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.

In this study, development of software, which can analyze and optimize an SRM by accurately calculating its performance, is aimed. Existing methods in the literature are investigated. Some studies for the calculation of performance use 2D field solutions and are known to be accurate / however, using field solutions is not feasible for the optimization purpose. So, a method based on a set of normalized permeance and force data are chosen for prediction of magnetizing characteristics. Selected methods are programmed into the software with a user friendly interface. The results from the software are compared with test results from an existing motor. It is found that the accuracy of the predictions is not acceptable if the effect of end winding leakage flux is not accounted for. An approach is proposed for accounting the end winding leakage. The software is modified accordingly. In this case, the results obtained are found to have good accuracy, compared with measurements. The SR motor design optimization problem is treated as a constrained wieght optimization problem. This problem is converted to an unconstrained optimization problem, by using the Augmented Lagrangian method. To decrease the computation time of some of the performance calculation algorithms, some modifications are made. These are described in the related sections. The derivatives for the optimization process are numerically calculated. The accuracy of the performance calculation is once again verified against test results at this stage. The optimization software is then used to optimize the design of an SR motor for a washing machine application. The results obtained are discussed.

A modular structural design methodology for composite blades is developed. This design method can be used to design composite rotor blades with sophisticate geometric cross-sections. This design method hierarchically decomposed the highly-coupled interdisciplinary rotor analysis into global and local levels. In the global level, aeroelastic response analysis and rotor trim are conduced based on multi-body dynamic models. In the local level, variational asymptotic beam sectional analysis methods are used for the equivalent one-dimensional beam properties. Compared with traditional design methodology, the proposed method is more efficient and accurate. Then, the proposed method is used to study three different design problems that have not been investigated before. The first is to add manufacturing constraints into design optimization. The introduction of manufacturing constraints complicates the optimization process. However, the design with manufacturing constraints benefits the manufacturing process and reduces the risk of violating major performance constraints. Next, a new design procedure for structural design against fatigue failure is proposed. This procedure combines the fatigue analysis with the optimization process. The durability or fatigue analysis employs a strength-based model. The design is subject to stiffness, frequency, and durability constraints. Finally, the manufacturing uncertainty impacts on rotor blade aeroelastic behavior are investigated, and a probabilistic design method is proposed to control the impacts of uncertainty on blade structural performance. The uncertainty factors include dimensions, shapes, material properties, and service loads.

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Fotis Papoulias, Roman B. Statnikov. Includes bibliographical references (p. 241). Also available online.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Choi, Seung-Kyum; Committee Member: Allen, Janet K.; Committee Member: Paredis, Chris. Part of the SMARTech Electronic Thesis and Dissertation Collection.

L'optimisation multidisciplinaire (MDO) à base de gradients est efficace et très utilisée pour le dimensionnement structural d'ailes flexibles. Cependant, dans le contexte de simulations numériques haute-fidélité, le calcul efficace des gradients reste un défi majeur. L'objectif de ce travail est d'étudier les approches les mieux adaptées aux spécificités du calcul de sensibilité des efforts aéroélastiques par rapport à des paramètres structuraux.Deux techniques de calcul de gradient haute-fidélité adaptées aux systèmes aéroélastiques fortement couplés sont proposées. La technique la plus intrusive repose sur les formulations directe et adjointe qui nécessitent un effort d'implémentation logicielle substantiel. Alternativement, nous proposons une approche découplée et non-intrusive, moins lourde à implémenter et cependant capable de fournir une approximation précise des gradients. Ces deux techniques ont été intégrées dans le logiciel CFD elsA de l'Onera.La précision, l'efficience et l'applicabilité de ces méthodes sont démontrées sur le cas-test avion de transport civil Common Research Model (CRM). Nous résolvons un problème inverse dont l'objectif est de retrouver, en conditions de vol de croisière, une loi cible de vrillage voilure. Ces deux méthodes s'avèrent comparables en matière de précision et de coût. Elles offrent ainsi une souplesse supplémentaire de mise en œuvre en fonction du niveau d'intégration recherché dans le processus MDO. / To improve the structural design of flexible wings, gradient based Multidisciplinary Design Optimization (MDO) techniques are effective and widely used. However, gradients calculation is not trivial and can be costly when high-fidelity models are considered. Our objective is to study different suitable approaches to compute gradients of aeroelastic loads with respect to structural design parameters.To this end, two high-fidelity aero-structure gradient computation techniques for strongly coupled aeroelastic systems are proposed. The most intrusive technique includes the well-established direct and adjoint formulations that require substantial implementation effort. In contrast, we propose an alternative uncoupled non-intrusive approach easier to implement and yet capable of providing accurate gradients approximations. Both techniques have been implemented in the Onera elsA CFD software.Accuracy, efficiency and applicability of these methods are demonstrated on the civil transport aircraft Common Research Model (CRM) test-case. More specifically, an inverse design problem is set up with the objective of matching an in-flight target twist law distribution. These two methods prove to be comparable in terms of accuracy and cost. Thus they offer additional operational flexibility depending on the level of integration sought in the MDO process.

