A indústria aeronáutica vem promovendo avanços tecnológicos em velocidades crescentes, para sobreviver em mercados extremamente competitivos. Neste cenário, torna-se imprescindível o uso de ferramentas de projeto que agilizem o desenvolvimento de novas aeronaves. Os atuais recursos computacionais permitiram um grande aumento no número de ferramentas que auxiliam o trabalho de projetistas e engenheiros. O projeto de uma aeronave é uma tarefa multidisciplinar por essência, o que logo incentivou o desenvolvimento de ferramentas computacionais que trabalhem com várias áreas ao mesmo tempo. Entre elas se destaca a otimização multidisciplinar em projeto, que une métodos de otimização à modelos matemáticos de áreas distintas de um projeto para encontrar soluções de compromisso. O presente trabalho introduz a otimização multidisciplinar em projeto (Multidisciplinary Design Optimization - MDO) e discorre sobre algumas aplicações possíveis desta metodologia. Foi realizada a implementação de um sistema de MDO para o projeto de asas flexíveis, considerando restrições de aeroelasticidade dinâmica e massa estrutural. Como meta, deseja-se encontrar distribuições ideais de rigidezes flexional e torcional da estrutura da asa, para maximizar a velocidade crítica de flutter e minimizar a massa estrutural. Para tanto, foram utilizados um modelo dinâmico-estrutural baseado no método dos elementos finitos, um modelo aerodinâmico não-estacionário baseado na teoria das faixas e nas soluções bidimensionais de Theodorsen, um modelo de previsão de flutter que utiliza o método K e, por fim, um otimizador baseado no método de algoritmos genéticos (AGs). São apresentados os detalhes empregados em cada modelo, as restrições aplicadas e a maneira como eles interagem ao longo da otimização. É feita uma análise para a escolha dos parâmetros de otimização por AG e em seguida a avaliação de dois casos, para verificação da funcionalidade do sistema implementado. Os resultados obtidos demonstram uma metodologia eficiente, que é capaz de buscar soluções ótimas para problemas propostos, que com devidos ajustes pode ter enorme valor para acelerar o desenvolvimento de novas aeronaves. / The aeronautical industry is always trying to speed up technological advances in order to survive in extremely competitive markets. In this scenario, the use of design tools to accelerate the development of new aircraft becomes essential. Current computational resources allow greater increase in the number of design tools to assist the work of aeronautical engineers. In essence, the design of an aircraft is a multidisciplinary task, which stimulates the development of computational tools that work with different areas at the same time. Among them, the multidisciplinary design optimization (MDO) can be distinguished, which combines optimization methods to mathematical models of distinct areas of a design to find compromise solutions. The present work introduces MDO and discourses on some possible applications of this methodology. The implementation of a MDO system for the design of flexible wings, considering dynamic aeroelasticity restrictions and the structural mass, was carried out. As goal, it is desired to find ideal flexional and torsional stiffness distributions of the wing structure, that maximize the critical flutter speed and minimize the structural mass. To do so, it was employed a structural dynamics model based on the finite element method, a nonstationary aerodynamic model based on the strip theory and Theodorsen’s two-dimensional solutions, a flutter prediction model based on the K method and a genetic algorithm (GA). Details on the model, restrictions applied and the way the models interact to each other through the optimization are presented. It is made an analysis for choosing the GA optimization parameters and then, the evaluation of two cases to verify the functionality of the implemented system. The results obtained illustrate an efficient methodology, capable of searching optimal solutions for proposed problems, that with the right adjustments can be of great value to accelerate the development of new aircraft.

