A new dynamic pushback control method for reducing fuel-burn costs: Using predicted taxi-out time

Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic Pushback Control(PDPC) method is proposed. The implementation of this method requires two steps: first, the taxi-out times for aircraft are predicted by the leastsquares support-vector regression approach of which the parameters are optimized by an introduced improved Firefly algorithm. Then, a dynamic pushback control model equipped with a linear gate-hold penalty function is built, along with a proposed iterative taxiway queue-threshold optimization algorithm for solving the model. A case study with data obtained from Beijing International airport(PEK) is presented. The taxi-out time prediction model achieves predictive accuracy within 3 min and 5 min by 84.71% and 95.66%, respectively. The results of the proposed pushback method show that total operation cost and fuel-burn cost achieve a 14.0% and 21.1%reduction, respectively, as compared to the traditional K-control policy.(3) From the perspective of implementation, using PDPC policy can significantly reduce the queue length in taxiway and taxi-out time. The total operation cost and fuel-burn cost can be curtailed by 37.2% and 52.1%,respectively, as compared to the non-enforcement of any pushback control mechanism. These results show that the proposed pushback control model can reduce fuel-burn costs and airport surface congestion effectively.     

Early analysis of precise orbit and clock offset determination for the satellites of the global BeiDou-3 system

Eight new-generation BeiDou satellites (BeiDou-3) have been launched into Medium Earth Orbit (MEO), allowing for global coverage since March 2018, and they are equipped with new hydrogen atomic clocks and updated rubidium clocks. Firstly, we analyzed the signals for the carrier-to-noise-density ratio (C/N0) and pseudorange multipath (MP) by using international GNSS (Global Navigation Satellite System) Monitoring and Assessment System (iGMAS) station data, and found that B1C has a lower C/N0, and B2a has the same level of C/N0 as the B1I and B3I signals. For pseudorange multipath, compared with the BeiDou-2 satellites, the obvious systematic variation of MP scatters related to the elevation angle is greatly improved for the BeiDou-3 and BeiDou-3e satellites signals. For the signals of the BeiDou-3 satellites, the order of the Root Mean Square (RMS) values of multipath and noise is B3I?<?B1I?<?B2a?<?B1C. Then, the comparison of the precise orbit determination and clock offset determination for the BeiDou-2, BeiDou-3, and BeiDou-3 experimental (BeiDou-3e) satellites was done by using 10 stations from iGMAS. The 3D precision of the 24?h orbit overlap is 24.55, 25.61, and 23.35?cm for the BeiDou-3, BeiDou-3e, and BeiDou-2 satellites, respectively. BeiDou-3 satellite has a comparable precision to that of the BeiDou-2 satellite. For the precision of clock offset estimation, the Standard Deviation (STD) of the BeiDou-3 MEO satellite is 0.350?ns, which is an improvement of 0.042?ns over that of the BeiDou-2 MEO satellite. The stabilities of the BeiDou-3 and BeiDou-3e onboard clocks are better than those of BeiDou-2 by factors of 2.84 and 1.61 at an averaging time of 1000 and 10,000?s, respectively.     

基于深度学习的组合体航天器模型预测控制

利用模型预测算法先预测控制结果后控制的类人行为特点，借助深度学习在多参数寻优上的优势，提出了一种基于卷积神经网络的模型预测控制算法，满足航天工程低硬件需求，实现组合航天器多场景下姿态控制律的重构。该算法首先利用模型预测控制将组合航天器从初始状态控制到预期状态，然后将控制过程中状态量用于3层3核卷积神经网络的训练，训练完成后，用该卷积神经网络代替模型预测对组合航天器进行控制，从而降低计算资源需求。仿真校验表明：该算法可预测5个控制周期内的控制参数，相比传统模型预测算法所需硬件计算时间降低约5倍，在一般硬件环境下30 s内即可完成各场景下的组合航天器姿态控制，控制精度在10 -4 量级。     

阵风载荷减缓系统故障分析

阵风引起的额外载荷会引起飞机结构疲劳,降低结构使用寿命。采用非定常气动力有理函数拟合方法建立时域状态空间下的动力学系统,设计了阵风载荷减缓系统。研究了阵风载荷减缓系统3种典型故障模式(副翼偏转饱和、舵机卡死、副翼偏转延时)的力学建模方法,并对机翼在阵风减缓系统故障模式下的阵风响应进行分析。仿真结果表明,3种故障模式均不利于阵风载荷减缓系统对阵风载荷的减缓,对于一些特定情况,故障模式下的阵风载荷减缓系统不仅不能减缓阵风载荷,还会带来由副翼偏转不当引起的额外负载。     

采用霍尔传感器的旋翼频率采集设计

为达到对旋翼飞机的控制,需要对旋翼转速进行采集.霍尔转速传感器以其高可靠性等优点常被用来测量转速.介绍了一种使用霍尔传感器进行旋翼转速采集系统,包括硬件构架,逻辑采集单元和软件设计,并给出了优化策略;通过试验数据分析,采集精度达到了预期.     

