基于改进牛顿法的航空发动机起动建模技术

为进行涡扇发动机起动过程性能仿真研究,在发动机慢车以上部件级模型的基础上,通过指数外推法获得低转速部件特性,在建立起动附件模型的同时,修正起动过程各部件总压恢复系数,从而建立起包含地面起动过程的全状态性能模型。在求解发动机各部件共同工作非线性方程组时,采用基于传统牛顿拉夫森迭代求解方法的改进方法,即在第1次完成中心差分得到Jacobian矩阵后,使用修正项迭代更新上一步的Jacobian矩阵。结果表明:该建模方法可以有效地建立起动过程性能模型,并大幅改善模型的执行效率、提高模型仿真求解速度。     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

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.     

固体火箭发动机柔性接头拉伸载荷下强度分析

柔性接头是固体火箭发动机摆动喷管的执行部件,由若干同心的环状球体的弹性件、增强件以及前后法兰相互交替地粘接在一起而成,采用轴对称有限元法对柔性接头在拉伸载荷下进行了强度分析,得到了在0.5MPa弹射压强的拉伸载荷作用下柔性接头应力分布,由此计算弹性件与增强件之间界面最大拉应力及层间剪应力分别为2.34MPa和0.28MPa,界面粘接强度满足使用要求。      

燃油周向分级对贫油熄火油气比的影响

为降低贫油熄火油气比,对双头部燃烧室进行了燃油周向分级贫油熄火模拟实验研究。实验考虑了进气速度、进气温度对贫油熄火油气比的影响。采用了三种不同长度的隔板来研究减少两个头部之间相互影响。试验结果表明:与不分级燃烧相比,燃油周向分级燃烧能够显著降低贫油熄火油气比。当燃烧室进气温度低于400K,贫油熄火油气比随燃烧室进气空气流速的上升而明显下降,当进气温度大于400K,贫油熄火油气比对燃烧室进气温度和速度不敏感;采取加在头部之间插入隔板的措施来降低燃烧室贫油熄火比,效果并不显著。      

飞机电源系统故障诊断专家系统的分析和设计

应用人工智能理论对某型飞机电源系统进行故障诊断分析。本文给出励磁电流过大故障树模型,建立电源系统知识库和推理机,完成飞机电源系统故障诊断专家系统的设计,进行故障诊断,得出异常或故障信息,为整个飞机非航电系统采用专家系统进行故障诊断提供经验。     

复合材料层板低速冲击剩余强度的研究

 针对复合材料层板受低速冲击后的剩余压缩强度问题进行分析计算,把冲击破坏区看作一个含有随机分布裂纹的圆形不均匀体,采用有限元建模分析,结合冲击后层板的试验所得的载荷/ 位移关系,计算得到冲击破坏区的剩余模量。再采用有限元建模分析含圆形冲击损伤区的矩形复合材料层板,求解应力及最大位移,并依据最大应力破坏准则,预测复合材料层板的冲击后压缩强度,计算结果与试验数据的比较表明分析结果可靠。     

Lift coefficient prediction at high angle of attack using recurrent neural network

In this paper, identification of dynamic stall effect of rotor blade is considered. Recurrent Neural Networks have the ability to identify the nonlinear dynamical systems from training data. This paper describes the use of recurrent neural networks for predicting the coefficient of lift (C_Z) at high angle of attack. In our approach, the coefficient of lift (C_Z) obtained from the experimental results (wind tunnel data) at different mean angle of attack θ_mean is used to train the recurrent neural network. Then the recurrent neural network prediction is compared with experimental ONERA OA212 airfoil data. The time and space complexity required to predict C_Z in the proposed method is less and it is easy to incorporate in any commercially available rotor code.     

应力严重系数法在直升机主桨叶寿命评估中的应用

应力严重系数法在定翼机机体寿命计算中已有成功应用，然而对于以高周损伤为主的直升机动部件(如主桨叶)一般均依靠6件全尺寸疲劳试验的方法进行定寿。这不仅需要大量经费，而且也要很长的周期。本文绕开全尺寸疲劳试验这一大的环节，根据相应材料特性数据，采用应力严重系数法对直8型机主桨叶根部接头进行寿命评估。文中给出的方法简单，精度较好，便于工程应用。     

计算机辅助工时定额管理系统

介绍了南飞公司劳资处开发的计算机辅助工时定额管理系统的主要功能，系统特点及运行效果等。