Ce travail porte sur le développement de méthodes numériques innovantes pour la conception aéro-acoustique optimale de forme des configurations supersoniques. Ce manuscrit présente tout d'abord l'analyse et le développement des approches numériques pour la prévision du bang sonique . Le couplage du calcul CFD tridimensionnel en champ proche prenant en compte la décomposition multipolaire de Fourier et la propagation atmosphérique basée sur un algorithme de tracé de rayons est amélioré par l’intégration d'un processus automatique d' adaptation anisotrope de maillage. La deuxième partie de ce travail se concentre sur l’élaboration et l'application des techniques de conception pour l'optimisation d'une configuration aile-fuselage supersonique. Un module de conception inverse, AIDA , fournit à partir d'une signature acoustique cible au sol à faible bang sonique la géométrie de la configuration correspondante. Pour améliorer a la fois les performances acoustique et aérodynamique, des techniques d'optimisation directes de forme sont utilisées pour résoudre des problèmes d'optimisation mono et multi- disciplinaires et une analyse détaillée est réalisée. Des stratégies innovantes basées sur la coopération et les jeux compétitifs sont enfin appliquées au problème d'optimisation multidisciplinaire offrant une alternative aux algorithmes traditionnels MDO . L’hybridation de ces deux stratégies ouvre la voie a une nouvelle façon d'explorer le front de Pareto de manière efficace. Celle-ci est mise en application sur un cas pratique. / This work addresses the development of original numerical methods for the aero-acoustic optimal shape design of supersonic configurations. The first axis of the present research is the enhancement of numerical approaches for the prediction of sonic boom. The three dimensional CFD near-field prediction matched using a multipole decomposition approach coupled with atmospheric propagation using on a ray-tracing algorithm is improved by the integration of an automated anisotropic mesh adaptation process. The second part of this work focuses on the formulation and development of design techniques for the optimization of a supersonic wing-body configuration. An inverse design module, AIDA, is able to determine an equivalent configuration provided a target shaped signature at ground level corresponding to a low-boom profile. In order to improve both the aerodynamic and the acoustic performance, direct shape optimization techniques are used to solve single and multi-disciplinary optimization problems and a detailed analysis is carried out. At last, innovative strategies based on cooperation and competitive games are then applied to the multi-disciplinary optimization problem providing an alternative to traditional MDO algorithms. Hybridizing the two strategies opens a new efficient way to explore the Pareto front and this is shown on a practical case.

Orientador: Saulo Henrique Pereira / Resumo: Efeitos térmicos em teoria de campos são estudados pela chamada Teoria de Campos a Temperatura Finita. Nessa dissertação estudamos os efeitos de temperatura de um campo fermiônico de dimensão de massa um (MDO), que obedece à equação Klein-Gordon em vez da de Dirac. A função de partição foi obtida por meio do formalismo de tempo imaginário e o resultado foi o mesmo que o obtido para campos fermiônicos padrões de Dirac. Obtemos os limites de alta e baixa temperatura, sendo que o limite de baixas temperaturas é proposto como sendo o responsável por manter os halos de matéria escura da galáxia numa região da mesma ordem ou maior que o raio galáctico. Para uma partícula leve com massa de 1eV e densidade de 0.1 partículas por cm³, o valor da massa total da matéria escura devido a partículas MDO é da mesma ordem da massa de uma galáxia típica. Tal resultado pode explicar a matéria escura como sendo formada por partículas fermiônicas de dimensão de massa um. Por fim, comparamos as estimativas de densidade dessas partículas com densidades obtidas através de dados de simulações numéricas e concluímos que para valores de massa entre 0.1eV a 1eV, as partículas MDO produzem uma massa típica de galáxias desde que a densidade delas esteja no intervalo de 10^(-2) cm^(-3) a 10^(5)cm^(-3). / Abstract: Thermal effects in feld theory are studied by the so called Finite Temperature Field Theory. In this dissertation we study the effects of temperature of a mass dimension one (MDO) fermionic field, which obeys the Klein-Gordon equation rather than the Dirac equation. The partition function was obtained via the imaginary time formalism and the result was the same as for the a Dirac fermionic field. We obtained the high and low temperature limits, and the latter is proposed as being responsable for keeping the dark matter halos of galaxies in a region greater than or of the same order as a typical galaxy radius. For a light particle of about 1eV and density of 0.1 particles per cm3 , the value of the total dark mass due to MDO particles is of the same order of a typical galaxy. Such result can explain dark matter as being formed by fermionic particles. Lastly, we compared those particles densities estimates with the ones obtained numeric simulation data and conclude that for mass values between 0.1eV and 1eV, the MDO particles yield a typical galaxy mass as long as their density is in the 10−2 cm−3 to 105 cm−3 interval / Mestre

