Numerical analysis and optimization of boundary layer suction on airfoils

Numerical approach of hybrid laminar flow control(HLFC) is investigated for the suction hole with a width between 0.5 mm and 7 mm. The accuracy of Menter and Langtry’s transition model applied for simulating the flow with boundary layer suction is validated. The experiment data are compared with the computational results. The solutions show that this transition model can predict the transition position with suction control accurately. A well designed laminar airfoil is selected in the present research. For suction control with a single hole, the physical mechanism of suction control, including the impact of suction coefficient and the width and position of the suction hole on control results, is analyzed. The single hole simulation results indicate that it is favorable for transition delay and drag reduction to increase the suction coefficient and set the hole position closer to the trailing edge properly. The modified radial basis function(RBF) neural network and the modified differential evolution algorithm are used to optimize the design for suction control with three holes. The design variables are suction coefficient, hole width, hole position and hole spacing. The optimization target is to obtain the minimum drag coefficient. After optimization,the transition delay can be up to 17% and the aerodynamic drag coefficient can decrease by 12.1%.     

Practical compensation for nonlinear dynamic thrust measurement system

The real dynamic thrust measurement system usually tends to be nonlinear due to the complex characteristics of the rig, pipes connection, etc. For a real dynamic measuring system,the nonlinearity must be eliminated by some adequate methods. In this paper, a nonlinear model of dynamic thrust measurement system is established by using radial basis function neural network(RBF-NN), where a novel multi-step force generator is designed to stimulate the nonlinearity of the system, and a practical compensation method for the measurement system using left inverse model is proposed. Left inverse model can be considered as a perfect dynamic compensation of the dynamic thrust measurement system, and in practice, it can be approximated by RBF-NN based on least mean square(LMS) algorithms. Different weights are set for producing the multi-step force, which is the ideal input signal of the nonlinear dynamic thrust measurement system. The validity of the compensation method depends on the engine’s performance and the tolerance error0.5%, which is commonly demanded in engineering. Results from simulations and experiments show that the practical compensation using left inverse model based on RBF-NN in dynamic thrust measuring system can yield high tracking accuracy than the conventional methods.     

Design and Application of Discrete Sliding Mode Control with RBF Network-based Switching Law

This article proposes a novel approach combining exponential-reaching-law-based equivalent control law with radial basis function (RBF) network-based switching law to strengthen the sliding mode control (SMC) tracking capacity for systems with uncertainties and disturbances. First, SMC discrete equivalent control law is designed on the basis of the nominal model of the system and the adaptive exponential reaching law, and subsequently, stability of the algorithm is analyzed. Second, RBF network is used to form the switching law in a direct and online manner with sliding-mode-related inputs and by approximating evaluation function; and the method to adjust its parameters is devised. Finally, comparable experiments are carried out to verify the application of the proposed approach to an inner-axis driven by a direct current (DC) torque motor through extra-low speed servo for a high precision flight simulator, and the axis works under deteriorating conditions such as periodically fluctuating torques of motor, nonlinear friction, and time-varying model parameters. The results show that the combined SMC can effectively improve the servo performance, for instance, to a stable 0.000 08 (°)/s speed response, the tracking error would be within 0.000 08° in 98% of operating times. Moreover, the hybrid nature of the approach imparts the RBF network the features of removing offline training and ease to set initial parameters.     

Using the radial basis function neural network to predict ionospheric critical frequency of F2 layer over Wuhan

Neural networks (NNs) have been applied to ionospheric predictions recently. This paper uses radial basis function neural network (RBF-NN) to forecast hourly values of the ionospheric F₂ layer critical frequency(f_oF₂), over Wuhan (30.5N, 114.3E), China. The false nearest neighbor method is used to determine the embedding dimension, and the principal component analysis (PCA) is used to reduce noise and dimension. The whole study is based on a sample of about 26,000 observations of f_oF₂ with 1-h time resolution, derived during the period from January 1981 to December 1983. The performance of RBF-NN is estimated by calculating the normalized root-mean-squared (NRMSE) error, and its results show that short-term predictions of f_oF₂ are improved.     

空间群Pn3mPn3P23子群链耦合系数的计算

本文利用陈金全教授的本征函数法计算了Pn3m Pn3 P2 3空间群的母分系数。最后的计算结果表明 ,用陈金全教授的本征函数法所求得的母分系数确实满足幺正、归一性 ,同时也证明了本征函数法对于求母分系数同样适用     

正规基上的快速乘逆算法

根据有限域GF(2~m)上的正规基表示,本文提出一种新的快速乘逆算法。该算法把计算乘逆的复杂忭从O(m)降低到O(1/m)。     

高超声速飞行器预设性能反演控制方法设计

为解决吸气式高超声速飞行器的飞行控制问题,提出了一种新型预设性能神经反演控制器设计方法。通过构造预设性能函数,保证速度跟踪误差和高度跟踪误差能够按照预设的收敛速度、超调量及稳态误差收敛至期望的区域,同时满足系统预设的瞬态性能和稳态精度。在反演控制设计结构下,引入径向基函数（RBF）神经网络对模型未知函数及不确定项进行逼近,提高了控制系统的鲁棒性。引入的RBF神经网络中仅有一个参数需要在线更新,有效提高了控制准确性,避免了通常反演控制方法中经常出现的"微分膨胀问题",并降低了计算量。通过仿真实验验证了所设计控制系统的有效性和可行性。      

民用飞机冲压空气涡轮系统适航工程技术研究

冲压空气涡轮系统是一种飞机应急能源,其在紧急情况下为飞机提供应急液压源和/或应急电源,对飞机应对紧急情况至关重要。参照 AP-21-AA-2011-03-R4 中关于航空器生命周期审定过程划分及合格审定活动,结合某型民用飞机冲压空气涡轮系统研制过程,从识别审定基础开始,将适航条款转化成需求,落实到产品设计中,明确条款的...     

直升机惯性传感器结构的模态优化

提出了一种基于迭代抽样和径向基插值的自适应代理模型方法。这种自适应方法以减少仿真计算数量和提高代理模型自适应能力为目的,使用多岛遗传算法选择新增样本点并使新增样本点位于设计空间的稀疏区域,使得所有的样本点均匀分布于设计空间。标准误差用来判断代理模型的精度大小以决定是否对代理模型进行更新。这种自适应代理模型结合多岛遗传算法对直升机的惯性传感器结构模态进行优化。用拉丁超立方抽样方法选择10个样本点构建初始的代理模型,自适应代理模型的计算结果表明2%的误差条件下需要额外增加7个样本点。优化结果表明不同的权重系数对最优模态特性的影响很大,惯性传感器结构的一至六阶模态值更加远离直升机的激励频率。     

面向全疆域设计需求的某涡轴发动机核心机转子减重优化

为满足某涡轴发动机平原、高原、高寒以及海洋环境下的全疆域设计需求,综合采用尺寸优化和拓扑优化对核心机转子盘体形状进行了减重优化。首先提出了一种基于本征正交分解的径向基神经网络代理模型构造方法,通过在关键区域补充采样,在样本总数相当的前提下,提高了寻优效率,缩短了优化所需的时间。利用该方法对核心机转子盘体尺寸进行优化,优化后结构重量减轻,应力分布和强度储备更趋合理。然后采用变密度法对涡轮盘螺栓孔附近区域进行拓扑优化,得到一种带凸耳形状的螺栓孔创新构型,解决了由于优化后盘体减薄而导致的螺栓孔应力上升过多的问题。结果表明：在转子强度、寿命满足规范要求的前提下,优化后的核心机转子减重15%,满足了全疆域设计需求对转子重量的要求。