An intelligent approach for flight risk prediction under icing conditions

Flight risk prediction is significant in improving the flight crew’s situational awareness because it allows them to adopt appropriate operation strategies to prevent risk expansion caused by abnormal conditions, especially aircraft icing conditions. The flight risk space representing the nonlinear mapping relations between risk degree and the three-dimensional commanded vector(commanded airspeed, commanded bank angle, and commanded vertical velocity) is developed to provide the crew with practi...     

无人机蜂群轨迹预测研究

传统防空火控算法中的轨迹预测模型无法对复杂的无人机蜂群进行有效地轨迹预测，而现有针对无人机机动轨迹的预测研究通常只考虑单个无人机，且模型量级过大。为了准确且快速地预测无人机蜂群轨迹，本文提出一种面向蜂群的轨迹预测方法。在获得蜂群轨迹后，首先基于DBSCAN 对其进行聚类，判断出蜂群中各个无人机的类别；然后基于分形算法，判断无人机轨迹是简单轨迹还是复杂轨迹；最后，采用卡尔曼滤波进行简单轨迹的预测，用基于LSTM 网络的方法进行复杂轨迹的预测。结果表明：本文提出的无人机蜂群轨迹预测方法的预测误差远远小于纯采用卡尔曼滤波方法预测的误差，且预测时间小于仅采用LSTM 网络方法预测的时间，可以较为准确地预测蜂群中不同集群无人机的轨迹，为反无人机蜂群火控解算提供基础。     

高压涡轮工作叶片内部流场特性试验研究

为研究变工况特性下涡轮叶片内部通道流场特性，选取高压涡轮二级工作叶片内部通道作为研究对象，在5种不同的进口雷诺数（Re）工况下，利用TRPIV（时序PIV）技术对通道内的流场特性进行了试验研究。Re变化为32426～64700，模拟了飞行循环过程中的若干典型工况。在先进加工技术的辅助下，保留了真实叶型约束下的完整内冷三通道带肋结构，捕捉到一些不同于常规截面两通道模型等简化模型中的流动现象，包括：弯头区域不对称主流分离结构和非对称二次涡系。通过数据分析，明确了高、低雷诺数下流动特性的差异。在高Re工况条件下，弯头出口附近的冲击区域增大；对于第一通道内的二次流，在接近弯头位置处，横向速度分量会导致纵向涡对的强度被削弱，高Re工况下拥有更加剧烈的影响，极有可能削弱吸力面的换热强度。     

Improving aircraft aerodynamic performance with bionic wing obtained by ice shape modulation

For Unmanned Aerial Vehicles (UAVs) with limited electrical power to achieve effectively anti-/de-icing at the leading edge of the wing, a strategy of ice shape modulation was proposed. Isolated simulated ice shape pieces printed by 3D printing technology are mounted on a NACA0012 finite wing model, and its lift/drag coefficients and suction-side velocity fields are measured by the six-component force balance and the Particle Imaging Velocimetry (PIV), respectively. The ratio of the spanwise length of a single ice shape piece to chord length and the spanwise length of the non-icing area between the two adjacent single ice shape pieces are defined as dimensionless ice shape length (w/c) and dimensionless modulation ratio (w/λ), respectively. The results indicate that for a fixed w/λ, the wing lift coefficient first increases and then drops with increasing w/c, and a peak value exists when w/c is between 0.1 and 0.2. The lower the w/λ is, the higher the wing lift coefficient will be. The periodical variation of the flow separation area along the spanwise direction is attributed on the one hand to the acceleration effect of the flow field in the non-icing area which reduces the separation area, and on the other hand to the cross-flow caused by the streamwise vortices from the non-icing area to the icing area which promotes the mixing of the flow field (similar to vortex generators). The obtained modulation law is verified through flight tests and provides guidance for the use of ice shape modulation scheme for UAVs that cannot be completely anti-/de-icing under severe weather conditions.     

Periodic acoustic source tracking using propagation delayed measurements

There exist a large class of acoustic sources which have an underlying periodic phenomenon. Unlike the well-studied Bearings-Only Tracking(BOT) of an aperiodic acoustic source,this paper considers the problem of tracking a periodic acoustic source. For periodic acoustic tracking, the signal emission time is known. However, the true measurement reception time is unknown because it is corrupted by noise due to propagation delay. We augment the sensor’s signal reception time onto bearing measuremen...     