Zukünftige Hyperschalltransportsysteme unterliegen umfangreichen technischen, physikalischen, ökonomischen und ökologischen Anforderungen. Im Detail sind diese Anforderungen stark untereinander verknüpft und somit ist eine multidisziplinäre Behandlung bei einem Entwurf von Hyperschall-Konfigurationen notwendig. Mit Hilfe höherwertiger numerischer Verfahren, wie CFD und FEM, sowie wachsender parallelisierter Rechensysteme lässt sich der Hyperschall-Entwurfsprozess in einen multidisziplinären Optimierungsprozess (MDO-Prozess) überführen. In der vorliegenden Arbeit wird daher ein neu entwickeltes Optimierungswerkzeug für den Vorentwurf von Hyperschall-Flugzeugen vorgestellt, welches die wichtigsten Aspekte der Aerodynamik, der Strukturmechanik, der Flugmechanik, der Antriebsintegration und der Missionsanalyse in einer multidisziplinären Analyse vereint. Alle Teilprozesse werden vollständig automatisiert und in den Analyseprozess integriert. Nach geometrischen Änderungen am Konfigurationsdesign erfolgt eine Aktualisierung des gesamten Entwurfs mit abschließender Leistungsbewertung. Die Funktionalität und Kapazität dieses MDO-Prozesses wird erfolgreich an einem existierenden Hyperschallentwurf, der HYCAT-1A, demonstriert. / Future hypersonic transport systems are characterized by extensive and strongly coupled technical, physical, economic and environmental requirements. Hence a multidisciplinary approach for preliminary design studies is necessary. Using high-fidelity numerical tools, e.g. CFD and FEM, on large-scale computer systems the hypersonic design process can be transformed into a multidisciplinary optimization process (MDO process). Thus in the present work a newly developed optimization tool is presented considering aerodynamic, structural, engine and mission characteristics. All sub-processes are integrated in a fully automated analysis environment. During the optimization the outer geometry is changed and all sub-processes are updated accordingly to evaluate the design performance. The functionality and possibilities of the developed MDO process are successfully shown on an existing hypersonic design, the HYCAT-1A configuration.

With constantly changing regulations on emissions, heavy commercial vehicles manufacturers have to adapt for their products to preserve their quality while meeting these new requirements. Over the past decades, noise emissions have become a great concern and new stricter laws demand companies to decrease their vehicle pass-by noise target values. To address the requirements from different disciplines, Scania follows a simulation driven design process to develop new concept models EATS. The collaboration among engineers from different fields is thereby necessary in order to obtain higher performance silencers. However, the preprocessing step in terms of acoustic simulations is time-consuming, which can slow the concept development process. In this thesis, a new method was introduced to automate the pre-processing of silencer acoustic models and allow for design optimisation based on acoustic performance results. A common Scania product study case was provided to several theses within the NXD organisation. The collaboration among the master thesis workers aimed to demonstrate the benefits of KBE and MDO and how they can be integrated within Scania’s current concept development and product introduction processes. The performed work was divided in the following steps: data collection, method development and concluding work. The first step consisted in gathering sufficient knowledge by conducting a thorough literature review and interviews. Then, an initial method was formulated and tested on a simplified silencer model. Once approved and verified, the method was applied to the study case EATS. The study case showed that a complex product can have its acoustic pre-processing step automated by ensuring a good connectivity among the required software and a correct denomination of the geometrical objects involved in the simulations. The method investigated how morphological optimisations can be performed at both global and local levels to enhance the transmission loss of a silencer. Besides optimising the acoustic performance of the models, the method allowed the identification of correlations and inter-dependencies among their design variables and ouput parameters. / Med ständiga förändringar i lagkrav som berör utsläpp måste tillverkare av tunga fordon anpassa sina produkter för att upprätthålla kvalitén samtidigt som de möter de nya kraven. De senaste årtiondena har ljudnivåerna från fordon blivit ett orosmoment, det stiftats striktare lagar som berör den ljudnivå som tunga fordon får emittera under ett förbifartsprov. För att adressera kraven från de olika disciplinerna följer Scania en simuleringsdriven utvecklingsprocess vid utveckling av nya efterbehandlingssystem. Samarbetet mellan ingenjörer från olika fält är därför nödvändigt för att utveckla högre prestanda efterbehandlingsystem. Uppställningen utav de akustiska simuleringarna är tidskrävande, vilket kan leda till en långsam utvecklingsprocess. I detta examensarbete föreslås en ny metod för att introducera en automatiserad uppställning av akustiska simuleringar på efterbehandlingssystem som tillåter optimering av de akustiska egenskaperna. Ett gemensamt studiefall gavs av Scania till flera examensarbeten skrivna vid NXD organisationen. Samarbetet mellan de olika examensarbetena syftade på att demonstrera fördelarna med KBE och MDO och hur de kan bli integrerade i Scanias nuvarande konceptutvecklings- och produktintroduktionsprocess. Examensarbetet är uppdelat i följande steg; datainsamling, metodutveckling och avslutandearbete. Det första steget innefattade insamling av kunskap genom att genomföra en grundlig litteraturstudie och flera intervjuer. Det nästkommande steget innefattade formulering av en initial metod vilken testades på ett simplifierat efterbehandlingssystem. När detta hade verifierats och godkänts applicerades metoden på efterbehandlingssystem i fallstudien. Fallstudien visade att även för en komplex produkt kan uppställningen av de akustiska simuleringarna bli automatiserade genom att säkerställa en bra koppling mellan de olika mjukvarorna och en korrekt benämning av de geometriska objekten involverade i simuleringen. Metoden undersökte hur morfologiska optimeringar kan bli genomförda både på en vittomfattande och lokal nivå för att förbättra transmissionsförlusten i ett efterbehandlingssystem. Förutom att optimera den akustiska prestandan av modellen kunde flera korrelationer mellan de olika konstruktiosparametrar identifieras likväl kunde korrelationer mellan konstruktiosparametrar och systemegenskaperna.

