Multi-Objective Optimization of the Performance of an UHB Turbofan with Regeneration

Every day the world faces the constant degradation of its environment. The global warming, between many other environmental problems, presents itself as a giant that, day by day, quietly grows and which the only warnings are the gradually severe effects that the planet displays. Before an increasingly real scenario, public concerns rise about the environmental conditions of the planet in the near future, as well as the consequences for the Mankind. The growth of the human population and its interaction with the environment that contains it, as well as a global economy in an increasing competitiveness obliges that an evolving society complies in the most effective way to the environmental and economic challenges in the future ahead. Being the aeronautical industry one of the main fields where the most recent ideas and technological innovations take place, several initiatives have been taken to cope with these challenges. The environmental problems of the planet as well as the economic challenges, namely the rise of the fuel prices, are more and more the center of attentions, if not the main objectives to overcome in current aeronautical projects. These projects aim the best possible answer in an expansion and strong demanding market. This dissertation focus on the study of several parameters of a Turbofan engine, the type of engine most used in commercial aviation around the world. At the present moment, we are facing a period of critical decisions by the air carriers in the renewal / upgrade of their fleet, consequently the new aircrafts will be equipped with Turbofan engines that promise improvements at all levels relatively to their predecessors. These new engines are characterized by a superior Bypass regarding the current engines; they are referred as UHB (Ultra Bypass Ratio) Turbofans and possess lower values of SFC (Specific Fuel Consumption). Therefore this study is intended to analyze the behaviour of these parameters along with the new Bypass values and also evaluate if the utilization of a heat regenerator will be viable to obtain lower values of SFC relatively to a configuration without regeneration. At last, it will be carried a parameter optimization for both sets, using a Genetic Algorithm designed for Multi-Objective Optimization.Todos os dias o mundo enfrenta o degradar constante do seu meio ambiente. O aquecimento global, entre muitos outros problemas ambientais, apresenta-se como um gigante que silenciosamente, dia após dia, ganha maior dimensão e cujos únicos avisos são os efeitos gradualmente mais severos que o planeta apresenta. Perante um cenário cada vez mais real, preocupações públicas levantam-se sobre as condições ambientais do planeta no futuro, bem como as consequências inerentes à Humanidade. O crescimento da população humana e a sua interacção com o ambiente que a envolve, bem como uma economia global em crescente competitividade, obriga a que uma sociedade em plena evolução responda de forma mais eficaz aos desafios ambientais e económicos que se avizinham. Sendo a indústria Aeronáutica um dos principais ramos onde as mais recentes ideias e inovações tecnológicas tomam lugar, várias iniciativas têem surgido para fazer face a estes desafios. Os problemas ambientais do planeta bem como os desafios económicos, nomeadamente a subida dos preços dos combustíveis, são cada vez mais o centro das atenções, se não mesmo os objectivos a superar nos projectos aeronáuticos da actualidade. Estes projectos visam a melhor resposta possível num mercado em expansão e de forte exigência. Esta dissertação incide no estudo de vários parâmetros de um motor Turbofan, sendo este tipo de motor o mais utilizado na aviação comercial em todo o mundo. Neste momento, estamos perante um período de decisões críticas por parte das operadoras aéreas na renovação/actualização das suas frotas, sendo que as novas aeronaves serão equipadas com motores Turbofan que prometem melhorias a todos os níveis relativamente aos seus antecessores. Estes novos motores caracterizam-se por um Bypass superior aos motores actuais, sendo por isso denominados de UHB (Ultra High Bypass Ratio) Turbofans e possuem valores menores de SFC (Specific Fuel Consumption). Com este estudo, procura-se analisar o comportamento desses parâmetros ao longo dos novos valores Bypass, averiguando ainda se a utilização de um regenerador de calor será viável de modo a obter valores inferiores de SFC em relação a uma configuração sem regeneração. Por fim procede-se a uma optimização dos parâmetros para ambos os casos estudados, com recurso a um Algoritimo Genético de Optimização Multi-Objetivos

Development of a modular Knowledge-Discovery Framework based on Machine Learning for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes

