| 基于降低温室效应的飞行高度层分配优化 |
| |
| 引用本文： | 田勇,万莉莉,叶博嘉,王中凤燕. 基于降低温室效应的飞行高度层分配优化[J]. 西南交通大学学报, 2018, 53(2): 400-405. DOI: 10.3969/j.issn.0258-2724.2018.02.025 |
| |
| 作者姓名： | 田勇 万莉莉 叶博嘉 王中凤燕 |
| |
| 作者单位： | 南京航空航天大学民航学院 |
| |
| 基金项目： | 国家自然科学基金资助项目61671237中央高校基本科研业务费专项资金资助项目NJ20140017江苏省自然科学基金资助项目BK20160798 |
| |
| 摘 要： | 为减小扇区空中交通飞行对环境的影响，使用高度层分配优化方法开展了基于降低温室效应的航空器绿色轨迹优化研究.首先针对扇区航空器运行的特点，结合区域扇区飞行冲突解脱方法，综合考虑扇区空中交通排放的CO2和产生的凝结尾对全球地表温度变化的影响；其次，以最小化全球地表温度变化为目标，建立区域扇区飞行调配模型，选用高度改变冲突调配策略，并采用带精英保留策略的遗传算法求解模型；最后，使用某市02号高空管制区的实际运行数据进行了实例验证.研究结果表明:该模型能够显著降低扇区航空器运行造成的全球地表温度增加；在25、50 a和100 a时间水平下全球地表温度增加值分别降低了98.74%、97.69%、97.11%；飞行高度层分配优化能大幅度降低温室效应.
|
| 关 键 词： | 温室效应 凝结尾 高度层分配 遗传算法 |
| 收稿时间： | 2017-03-15 |
Flight Level Allocation Optimization to Reduce Greenhouse Effect |
| |
| TIAN Yong,WAN Lili,YE Bojia,WANG Zhongfengyan. Flight Level Allocation Optimization to Reduce Greenhouse Effect[J]. Journal of Southwest Jiaotong University, 2018, 53(2): 400-405. DOI: 10.3969/j.issn.0258-2724.2018.02.025 |
| |
| Authors: | TIAN Yong WAN Lili YE Bojia WANG Zhongfengyan |
| |
| Abstract: | To reduce the regional environmental impacts of air traffic flow, this study investigated a green trajectory optimization method for reducing greenhouse effect. According to the characteristics of the regional sector aircraft and the flight conflict resolution method, the influences of CO2 emissions and aircraft contrails on global surface temperature change were analysed and a regional aircraft deployment model was established to minimise the greenhouse effect. A genetic algorithm based on the elite retention strategy was designed. The feasibility of this algorithm was verified using real flight operations data of ZBAAAR02 as an example. The calculation result shows that the model can effectively reduce the rise in global temperature due to flight operations in the sector. The global surface temperature can decrease by 98.74%, 97.69%, and 97.11% in 25, 50, and 100 years respectively with this model. The results obtained suggests that flight level allocation model optimisation can effectively reduce the greenhouse effect. |
| |
| Keywords: | |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《西南交通大学学报》浏览原始摘要信息 |
|
点击此处可从《西南交通大学学报》下载免费的PDF全文 |
