOIL,并分析了该软件的适用性与局限。之后给出了使用XFOIL 与 Matlab 进行联合求解的方法,在无人干预的情况下完全实现了翼型设计与优化的自动化,提高了设计效率。在翼型优化阶段,为保持较高的精度和寻优效率,设计了翼型参数的实数编码方法。针对传统遗传优化算法了改进,设计了染色体变精度杂交方法以及动态惩罚方法。最后,给出了基于遗传算法的多点优化方案,以及翼型多目标快速优化一体化设计方案。仿真分成两部分进行,首先改进的 Hicks-Henne 型函数能够有效实现参数化翼型的后缘夹角改变。通过与 NSGA-II 方法的优化结果对比,本文的方法在一定迭代次数范围内获得的升阻比更高,失速特性更加缓和,特别是在综合提高翼型优化效率方面表现较好。仿真结果表明,该方法能够快速获得多种工况下具有较高升阻比的翼型,也可以作为进一步优化的初始翼型,能提高翼型优化效率。     

Research of low boom and low drag supersonic aircraft design

Sonic boom reduction will be an issue of utmost importance in future supersonic transport, due to strong regulations on acoustic nuisance. The paper describes a new multi-objective optimization method for supersonic aircraft design. The method is developed by coupling Seebass–George–Darden(SGD) inverse design method and multi-objective genetic algorithm.Based on the method, different codes are developed. Using a computational architecture, a conceptual supersonic aircraft design environment(CSADE) is constructed. The architecture of CSADE includes inner optimization level and out optimization level. The low boom configuration is generated in inner optimization level by matching the target equivalent area distribution and actual equivalent area distribution. And low boom/low drag configuration is generated in outer optimization level by using NSGA-II multi-objective genetic algorithm to optimize the control parameters of SGD method and aircraft shape. Two objective functions, low sonic boom and low wave drag, are considered in CSADE. Physically reasonable Pareto solutions are obtained from the present optimization. Some supersonic aircraft configurations are selected from Pareto front and the optimization results indicate that the swept forward wing configuration has benefits in both sonic boom reduction and wave drag reduction. The results are validated by using computational fluid dynamics(CFD) analysis.     

Optimization Design System for Composite Structures Based on Grid Technology

To solve the topology optimization of complicated multi-objective continuous/discrete design variables in aircmit structure design, a Parallel Pareto Genetic Algorithm （PPGA） is presented based on grid platform in this paper. In the algorithm, the commercial finite element analysis （FEA） software is integrated as the calculating tool for analyzing the objective functions and the filter of Pareto solution set based on weight information is introduced to deal with the relationships among all objectives. Grid technology is utilized in PPGA to realize the distributed computations and the user interface is developed to realize the job submission and job management locally/remotely. Taking the aero-elastic tailoring of a composite wing for optimization as an example, a set of Pareto solutions are obtained for the decision-maker. The numerical results show that the aileron reversal problem can be solved by adding the limited skin weight in this system. The algorithm can be used to solve complicated topology optimization for composite structures in engineering and the computation efficiency can be improved greatly by using the grid platform that aggregates numerous idle resources.     

一类公务机客舱布置的多目标优化

针对双发涡扇公务机在总体设计阶段的客舱布置,建立了基于经济性与舒适性的优化模型并计算了一个案例。运用回归分析对大量该类飞机的历史数据进行了统计分析,得到了若干客舱几何参数与飞机总体参数及经济性、舒适性指标的数学关系式,并提出了两类指标的数学模型并进行了无量纲化。最后通过线性加权法求解了基于经济性与舒适性的多目标优化问题...     

平流层飞艇总体多目标优化设计与决策

将多目标优化与多属性决策相结合应用于平流层飞艇总体多目标优化中。建立平流层飞艇多目标优化模型,实现优化模型参数化建模,采用多目标进化算法NSGA－Ⅱ得到Pareto最优解集,构成多属性决策矩阵,采用模糊熵权TOPSIS（ M－TOPSIS）法对Pareto非劣解进行排序,获得最佳设计方案。最终结果验证了NSGA－Ⅱ平流层飞艇多目标优化中的有效性。     

部件级多组件结构系统的整体式拓扑布局优化

基于多组件结构系统整体式拓扑布局优化设计方法,研究了同时含有部件布局、组件布局、主结构框架构型和部件结构构型4类设计变量的复杂系统协同优化设计问题,是整体式拓扑布局优化设计面向复杂飞行器结构系统设计的拓展。采用多点约束(MPC)模拟组件、部件及支撑结构之间的刚性连接,采用有限包络圆方法(FCM)解决组件之间、组件与设计域边界之间的几何干涉问题。通过整体式拓扑布局的刚度优化设计,部件和组件均可以获得优化的布局位置,同时主结构框架构型和部件结构构型获得优化的结构样式,充分体现了整体式拓扑布局优化设计方法应用于复杂结构系统设计的能力。     

超临界机翼多目标气动优化设计的策略与方法

超临界机翼的气动设计十分复杂,往往需要借助于有效的优化手段。然而,优化方法本身往往无法直接表达真实完整的设计意图,因此需要将工程需求和约束转换为优化方法所能处理的数学形式。本文首先探讨了梯度优化方法和进化类优化方法在气动优化中的表现。之后简要总结了前人在飞机气动设计中提出的准则和要求,并基于压力分布形态定义了超临界机翼气动设计的关键特征及定量要求,探究其在超临界机翼气动优化设计中的应用效果。研究结果表明,在多目标优化中引入面向压力分布形态特征的目标和约束,能有效引导优化体现工程设计思想,进而提高优化效率。     

基于Pareto集与多目标决策的飞控参数优化

针对传统的单目标优化方法不能对飞控系统多个性能指标同时进行优化的问题,提出了一种基于Pareto遗传算法和多目标决策的飞控系统参数优化方法。通过NSGA-Ⅱ算法对飞控系统参数进行优化获得最优解集,在此基础上首先进行方案的初选,然后利用综合权重的Vague集决策方法对备选方案进行模糊评价和优选,找到最终满意解。仿真结果验证了所设计方法的有效性。