Master of Engineering (Research) / The overall objective of this research was to realise the practical application of Hierarchical Asynchronous Parallel Evolutionary Algorithms for Multi-objective and Multidisciplinary Design Optimisation (MDO) of UAV Systems using high fidelity analysis tools. The research looked at the assumed aerodynamics and structures of two production UAV wings and attempted to optimise these wings in isolation to the rest of the vehicle. The project was sponsored by the Asian Office of the Air Force Office of Scientific Research under contract number AOARD-044078. The two vehicles wings which were optimised were based upon assumptions made on the Northrop Grumman Global Hawk (GH), a High Altitude Long Endurance (HALE) vehicle, and the General Atomics Altair (Altair), Medium Altitude Long Endurance (MALE) vehicle. The optimisations for both vehicles were performed at cruise altitude with MTOW minus 5% fuel and a 2.5g load case. The GH was assumed to use NASA LRN 1015 aerofoil at the root, crank and tip locations with five spars and ten ribs. The Altair was assumed to use the NACA4415 aerofoil at all three locations with two internal spars and ten ribs. Both models used a parabolic variation of spar, rib and wing skin thickness as a function of span, and in the case of the wing skin thickness, also chord. The work was carried out by integrating the current University of Sydney designed Evolutionary Optimiser (HAPMOEA) with Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) tools. The variable values computed by HAPMOEA were subjected to structural and aerodynamic analysis. The aerodynamic analysis computed the pressure loads using a Boeing developed Morino class panel method code named PANAIR. These aerodynamic results were coupled to a FEA code, MSC.Nastran® and the strain and displacement of the wings computed. The fitness of each wing was computed from the outputs of each program. In total, 48 design variables were defined to describe both the structural and aerodynamic properties of the wings subject to several constraints. These variables allowed for the alteration of the three aerofoil sections describing the root, crank and tip sections. They also described the internal structure of the wings allowing for variable flexibility within the wing box structure. These design variables were manipulated by the optimiser such that two fitness functions were minimised. The fitness functions were the overall mass of the simulated wing box structure and the inverse of the lift to drag ratio. Furthermore, six penalty functions were added to further penalise genetically inferior wings and force the optimiser to not pass on their genetic material. The results indicate that given the initial assumptions made on all the aerodynamic and structural properties of the HALE and MALE wings, a reduction in mass and drag is possible through the use of the HAPMOEA code. The code was terminated after 300 evaluations of each hierarchical level due to plateau effects. These evolutionary optimisation results could be further refined through a gradient based optimiser if required. Even though a reduced number of evaluations were performed, weight and drag reductions of between 10 and 20 percent were easy to achieve and indicate that the wings of both vehicles can be optimised.

Parametric strategies for design automation and optimization can have a big impact on engineering design. When parametric tasks and optimization frameworks and methods are combined, theses strategies can be used to make up what is known as a multidisciplinary design optimization (MDO) schema. Knowledge of a design space can be modeled by using a MDO schema to represent the design process. However, current MDO frameworks used to create this schema lack the scope to capture enterprise wide knowledge for reuse and collaboration. Concurrent with the development of MDO, many companies are moving toward increased use of product lifecycle management (PLM). More applications are being integrated into PLM as its usage increases; however, it has not to date been able to fully embrace the sophisticated knowledge model demands of engineering design. It has functioned primarily as a data storage and electronic email and tracking system. This thesis proposes to integrate an MDO knowledge representation in the form of a design space model with a PLM system to provide knowledge management for the product design process throughout the enterprise. In this thesis a solution has been developed by leveraging PLM workflow management, and parametric PLM strategies. The PLM workflow management module was customized with action handlers, adding the ability to automate engineering tasks such as updating models and performing analysis. An optimization action handler was also added that iterates design processes by duplicating the entire workflow job and initiating it with updated inputs in order to explore and improve the design. This thesis proposes a new approach to PLM and MDO framework usage that enables the complete representation of a design space with absolute, enterprise wide reuse. Because of the synergy that is created between PLM and MDO through this approach, both software providers and users in industry are looking at it as a way to achieve their greatest challenges. This thesis achieves the common knowledge representation that industry has been actively pursuing, because of this industry leaders have been impressed and believe that this approach will quickly take hold and usher in a new era for product design.

