基于侧风影响的CSPRs起飞尾流间隔优化
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摘要
尾流间隔对跑道容量有重要影响。为了提高近距平行跑道(Closely Spaced Parallel Runways,CSPRs)容量,在充分考虑尾流间隔影响因素的基础上,利用侧风对尾流运动的影响,综合考虑尾流运动消散及航空器尾流抵抗能力,建立了CSPRs起飞尾流间隔模型。以上海虹桥机场为例,B747-400为起飞前机,B737-700为起飞后机,利用MATLAB软件模拟仿真了不同侧风条件下的尾流运动轨迹,对起飞尾流间隔进行优化计算,确定有利侧风量≥2. 5 m/s为实施优化后无尾流影响起飞间隔的临界侧风值,采用欧控(Eurocontrol,European Organization for the Safety of Air Navigation)现行尾流间隔的遭遇风险与计算结果做对比,验证了其安全性能完全满足实际运行需求。
This paper intends to introduce the factors affecting the model of wake separation for the aeroplane takeoff,and for the said purpose,we would like to propose a three stages of eddy motion for the wake dissipation. To achieve the purpose,the paper has first of all intended to prepare a plane rectangular coordinating system based on the relative motion relationship between the two paired aeroplanes. And,then,on the said basis,it would be possible to consider and determine and formulate an aircraft wake encounter degree and wake the motion dissipation model between the aircraft wake intervals. And,later,on the basis of fully considering the influential factors of wake interval,it would be possible to establish the CSPRs( Closely Spaced Parallel Runways) take-off wake interval model by taking into full account the impacts of the crosswind on the wake motion and the dissipation of the wake motion and the aircraft wake resistance.Thus,finally,taking Shanghai Hongqiao Airport as a case study sample,the paper has done the calculation of the wake motion of the aircraft 36 L/18 R and its take-off procesure and B747-400 as the leading aircraft while B737-700 as the trailing aircraft. That is to say,taking the critical strength of the aircraft wake and the dissipation time of its wake for example,we have investigated the eddy current trajectories under the uncrosswind and adverse crosswind,so as to decide whether to continue to calculate the eddy current trajectory under the influence of favorable crosswind in accordance with the trajectory. And,in our investigation,we have managed to simulate the corresponding wake motion trajectory under different crosswind conditions in hoping to optimize the taking-off wake interval with the help of a software known as MATLAB. The simulation results we have gained demonstrate that the dissipation process of eddy motion can be influenced by the different crosswind conditions. The favorable crosswind volume has to be settled at about ≥2. 5 m/s as the critical crosswind takeoff interval without wake impact as the result of optimization. What is more,as compared with the calculation results in reference to the value of Eurocontrol( European Organization for the Safety of Air Navigation) wake encounter risk,we have confirmed and determined the safety performance of the above models in Shanghai Hongqiao Airport and in turn have faithfully been executing the optimized safety performance of the wake interval under the corresponding crosswind conditions.
This paper intends to introduce the factors affecting the model of wake separation for the aeroplane takeoff,and for the said purpose,we would like to propose a three stages of eddy motion for the wake dissipation. To achieve the purpose,the paper has first of all intended to prepare a plane rectangular coordinating system based on the relative motion relationship between the two paired aeroplanes. And,then,on the said basis,it would be possible to consider and determine and formulate an aircraft wake encounter degree and wake the motion dissipation model between the aircraft wake intervals. And,later,on the basis of fully considering the influential factors of wake interval,it would be possible to establish the CSPRs( Closely Spaced Parallel Runways) take-off wake interval model by taking into full account the impacts of the crosswind on the wake motion and the dissipation of the wake motion and the aircraft wake resistance.Thus,finally,taking Shanghai Hongqiao Airport as a case study sample,the paper has done the calculation of the wake motion of the aircraft 36 L/18 R and its take-off procesure and B747-400 as the leading aircraft while B737-700 as the trailing aircraft. That is to say,taking the critical strength of the aircraft wake and the dissipation time of its wake for example,we have investigated the eddy current trajectories under the uncrosswind and adverse crosswind,so as to decide whether to continue to calculate the eddy current trajectory under the influence of favorable crosswind in accordance with the trajectory. And,in our investigation,we have managed to simulate the corresponding wake motion trajectory under different crosswind conditions in hoping to optimize the taking-off wake interval with the help of a software known as MATLAB. The simulation results we have gained demonstrate that the dissipation process of eddy motion can be influenced by the different crosswind conditions. The favorable crosswind volume has to be settled at about ≥2. 5 m/s as the critical crosswind takeoff interval without wake impact as the result of optimization. What is more,as compared with the calculation results in reference to the value of Eurocontrol( European Organization for the Safety of Air Navigation) wake encounter risk,we have confirmed and determined the safety performance of the above models in Shanghai Hongqiao Airport and in turn have faithfully been executing the optimized safety performance of the wake interval under the corresponding crosswind conditions.
