Industrial and military vehicles, including trucks, tanks and others, employ cooling systems that address passenger cooling and auxiliary cooling loads ranging from a few Watts to 50 kW or more. Such systems are typically powered using vapor-compression cooling systems that either directly supply cold air to the various locations, or cool an intermediate single-phase coolant closed loop, which in turn serves as the coolant for the passenger cabins and auxiliary loads such as electronics modules. Efforts are underway to enhance the performance of such systems, and also to develop more light weight and compact systems that would remove high heat fluxes. The distributed cooling configuration offers the advantage of a smaller refrigerant system package. The heat transfer between the intermediate fluid and air or with the auxiliary heat loads can be fine tuned through the control of flow rates and component sizes and controls to maintain tight tolerances on the cooling performance. Because of the additional loop involved in such a configuration, there is a temperature penalty between the refrigerant and the ultimate heat sink or source, but in some configurations, this may be counteracted through judicious design of the phase change-to-liquid coupled heat exchangers. Such heat exchangers are inherently smaller due to the high heat transfer coefficients in phase change and single-phase liquid flow compared to air flow. The additional loop also requires a pump to circulate the fluid, which adds pumping power requirements. However, a direct refrigerant-to-heat load coupling system might in fact be suboptimal if the heat loads are distributed across large distances. This is because of the significantly higher pressure drops (and saturation temperature drops) incurred in transporting vapor or two-phase fluids through refrigerant lines across long plumbing elements. An optimal system can be developed for any candidate application by assessing the tradeoffs in cooling capacity, heat exchanger sizes and configurations, and compression, pumping and fan power. In this study, a versatile simulation platform for a wide variety of direct and indirectly coupled cooling systems was developed to enable comparison of different component geometries and system configurations based on operating requirements and applicable design constraints. Components are modeled at increasing levels of complexity ranging from specified closest approach temperatures for key components to models based on detailed heat transfer and pressure drop models. These components of varying complexity can be incorporated into the system model as desired and trade-off analyses on system configurations performed. Employing this platform as a screening, comparison, and optimization tool, a number of conventional vapor-compression and distributed cooling systems were analyzed to determine the efficacy of the distributed cooling scheme in mobile cooling applications. Four systems serving approximately a 6 kW cooling duty, two with air-coupled evaporators and two with liquid-coupled evaporators, were analyzed for ambient conditions of 37.78°C and 40% relative humidity. Though the condensers and evaporators are smaller in liquid-coupled systems, the total mass of the heat exchangers in the liquid-coupled systems is larger due to the additional air-to-liquid heat exchangers that the configuration requires. Additionally, for the cooling applications considered, the additional compressor power necessitated by the liquid-coupled configuration and the additional power consumed by the liquid-loop pumps result in the coefficient of performance being lower for liquid-coupled systems than for air-coupled systems. However, the use of liquid-coupling in a system does meet the primary goal of decreasing the system refrigerant inventory by enabling the use of smaller condensers and evaporators and by eliminating long refrigerant carrying hoses.

The expected growth of civil aviation over the next twenty years places significant emphasis on revolutionary technology development aimed at mitigating the environmental impact of commercial aircraft. As the number of technology alternatives grows along with model complexity, current methods for Pareto finding and multiobjective optimization quickly become computationally infeasible. Coupled with the large uncertainty in the early stages of design, optimal designs are sought while avoiding the computational burden of excessive function calls when a single design change or technology assumption could alter the results. This motivates the need for a robust and efficient evaluation methodology for quantitative assessment of competing concepts. This research presents a novel approach that combines Bayesian adaptive sampling with surrogate-based optimization to efficiently place designs near Pareto frontier intersections of competing concepts. Efficiency is increased over sequential multiobjective optimization by focusing computational resources specifically on the location in the design space where optimality shifts between concepts. At the intersection of Pareto frontiers, the selection decisions are most sensitive to preferences place on the objectives, and small perturbations can lead to vastly different final designs. These concepts are incorporated into an evaluation methodology that ultimately reduces the number of failed cases, infeasible designs, and Pareto dominated solutions across all concepts. A set of algebraic samples along with a truss design problem are presented as canonical examples for the proposed approach. The methodology is applied to the design of ultra-high bypass ratio turbofans to guide NASA's technology development efforts for future aircraft. Geared-drive and variable geometry bypass nozzle concepts are explored as enablers for increased bypass ratio and potential alternatives over traditional configurations. The method is shown to improve sampling efficiency and provide clusters of feasible designs that motivate a shift towards revolutionary technologies that reduce fuel burn, emissions, and noise on future aircraft.

