<p> The research presented in this dissertation investigates the relationship between critical technologies and technology maturity assessments at a key decision point in the product development life cycle. This study utilizes statistical methods for assessing technology maturity at a key decision point. A regression model is established and utilized for predicting the probability of a system achieving technology maturity. The study disclosed with a 95% confidence that there is statistical evidence that utilization of heritage technology developments, as originally designed, significantly increases the probability of achieving technology maturity at a key decision point. This finding is significance due to the potential for engineers to overestimate technology maturity when utilizing heritage designs. One challenge facing systems engineers is quantifying the impact technology developments have on technology maturity assessments, especially when transitioning from formulation to implementation. Correctly assessing the maturity of a technology is crucial for an organization&rsquo;s ability to manage performance, cost, and schedule. The findings from this research has the potential to reduce unacceptable or unsatisfactory technical performance and programmatic overruns through the minimization of inaccurate maturity determinations.</p><p>

<p> Carbon sequestration is a promising solution to mitigate the accumulation of greenhouse gases. Depleted oil and gas reservoirs are desirable vessels for carbon sequestration. It is crucial to maintain the sealing ability of carbon sequestration fields with high concentrations of CO₂.</p><p> A systematic well integrity evaluation system has been developed and validated for carbon sequestration fields. The system constitutes 1) a newly developed analytical model for assessing cement sheath integrity under various operating conditions, 2) quantifications of well parameters contributing to the probability of well leakage, and 3) genetic-neural network algorithm for data analysis and well-leakage probability assessment.</p><p> A wellbore system consists of well casing, cement sheath, and formation rock. A new analytical stress model was developed. The new analytical model solves for the stresses in the casing-cement sheath formation system loaded by the isotropic and anisotropic horizontal in-situ stresses. Further analyses with the analytical model reveal that Young&rsquo;s modulus of cement sheath is a major factor that contributes to the sealing ability of the cement sheath, while Poisson&rsquo;s ratio and cohesion play less important roles in the cement sheath sealing ability. The cement sheath in the shale formation exhibits higher sealing ability than that in the sandstone formation. The sealing ability of weak cement is higher than that of strong cement.</p><p> Descriptive quantifications of well parameters were made in this study for analyzing their effect on the probability of well leakage. These parameters include well cement placement relative to aquifers and fluid reservoir zones, cement type, cement sheath integrity in operating conditions, well aging, and well plugging conditions. It is the combination of these parameters that controls the probability of well leakage. A significant proportion of wells were identified as risky wells in these two fields. It is concluded that the well trained neural network model can be used to predict the well leakage risk over the CO₂ sequestration lifespan, which can promote prevention activities and mitigations to the CO₂ leakage risky wells.</p>

<p>System of Systems Engineering (SoSE) is an emerging technical discipline that is increasingly referenced in industry, primarily due to the explosion of technology over recent decades. Its meteoric rise, however, has not been followed by a comprehensive study of what truly defines this new methodology. Despite its widespread use, SoSE still lacks a cohesive, agreed-upon definition or standard curriculum. </p><p> This thesis defines a common, cross-disciplinary framework for SoSE that can be further developed through collaboration between academics and technical professionals. After establishing key SoSE concepts and their roots in traditional SE, this thesis reviews a wide spectrum of present applications and opportunities for future use of SoSE principles in hopes of encouraging a more unified understanding and development of SoSE as a technical discipline. </p>

<p> The contributions of this dissertation increase the fidelity of conceptual hypersonic mission design through the following innovations: 1) the introduction of coupling between the effects of ablation of the thermal protection system (TPS) and flight dynamics, 2) the introduction of rigid body dynamics into trajectory design, and 3) simplifying the design of hypersonic missions that involve multiple phases of flight. These contributions are combined into a unified conceptual mission design framework, which is in turn applicable to slender hypersonic vehicles with ablative TPS. Such vehicles are employed in military applications, wherein speed and terminal energy are of critical importance. </p><p> The fundamental observation that results from these contributions is the substantial reduction in the maximum terminal energy that is achievable when compared to the state-of-the art conceptual design process. Additionally, the control history that is required to follow the maximum terminal energy trajectory is also significantly altered, which will in turn bear consequence on the design of the control actuators. </p><p> The other important accomplishment of this dissertation is the demonstration of the ability to solve these class of problems using indirect methods. Despite being built on a strong foundation of the calculus of variations, the state-of-the-art entirely neglects indirect methods because of the challenge associated with solving the resulting boundary value problem (BVP) in a system of differential-algebraic equations (DAEs). Instead, it employs direct methods, wherein the optimality of the calculated trajectory is not guaranteed. The ability to employ indirect methods to solve for optimal trajectories that are comprised of multiple phases of flight while also accounting for the effects of ablation of the TPS and rigid body dynamics is a substantial advancement in the state-of-the-art.</p><p>