This work details the development of a stability and control module for implementation into a Multidisciplinary Design Optimization (MDO) framework for the conceptual design of conventional and advanced aircraft. A novel approach, called the Variance Constrained Flying Qualities (VCFQ) approach, is developed to include closed-loop dynamic performance metrics in the design optimization process. The VCFQ approach overcomes the limitations of previous methods in the literature, which only functioned for fully decoupled systems with single inputs to the system. Translation of the modal parameter based flying qualities requirements into state variance upper bounds allows for multiple-input control laws which can guarantee upper bounds on closed-loop performance metrics of the aircraft states and actuators to be rapidly synthesized. A linear matrix inequality (LMI) problem formulation provides a general and scalable numerical technique for computing the feedback control laws using convex optimization tools. The VCFQ approach is exercised in a design optimization study of a relaxed static stability transonic transport aircraft, wherein the empennage assembly is optimized subject to both static constraints and closed-loop dynamic constraints. Under the relaxed static stability assumption, application of the VCFQ approach resulted in a 36% reduction in horizontal tail area and a 32% reduction in vertical tail area as compared to the baseline configuration, which netted a weight savings of approximately 5,200 lbs., a 12% reduction in cruise trimmed drag, and a static margin which was marginally stable or unstable throughout the flight envelope. State variance based dynamic performance constraints offer the ability to analyze large, highly coupled systems, and the linear matrix inequality problem formulation can be extended to include higher-order closed-loop design objectives within the MDO. Recommendations for further development and extensions of this approach are presented at the end. / This material is based on research sponsored by Air Force Research Laboratory under agreement number FA8650-09-2-3938. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory or the U.S. Government. / Ph. D.

The purpose of this study was to extend the analysis methods in PACELAB APD 3.1, a recent commercially available aircraft preliminary design tool with potential for MDO applications, for higher fidelity with physics-based instead of empirical methods and to enable the analysis of nonconventional aircraft configurations. The implementation of these methods was first validated against both existing models and wind tunnel data. Then, the original and extended PACELAB APD versions were used to perform minimum-fuel optimizations for both a traditional cantilever and strut-braced wing aircraft for a medium-range regional transport mission similar to that of a 737-type aircraft, with a minimum range of 3,115 nm and a cruise Mach number of 0.78. The aerodynamics, engine size / weight estimation and structural modules were heavily modified and extended to accomplish this. Comparisons to results for the same mission generated with FLOPS and VT MDO are also discussed. For the strut-braced configuration, large fuel savings on the order of 37% over the baseline 737-800 aircraft are predicted, while for the cantilever aircraft savings of 10-30% are predicted depending on whether the default or VT methods are utilized in the PACELAB analysis. This demonstrates the potential of the strut-braced configuration for reducing fuel costs, as well as the benefit of MDO in the aircraft conceptual design process. For the cantilever aircraft, FLOPS and VT MDO predict fuel savings of 8% and 23%, respectively. VT MDO predicts a fuel savings of 28% for the strut-braced aircraft over the baseline. / Master of Science

The process developed herein uses a Multiple Objective Genetic Optimization (MOGO) algorithm. The optimization is implemented in ModelCenter (MC) from Phoenix Integration. It uses a genetic algorithm that searches the design space for optimal, feasible designs by considering three Measures of Performance (MOPs): Cost, Effectiveness, and Risk. The complete synthesis model is comprised of an input module, the three primary AUV synthesis modules, a constraint module, three objective modules, and a genetic algorithm. The effectiveness rating determined by the synthesis model is based on nine attributes identified in the US Navy's UUV Master Plan and four performance-based attributes calculated by the synthesis model. To solve multi-attribute decision problems the Analytical Hierarchy Process (AHP) is used. Once the MOGO has generated a final generation of optimal, feasible designs the decision-maker(s) can choose candidate designs for further analysis. A sample AUV Synthesis was performed and five candidate AUVs were analyzed. / Master of Science

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.

Der Vortrag zeigt die einzelnen notwendigen Schritte auf, die zur Lösung des Resonanzproblems an der Vorderradaufhängung eines E-Rollstuhls der Firma MEYRA-ORTOPEDIA notwendig waren. Alle Lösungsschritte wurden mit Creo Elements/Pro und seinen Modulen Mechanism Design Option (MDO) und Advanced Mechanica erarbeitet.