abstract: This dissertation is to address product design optimization including reliability-based design optimization (RBDO) and robust design with epistemic uncertainty. It is divided into four major components as outlined below. Firstly, a comprehensive study of uncertainties is performed, in which sources of uncertainty are listed, categorized and the impacts are discussed. Epistemic uncertainty is of interest, which is due to lack of knowledge and can be reduced by taking more observations. In particular, the strategies to address epistemic uncertainties due to implicit constraint function are discussed. Secondly, a sequential sampling strategy to improve RBDO under implicit constraint function is developed. In modern engineering design, an RBDO task is often performed by a computer simulation program, which can be treated as a black box, as its analytical function is implicit. An efficient sampling strategy on learning the probabilistic constraint function under the design optimization framework is presented. The method is a sequential experimentation around the approximate most probable point (MPP) at each step of optimization process. It is compared with the methods of MPP-based sampling, lifted surrogate function, and non-sequential random sampling. Thirdly, a particle splitting-based reliability analysis approach is developed in design optimization. In reliability analysis, traditional simulation methods such as Monte Carlo simulation may provide accurate results, but are often accompanied with high computational cost. To increase the efficiency, particle splitting is integrated into RBDO. It is an improvement of subset simulation with multiple particles to enhance the diversity and stability of simulation samples. This method is further extended to address problems with multiple probabilistic constraints and compared with the MPP-based methods. Finally, a reliability-based robust design optimization (RBRDO) framework is provided to integrate the consideration of design reliability and design robustness simultaneously. The quality loss objective in robust design, considered together with the production cost in RBDO, are used formulate a multi-objective optimization problem. With the epistemic uncertainty from implicit performance function, the sequential sampling strategy is extended to RBRDO, and a combined metamodel is proposed to tackle both controllable variables and uncontrollable variables. The solution is a Pareto frontier, compared with a single optimal solution in RBDO. / Dissertation/Thesis / Ph.D. Industrial Engineering 2012

No description available.

En écotoxicologie, les effets des substances toxiques sur les organismes vivants sont classiquement mesurés au niveau individuel, en laboratoire et selon des normes, ce qui assure la reproductibilité des bioessais et le contrôle des facteurs environnementaux. Ces tests standardisés, en toxicité aiguë ou chronique, portent généralement sur la survie, la reproduction et la croissance d'organismes modèles de laboratoire ; leur analyse statistique conduit à l'estimation de concentrations critiques d'effet. Ce sont ces concentrations qui sont utilisées en analyse quantitative du risque en écotoxicologie. Cependant, pour l'estimation d'un même type de concentration critique d'effet, différentes méthodes/modèles peuvent être utilisés qui sont plus ou moins adaptés en fonction du type de jeux de données. Le premier objectif de ce travail de thèse est donc de sélectionner les méthodes/modèles les plus adaptés afin d'améliorer l'analyse des données issus des tests de toxicité et donc l'estimation des concentrations critiques d'effet. Habituellement, les jeux de données sont construits à partir de tests standards en fonction de l'organisme étudié : la durée du test est généralement fixée et des recommandations sont faites, par exemple sur le nombre minimal d'organismes à exposer à un nombre minimal de concentrations. Il est donc légitime de penser que ces recommandations ne sont pas forcément les plus adaptées pour toutes les concentrations critiques d'effet et les méthodes/modèles les plus adaptés. C'est pourquoi, le deuxième objectif de cette thèse est d'optimiser les plans d'expérience afin d'aller soit vers une amélioration des estimations des concentrations critiques d'effet à coût constant soit pour un même niveau de qualité des estimations, d'éviter le gaspillage en temps et en organismes / In ecotoxicology, the effects of toxic compounds on living organisms are usually measured at the individual level, in the laboratory and according to standards. This ensures the reproducibility of bioassays and the control of environmental factors. Bioassays, in acute or chronic toxicity, generally apply to survival, reproduction and growth of organisms. The statistical analysis of standardized bioassays classically leads to the estimation of critical effect concentrations used in risk assessment. Nevertheless, several methods/models are used to determine a critical effect concentration. These methods/models are more and less adapted to the data type. The first aim of this work is to select the most adapted methods/models to improve data analysis and so the critical effect concentration estimation. Usually, data sets are built from standard bioassays and so follow recommendations about exposure duration, number and range of tested concentrations and number of individuals per concentration. We can think that these recommendations are not the most adapted for each critical effect concentration and each method/model. That’s why, the second aim of this work is to optimize the experimental design in order to improve the critical effect concentration estimations for a fixed cost or at least to reduce the waste of time and organisms

La conception des systèmes embarqués est une tâche complexe. Les ingénieurs sont confrontés à divers contraintes liées à la technologie, au coût,à la complexité et aux contraintes de sécurité. Toutes ces contraintes ont un grand impact sur l’architecture du système et par conséquence sur le coût final. Nous proposons dans cette thèse une approche pour la conception des système et l’optimisation de l’architecture guidée par les contraintes de sécurité et de coût. Elle s’agit d’une approche de synthèse de l’architecture qui prend en compte les contraintes de sécurité dans le contexte du standard ISO 26262. Elle permet, d’une part, d’atteindre une architecture préliminaire du système en choisissant les éléments de l’architecture permettant de réduire le coût global. D’autre part, elle conduit à une allocation des fonctions aux éléments de l’architecture qui respecte les contraintes liées aux niveaux de sécurité et les défaillances de ces éléments. Nous utilisons des algorithmes exhaustive et génétique pour l’exploration de l’espace de conception. En l’appliquant sur un cas d’étude industriel, nous démontrons sa contribution pour parvenir à la conception conforme et sa capacité à réduire les coûts entraîne par les contraintes de sécurité / The embedded system design is a challenging task. The engineers are faced with technological, cost, complexity and safety constraints. These constraints have a big impact on the system architecture and consequently on the final cost. we propose in this thesis an approach for system design and architecture optimization driven by safety and cost constraints. It consists of an architecture synthesis approach that takes into account the safety constraints in the ISO 26262 context. It allows, at one hand, to reach a system preliminary architecture by choosing the architecture elements that reduce the overall cost. On the other hand, it leads to a functions mapping that respects the safety constraints related to the integrity levels and to the dependent failures. We use exhaustive and genetic algorithm for the design space exploration. By applying it on an industrial study-case we demonstrate its contribution in reaching compliant design and its capability in reducing the safety constraints costs.