引文
[1] HALLOCK J,OSGOOD S,KONOPKA J. Wake vortex effects on parallel runway operations[C]//American Institute of Aeronautics and Astronautics(AIAA). Proceedings of the 41st Aerospace Sciences Meeting and Exhibit.Montreal:AIAA,2003.
[2] HOLZAPFEL F. Probabilistic two-phase wake vortex decay and transport model[J]. Journal of Aircraft,2003,40(2):323-331.
[3] HOLZAPFEL F. Probabilistic two-phase aircraft wakevortex model:further development and assessment[J].Journal of Aircraft,2006,43(3):700-708.
[4] PROCTOR F H,HAMILTON D W. Evaluation of fasttime wake vortex prediction models[C]//American Institute of Aeronautics and Astronautics(AIAA). Proceedings of the 47th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. Montreal:AIAA,2009.
[5] HESSE H,PALACIOS R. Dynamic load alleviation in wake vortex encounters[J]. Journal of Guidance Control&Dynamics,2016,39(4):801-813.
[6] HU Jun(胡军). Study on the safety interval of wake in air traffic(空中交通中的尾流安全间隔研究)[D]. Nanjing:Nanjing University of Aeronautics and Astronautics,2001.
[7] WEI Zhiqiang(魏志强). The research modeling and simulation of flow field and safety spacing for wake vortex(尾涡流场及安全间隔的建模与仿真)[D]. Tianjin:Civil Aviation University of China,2008.
[8] XU Xiaohao(徐肖豪),ZHAO Hongsheng(赵鸿盛),YANG Chuansen(杨传森),et al. Large eddy simulation of wake vortex during approach[J]. Journal of Nanjing University of Aeronautics and Astronautics(南京航空航天大学学报),2010,42(2):179-184.
[9] XUE Yuan(薛源),XU Haojun(徐浩军),ZHU Hequan(朱和铨),et al. Flight risk probability evaluation in wakes based on multivariate extremum copula[J]. Acta Aeronautica et Astronatica Sinica(航空学报),2014,35(3):714-726.
[10] LI Yaowei(厉耀威). Wake vortex separation reduction and its analysis of collision safety(尾流间隔缩减及其碰撞安全性分析)[D]. Nanjing:Nanjing University of Aeronautics and Astronautics,2015.
[11] XIAO Qing(肖琴),LUO Fan(罗帆). On the safety risk assessment of the airport flight area based on the catastrophe theory and fuzzy set[J]. Journal of Safety and Environment(安全与环境学报). 2018,18(5):1730-1736.
[12] WINCKELMANS G,DUQUESNE T,TREVE V,et al.Summary description of the models used in the Vortex Forecast System(VFS)[R]. Belgium:Catholic University of Louvain,2005.
[13] SARPKAYA T. New model for vortex decay in the atmosphere[J]. Journal of Aircraft,2000,37(1):53-61.
[14] ROBERT E R,DONALD P D,GEORGE C G. Algorithm for prediction of trailing vortex evolution[J]. Journal of Aircraft,2001,38(5):911-917.
[15] LIU H T. Tow-tank simulation of vortex wake dynamics[C]//Federal Aviation Administration(FAA). Proceedings of the Aircraft Wake Vortices Conference. Washington,D. C.:FAA,1991.
[16] Civil Aviation Administration of China(中国民用航空局). CCAR-93TM-R5 Air traffic management rules for civil aviation of China(中国民用航空局空中交通管理规则)[S]. Beijing:Civil Aviation Administration of China,2017.
[17] MH/T 4016. 2—2007 Civil aviation industry standards of the People's Republic of China(中华人民共和国民用航空行业标准)[S].
[18] GAO Shujie(高淑杰). Research on wind speed forecasting based on error correction and fuzzy evaluation(基于误差修正和模糊评价的风速预测研究)[D].Taiyuan:Taiyuan University of Technology,2016.
[19] DUAN Xuewei(段学伟). Study on very short term wind speed and short term wind power prediction based on error analysis(基于误差分析修正的超短期风速及短期风电功率预测研究)[D]. Jinan:Shandong University,2016.
[20] LI Ning(李宁). Research on prediction method of ultrashort-term wind speed of wind farm based on normal distribution noise neural network(基于正态分布噪声神经网络的风电场超短期风速预测方法研究)[D].Lanzhou:Lanzhou University of Technology,2017.
[21] TIMOTHY H,MELANIE S. Analysis of localizer and glide slope flight technical error[C]//Institute of Electrical and Electronics Engineers(IEEE). Proceedings of Digital Avionics Systems Conference. Philadelphia:IEEE,2008.