With constantly changing regulations on emissions, heavy commercial vehicles manufacturershave to adapt for their products to preserve their quality while meetingthese new requirements. Over the past decades, noise emissions have become a greatconcern and new stricter laws demand companies to decrease their vehicle pass-bynoise target values.To address the requirements from different disciplines, Scania follows a simulationdriven design process to develop new concept models EATS. The collaboration amongengineers from different fields is thereby necessary in order to obtain higher performancesilencers. However, the pre-processing step in terms of acoustic simulationsis time-consuming, which can slow the concept development process.In this thesis, a new method was introduced to automate the pre-processing of silenceracoustic models and allow for design optimisation based on acoustic performanceresults. A common Scania product study case was provided to several theseswithin the NXD organisation. The collaboration among the master thesis workersaimed to demonstrate the benefits of KBE and MDO and how they can be integratedwithin Scania’s current concept development and product introduction processes.The performed work was divided in the following steps: data collection, methoddevelopment and concluding work. The first step consisted in gathering sufficientknowledge by conducting a thorough literature review and interviews. Then, an initialmethod was formulated and tested on a simplified silencer model. Once approvedand verified, the method was applied to the study case EATS.The study case showed that a complex product can have its acoustic pre-processingstep automated by ensuring a good connectivity among the required software anda correct denomination of the geometrical objects involved in the simulations. Themethod investigated how morphological optimisations can be performed at bothglobal and local levels to enhance the transmission loss of a silencer. Besides optimisingthe acoustic performance of the models, the method allowed the identificationof correlations and inter-dependencies among their design variables and ouput parameters.

La conception de lanceurs est un problème d'optimisation multidisciplinaire (MDO) complexe qui a la particularité d'intégrer une optimisation de trajectoire très contrainte, difficile à résoudre et fortement couplée à toutes les autres disciplines entrant en jeu dans le processus de conception (e.g. propulsion, aérodynamique, structure, etc.). Cette thèse s'intéresse aux méthodes permettant d'intégrer judicieusement l'optimisation de la trajectoire au sein du processus d'optimisation des variables de conception. Une nouvelle méthode, appelée "Stage-Wise decomposition for Optimal Rocket Design" (SWORD), a été proposée. Celle-ci décompose le processus de conception suivant les différentes phases de vol et transforme le problème d'optimisation de lanceur multiétage en un problème de coordination des optimisations de chacun des étages, plus facile à résoudre. La méthode SWORD a été comparée à la méthode MDO classique (Multi Discipline Feasible) dans le cas d'une optimisation globale d'un lanceur tri-étage. Les résultats montrent que la méthode SWORD permet d'améliorer l'efficacité du processus d'optimisation, tant au niveau de la vitesse de recherche de l'espace de solutions faisables que de la qualité de l'optimum trouvé en temps de calcul limité. Afin d'améliorer la vitesse de convergence de la méthode tout en ne requérant pas de connaissance a priori de l'utilisateur au niveau de l'initialisation et l'espace de recherche, une stratégie d'optimisation dédiée à la méthode SWORD a été développée.