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.

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).

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.

This thesis presents the work of two significant projects. In the first project, a suite of benchmark problems for grid energy management are presented which demonstrate several issues characteristic to the dynamic optimization of these systems. These benchmark problems include load following, cogeneration, tri-generation, and energy storage, and each one assumes perfect foresight of the entire time horizon. The Gekko Python package for dynamic optimization is introduced and two different solution methods are discussed and applied to solving these benchmarks. The simultaneous solve mode out-performs the sequential solve mode in each benchmark problem across a wide range of time horizons with increasing resolution, demonstrating the ability of the simultaneous mode to handle many degrees of freedom across a range of problems of increasing difficulty. In the second project, combined optimization of propulsion system design, flight trajectory planning and battery mass optimization is applied to solar-regenerative high-altitude long-endurance (SR-HALE) aircraft through a sequential iterative approach. This combined optimization approach yields an increase of 20.2% in the end-of-day energy available on the winter solstice at 35°N latitude, resulting in an increase in flight time of 2.36 hours. The optimized flight path is obtained by using nonlinear model predictive control to solve flight and energy system dynamics over a 24 hour period with a 15 second time resolution. The optimization objective is to maximize the total energy in the system while flying a station-keeping mission, staying within a 3 km radius and above 60,000 ft. The propulsion system design optimization minimizes the total energy required to fly the optimal path. It uses a combination of blade element momentum theory, blade composite structures, empirical motor and motor controller mass data, as well as a first order motor performance model. The battery optimization seeks to optimally size the battery for a circular orbit. Fixed point iteration between these optimization frameworks yields a flight path and propulsion system that slightly decreases solar capture, but significantly decreases power expended. Fully coupling the trajectory and design optimizations with this level of accuracy is infeasible with current computing resources. These efforts show the benefits of combining design and trajectory optimization to enable the feasibility of SR-HALE flight.

Using MIL-HDBK-419A, MATLAB and Nomographs, Shielding Effectiveness for the Magnetic Field, Electric Field, and Plane Wave were calculated over a frequency range from 10 Hz to 1 GHz. The three shielding tapes used included superalloy, aluminum, and mumetal. Calculations for Shielding Effectiveness involve the computation of Absorption Loss, Reflection Loss, and Re-Reflection Correction Factor. From the outcome of the calculations, it was suitable to conclude that all three metals fulfill the 40 dB Shielding Effectiveness requirements for SGEMP fields for frequencies greater or equal to 1 MHz. Accordingly, all three shielding tapes provide at least 40 dB of shielding to protect certain frequencies against SGEMP Magnetic Field. However, results vary for frequencies below 1 MHz.

New Horizons, Voyager 1 & 2, and Pioneer 10 & 11 are the only spacecraft to ever venture past Pluto and provide information about space at those large distances. These spacecraft were very expensive and primarily designed to study planets during gravitational assist maneuvers. They were not designed to explore space past Pluto and their study of this environment is at best a secondary mission. These spacecraft rely on radioisotope thermoelectric generators (RTGs) to provide power, an expensive yet necessary approach to generating sufficient power. With Cubesats graduating to interplanetary capabilities, such as the Mars-bound MarCO spacecraft, matching the modest payload requirements to study the outer Solar System (OSS) with the capabilities of low-power nano-satellites may enable much more affordable access to deep space. This paper explores a design concept for a low-cost, small spacecraft, designed to study the OSS and satisfy mission requirements with solar power. The general spacecraft design incorporates a parabolic reflector that acts as both a solar concentrator and a high gain antenna. This paper explores a working design concept for a small spacecraft to operate up to 100 astronomical units (AU) from the sun. Deployable reflector designs, thermal and radiation environments, communications and power requirements, solar system escape trajectory options, and scientific payload requirements are detailed, and a working system is proposed that can fulfill mission requirements with expected near-future innovations in a few key technologies.