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.     

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...     

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.     

System-level prognostics approach for failure prediction of reaction wheel motor in satellites

The reaction wheels actuated by motors are widely used for advanced attitude control of satellites. During the satellite operation, the performance of reaction wheel motor degrades and results in unexpected failures. To guarantee the reliability and safety of satellites, it is important to predict its remaining useful life while it is in operation. To address this issue, this study presents a system-level prognostics approach for the reaction wheel motor, by regarding it as a system composed of multiple components. The approach is demonstrated by using the motor operation data obtained during the accelerated-life tests on ground for 3 years. Health degradation of each components of the motor are estimated using the adaptive extended Kalman filter. Failure threshold of the motor performance is established by the design requirement on characteristic curve. The anomaly detection and failure prediction are performed using the shifting kernel particle filter.     

镁粉与二氧化碳动态点火燃烧特性数值研究

Mg粉/CO₂粉末发动机是火星探测中较为理想的原位资源利用方案，为了掌握Mg/CO₂粉末发动机稳定点火燃烧特性，在考虑氧化层厚度对Mg颗粒熄火影响的基础上，基于涡耗散/有限速率模型建立了点火燃烧模型，并应用数值计算方法研究了Mg粉颗粒粒径（5μm， 10μm， 15μm， 20μm和25μm）、入口预混气流雷诺数（1500， 2000， 2500， 3000和3500）和CO₂/Mg氧燃比（0.5， 1， 1.5， 2和2.5）对Mg粉/CO₂动态点火燃烧的影响。计算结果表明：雷诺数和氧燃比恒定时，随着粒径从5μm增加到10μm，平均温度升高，平均点火时间延长，燃烧效率增加；随着粒径从10μm增加到25μm，平均温度降低，平均点火时间延长，燃烧效率减少。粒径和氧燃比恒定时，平均温度随雷诺数增加而下降；平均点火时间和燃烧效率随雷诺数增加基本不变。粒径和雷诺数恒定，随着氧燃比从0.5增大到1.5，平均温度升高；随着氧燃比从1.5增大到2.5，平均温度下降；平均点火时间和燃烧效率随氧燃比增大基本不变。     

溶胶-凝胶法制备纳米TiO2 及粒径控制工艺

采用溶胶-凝胶法,以钛酸丁酯为前驱体,乙二醇作为螯合剂制备纳米TiO2 粒子。考察钛的乙二

醇盐的浓度、pH 值、温度等因素对TiO2 粒径的影响,并用红外光谱和SEM 对纳米TiO2 粒子进行结构和形貌表

征。结果表明,采用溶胶凝胶法可以制备出呈椭圆形且粒径分布均匀的TiO2 纳米粒子。使用硝酸铵可以有效

阻止TiO2 纳米粒子团聚。当pH 值为2 ~3、温度为20 ~40℃,钛的乙二醇盐在丙酮中的浓度为0. 03、0. 05 及

0. 07 M 时,粒径分别为150、240 及600 nm。

     

Particle filter-based real-time phase line bias estimation for GNSS-based attitude determination with common-clock receivers

Global navigation satellite system (GNSS)-based attitude determination has been widely adopted in a wide variety of terrestrial, sea, air, and space applications. Recently, the emergence of commercial multi-GNSS common-clock receivers has brought new opportunities for high-precision GNSS-based attitude determination with single-differenced (SD) model. However, the key requirement of using this approach is the accurate estimation of the troublesome line bias (LB) in real-time. In this contribution, we propose a particle filter-based real-time phase LB estimation approach that apply to SD model with single-system single-frequency observations from common-clock receiver. We first analyzed the relationship between the integer ambiguity ratio value and the phase LB. It is proved that the accuracy of a given phase LB value can be qualified by the related ambiguity resolution ratio value, and the normalized ratio value can therefore be used to represent the likelihood function of observations. Then, we presented the particle filter-based real-time phase LB estimation procedure, and assessed its performance using GPS L1/BDS B1I observations from two datasets collected with different types of common-clock receivers in terms of the accuracy and convergence time of phase LB estimation, the computation load, and the positioning and attitude determination accuracy with respect to the double-differenced (DD) model. Experimental results demonstrated that the phase LB could be accurately estimated with short convergence time (generally within 15 epochs). Moreover, compared with the classical DD approach, the particle filter-based SD approach delivers comparable positioning root-mean-square (RMS) errors in the North and East components but significantly smaller RMS errors in the Up component. Accordingly, the achievable yaw accuracy is comparable whereas the pitch accuracy is remarkably improved. The improvements of positioning accuracy in the Up component and pitch accuracy are approximately 35.7 % to 63.7 %, and 33.3 % to 63.1 %, respectively. Additionally, the single-epoch computation time with our particle filter-based SD approach is generally 0.08 s, which is obviously larger than the DD approach but could still meet the requirements of real-time applications below 10 Hz sampling.     

基于轨迹拐点滤波的激光雷达里程计定位算法研究

在GPS拒止环境下，激光雷达里程计可以利用帧间匹配跟踪车辆实现定位，但是定位误差随时间累积的特性造成激光雷达里程计(LO)缺乏持续性。为解决LO的误差累积问题，引入轻量级地图OSM。基于粒子滤波框架，以LO作为运动模型的输入，通过两次筛选提取拐点，利用拐点匹配完成与地图的对齐，并以粒子的均值作为车辆校正后的位置，实现对定位误差的校正。提出了一种新的粒子权重模型，利用不同节点的相似度模型及测量值作为粒子权重的更新依据，避免拐点与路网节点的错误关联导致定位误差加大。经由KITTI数据集上的实验验证，该算法可以有效克服LO误差漂移问题，相较于原始LO定位精度至少提高了49.22%，且具有较好的实时性。