Method for utilizing PIV to investigate high curvature and acceleration boundary layer flows around the compressor blade leading edge

Particle Image Velocimetry (PIV) is a well-developed and contactless technique in experimental fluid mechanics, but the strong velocity gradient and streamline curvature near the wall substantially limits its accuracy improvement. This paper presents a data processing procedure combining conventional PIV and newly developed Mirror Interchange (MI) based Interface-PIV for the measurement of the boundary layer parameter development in the blade leading edge region. The synthetic particle images are used to analyze the measurement errors in the entire procedure. Overall, three types of errors, namely the errors caused by the Window Deformation Iterative Multigrid (WIDIM) algorithm, the discrete data interpolation and integration, and the wall offset uncertainty, comprise the main measurement error. Specifically, the errors due to the discrete data interpolation and integration and the WIDIM algorithm comprise the mean bias, which can be corrected through the error analysis method proposed in the present work. Meanwhile, the errors due to the WIDIM algorithm and the wall offset uncertainty contribute to the measurement uncertainty. Computational fluid dynamics-based synthetic particle flows were generated to verify the newly developed PIV data processing procedure and the corresponding error analysis method. Results showed that the data processing method could improve the accuracy of PIV measurements for boundary layer flows with high curvature and acceleration and even with significant flow separation bubbles. Finally, the data processing method is also applied in a PIV experiment to investigate the boundary layer flows around a compressor blade leading edge, and several credible boundary flow parameters were obtained.     

Measurement-driven Gauss-Hermite particle filter with soft spatiotemporal constraints for multi-optical theodolites target tracking

Multi-Optical Theodolite Tracking systems (MOTTs) can stealthily extract the target’s status information from bearings only through non-contact measurement. The constrained MOTTs are partially compatible, yet many existing research works and results are based on the known model, ignoring its discrimination with the target maneuvering behavior pattern. To compensate for these mismatches, this paper develops a Measurement-driven Gauss-Hermite Particle Filter (MGHPF), which elegantly fuses the spatiotemporal constraints and its soft form to perform MOTT missions. Specifically, the target dynamic model and tracking algorithm are based on the target behavior pattern with the adaptive turn rate, fully exploiting the spatial epipolar geometry characteristics for each intersection measurement by a minimax strategy. Then, the center of the feasible area is approximated via the analytic coordinate transformation, and the latent samples are updated via the deterministic Gauss-Hermite integral method with the target’s predictive turn rate. Simultaneously, the effects of truncation correction and compensation feedback from the current measurement and historical estimation data are adaptively incorporated into the PF’s importance distribution to cover the mixture likelihood. Besides, an effective causality-invariant updating rule is provided to estimate the parameters of these soft spatiotemporal constrained MOTTs with convergence guarantees. Simulated and measured results show good agreement; compared with the state-of-the-art Multi-Model Rao-Blackwell Particle Filter (MMRBPF), the proposed MGHPF improves the filtering accuracy by 7.4%-34.7% and significantly reduces the computational load.     

Evolution of turbulent boundary layer over a three-dimensional bump

A bump is typically used in the inlet system of an aircraft engine to compress the incoming airflow and to reduce boundary layer thickness developed over fuselage. In this work, the turbulent flow over a three-dimensional bump is experimentally studied. The bump model is mounted in a closed return wind tunnel operated at the nominal velocity 10 m/s, corresponding to a friction Reynolds number of 2300. The flow field upstream the bump, along the bump centerline and at two different spanwise plane...     

基于DKF的IMU误差预测算法

作为导航领域常用的组合导航方式,全球导航卫星系统(GNSS)/惯性导航系统(INS)组合导航在GNSS信号失锁后,由于惯性测量单元(IMU)误差随时间迅速积累,其定位结果会偏离载体真实位置,导航精度下降.针对此问题,提出了一种长短期记忆网络(LSTM)辅助的算法,称之为深度卡尔曼滤波(DKF)算法.DKF算法的核心思想是使用LSTM训练IMU误差模型,然后通过训练出的模型预测IMU误差,最后将预测的IMU误差代入IMU数据以校正导航结果.仿真结果表明:在200s测试数据上,DKF算法将误差从1.1537m/s降低到0.3746m/s.与平均预测、卡尔曼预测和最小二乘估计等方法相比,DKF算法的误差最小,具有更优越的导航性能.     

Numerical simulations of a continuously injected relativistic electron beam relaxation into a plasma with large-scale density gradients

In this paper the influence of large-scale decreasing and increasing gradients of the density of magnetized plasma on the relaxation process of a continuously injected relativistic electron beam with an energy of 660 keV ($v_b=0.9c$) and a pitch-angle distribution is studied using particle-in-cell numerical simulations. It is found that for the selected parameters in the case of a smoothly decreasing gradient and in a homogeneous plasma the formation of spatially limited plasma oscillations of large amplitude occurs. In such cases, modulation instability develops and a long-wave longitudinal modulation of the ion density is formed. In addition, the large amplitude of plasma waves accelerates plasma electrons to energies on the order of the beam energy. In the case of increasing and sharply decreasing gradients, a significant decrease in the amplitude of plasma oscillations and the formation of a turbulent ion density spectrum are observed. The possibility of acceleration of beam electrons to energies more than 2 times higher than the initial energy of the beam particles is also demonstrated. This process takes place not only during beam propagation in growing plasma density, but also in homogeneous plasma due to interaction of beam particles with plasma oscillations of large amplitude.