点火瞬态过程仿真模型参数辨识

建立了固体火箭发动机点火瞬态过程一维非定常流场仿真模型,采用系统辨识方法进行了模型参数不确定性研究。基于点火试验用缩比发动机试验结果,得到了传热模型参数和瞬态燃速模型参数的最优估计,提高了点火瞬态过程一维仿真模型的预估精度。采用近似方法,构建Kriging近似函数,有效解决了一维非定常流场仿真的计算复杂性问题。     

基于Kriging模型梯度解析解的改进一次二阶矩方法

改进一次二阶矩（AFOSM）法是一种基于功能函数梯度的结构可靠性分析方法，鉴于其对隐式函数的梯度较难求解，提出了一种基于Kriging模型梯度解析解的AFOSM方法，利用Kriging代理模型的解析表达式推导得到功能函数对输入变量的梯度解析解，为AFOSM中设计点的确定提供高精度的梯度信息。通过Kriging与AFOSM的结合，很好地解决了基于有限元模型的隐式情况下梯度计算量相当大、可靠性分析难的问题。数值与工程算例验证了所提Kriging梯度解析解的较高精确性，同时验证了所提基于Kriging解析解的AFOSM结构可靠性分析方法的正确性与较高精度。     

基于自适应Kriging代理模型的交叉熵重要抽样法

对于复杂失效域和小失效概率耦合的可靠性分析问题，本文提出了一种交叉熵重要抽样（CE-IS）方法结合自适应Kriging （AK）代理模型的求解方法（CE-IS-AK）。所提方法基于交叉熵原理，用混合高斯模型逐步逼近最优重要抽样密度函数，并采用AK模型协助逼近过程中混合高斯模型的参数的更新，从而提高了CE-IS方法的计算效率。另外，本文还改进了CE-IS方法的收敛准则，避免了方法的冗余迭代，扩大了方法的适用范围。由于在CE-IS方法中引入了AK模型，因此，本文方法所构建的重要抽样函数在保证精度的基础上提高了效率。相较于AK-MCS方法，本文方法中引入了重要抽样的思想，因此在Kriging训练点数目基本相同的情况下，大幅缩减小失效概率计算时样本池规模，并且由于利用了混合高斯模型，因而对多失效域具有较好的适用性。算例分析也证明了本文所提方法的优越性。     

基于混沌理论的滚动轴承振动信号融合模型预测

提出融合算法模型,在混沌理论的基础上对滚动轴承振动信号进行预测。基于相图法、最大Lyapunov指数法和关联维数法对滚动轴承振动信号进行混沌判别,证明其混沌性。以预测值和真值间差值范数最小为目标导向优化出Kriging模型、最小二乘支持向量机(LSSVM)模型和极端学习机(ELM)模型的权重,加权法构建融合算法模型。相空间重构法构建滚动轴承振动信号预测的训练样本,并对融合模型、Kriging模型、LSSVM模型和ELM模型进行训练,训练好的模型用于振动轴承振动信号混沌预测。以案例1和案例2共两个实验的滚动轴承振动信号为对象进行验证,两案例的最大Lyapunov指数大于0,从而判断这两个案例的轴承振动信号呈现混沌特性。另外,从方均误差、方均根误差和平均绝对误差指标来评价,融合算法模型的指标值均小于单一模型算法,融合算法模型的预测精度优于单一模型算法。     

基于自适应代理模型的结构动力可靠度分析方法

结构动力可靠度分析对于衡量结构的安全状态和工作性能具有重要的指导意义。采用一种同时考虑 动态激励载荷和材料力学性能参数随机性的动力可靠度计算高效方法,通过建立不确定性材料力学性能参数 与条件动力可靠度之间的 Kriging代理模型,推导动力可靠度的解析表达式;提出一个新的学习函数来构建自 适应的 Kriging代理过程,通过复合材料飞行器蒙皮骨架结构在随机振动载荷和随机材料力学性能参数共同作 用下的动力可靠度分析对所提方法的准确性与高效性进行验证。结果表明:所提方法不仅能够避免使用代理 模型对动力可靠度求解时由于使用数值积分所引入的误差,同时能够使用尽可能少的计算成本获得准确的动 力可靠度结果。     