供热系统集约化运行的能耗监测及节能调节问题探讨

对我校供热系统的现状进行了分析；指出了锅炉热效率及能耗监控方面的不足，并针对锅炉热效率提高和二次网循环泵变频调节进行了节能分析计算；同时根据我校实际情况对循环泵设备配置及控制进行了分析，提出了要加强技术指标量化考核和能耗监测，提高效率、节能降耗，实现供热系统的科学化、集约化运行。     

无旋锥形液膜表面波不稳定性试验研究

为了研究针栓式喷注器无旋锥形液膜表面波不稳定特性,采用高速摄影获得了不同压降下表面波波动图像,测量了液膜表面波破碎点波长、振幅以及破碎长度等特征信息。利用试验结果修正了无旋锥形液膜色散方程中的参数C和ln(η_bη_0),并求解了色散方程。研究了喷注压降对液膜破碎长度、破碎时间以及破碎点波长的影响。结果表明:随着喷注压降的增加,液膜破碎长度和破碎时间均降低,并且降低趋势越来越缓,液膜表面波发展的非线性增强,理论值与试验值的偏差由3.9%增大到29.2%;液膜破碎位置处扰动波长随喷注压降的增加而降低,并且试验值比理论值偏大50%左右,无旋锥形液膜破碎模型可定性分析针栓式喷注器液膜表面波不稳定性。     

导风轮叶片偏置对高压比串列离心压气机性能的影响

为提升高压比串列离心压气机的性能,借鉴常规一体化离心叶轮中偏置分流叶片的方法,针对某高压比串列离心压气机,应用数值仿真手段分析了串列叶轮中导风轮叶片周向偏置对压气机流场和性能的影响。通过对不同导风轮叶片偏置方案下压气机流场的分析,建立了压气机流动损失与偏置参数的关联性。研究表明:采用较大的偏置参数γ可降低导风轮叶片1前缘的激波强度,改善激波作用导致的泄漏涡破碎和流动分离,但过大或过小的γ方案中导风轮叶顶会出现二次泄漏致使低能流体的掺混损失增加;γ=65%方案压气机综合性能最佳,其压比和效率较γ=50%分别提高了1.5%和1.4%;对于串列离心压气机导风轮叶片周向位置的优化,在避免导风轮叶顶形成较强二次泄漏的前提下,应考虑采用较大的偏置参数γ,同时应防止诱导轮尾迹流体参与导风轮的叶顶泄漏。     

基于压缩量偏差约束的整体叶盘砂布轮数控抛光路径规划

数控抛光是实现整体叶盘叶片表面光整加工自动化、高效化的关键技术,而抛光路径规划对表面质量有着显著的影响。在抛光曲面时,砂布轮沿接触曲线上的径向压缩量偏差导致材料去除量一致性较差。针对该问题,提出一种基于压缩量偏差约束的路径规划方法。通过对砂布轮受曲面挤压变形几何分析,建立了自由曲面抛光接触线上砂布轮压缩变形量分布模型。在给定刀触点处,以接触曲线上最大压缩量偏差最小化为评价指标构建了刀轴矢量优化模型,并利用改进的粒子群优化（PSO）算法进行求解。基于最优刀轴矢量,完成自由曲面上等参数相邻刀触轨迹曲线的计算。最后,通过数据对比和试验,验证了所提方法的正确性和有效性。结果表明,抛光区域的轮廓度、粗糙度均得到明显的改善。     

风扇/压气机周向模态识别中传感器角度偏差的影响

基于任意角度压缩感知(CS)方法分析了传感器安装角度偏差对风扇/压气机周向模态识别重构的影响,设计了一套自适应角度优化程序修正重构误差。利用数值试验探究了传感器角度偏差和数量对周向模态重构结果的影响,研究表明:当角度偏差等级为2.5%时,平均重构误差达到10%以上,若保证重构误差基本不变,将传感器数量从7个增加至25个,仅可以将角度偏差等级放宽至4%。而采用小生境微种群遗传算法进行自适应角度优化,在20 dB信噪比下,通过自适应角度优化可将角度偏差等级从2.5%放宽至10%,降低了传感器安装的精度要求。成功优化了一款冷却风扇在前三阶叶片通过频率下的主要周向声模态重构幅值。自适应角度优化算法有效提升了基于压缩感知的风扇/压气机周向模态重构可靠性。