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Daniel Guggenheim School of Aerospace Engineering
Daniel Guggenheim School of Aerospace Engineering
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ItemDetermination of flame characteristics in a low swirl burner at gas turbine conditions through reaction zone imaging(Georgia Institute of Technology, 2012-08-27) Periagaram, Karthik BalasubramanianThis thesis explores the effects of operating parameters on the location and shape of lifted flames in a Low Swirl Burner (LSB). In addition, it details the development and analysis of a CH PLIF imaging system for visualizing flames in lean combustion systems. The LSB is studied at atmospheric pressure using LDV and CH PLIF. CH* chemiluminescence is used for high pressure flame imaging. A four-level model of the fluorescing CH system is developed to predict the signal intensity in hydrocarbon flames. Results from imaging an atmospheric pressure laminar flame are used to validate the behavior of the signal intensity as predicted by the model. The results show that the fluorescence signal is greatly reduced at high pressure due to the decreased number of CH molecules and the increased collisional quenching rate. This restricts the use of this technique to increasingly narrow equivalence ratio ranges at high pressures. The limitation is somewhat alleviated by increasing the preheat temperature of the reactant mixture. The signal levels from high hydrogen-content syngas mixtures doped with methane are found to be high enough to make CH PLIF a feasible diagnostic to study such flames. Finally, the model predicts that signal levels are unlikely to be significantly affected by the presence of strain in the flow field, as long as the flames are not close to extinction. The results from the LSB flame investigation reveal that combustor provides reasonably robust flame stabilization at low and moderate values of combustor pressure and reference velocities. However, at very high velocities and pressures, the balance between the reactant velocity and the turbulent flame speed shifts in favor of the former resulting in the flame moving downstream. The extent of this movement is small, but indicates a tendency towards blow off at higher pressures and velocities that may be encountered in real world gas turbine applications. There is an increased tendency of relatively fuel-rich flames to behave like attached flames at high pressure. These results raise interesting questions about turbulent combustion at high pressure as well as provide usable data to gas turbine combustor designers by highlighting potential problems.
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ItemValue-informed space systems design and acquisition(Georgia Institute of Technology, 2011-12-16) Brathwaite, Joy DanielleInvestments in space systems are substantial, indivisible, and irreversible, characteristics that make them high-risk, especially when coupled with an uncertain demand environment. Traditional approaches to system design and acquisition, derived from a performance- or cost-centric mindset, incorporate little information about the spacecraft in relation to its environment and its value to its stakeholders. These traditional approaches, while appropriate in stable environments, are ill-suited for the current, distinctly uncertain and rapidly changing technical, and economic conditions; as such, they have to be revisited and adapted to the present context. This thesis proposes that in uncertain environments, decision-making with respect to space system design and acquisition should be value-based, or at a minimum value-informed. This research advances the value-centric paradigm by providing the theoretical basis, foundational frameworks, and supporting analytical tools for value assessment of priced and unpriced space systems. For priced systems, stochastic models of the market environment and financial models of stakeholder preferences are developed and integrated with a spacecraft-sizing tool to assess the system's net present value. The analytical framework is applied to a case study of a communications satellite, with market, financial, and technical data obtained from the satellite operator, Intelsat. The case study investigates the implications of the value-centric versus the cost-centric design and acquisition choices. Results identify the ways in which value-optimal spacecraft design choices are contingent on both technical and market conditions, and that larger spacecraft for example, which reap economies of scale benefits, as reflected by their decreasing cost-per-transponder, are not always the best (most valuable) choices. Market conditions and technical constraints for which convergence occurs between design choices under a cost-centric and a value-centric approach are identified and discussed. In addition, an innovative approach for characterizing value uncertainty through partial moments, a technique used in finance, is adapted to an engineering context and applied to priced space systems. Partial moments disaggregate uncertainty into upside potential and downside risk, and as such, they provide the decision-maker with additional insights for value-uncertainty management in design and acquisition. For unpriced space systems, this research first posits that their value derives from, and can be assessed through, the value of information they provide. To this effect, a Bayesian framework is created to assess system value in which the system is viewed as an information provider and the stakeholder an information recipient. Information has value to stakeholders as it changes their rational beliefs enabling them to yield higher expected pay-offs. Based on this marginal increase in expected pay-offs, a new metric, Value-of-Design (VoD), is introduced to quantify the unpriced system's value. The Bayesian framework is applied to the case of an Earth Science satellite that provides hurricane information to oil rig operators using nested Monte Carlo modeling and simulation. Probability models of stakeholders' beliefs, and economic models of pay-offs are developed and integrated with a spacecraft payload generation tool. The case study investigates the information value generated by each payload, with results pointing to clusters of payload instruments that yielded higher information value, and minimum information thresholds below which it is difficult to justify the acquisition of the system. In addition, an analytical decision tool, probabilistic Pareto fronts, is developed in the Cost-VoD trade space to provide the decision-maker with additional insights into the coupling of a system's probable value generation and its associated cost risk.
