A Bayesian adaptive sampling method is developed for highly coupled multidisciplinary design problems. The method addresses a major challenge in aerospace design: exploration of a design space with computationally expensive analysis tools such as computational fluid dynamics (CFD) or finite element analysis. With a limited analysis budget, it is often impossible to optimize directly or to explore a design space with off-line design of experiments (DoE) and surrogate models. This difficulty is magnified in multidisciplinary problems with feedbacks between disciplines because each design point may require iterative analyses to converge on a compatible solution between different disciplines. Bayesian Collaborative Sampling (BCS) is a bi-level architecture for adaptive sampling that simulataneously - concentrates disciplinary analyses in regions of a design space that are favorable to a system-level objective - guides analyses to regions where interdisciplinary coupling variables are probably compatible BCS uses Bayesian models and sequential sampling techniques along with elements of the collaborative optimization (CO) architecture for multidisciplinary optimization. The method is tested with the aero-structural design of a glider wing and the aero-propulsion design of a turbojet engine nacelle.

Thesis (M.S.)--Mississippi State University. Department of Mechanical Engineering. / Title from title screen. Includes bibliographical references.

A general multidisciplinary design problem features coupling and feedback between contributing analyses. This feedback may lead to convergence issues requiring significant iteration in order to obtain a feasible design. This work casts the multidisciplinary design problem as a dynamical system in order to leverage the benefits of dynamical systems theory in a new domain. Three areas from dynamical system theory are chosen for investigation: stability analysis, optimal control, and estimation theory. Stability analysis is used to investigate the existence of a solution to the design problem and how that solution can be found. Optimal control techniques allow consideration of contributing analysis output and design variables constraints at the same level of the optimization hierarchy. Finally, estimation methods are employed to rapidly evaluate the robustness of the multidisciplinary design. These three dynamical system techniques are then combined in a methodology for the rapid robust design of linear multidisciplinary systems. While inherently linear, the developed robust design methodology is shown to be extensible to nonlinear systems. The applicability and performance of the developed technique is demonstrated through linear and nonlinear test problems including the design of a hypersonic aerodynamic surface for a system in which an increase in range or improvement in landed accuracy is sought. In addition, it is shown that the developed robust design methodology scales well compared to other methods.

La variété des concepts d'aéronef à voilure tournante n'a d'égal que l'étendue de leur hamp applicatif. Dès lors, se pose une question essentielle : quel concept est le plus adapté face à un certain nombre de missions ou de spécifications ? Une partie essentielle de la réponse réside dans l'étude des performances de vol et des impacts environnementaux de l'appareil. Le projet de recherche fédérateur C.R.E.A.T.I.O.N. pour " Concepts of Rotorcraft Enhanced Assessment Through Integrated Optimization Network " a pour but de mettre en place une plateforme numérique de calculs multidisciplinaires et multiniveaux capables d'évaluer de tels critères. La multidisciplinarité fait écho aux différentes disciplines associées à l'évaluation des giravions tandis que l'aspect multi-niveaux reflète la possibilité d'étudier un concept quelque soit l'état des connaissances sur ce dernier. La thèse s'inscrit dans ce projet. Une première implication est le développement de modèles de performances de vol et leur intégration dans des boucles de calcul multidisciplinaires. Au-delà de cet aspect de modélisation physique, la multidisciplinarité touche aussi le champ des mathématiques appliquées. Les méthodes d'optimisation multi objectifs multi paramètres, l'aide à la décision pour la sélection d'un optimum de meilleur compromis, l'exploration de bases de données, la création de modèles réduits sont autant de thématiques explorées dans cette thèse.

