Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2007. / Includes bibliographical references (p. 77-78).

Commercial aviation and air traffic is still expected to grow by 4-5% annually in the future and thus the effect of aircraft operation on the environment and its consequences for the climate change is a major concern for all parties involved in the aviation industry. One important aspect of aircraft engine operation is the performance degradation of such engines over their lifetime while another aspect involves the aircraft flight trajectory itself. Therefore, the first aim of this work is to evaluate and quantify the effect of engine performance degradation on the overall aircraft flight mission and hence quantify the impact on the environment with regards to the following two objectives: fuel burned and NOxemissions. The second part of this study then aims at identifying the potential for optimised aircraft flight trajectories with respect to those two objectives. A typical two-spool high bypass ratio turbofan engine in three thrust variants (low, medium and high) and a typical narrow body single-aisle aircraft similar to the A320 series were modelled as a basis for this study. In addition, an existing emissions predictions model has been adapted for the three engine variants. Detailed parametric and off-design analyses were carried out to define and validate the performance of the aircraft, engine and emissions models. The obtained results from a short and medium range flight missions study showed that engine degradation and engine take-off thrust reduction significantly affect total mission fuel burn and total mission NOx emissions (including take-off) generated. A 2% degradation of compressor, combustor and turbine component parameters caused an increase in total mission fuel burn of up to 5.3% and an increase in NOx emissions of up to 5.9% depending on the particular mission and aircraft. However, take-off thrust reduction led to a decrease in NOx emissions of up to 41% at the expense of an increase in take-off distance of up to 12%. Subsequently, a basic multi-disciplinary aircraft trajectory optimisation framework was developed and employed to analyse short and medium range flight trajectories using one aircraft and engine configuration. Two different optimisation case studies were performed: (1) fuel burned vs. flight time and (2) fuel burned vs. NOx emitted. The results from a short range flight mission suggested a trade-off between fuel burned versus flight time and showed a fuel burn reduction of 3.0% or a reduction in flight time of 6.7% when compared to a “non-optimised” trajectory. Whereas the optimisation of fuel burn versus NOx emissions revealed those objectives to be non- conflicting. The medium range mission showed similar results with fuel burn reductions of 1.8% or flight time reductions of 7.7% when compared to a “non- optimised” trajectory. Accordingly, non-conflicting solutions for fuel burn versus NOx emissions have been achieved. Based on the assumptions introduced for the trajectory optimisation analyses, the identified optimised trajectories represent possible solutions with the potential to reduce the environmental impact. In order to increase the simulation quality in the future and to provide more comprehensive results, a refinement and extension of the framework also with additional models taking into account engine life, noise, weather or operational procedures, is required. This will then also allow the assessment of the implications for airline operators in terms of Direct Operating Costs (DOC). In addition, the degree of optimisation could be improved by increasing the number and type of optimisation variables.

La prédiction de trajectoires d'avions à partir des données disponibles au sol est un problème critique pour le contrôle aérien. Une prédiction fiable et efficace est un prérequis pour l'implémentation d'outils automatiques pour la détection et la résolution de conflits entre les trajectoires. Dans ce contexte, nous proposons de nouvelles méthodes non paramétriques pour la prédiction d'intervalle contenant une proportion attendue des données avec un haut niveau de confiance. Dans un premier temps, nous traitons le problème de l'estimation d'une distribution de probabilité à partir d'un petit échantillon. En considérant l'interprétation des distributions de possibilité comme une famille de distributions de probabilité, nous décrivons un ensemble de distributions de possibilité qui résument différents types d'intervalles statistiques. Ensuite, nous proposons un cadre de travail pour vérifier si un modèle, construit à partir de données, respecte les propriétés de recouvrement requises par les intervalles de prédiction. Nous introduisons aussi deux mesures pour comparer des modèles de prédiction d'intervalle qui ont des tailles moyennes et des taux de recouvrement différents. A partir de nos travaux sur les intervalles statistiques (et leurs distributions de possibilité associés), nous présentons une nouvelle méthode pour induire des intervalles de prédictions bornés pour des méthodes de régression des moindres carrés non paramétriques sans assumer que la prédiction est non biaisée et que les erreurs sont homoscédastiques. Nos intervalles de prédiction sont construits en utilisant des intervalles de tolérances sur les erreurs dans le voisinage du point à prédire. Pour cela, nous décrivons une méthode de sélection de voisinage à taille fixe ou de voisinage à taille variable dépendant de la quantité d'informations autour du point. Nous obtenons un algorithme qui induit, dans la majorité des cas, les intervalles de prédiction fiables les plus petits possibles. Les méthodes que nous proposons sont comparées avec les méthodes les plus connues au niveau théorique et au niveau pratique. Une évaluation est effectuée sur neuf bases de données. La taille, l'efficacité, la fiabilité et la précision des intervalles prédits sont comparés. Ces expérimentations montrent que nos approches sont significativement plus précises et fiables que les autres. Enfin nous appliquons nos méthodes au problème de la prédiction de trajectoires d'avions et nous comparons les résultats avec ceux des méthodes classiques et des modèles physiques.

No description available.

The prediction of contrails have been studied since the 1930s primarily for militaryapplications. In present times, contrail avoidance strategies are gaining popularity insustainable aviation. In this project, the theory behind their formation, persistenceand the mitigation strategies are explored, studied and implemented.Several methods are evaluated in order to predict the critical temperature. Aircraftparameters are included in the prediction of contrails and implemented. This dynamicprogramming is contrasted against real case operational flight plans.The first implementation considers an operational flight plan for which contrails are pre-dicted along the trajectory. The second involves the prediction of contrails at the end ofthe vertical trajectory optimisation. The optimisation for contrail persistence avoidanceis also accomplished. Results show that contrail persistence can be avoided. / Förutsägelsen av kondensspår har studerats sedan 1930-talet, främst för militära tillämp-ningar. I nutid, strategier för undvikande av långvariga kondensspår ökar i popularitetinom hållbar flygning. I det här examensarbetet, utforskas och studeras teorin bakombildning, uthållighet och begränsningsstrategier för kondensspår för att sedan imple-menteras.Flera metoder evalueras för att förutsäga den kritiska temperaturen. Flygplansparame-trar är inkluderade och implementerade i förutsägelsen av kondesspår. Den dynamiskaprogrammeringen jämförs mot verkliga operativa färdplaner.Den första implementeringen avser en operativ färdplan för vilken kondensspår förut-spås längs banan. Den andra implementeringen involverar förutsägelse av kondensspåri slutet av den vertikala banoptimeringen. Optimeringen med avseende på långvarigakondensspår genomförs också. Resultaten visar att långvariga kondensspår kan und-vikas.

Reducing emissions is a very prevailing topic also in aviation industry. Besides technological improvements it is necessary to also adjust procedures and operations. We present a tool that is able to optimize flight trajectories not only regarding economical factors but also ecological ones. Due to the utilization of a flight performance model and a detailed engine model, it is possible to determine an aircraft’s emission quantities during all phases of a flight. Besides those like CO2, NOx, CO, Black Carbon, etc. we are also considering contrail formation and their influence on the global warming. By transforming emissions into monetary values we can find a trade off between multiple criteria. After describing the employed models and software architecture we present some use cases where we successfully applied our toolchain.