Multidisciplinary design optimization (MDO) is a technique that has found use in the field of aerospace engineering for aircraft design. It uses optimization to simultaneously solve design problems with several disciplines involved. In order to predict aircraft performance an engine performance simulation model, also called “rubber engine”, is vital. The goal of this project is to validate and integrate a rubber engine model into an MDO environment. A method for computer simulation of gas turbine aero engine performance was created. GasTurb v11, a commercial gas turbine performance simulation software, was selected for doing the simulation models. The method was validated by applying it to five different jet engines of different size, different type and different age. It was shown that the simulation engine model results are close to the engine manufacturer data in terms of SFC and net thrust during cruise, maximum climb (MCL) and take off (MTO) thrust ratings. The cruise, take off and climb SFC was in general predicted within 2% error when compared to engine manufacturer performance data. The take off and climb net thrust was in general predicted with less than 5% error. The integration of the rubber engine model with the MDO framework was started and it was demonstrated that the model can run within the MDO software. Four different jet engine models have been prepared for use within the optimization software. The main conclusion is that GasTurb v11 can be used to make accurate jet engine performance simulation models and that it is possible to incorporate these models into an MDO environment.

A set of techniques is developed that allows the incorporation of flight dynamics metrics as an additional discipline in a high-fidelity aerodynamic optimization. Specifically, techniques for including static stability constraints and handling qualities constraints in a high-fidelity aerodynamic optimization are demonstrated. These constraints are developed from stability derivative information calculated using high-fidelity computational fluid dynamics (CFD). Two techniques are explored for computing the stability derivatives from CFD. One technique uses an automatic differentiation adjoint technique (ADjoint) to efficiently and accurately compute a full set of static and dynamic stability derivatives from a single steady solution. The other technique uses a linear regression method to compute the stability derivatives from a quasi-unsteady time-spectral CFD solution, allowing for the computation of static, dynamic and transient stability derivatives. Based on the characteristics of the two methods, the time-spectral technique is selected for further development, incorporated into an optimization framework, and used to conduct stability-constrained aerodynamic optimization. This stability-constrained optimization framework is then used to conduct an optimization study of a flying wing configuration. This study shows that stability constraints have a significant impact on the optimal design of flying wings and that, while static stability constraints can often be satisfied by modifying the airfoil profiles of the wing, dynamic stability constraints can require a significant change in the planform of the aircraft in order for the constraints to be satisfied.

A set of techniques is developed that allows the incorporation of flight dynamics metrics as an additional discipline in a high-fidelity aerodynamic optimization. Specifically, techniques for including static stability constraints and handling qualities constraints in a high-fidelity aerodynamic optimization are demonstrated. These constraints are developed from stability derivative information calculated using high-fidelity computational fluid dynamics (CFD). Two techniques are explored for computing the stability derivatives from CFD. One technique uses an automatic differentiation adjoint technique (ADjoint) to efficiently and accurately compute a full set of static and dynamic stability derivatives from a single steady solution. The other technique uses a linear regression method to compute the stability derivatives from a quasi-unsteady time-spectral CFD solution, allowing for the computation of static, dynamic and transient stability derivatives. Based on the characteristics of the two methods, the time-spectral technique is selected for further development, incorporated into an optimization framework, and used to conduct stability-constrained aerodynamic optimization. This stability-constrained optimization framework is then used to conduct an optimization study of a flying wing configuration. This study shows that stability constraints have a significant impact on the optimal design of flying wings and that, while static stability constraints can often be satisfied by modifying the airfoil profiles of the wing, dynamic stability constraints can require a significant change in the planform of the aircraft in order for the constraints to be satisfied.