Mechatronic systems encompass a wide range of disciplines, including mechanical and electrical engineering, and hence the development process for mechatronic system is collaborative in nature. Currently the collaborative development of mechatronic systems is inefficient and error-prone because contemporary design environments do not allow sufficient information flow of design and manufacturing data across different engineering domains. Mechatronic systems need to be designed in an integrated fashion allowing designers from multiple engineering domains to receive updates regarding design modifications throughout the design process. One approach to facilitate integrated design of mechatronic systems is to integrate mechanical with electrical engineering CAD systems. Currently there exist numerous techniques that were developed to support various levels of integration between CAD/CAE systems. Standardized data exchange formats, e.g., STEP and IGES, support information exchange between various different CAD and PDM systems. Multi-Representation Architecture (Peak et al.) supports the integration of geometric information in CAD tools with analysis information in CAE tools. Other integration techniques include the Core Product Model (developed at NIST), Active Semantic Networks (Roller et al.), Constraint Linking Bridge (Kleiner et al.), and others. All these techniques have their areas of focus as well as research gaps that need to be covered. One area that needs research attention is the information exchange between mechanical and electrical domains, which is the focus of this thesis. In this thesis, the information exchange between mechanical and electrical domains is explored from two perspectives: conceptual design perspective, in which constraint relationship between attributes of mechanical and electrical components is identified and classified based on the physical forms, functions, and behavior of the mechatronic system; system realization perspective, in which the identified constraints are modeled for propagation between MCAD and ECAD systems. SysML is used to model the constraints between mechanical and electrical components. By means of an illustrative example (a robot arm), the constraint modeling and propagation developed in my thesis are demonstrated and implemented utilizing a MCAD system (SolidWorks) and an ECAD system (EPLAN Electric P8).

Die rechnergestützte Topologieoptimierung wird zur Gestaltoptimierung, also im Wesentlichen zur Gewichtsreduktion von Bauteilen oder komplexeren Strukturen eingesetzt. Da die Funktionalität im Rahmen von FEM-Programmen zur Verfügung gestellt wird, erfordert sie umfangreiche Kenntnisse zur Bedienung der Software und der festigkeitstechnischen Grundlagen und wird daher überwiegend von Berechnungsexperten im rein technischen Kontext im Maschinenbau oder Luft- und Raumfahrzeugbau angewendet. Allerdings zeigen vereinzelte Arbeiten wie die Sitzmöbel »Bone Furniture«, die aus einer Zusammenarbeit des Studios »Joris Laarman Lab« mit Opel resultieren (Laarman 2006, Abbildung 1), dass derartige Methoden für das Design interessant sein können. [... aus der Einleitung]

abstract: This study focuses on implementing probabilistic nature of material properties (Kevlar® 49) to the existing deterministic finite element analysis (FEA) of fabric based engine containment system through Monte Carlo simulations (MCS) and implementation of probabilistic analysis in engineering designs through Reliability Based Design Optimization (RBDO). First, the emphasis is on experimental data analysis focusing on probabilistic distribution models which characterize the randomness associated with the experimental data. The material properties of Kevlar® 49 are modeled using experimental data analysis and implemented along with an existing spiral modeling scheme (SMS) and user defined constitutive model (UMAT) for fabric based engine containment simulations in LS-DYNA. MCS of the model are performed to observe the failure pattern and exit velocities of the models. Then the solutions are compared with NASA experimental tests and deterministic results. MCS with probabilistic material data give a good prospective on results rather than a single deterministic simulation results. The next part of research is to implement the probabilistic material properties in engineering designs. The main aim of structural design is to obtain optimal solutions. In any case, in a deterministic optimization problem even though the structures are cost effective, it becomes highly unreliable if the uncertainty that may be associated with the system (material properties, loading etc.) is not represented or considered in the solution process. Reliable and optimal solution can be obtained by performing reliability optimization along with the deterministic optimization, which is RBDO. In RBDO problem formulation, in addition to structural performance constraints, reliability constraints are also considered. This part of research starts with introduction to reliability analysis such as first order reliability analysis, second order reliability analysis followed by simulation technique that are performed to obtain probability of failure and reliability of structures. Next, decoupled RBDO procedure is proposed with a new reliability analysis formulation with sensitivity analysis, which is performed to remove the highly reliable constraints in the RBDO, thereby reducing the computational time and function evaluations. Followed by implementation of the reliability analysis concepts and RBDO in finite element 2D truss problems and a planar beam problem are presented and discussed. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2012