Die physikalischen und chemischen Phänomene vor, während und nach der Verbrennung in Motoren mit Benzindirekteinspritzung (BDE) sind komplex und umfassen unterschiedliche Wechselwirkungen zwischen Flüssigkeiten, Gasen und der umgebenden Brennraumwand. In den letzten Jahren wurden verschiedene Simulationstools und Messtechniken entwickelt, um die an den Verbrennungsprozessen beteiligten Komponenten zu bewerten und zu optimieren. Die Möglichkeit, den gesamten Gestaltungsraum zu erkunden, ist jedoch durch den hohen Aufwand zur Generierung und zur Analyse der nichtlinearen und multidimensionalen Ergebnisse begrenzt. Das Ziel dieser Arbeit ist die Entwicklung und Validierung eines Datenanalysewerkzeugs zur Erkenntnisgewinnung. Im Rahmen dieser Arbeit wird der gesamte Prozess als auch das Werkzeug als "Knowledge-Discovery Framework" bezeichnet. Dieses Werkzeug soll in der Lage sein, die im BDE-Kontext erzeugten Daten durch Methoden des maschinellen Lernens zu analysieren. Anhand einer begrenzten Anzahl von Beobachtungen wird damit ermöglicht, die untersuchten Gestaltungsräume zu erkunden sowie Zusammenhänge in den Beobachtungen der komplexen Phänomene schneller zu entdecken. Damit können teure und zeitaufwendige Auswertungen durch schnelle und genaue Vorhersagen ersetzt werden. Nach der Einführung der wichtigsten Datenmerkmale im Bereich der BDE Anwendungen wird das Framework vorgestellt und seine modularen und interdisziplinären Eigenschaften dargestellt. Kern des Frameworks ist eine parameterfreie, schnelle und dynamische datenbasierte Modellauswahl für die BDE-typischen, heterogenen Datensätze. Das Potenzial dieses Ansatzes wird in der Analyse numerischer und experimenteller Untersuchungen an Düsen und Motoren gezeigt. Insbesondere werden die nichtlinearen Einflüsse der Auslegungsparameter auf Einström- und Sprayverhalten sowie auf Emissionen aus den Daten extrahiert. Darüber hinaus werden neue Designs, basierend auf Vorhersagen des maschinellen Lernens identifiziert, welche vordefinierte Ziele und Leistungen erfüllen können. Das extrahierte Wissen wird schließlich mit der Domänenexpertise validiert, wodurch das Potenzial und die Grenzen dieses neuartigen Ansatzes aufgezeigt werden

Development of a modular Knowledge-Discovery Framework based on Machine Learning for the interdisciplinary analysis of complex phenomena in the context of GDI combustion processes

In this work, a novel knowledge discovery framework able to analyze data produced in the Gasoline Direct Injection (GDI) context through machine learning is presented and validated. This approach is able to explore and exploit the investigated design spaces based on a limited number of observations, discovering and visualizing connections and correlations in complex phenomena. The extracted knowledge is then validated with domain expertise, revealing potential and limitations of this method

9th EASN International Conference on Innovation in Aviation & Space

This Special Issue book contains selected papers from works presented at the 9th EASN (European Aeronautics Science Network) International Conference on Innovation in Aviation & Space, which was held in Athens, Greece from the 3rd until the 6th of September, 2019. About 450 participants contributed to a high-level scientific gathering, providing some of the latest research results on the topic, as well as some of the latest relevant technological advancements. Eight interesting articles, which cover a wide range of topics including characterization, analysis and design, as well as numerical simulation, are contained in this Special Issue

Old cellulose for new multifunctional networks

Dissertação para obtenção do Grau de Doutor em Ciência e Engenharia de MateriaisCellulose is considered to be the most abundant and renewable natural polymer on earth. It is the main component of plant cells. The exploration of the utility and applications of this material and its derivatives has never stopped since human´s birth. It is well known that cellulose based materials can generate films and fibers, which can be, for instance, produced from cellulosic solutions. The Cellulose rich chemical structure allows different behaviors of the polymer in solution, which is the driving force for diverse films and fibers features. The main goal of this work is the manufacture and characterization of new application of the renewable cellulosic-based materials, which are at the origin of stimuli-responsive and/or functional soft films and fibers. The several materials obtained have in common the main chain cellulose backbone but present different liquid crystalline properties. Firstly rheology coupled to nuclear magnetic resonance techniques (rheo-NMR) were used to characterize a cellulose-water based liquid crystalline solution in order to establish structure/properties relationships, which were the basis to improve the design of films and fibers produced in the framework of this work. The results achieved were at the origin of a paper published in Macromolecules. Then films were produced and due to their structure and enhanced mechanical properties, different applications were realized by producing cellulosic gratings, which mimic the periodic structures that can be found in some petals of plants and a soft cellulose moisture motor was built for the first time. Two manuscripts were published, one related to the grating mimics, in Macromolecular Chemistry and Physics, and the other one dedicated to the mechanical properties and the bending of a cellulosic film controlled by moisture action in Scientific Reports (Nature Publishing Group). Concerning cellulosic fibers, two methods were selected to fabricate micro/nano networks. In order to produce suspended aligned arrays, electrospinning was chosen due to its versatility. On the obtained nano/micro cylinders, nematic and cholesteric droplets were threaded producing necklaces of liquid crystal beads for the first time. The fiber changes not only the topology of the droplet but also distorts its spherical shape to an approximately ellipsoidal droplet. An additional cylindrical surface with planar anchoring along the droplet’s long axis was also added. Designing nematic and cholesteric liquid crystal microdroplets on thin long threads opened new routes to produce fiber waveguides decorated with complex microresonators. Two Soft Matter scientific papers were published based on this work (One was chosen as the cover of that issue). Finally, nano-fibers produced by cellulose acid hydrolises were prepared and a new electro-optical sensor was built up and characterized and the results published in Liquid Crystals journal. Throughout this work Landau-de-Gennes theory was used in order to interpret and understand some of the experimental results achieved.Portuguese Science and Technology Foundation - SFRH/BD/63574/2009, PTDC/CTM/099595/2008, PTDC/CTM-POL/1484/2012, PTDC/CTM/101776/2008, PTDC/FIS/110132/2009, and PEst- C/CTM/LA0025/2011 (Strategic Project - LA 25-2011-2012