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ItemA conceptual methodology for the prediction of engine emissions(Georgia Institute of Technology, 2010-11-15) Rezvani, RezaCurrent emission prediction models in the conceptual design phase are based on historical data and empirical correlations. Two main reasons contributing to the current state of emission models are complexity of the phenomena involved in the combustor and relatively low priority of having a more detailed emissions model at the conceptual design phase. However, global environmental concerns and aviation industry growth highlight the importance of improving the current emissions prediction approaches. There is a need to have an emission prediction model in the conceptual design phase to reduce the prediction uncertainties and perform parametric studies for different combustor types and operating conditions. The research objective of this thesis is to develop a methodology to have an initial estimate of gas turbines' emissions, capture their trends and bring more information forward to the conceptual design phase regarding the emission levels. This methodology is based on initial sizing of the combustor and determining its flow-fractions at each section using a 1D flow analysis. A network of elementary chemical reactors is considered and its elements are sized from the results of the 1D flow analysis to determine the level of emissions at the design and operating conditions. Additional phenomena that have significant effects on the prediction of emissions are also considered which are: 1) droplet evaporation and diffusion burning, and 2) fuel-air mixture non-uniformity. A simplified transient model is developed to determine the evaporation rate for a given droplet size distribution and to obtain the amount of vaporized fuel before they ignite. A probabilistic unmixedness model is also employed to consider the range of equivalence ratio distribution for the fraction of the fuel that is vaporized and mixed with air. An emission model is created for the single annular combustor (SAC) configuration and applied to two combustors to test the prediction and parametric capabilities of the model. Both uncertainty and sensitivity analyses are performed to assess the capability of the model to reduce the prediction uncertainty of the model compared to the simpler models without considering the droplet evaporation and mixture non-uniformity. The versatility of the model is tested by creating an emission model for a Rich-Quench-Lean (RQL) combustor, and the results are compared to limited actual data. In general, the approach shows a good performance predicting the NOx emission level compared to CO emission level and capturing their trends. Especially in the RQL combustor case, a more detailed model is required to improve the prediction of the CO emission level.
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ItemEfficient ranging-sensor navigation methods for indoor aircraft(Georgia Institute of Technology, 2010-07-09) Sobers, David Michael, Jr.Unmanned Aerial Vehicles are often used for reconnaissance, search and rescue, damage assessment, exploration, and other tasks that are dangerous or prohibitively difficult for humans to perform. Often, these tasks include traversing indoor environments where radio links are unreliable, hindering the use of remote pilot links or ground-based control, and effectively eliminating Global Positioning System (GPS) signals as a potential localization method. As a result, any vehicle capable of indoor flight must be able to stabilize itself and perform all guidance, navigation, and control tasks without dependence on a radio link, which may be available only intermittently. Since the availability of GPS signals in unknown environments is not assured, other sensors must be used to provide position information relative to the environment. This research covers a description of different ranging sensors and methods for incorporating them into the overall guidance, navigation, and control system of a flying vehicle. Various sensors are analyzed to determine their performance characteristics and suitability for indoor navigation, including sonar, infrared range sensors, and a scanning laser rangefinder. Each type of range sensor tested has its own unique characteristics and contributes in a slightly different way to effectively eliminate the dependence on GPS. The use of low-cost range sensors on an inexpensive passively stabilized coaxial helicopter for drift-tolerant indoor navigation is demonstrated through simulation and flight test. In addition, a higher fidelity scanning laser rangefinder is simulated with an Inertial Measurement Unit (IMU) onboard a quadrotor helicopter to enable active stabilization and position control. Two different navigation algorithms that utilize a scanning laser and techniques borrowed from Simultaneous Localization and Mapping (SLAM) are evaluated for use with an IMU-stabilized flying vehicle. Simulation and experimental results are presented for each of the navigation systems.
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ItemAdaptive and neuroadaptive control for nonnegative and compartmental dynamical systems(Georgia Institute of Technology, 2010-06-29) Volyanskyy, KostyantynNeural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we developed a new neuroadaptive control architecture for nonlinear uncertain dynamical systems as well as nonlinear nonnegative uncertain dynamical systems. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A subclass of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this research, we developed a direct adaptive and neuroadaptive control framework for stabilization, disturbance rejection and noise suppression for nonnegative and compartmental dynamical systems with exogenous system disturbances. Furthermore, we developed a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. Specifically, the proposed framework involves a new and novel controller architecture involving additional terms, or Q-modification terms, in the update laws that are constructed using a moving time window of the integrated system uncertainty. The Q-modification terms can be used to identify the ideal neural network system weights which can be used in the adaptive law. In addition, these terms effectively suppress system uncertainty. Finally, neuroadaptive output feedback control architecture for nonlinear nonnegative dynamical systems with input amplitude and integral constraints is developed. This architecture is used to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure- and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multi-compartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient's physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. The effect of spontaneous breathing is incorporated within the lung model and the control framework.