基于Navier-Stokes方程跨声速翼型和机翼气动优化设计

将响应面方法引入到气动优化设计上来,进行了基于N-S方程跨声速翼型、机翼气动优化设计。通过去掉完全二阶多项式响应面模型中的二阶交叉项,大大减少了构造高维响应面模型所需要的计算量。合理地选择优化设计空间,保证了构造的响应面模型具有较高精度。跨声速翼型、机翼减阻优化算例结果表明该方法能有效地适用于气动优化设计问题,设计质量高,方法实用可靠,有较高的工程应用前景。     

进口导流叶排对轴流压气机级畸变响应特性影响

基于轴流压气机叶片排实验特性，应用畸变传递的矩阵分析模型，对带有进口导流叶片排的轴流压气机级容总压畸变特性进行了详细分析，初步建立了进口导流叶片排对总压畸变及其沿轴流压气机叶片排衰减特性影响规律。计算结果表明，与无导流叶片排相比，带有进口导流叶片排的轴流压气机级具有更强的总压畸变、总温畸变和静压畸变衰减能力，有利于提高轴流压气机稳定工作范围。     

固体火箭冲压发动机补燃室的响应面法优化设计

影响固体火箭冲压发动机补燃室燃烧效率的因素很多,且各因素对燃烧效率的影响很难用精确的解析函数式来表示。采用基于正交多项式的响应面法结合数值模拟的优化方法对某实验发动机补燃室进行了设计,结果表明:这种优化方法可以减少为得到近似函数式而对补燃室流场进行计算的次数,节省计算时间,能方便地对发动机补燃室各个参数进行优化与分析。     

联接翼气动／结构协同优化设计

联接翼是一种将前翼和后翼连接在一起的飞行器布局形式。针对联接翼气动／结构一体化的布局概念，通过结构有限元参数化建模、结构优化、试验设计和响应面模型技术，采用基于响应面的协同优化算法对其进行了气动与结构一体化设计，所获计算结果对大展弦比联接翼飞机构型初步设计具有参考价值。     

On prediction of re-entry time of an upper stage from GTO

The evolution of objects in geostationary transfer orbit (GTO) is determined by a complex interplay of atmospheric drag and luni-solar gravity. These orbits are highly eccentric (eccentricity >0.7) and have large variations in velocity and perturbations during a revolution. The periodic changes in the perigee altitudes of these orbits are mainly due to the gravitational perturbations of the Sun and the Moon. The re-entry time of the objects in such orbits is sensitive to the initial conditions. The aim of this paper is to study the re-entry time of the cryogenic stage of the Indian geo-synchronous launch vehicle, GSLV-F04/CS, which has been decaying since 2 September 2007 from initial orbit with eccentricity equal to 0.706. Two parameters, initial eccentricity and ballistic coefficient, are chosen for optimal estimation. It is known that the errors are more in eccentricity for the observations based on two line elements (TLEs). These two parameters are computed with response surface method using a genetic algorithm for the selected eight different zones, based on rough linear variation of the mean apogee altitude during 200 days orbit evolution. The study shows that the GSLV-F04/CS will re-enter between 5 December 2010 and 7 January 2011. The methodology is also applied to study the re-entry of six decayed objects (cryogenic stages of GSLV and Molniya satellites). Good agreement is noticed between the actual and the predicted re-entry times. The absolute percentage error in re-entry prediction time for all the six objects is found to be less than 7%. The present methodology is being adopted at Vikram Sarabhai Space Centre (VSSC) to predict the re-entry time of GSLV-F04/CS.     

弹翼展开机构可靠性分析

提出了一种折迭弹翼机构在指定时间内展开到位的可靠性分析方法，文中采用序列响应面法和全概率定理解决了涉及机构动力学随机参数及发射攻角随机参数的双重随机性问题，基于本方法所研制的RSMM程序应用效果良好。     

复合材料瞬变电磁检测的模拟试验

建立了小尺度浅层瞬变电磁法检测碳纤维复合材料的计算模型.沿测线将计算模型进行简化,通过Hankel变换求取测点的瞬变电磁响应,组合所有测点的数据获得复合材料的瞬变电磁响应.结果表明:异常与试块缺陷有很好的对应关系,计算精度随测点间距的减小而增加.通过与检测试验数据的对比,分析和验证了计算模型的适用性和精度.     

基于神经网络的翼盒结构响应重构方法应用

翼盒结构复杂，航行中承载条件恶劣，利用有限测点信息重构其它位置响应对于实时健康监测具有很强的现实意义。通过误差反向传播神经网络训练得到响应之间的非线性关系，建立基于神经网络的响应重构方法，开展有限元分析对其进行数值仿真验证，并将该方法应用于实测随机激励环境下翼盒典型承力结构的响应重构及损伤定位与判断分析。结果表明：采用该方法重构出的预测响应功率谱密度的均方根相对误差不超过1.90 dB，主要频点误差小于10%；判断出翼盒关键测点e 的损伤或故障发生在所截取片段数据3 s 后，其故障特征频率为240 Hz 左右，该方法应用于响应重构预示及健康监测分析具有可行性。     

Stochastic structural optimization using particle swarm optimization, surrogate models and Bayesian statistics

This paper focuses on a method to solve structural optimization problems using particle swarm optimization (PSO), surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method (RSM) and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem.     

着陆姿态不确定下的着陆器缓冲机构优化设计

以某型着陆器为研究对象，建立其软着陆过程的动力学仿真模型，并结合Monte Carlo法研究不确定着陆姿态下的某型软着陆性能。然后，分析着陆器的软着陆性能与其缓冲机构构型参数之间的相关关系，并基于实验设计方法与动力学仿真模型得到样本点，建立以着陆器缓冲机构构型参数和着陆姿态参数为输入、软着陆性能指标值为输出的响应面模型。最后，基于响应面模型，考虑着陆器姿态的不确定性，运用结合第二代非劣排序遗传算法(NSGA-II)和多岛遗传算法(MIGA)的分级优化方法实现了着陆器缓冲机构的优化计算，得到了最佳缓冲机构构型参数。通过仿真模型校验，优化后着陆器的抗翻倒能力与底面抗损坏能力分别提升了3.546%和 5.140% 。