[22] SEBASTIAN K,FRANK H,JAN K. Wake vortex encounter risk assessment for crosswind departures[J].Journal of Aircraft,2012,49(1):281-291.
[2] HOLZAPFEL F. Probabilistic two-phase wake vortex decay and transport model[J]. Journal of Aircraft,2003,40(2):323-331.
[3] HOLZAPFEL F. Probabilistic two-phase aircraft wakevortex model:further development and assessment[J].Journal of Aircraft,2006,43(3):700-708.
[4] PROCTOR F H,HAMILTON D W. Evaluation of fasttime wake vortex prediction models[C]//American Institute of Aeronautics and Astronautics(AIAA). Proceedings of the 47th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. Montreal:AIAA,2009.
[5] HESSE H,PALACIOS R. Dynamic load alleviation in wake vortex encounters[J]. Journal of Guidance Control&Dynamics,2016,39(4):801-813.
[6] HU Jun(胡军). Study on the safety interval of wake in air traffic(空中交通中的尾流安全间隔研究)[D]. Nanjing:Nanjing University of Aeronautics and Astronautics,2001.
[7] WEI Zhiqiang(魏志强). The research modeling and simulation of flow field and safety spacing for wake vortex(尾涡流场及安全间隔的建模与仿真)[D]. Tianjin:Civil Aviation University of China,2008.
[8] XU Xiaohao(徐肖豪),ZHAO Hongsheng(赵鸿盛),YANG Chuansen(杨传森),et al. Large eddy simulation of wake vortex during approach[J]. Journal of Nanjing University of Aeronautics and Astronautics(南京航空航天大学学报),2010,42(2):179-184.
[9] XUE Yuan(薛源),XU Haojun(徐浩军),ZHU Hequan(朱和铨),et al. Flight risk probability evaluation in wakes based on multivariate extremum copula[J]. Acta Aeronautica et Astronatica Sinica(航空学报),2014,35(3):714-726.
[10] LI Yaowei(厉耀威). Wake vortex separation reduction and its analysis of collision safety(尾流间隔缩减及其碰撞安全性分析)[D]. Nanjing:Nanjing University of Aeronautics and Astronautics,2015.
[11] XIAO Qing(肖琴),LUO Fan(罗帆). On the safety risk assessment of the airport flight area based on the catastrophe theory and fuzzy set[J]. Journal of Safety and Environment(安全与环境学报). 2018,18(5):1730-1736.
[12] WINCKELMANS G,DUQUESNE T,TREVE V,et al.Summary description of the models used in the Vortex Forecast System(VFS)[R]. Belgium:Catholic University of Louvain,2005.
[13] SARPKAYA T. New model for vortex decay in the atmosphere[J]. Journal of Aircraft,2000,37(1):53-61.
[14] ROBERT E R,DONALD P D,GEORGE C G. Algorithm for prediction of trailing vortex evolution[J]. Journal of Aircraft,2001,38(5):911-917.
[15] LIU H T. Tow-tank simulation of vortex wake dynamics[C]//Federal Aviation Administration(FAA). Proceedings of the Aircraft Wake Vortices Conference. Washington,D. C.:FAA,1991.
[16] Civil Aviation Administration of China(中国民用航空局). CCAR-93TM-R5 Air traffic management rules for civil aviation of China(中国民用航空局空中交通管理规则)[S]. Beijing:Civil Aviation Administration of China,2017.
[17] MH/T 4016. 2—2007 Civil aviation industry standards of the People's Republic of China(中华人民共和国民用航空行业标准)[S].
[18] GAO Shujie(高淑杰). Research on wind speed forecasting based on error correction and fuzzy evaluation(基于误差修正和模糊评价的风速预测研究)[D].Taiyuan:Taiyuan University of Technology,2016.
[19] DUAN Xuewei(段学伟). Study on very short term wind speed and short term wind power prediction based on error analysis(基于误差分析修正的超短期风速及短期风电功率预测研究)[D]. Jinan:Shandong University,2016.
[20] LI Ning(李宁). Research on prediction method of ultrashort-term wind speed of wind farm based on normal distribution noise neural network(基于正态分布噪声神经网络的风电场超短期风速预测方法研究)[D].Lanzhou:Lanzhou University of Technology,2017.
[21] TIMOTHY H,MELANIE S. Analysis of localizer and glide slope flight technical error[C]//Institute of Electrical and Electronics Engineers(IEEE). Proceedings of Digital Avionics Systems Conference. Philadelphia:IEEE,2008.
[22] SEBASTIAN K,FRANK H,JAN K. Wake vortex encounter risk assessment for crosswind departures[J].Journal of Aircraft,2012,49(1):281-291.