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Quantum Inspired Algorithms For Learning And Control Of Stochastic Systems, Karthikeyan Rajagopal
Quantum Inspired Algorithms For Learning And Control Of Stochastic Systems, Karthikeyan Rajagopal
Doctoral Dissertations
"Motivated by the limitations of the current reinforcement learning and optimal control techniques, this dissertation proposes quantum theory inspired algorithms for learning and control of both single-agent and multi-agent stochastic systems.
A common problem encountered in traditional reinforcement learning techniques is the exploration-exploitation trade-off. To address the above issue an action selection procedure inspired by a quantum search algorithm called Grover's iteration is developed. This procedure does not require an explicit design parameter to specify the relative frequency of explorative/exploitative actions.
The second part of this dissertation extends the powerful adaptive critic design methodology to solve finite horizon stochastic optimal …
Development Of Ionic Liquid Multi-Mode Spacecraft Micropropulsion Systems, Steven Paul Berg
Development Of Ionic Liquid Multi-Mode Spacecraft Micropropulsion Systems, Steven Paul Berg
Doctoral Dissertations
"This dissertation presents work on development of multi-mode specific spacecraft propulsion systems. Specifically, this work attempts to realize a single propellant capable of both chemical monopropellant and electric electrospray rocket propulsion, develop methods to characterize multi-mode propulsion system performance, and realize a system capable of both monopropellant and electrospray propulsion for a small spacecraft. Selection criteria for ionic liquid propellants capable of both monopropellant and electrospray propulsion are developed. These are based on desired physical properties and performance considering use in both propulsive modes. From these insights, a monopropellant mixture of 1-ethyl-3-methylimidazolium ethyl sulfate and hydroxylammonium nitrate is selected and …
Analysis Of Ion Emitting Jet Structures During Ionic Liquid Electrospraying, Shawn W. Miller
Analysis Of Ion Emitting Jet Structures During Ionic Liquid Electrospraying, Shawn W. Miller
Doctoral Dissertations
"The ionic liquid [Bmim][DCA] is a propellant candidate for a standalone electrospray thruster or a dual-mode propulsion system. Characterization of positive polarity ions produced by [Bmim][DCA] capillary emitters with a nominal extraction voltage of 2.0 kV within a quadrupole and time-of-flight mass spectrometers is presented along with the predictions of propulsion performance. Flow rates from 0.05 to 2.18 nL/s are used to investigate the impact variations in the flow parameter have on the electrospray plume. The retarding potential analysis reveals ions emitted from the capillary are formed below the emitter potential of 500 eV. Angular distributions indicate broadening of both …
Advancements In Uncertainty Quantification With Stochastic Expansions Applied To Supersonic And Hypersonic Flows, Thomas Kelsey West Iv
Advancements In Uncertainty Quantification With Stochastic Expansions Applied To Supersonic And Hypersonic Flows, Thomas Kelsey West Iv
Doctoral Dissertations
"The primary objective of this study was to develop improved methodologies for efficient and accurate uncertainty quantification with stochastic expansions and apply them to problems in supersonic and hypersonic flows. Methods introduced included approaches for efficient dimension reduction, sensitivity analysis, and sparse approximations. These methods and procedures were demonstrated on multiple stochastic models of hypersonic, planetary entry flows, which included high-fidelity, computational fluid dynamics models of radiative heating on the surface of hypersonic inflatable aerodynamic decelerators during Mars and Titan entry. For these stochastic problems, construction of an accurate surrogate model was achieved with as few as 10% of the …
Investigation Of Robust Optimization And Evidence Theory With Stochastic Expansions For Aerospace Applications Under Mixed Uncertainty, Harsheel R. Shah
Investigation Of Robust Optimization And Evidence Theory With Stochastic Expansions For Aerospace Applications Under Mixed Uncertainty, Harsheel R. Shah
Doctoral Dissertations
One of the primary objectives of this research is to develop a method to model and propagate mixed (aleatory and epistemic) uncertainty in aerospace simulations using DSTE. In order to avoid excessive computational cost associated with large scale applications and the evaluation of Dempster Shafer structures, stochastic expansions are implemented for efficient UQ. The mixed UQ with DSTE approach was demonstrated on an analytical example and high fidelity computational fluid dynamics (CFD) study of transonic flow over a RAE 2822 airfoil.
Another objective is to devise a DSTE based performance assessment framework through the use of quantification of margins and …
Pulsed Inductive Plasma Studies By Spectroscopy And Internal Probe Methods, Warner C. Meeks
Pulsed Inductive Plasma Studies By Spectroscopy And Internal Probe Methods, Warner C. Meeks
Doctoral Dissertations
The broad effort of the Missouri Plasmoid Experiment is to elucidate the energy conversion processes in a pulsed inductive discharge due to the presence of plasma. The test article is a 440 to 490 kHz theta-pinch (or solenoidal) geometry coil with a stored energy of around 80 joules. In this work experimental hydrogen, helium, argon and xenon data at back-fill pressures of 10 to 100 mTorr (1.3 to 133.3 Pa) are obtained and interpreted. Spectral and internal probe studies were performed on MPX Mk.I and Mk.II devices, respectively. IR spectra were acquired in the Mk.I device for argon and xenon. …
Optimization Based Control Design Techniques For Distributed Parameter Systems, Manoj Kumar
Optimization Based Control Design Techniques For Distributed Parameter Systems, Manoj Kumar
Doctoral Dissertations
"The study presents optimization based control design techniques for the systems that are governed by partial differential equations. A control technique is developed for systems that are actuated at the boundary. The principles of dynamic inversion and constrained optimization theory are used to formulate a feedback controller. This control technique is demonstrated for heat equations and thermal convection loops. This technique is extended to address a practical issue of parameter uncertainty in a class of systems. An estimator is defined for unknown parameters in the system. The Lyapunov stability theory is used to derive an update law of these parameters. …