Improved predictions of equatorial TEC for real time applications

It is important to use models developed specifically for the equatorial ionospheric estimation for real-time applications, particularly in Satellite Navigation. This work demonstrates a methodology for improved predictions of VTEC in real time using the model developed for the equatorial ionosphere by the authors. This work has been done using TEC data of the low solar activity period of 2005 obtained using dual frequency GPS receivers installed under the GAGAN project of ISRO. For the purpose, the model is first used in conjunction with Kriging technique. Improvement in accuracy is observed when compared with the estimations from the model alone using the measurements as true reference. Further improvement is obtained by Bayesian combination of these estimates with independent Neural Network based predictions. Statistical performance of improvement is provided. An improvement of ∼1 m in confidence level of estimation of VTEC is obtained.     

Global aerodynamic design optimization based on data dimensionality reduction

In aerodynamic optimization, global optimization methods such as genetic algorithms are preferred in many cases because of their advantage on reaching global optimum. However, for complex problems in which large number of design variables are needed, the computational cost becomes prohibitive, and thus original global optimization strategies are required. To address this need, data dimensionality reduction method is combined with global optimization methods, thus forming a new global optimization system, aiming to improve the efficiency of conventional global optimization. The new optimization system involves applying Proper Orthogonal Decomposition (POD) in dimensionality reduction of design space while maintaining the generality of original design space. Besides, an acceleration approach for samples calculation in surrogate modeling is applied to reduce the computational time while providing sufficient accuracy. The optimizations of a transonic airfoil RAE2822 and the transonic wing ONERA M6 are performed to demonstrate the effectiveness of the proposed new optimization system. In both cases, we manage to reduce the number of design variables from 20 to 10 and from 42 to 20 respectively. The new design optimization system converges faster and it takes 1/3 of the total time of traditional optimization to converge to a better design, thus significantly reducing the overall optimization time and improving the efficiency of conventional global design optimization method.     

基于Kriging模型插值的孔位修正策略

飞机装配时的孔位精度直接影响其最终装配质量，而待制孔零件易发生变形和整体偏移，因此一般通过基准孔信息对待制孔位进行补偿。提出一种基于Kriging插值的孔位修正方法，通过基准孔建立孔位理论坐标与实际偏差值的Kriging模型，进而预测待制孔的孔位偏差，并给出每个位置的预测标准误差，以指导基准孔的增添和布置。最后通过有限元和数值实验分别验证了零件在极限变形和整体平移旋转情况下该方法的有效性，实现了孔位估计误差小于0.3 mm。     

Stationary flow fields prediction of variable physical domain based on proper orthogonal decomposition and kriging surrogate model

In this paper a new flow field prediction method which is independent of the governing equations, is developed to predict stationary flow fields of variable physical domain. Predicted flow fields come from linear superposition of selected basis modes generated by proper orthogonal decomposition(POD). Instead of traditional projection methods, kriging surrogate model is used to calculate the superposition coefficients through building approximate function relationships between profile geometry parameters of physical domain and these coefficients. In this context,the problem which troubles the traditional POD-projection method due to viscosity and compressibility has been avoided in the whole process. Moreover, there are no constraints for the inner product form, so two forms of simple ones are applied to improving computational efficiency and cope with variable physical domain problem. An iterative algorithm is developed to determine how many basis modes ranking front should be used in the prediction. Testing results prove the feasibility of this new method for subsonic flow field, but also prove that it is not proper for transonic flow field because of the poor predicted shock waves.     

基于EFFD方法的自然层流短舱优化设计

采用extended free-form deformation(EFFD)方法研究了自然层流(natural laminar flow,NLF)短舱的气动外形优化设计方法.使用基于Bernstein基函数的EFFD方法完成了NLF短舱剖面的参数化,利用基于k-εSST(shear stress transport)两方程湍流模型的γ-θ转捩模型进行自然转捩预测,结合EFFD、一种混合动网格方法、Kriging代理模型和改进的粒子群算法(particle swarm optimization,PSO)建立了针对NLF短舱气动外形的优化设计框架.采用该框架分别对通气NLF短舱和带动力NLF短舱进行优化设计.单独通气NLF短舱优化结果的外表面实现48%的层流,阻力系数比初始通气NLF短舱减小了0.0003.带动力NLF短舱的优化结果外表面保持了41%的层流.这些结果表明采用相关技术建立的优化设计框架在NLF短舱设计中具有一定应用价值.