基于遗传算法的民用航空发动机送修方案决策研究

为了给航空发动机在整个使用周期内送修方案的制定提供支持，降低发动机使用周期内的大修成本，针对单元体结构的民用航空发动机，基于制造商的发动机维修管理大纲，同时考虑时寿件寿命和单元体超出软时限导致性能衰退而造成发动机送修的情况，设定大修间隔不超过最大送修间隔，建立了一种以送修时间间隔为优化变量，以单位飞行小时送修成本最小为优化目标的发动机大修成本优化模型。采用遗传算法对模型进行求解，并以V2500发动机为例，对其25年里多次返厂送修方案进行了优化，表明当送修次数为6次时返厂大修成本最低，并给出了相应的各单元体的修理级别，该方法可为航空公司制定发动机送修方案提供参考。      

氙离子推力器阳极工质分配方式优化

使用两种数值方法研究微尺度下惰性气体的流动现象,验证表明壁面速度滑移条件的N-S（Navier-Stokes）方法能够较好地模拟离子推力器气体分配环内工质流动特性.为了降低氙工质注入放电室过程中气流速度,并改善其周向均匀性,针对现有气体分配环构型提出符合4级环切场离子推力器放电特性的改进方案:增加2级供气通道,进行双侧45°角开孔并增加气孔数目.数值计算表明:结构优化后氙气进入放电室周向均匀性提高37%,气流速度降低32%；推力器装配优化方案气体分配环进行实验,大束流工况下束离子电离能耗自183W/A下降至167W/A,离子推力器放电室性能得到了提高.      

涵道比对大型客机经济性和环保性的影响

为了综合评估配装发动机的涵道比对客机的经济性和环保性的影响，建立了一套包括动力、几何、气动、质量、性能、经济性、噪声、排放分析模型的多学科分析流程.以典型宽体客机为应用算例，分析了不同涵道比（8~14）发动机对宽体客机经济性和环保指标的影响.综合分析结果表明:增大发动机涵道比有利于降低客机噪声和起降循环氮氧化合物污染物的排放；而发动机涵道比为11左右时，客机的现金使用成本最低，航线氮氧化合物污染物排放量最少.      

A geographical and operational deep graph convolutional approach for flight delay prediction

Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning, flight scheduling, airport operation, and passenger service. Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity, which brings critical challenges to accurate flight delay prediction. In recent years, Graph Convolutional Networks (GCNs) have become popular in flight delay prediction due to the advantage in extracting complicated relationships. However, most of the existing GCN-based methods have failed to effectively capture the spatial–temporal information in flight delay prediction. In this paper, a Geographical and Operational Graph Convolutional Network (GOGCN) is proposed for multi-airport flight delay prediction. The GOGCN is a GCN-based spatial–temporal model that improves node feature representation ability with geographical and operational spatial–temporal interactions in a graph. Specifically, an operational aggregator is designed to extract global operational information based on the graph structure, while a geographical aggregator is developed to capture the similar nature among spatially close airports. Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.