Aerodynamic design optimization of nacelle/pylon position on an aircraft

The arbitrary space-shape free form deformation (FFD) method developed in this paper is based on non-uniform rational B-splines (NURBS) basis function and used for the integral parameterization of nacelle-pylon geometry. The multi-block structured grid deformation technique is established by Delaunay graph mapping method. The optimization objects of aerodynamic characteristics are evaluated by solving NavierStokes equations on the basis of multi-block structured grid. The advanced particle swarm optimization (PSO) is utilized as search algorithm, which com-bines the Kriging model as surrogate model during optimization. The optimization system is used for optimizing the nacelle location of DLR-F6 wing-body-pylon-nacelle. The results indicate that the aerodynamic interference between the parts is significantly reduced. The optimization design system established in this paper has extensive applications and engineering value.     

基于改进的动态Kriging模型的结构可靠度算法

对于复杂航空航天机械产品,极限状态方程往往表现出隐式、高度非线性的特点,而且通常需要调用有限元分析,从而耗费大量时间。将混合粒子群-模拟退火（PSOSA）算法应用到Kriging模型中相关参数的寻优过程,提高了预测精度。同时结合动态更新机制,逐渐加入样本点,尽可能减少函数的调用次数,从而提高了计算效率,并将该算法应用到结构可靠性分析中。通过案例分析,和传统蒙特卡罗模拟方法、响应面等经典方法进行对比,所提算法与蒙特卡罗模拟方法计算结果更加接近,计算时间大大缩短,效率和精度都明显改进。      

基于梯度增强型Kriging模型的气动反设计方法

基于Kriging模型的代理优化算法目前在气动优化设计中得到了广泛应用。但在高维(设计变量大于30个)气动优化中,计算量过大的问题对其进一步发展产生了严重制约。将翼型和机翼气动反设计问题转化为优化问题,采用Adjoint方法进行快速梯度求解,利用基于梯度增强型Kriging(GEK)模型的代理优化算法分别开展了18、36和108个设计变量的气动反设计。首先,通过采用在设计空间局部建立GEK模型的方法成功地将基于代理优化算法的气动反设计问题的维度拓展到了100维以上。其次,研究了梯度计算精度对基于GEK模型的反设计的影响,发现梯度精度越高,反设计的最终效果越好,同时效率相当。最后,通过不同维度的气动反设计算例,比较了改进拟牛顿法(BFGS)、基于GEK模型和Kriging模型的代理气动反设计方法,结果表明基于GEK模型的代理优化算法的效率大幅度高于基于Kriging模型的代理优化算法,并且维度越高,效率优势越明显;同时,基于GEK模型的代理优化算法在优化效果及分析程序调用次数上相比于BFGS方法也略有优势。     

Variable-fidelity optimization with design space reduction

Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity (LF) model provides physics-based approximation of the high-fidelity (HF) model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.     

An efficient algorithm for calculating Profust failure probability

For efficiently estimating the Profust failure probability based on probability input variables and fuzzy-state assumption, a General Performance Function(GPF) expression is established under the strict mathematical derivation for the Profust reliability model. By constructing the GPF,the calculation of the Profust failure probability can be transformed into the calculation of the traditional failure probability. Then various existing methods for the traditional failure probability can be used to estimate the Profust failure probability. Due to the high efficiency of the Adaptive Kriging(AK) model and the universality of the Monte Carlo Simulation(MCS), AK inserted MCS(abbreviated as AK-MCS) has been proven to be an efficient method for estimating the failure probability. Therefore, the AK-MCS combined with the GPF(abbreviated as AK-MCS + GPF)is proposed for estimating Profust failure probability. The proposed method greatly reduces the computational cost while ensuring the accuracy. Finally, four examples are given to validate the proposed AK-MCS + GPF. The results of the examples show the rationality and the efficiency of the proposed AK-MCS + GPF.     

Rotorcraft flight endurance estimation based on a new battery discharge model

To avoid the numerical complexities of the battery discharge law of electric-powered rotorcrafts,this study uses the Kriging method to model the discharge characteristics of Li-Po batteries under standard conditions.A linear current compensation term and an ambient temperature compensation term based on radial basis functions are then applied to the trained Kriging model,leading to the complete discharged capacity-terminal voltage model.Using an orthogonal experimental design and a sequential method,the coefficients of the current and ambient temperature compensation terms are determined through robust optimization.An endurance calculation model for electric-powered rotorcrafts is then established,based on the battery discharge model,through numerical integration.Laboratory tests show that the maximum relative error of the proposed discharged capacity-terminal voltage model at detection points is 0.0086,and that of the rotorcraft endurance calculation model is 0.0195,thus verifying their accuracy.A flight test further demonstrates the applicability of the proposed endurance model to general electric-powered rotorcrafts.     

飞机多学科设计优化中的近似方法分析

首先介绍了近似方法中的二次响应面方法、径向基神经网络方法、Kriging方法和增强的径向基函数方法。结合测试函数和某机翼模型为例,分别用这四种方法构造测试函数和某机翼结构和气动学科的近似模型,并总结这四种方法的特点和在对各种模型近似中的适用性。结果表明,Kriging方法和增强的径向基函数方法的近似是非常精确和稳健的。     

基于Kriging模型的浮空器氦气昼夜温差最优化

分析浮空器氦气昼夜温差时通常将整个囊体蒙皮涂层设置为同一种材料,分析材料的吸收率与发射率对氦气昼夜温差的影响。为进一步减小氦气昼夜温差,提出了将囊体分为迎光面和背光面,迎光面采用吸收率低的材料,背光面采用发射率高的材料。建立了囊体热力学模型,采用Kriging模型对囊体不同部位的材料特性进行优化,其基本思想是将囊体划分为48个部分,采用拉丁超立方体方法进行抽样,进行热力学分析得到样本的响应,以此建立Kriging近似模型。经过该方法优化后发现,氦气的昼夜温差减小到28.6 K,比传统的分析减少7.7%。      

基于Kriging模型的翼型多目标气动优化设计研究

在翼型气动优化设计中引入Kriging代理模型,发展了一套高效、稳定的气动优化设计程序。采用拉丁超立方试验设计方法在设计空间内构造一系列样本点,通过求解二维可压缩的雷诺平均NS方程（RANS）得到其响应值来建立初始Kriging模型。优化设计采用Hicks-henne函数对翼型几何外形进行参数化表示,以阻力极小化为设计目标,考虑面积、升力、力矩等约束条件,通过算例证明,发展的优化设计方法不仅可行,而且具有高效稳定的特性。与传统的优化设计方法比较,大大减少了设计时间。     

基于流体力学和电磁学方程数值求解的飞行器气动隐身一体化设计

介绍了基于流体力学和电磁学方程数值求解的飞行器气动隐身一体化设计方法.首先介绍了精度相对较高的飞行器气动和隐身特性数值计算方法,即,对于气动性能计算,求解的是结构网格上的NS方程加BL代数湍流模式;对于隐身特性计算,是用时域有限体积法来求解电磁学微分方程以获取RCS值.由于采用了高精度的数值方法,优化时单一设计点的气动性能计算和隐身性能计算变得较为耗时,因此在进行多目标遗传算法优化时本文采用了一种"少量样本计算+Kriging响应面模型建模"的优化策略.针对某类似X-47飞行器的一体化设计算例计算表明,上述设计方法是可行的,实现了优化设计中引入高精度的性能分析方法,有望提高优化结果的可信度.