O. Boucher, N. Bellouin, H. Clark, E. Gryspeerdt, Julien Karadayi
{"title":"全球观测系统(IAGOS)项目中在役飞机实际飞行轨迹和时间优化飞行轨迹的比较","authors":"O. Boucher, N. Bellouin, H. Clark, E. Gryspeerdt, Julien Karadayi","doi":"10.3390/aerospace10090744","DOIUrl":null,"url":null,"abstract":"Airlines optimize flight trajectories in order to minimize their operational costs, of which fuel consumption is a large contributor. It is known that flight trajectories are not fuel-optimal because of airspace congestion and restrictions, safety regulations, bad weather and other operational constraints. However, the extent to which trajectories are not fuel-optimal (and therefore CO2-optimal) is not well known. In this study, we present two methods for optimizing the flight cruising time by taking best advantage of the wind pattern at a given flight level and for constant airspeed. We test these methods against actual flight trajectories recorded under the In-service Aircraft for a Global Observing System (IAGOS) programme. One method is more robust than the other (computationally faster) method, but when successful, the two methods agree very well with each other, with optima generally within the order of 0.1%. The IAGOS actual cruising trajectories are on average 1% longer than the computed optimal for the transatlantic route, which leaves little room for improvement given that by construction the actual trajectory cannot be better than our optimum. The average degree of non-optimality is larger for some other routes and can be up to 10%. On some routes, there are also outlier flights that are not well optimized; however, the reason for this is not known.","PeriodicalId":50845,"journal":{"name":"Aerospace America","volume":"1 1","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Actual and Time-Optimized Flight Trajectories in the Context of the In-Service Aircraft for a Global Observing System (IAGOS) Programme\",\"authors\":\"O. Boucher, N. Bellouin, H. Clark, E. Gryspeerdt, Julien Karadayi\",\"doi\":\"10.3390/aerospace10090744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Airlines optimize flight trajectories in order to minimize their operational costs, of which fuel consumption is a large contributor. It is known that flight trajectories are not fuel-optimal because of airspace congestion and restrictions, safety regulations, bad weather and other operational constraints. However, the extent to which trajectories are not fuel-optimal (and therefore CO2-optimal) is not well known. In this study, we present two methods for optimizing the flight cruising time by taking best advantage of the wind pattern at a given flight level and for constant airspeed. We test these methods against actual flight trajectories recorded under the In-service Aircraft for a Global Observing System (IAGOS) programme. One method is more robust than the other (computationally faster) method, but when successful, the two methods agree very well with each other, with optima generally within the order of 0.1%. The IAGOS actual cruising trajectories are on average 1% longer than the computed optimal for the transatlantic route, which leaves little room for improvement given that by construction the actual trajectory cannot be better than our optimum. The average degree of non-optimality is larger for some other routes and can be up to 10%. On some routes, there are also outlier flights that are not well optimized; however, the reason for this is not known.\",\"PeriodicalId\":50845,\"journal\":{\"name\":\"Aerospace America\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2023-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aerospace America\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3390/aerospace10090744\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace America","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/aerospace10090744","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
Comparison of Actual and Time-Optimized Flight Trajectories in the Context of the In-Service Aircraft for a Global Observing System (IAGOS) Programme
Airlines optimize flight trajectories in order to minimize their operational costs, of which fuel consumption is a large contributor. It is known that flight trajectories are not fuel-optimal because of airspace congestion and restrictions, safety regulations, bad weather and other operational constraints. However, the extent to which trajectories are not fuel-optimal (and therefore CO2-optimal) is not well known. In this study, we present two methods for optimizing the flight cruising time by taking best advantage of the wind pattern at a given flight level and for constant airspeed. We test these methods against actual flight trajectories recorded under the In-service Aircraft for a Global Observing System (IAGOS) programme. One method is more robust than the other (computationally faster) method, but when successful, the two methods agree very well with each other, with optima generally within the order of 0.1%. The IAGOS actual cruising trajectories are on average 1% longer than the computed optimal for the transatlantic route, which leaves little room for improvement given that by construction the actual trajectory cannot be better than our optimum. The average degree of non-optimality is larger for some other routes and can be up to 10%. On some routes, there are also outlier flights that are not well optimized; however, the reason for this is not known.