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.

Orientador: Saulo Henrique Pereira / Resumo: Neste trabalho é construída a evolução completa do Universo impulsionada pelo espinor escuro com dimensão de massa um, chamado MDO. O modelo começa pela inflação cósmica, passando pela era dominada pela matéria escura, terminando com a recente expansão acelerada. Além disso, é feita uma primeira aproximação à teoria de perturbação escalar. Foi mostrado que a dinâmica do campo fermiônico MDO, respeitando um potencial com quebra de simetria, pode reproduzir todas as fases do Universo de uma maneira natural e elegante. As equações dinâmicas em geral e as condições de Slow-Roll, no limite H mp, também são apresentadas para o referido sistema. A análise numérica para o número de e-folds durante a inflação, densidade de energia após este período, o tempo presente e o tamanho real do Universo estão de acordo com o modelo padrão de cosmologia. Uma interpretação da fase inflacionária como resultado do princípio de exclusão de Pauli também é possível se o campo de MDO for tratado como um valor médio de seu análogo quântico / Doutor

Les avantages que présentent les systèmes électriques par rapport aux autres systèmes (mécaniques, hydrauliques et pneumatiques) ont permis d’intensifier l’électrification des systèmes embarqués à bord des aéronefs : c’est le concept d’avion plus électrique. Dans ce contexte, l’approche de conception intégrée par optimisation (CIO) de ces systèmes s’avère aujourd’hui une nécessité pour pouvoir répondre aux exigences en termes d’efficacité énergique, de fiabilité et de masse... Dans cette thèse, nous avons appliqué la CIO à une chaine de conversion électromécanique utilisée dans le système de conditionnement d’air d’un avion. Deux objectifs sont ciblés : la minimisation de la masse du système et l’augmentation de son efficacité énergétique. Ces objectifs sont intégrés à diverses contraintes hétérogènes, allant de la qualité réseau au respect de la mission de vol dans le plan couple – vitesse, en passant par la thermique,… Compte tenu de la complexité du système étudié et de son caractère multidisciplinaire, des approches de conception par optimisation dites « MDO » (pour Multidisciplinary Design Optimization) sont étudiées. En effet, au delà des compétences physiques et techniques, la conception intégrée par optimisation des systèmes complexes nécessite des efforts supplémentaires en termes de méthodologies de conception. Nous avons présenté dans cette thèse trois approches : Approches mono-niveau : séquentielle et globale ; Approche multi-niveaux, couplant niveaux système et niveau constituants (filtre, onduleur, machine) ; des formulations adaptées à notre problème de conception sont présentées afin de résoudre les problèmes liés aux optimisations mono-niveau. Les performances des différentes approches de conception sont présentées analysées et comparées. Les résultats obtenus montrent clairement les avantages que présente la formulation multi-niveaux par rapport aux approches classiques de conception. / The benefits of electrical systems compared to other systems (mechanical, hydraulic and pneumatic) are a serious motivation for the electrification of embedded systems in “more electric aircraft”. In this framework, the integrated optimal design of these systems appears necessary to meet requirements in terms of efficiency, reliability and weight reduction. In this thesis, we have applied the integrated optimal design to an electromechanical system used in the air conditioning system of a more electric aircraft. Two objectives are targeted: the minimization of the system weight and the increase of its efficiency. Both objectives are integrated with several heterogeneous constraints, from network quality till flight mission fulfilment in the torque vs speed plan. Because of the complexity of the studied system and its multidisciplinary nature, "MDO" approaches (for multidisciplinary Design Optimization) are studied. In fact, beyond physical and technical skills, integrated optimal design of complex systems requires additional efforts in terms of design methodologies. Three approaches are presented in this thesis: One-level Approaches: sequential and global; Multilevel approach, coupling “system” level with “device” level (filter, inverter, electric machine); a set of formulations adapted to our design problem are presented to solve the issues associated to the one-level approaches. The performance of these design approaches are presented, analyzed and compared. The results clearly show the advantages that involves multilevel formulation compared to conventional design approaches.