O mercado de tintas e vernizes é um dos maiores demandantes de solventes. Nos últimos anos, a reformulação de sistemas solventes tem ganhado forca, e três são as razões principais para isso: redução de custo, mantendo o desempenho; melhoria do desempenho; e busca por solventes menos agressivos ao homem e a natureza, quer seja voluntariamente ou por imposição de legislação. Dentre as varias propriedades necessárias de um solvente para formulação de tintas e vernizes, a taxa de evaporação e os parâmetros de solubilidade de Hansen são os mais importantes. Em sua grande maioria, os ajustes e substituições de formulação de solventes são realizados pelo método da tentativa e erro, que é caro e demorado. A teoria e modelos sobre os parâmetros de solubilidade já são bastante conhecidos, mas pouco foi explorado sobre modelos para prever a taxa de evaporação de solventes e misturas com base no método do evaporômetro determinado pela ASTM D3539. O objetivo deste trabalho é avaliar os modelos disponíveis em literatura para cálculo da taxa de evaporação de solventes e suas misturas, e por fim, com base em conceitos de otimização e projeto de mistura auxiliado por computador (Computer-Aided Mixture/Blend Design), propor uma metodologia para obter misturas de custo otimizado que satisfaçam as restrições de evaporação e solubilidade. Devido às equações das restrições dos modelos das propriedades, este problema de otimização é classificado como programação não-linear (NLP Non-Linear Programming). Embora os modelos de taxa de evaporação dos solventes e das misturas não apresentem resultados consistentes para todo e qualquer caso, devido a desvios muitas vezes causados pelos solventes de rápida evaporação, estes modelos associados à teoria de solubilidade de Hansen se tornam uma ferramenta de grande importância na formulação de sistemas solventes. Os resultados observados com esta metodologia têm grande concordância com os resultados obtidos experimentalmente. / Paint and coatings are one of the most solvent demanding markets. In recent years, reformulation of solvent systems has gained strength, and there are three main reasons: cost reduction maintaining performance, performance improvement, and the search for less aggressive solvents to human and environment, voluntarily or by legislation. Among several properties required for these solvents, evaporation rate and Hansen solubility parameters are the most important ones. Most adjustments and replacements of solvents in formulation are performed by trial and error methods, which are expensive and time consuming. The solubility parameters theory and models are already well known but little was explored about models to predict solvents and mixtures evaporation rate based on the evaporometer method determined by ASTM D3539. The object of this study is to evaluate the available models for calculating the evaporation rate of solvents and their mixtures, and then, based on optimization concepts and computer-aided Mixture/Blend Design, to propose a methodology to obtain cost-optimized mixtures that meet evaporation and solubility constraints. Due to the equations restrictions of properties models, this optimization problem is classified as NLP - Non-Linear Programming. Although evaporation rate models of solvents and mixtures do not show consistent results for every case most deviations were caused by fast evaporation solvents -, these models associated with the Hansen solubility theory become an important tool in the solvent systems formulation. The results observed with this method have good agreement with experimental results.

Práce je zaměřena na sestavení numerického modelu akumulace tepelné energie s fázovou přeměnou. Následně je tento model použit při tvarové optimalizaci, jejíž cílem je maximalizace uloženého tepla v tepelném výměníku. Kvůli komplexitě objektové funkce byl zvolen genetický algoritmus pro řešní úloh tvarové optimalizace. Práce obsahuje analýzu dvou problému týkající se tvarové optimalizace s následnou diskuzí nad obdrženými výsledky. Celý problém byl implementován v softwaru Matlab.

The concept of human-powered vertical flight was studied in great depth. Through the manipulation of preexisting theory and analytical methods, a collection of design tools was created to expediently conceptualize and then analyze virtually any rotor. The tools were then arranged as part of a complete helicopter rotor design process. The lessons learned as a result of studying this process—and the tools of which it consists—are presented in the following discussion. It is the belief of the author that by utilizing these tools, as well as the suggestions that accompany them, future engineers may someday build a human-powered helicopter capable of winning the Sikorsky Prize.