<p> There&rsquo;s always a requirement for faster, more accurate, and easier to implement threat identification systems for concealed electronics, to thwart terrorism and espionage attempts. Common electronic devices are used in the design of improvised explosive devices (IEDs) that target military and civilian populations alike, while concealed recording devices illegally capture proprietary and confidential data, compromising both governmental and industrial information resources. This research proposes a unique nonintrusive, repeatable, reliable and scalable D&amp;I system for identifying threat devices by unintended radiated emissions (URE). Only a passive URE system, as opposed to active or hybrid systems, is appropriate for bomb detection or human interrogation, since potentially hazardous energy radiations are not emitted. Additionally, the proposed system is distinctive in its simplicity, allowing rapid implementation, and easy expandability. Finally, validation testing is provided to demonstrate the system&rsquo;s reliability and repeatability. </p><p> URE is the electromagnetic emissions that active electronic equipment, such as radios and cellphones radiate. URE is analogous to a human fingerprint, since on a microscopic level, each and every URE signature is unique. However same-type electronic devices put out similar radiations and electronics of the same model have almost identical radio frequency signatures. URE signatures can change with device settings, such as a channel on a radio, or Airplane versus Clock mode on a cell phone. This uniqueness of URE data per device setting enables URE to be used to determine the mode of an operational electronic device. The characteristics of URE enable it to be used for explosive ordinance detection (EOD) and applications such as quality control in manufacturing, electronics troubleshooting,device identification for inventory, and detection of prohibited hidden electronics. </p><p> The proposed D&amp;I process also addresses big data problems involved in capturing URE data and building a database of URE characteristics for identification. Issue interpretation is utilized with the URE data to distinguish between threat and non-threat electronic devices, using multiple criteria decision analysis (MCDA) and decision-making techniques to determine type, model and mode of the hidden devices. The outlined URE data handling methods and specified decision analysis techniques for URE data processing are further unique contributions of this research. </p><p> Optimization, verified by testing, is used to improve the speed and accuracy of the identification decision algorithm. The developed system is validated with URE data from 166 devices, which are representative of IED and espionage threats, but the system is extendable to all URE D&amp;I applications, such as Quality Assurance, Inventory, and smart applications. Due to the immaturity of the URE D&amp;I field and lack of documentation on the topic, the properties and potential of this more effective D&amp;I system, compared to current methods, will be of interest to explosive ordnance disposal, security service, electronic system manufacturing, automated inventory, and mobile application development communities and potentially others as well. </p><p>

<p> As humans strive to explore deeper into the solar system, the need for efficient, compact, and reliable life support systems for providing breathable air and drinkable water become critical to mission success. One element of providing breathable air is the removal of metabolic gaseous waste products, primarily consisting of carbon dioxide, from the cabin air. Recent work on human performance has suggested that carbon dioxide has effects on human performance at lower concentrations than previously anticipated and at concentrations lower than presently controlled to on the International Space Station. Such performance requirements represent a substantial challenge and provide the opportunity for an alternative solution to the zeolites presently in use. The present work examines the feasibility of using liquid a bsorbents to perform carbon dioxide absorption in enclosed microgravity environments.</p><p> The use of liquid absorbents for carbon dioxide removal (or capture) is well studied in literature. Chief among the absorbents studied is monoethanolamine, an organic base which reacts to neutralize carbon dioxide. The reactivity of bases with amines increases the mass transfer rate, a particularly desirable feature for systems requiring compact architectures. To improve the diffusivity of carbon dioxide and reaction products, amines are typically dissolved in water, which has a low viscosity and solubilizes amines well. However, as analyzed in this work, aqueous sorbents are unattractive in enclosed environments because the water will evaporate into the cabin. As an alternative, an off-the-shelf, non-aqueous mixture of aminoethylethyleneamine and triethylene glycol was developed which shows moderate viscosity characteristics with low-volatility components and full miscibility.</p><p> This work investigates for the first time the use of electrospray as a nanoscalegas -liquid contactor to improve the mass transfer while using a viscous liquid absorbent. Experimental investigation of this phenomenon concludes that electrospray shows a high overall mass transfer rate at all loadings than a stationary film. The proposed reason for the continued high mass transfer rate is the continuous refreshing of the gas-liquid interface with unreacted amine. Varying parameters for the concentrations of carbon dioxide and a mine, the liquid flow rate, and the driving electricfield show the data may be collapsed by an empirical dimensionless group which relates to the liquid pool at the bottom of the spray that represents a well-mixed interface. In addition, the influence of carbon dioxide reacting with the surface of the electrospray cone was studied experimentally with monoethanolamine, concluding that emitted current increases with carbon dioxide partial pressure due to production of ionic reaction products changing electrical conductivity. </p><p> Finally, the mass transfer of water vapor and carbon dioxide through a microporous polytetrafluoroethylene membrane into aqueous and non-aqueous aminoethylethanola mine solutions. Aqueous solutions show water vapor losses, consistent with expectations, which would impose a condensation risk to cabin environments.</p><p>

<p> Adaptation can have different objectives. Compared to a learning behavior, which is mainly to optimize the rewards/experience obtained through the learning process, adaptive control is a type of adaptation that follows a specific target guided by a controller. Although the targets may be different, the two types of adaption share common research interests.</p><p> One of the popular research techniques for studying adaptation is the use of multiple models, where the system will utilize information from multiple environment observers instead of one to improve the adaptation behavior in terms of stability, speed and accuracy. In this thesis, applications of multiple models for two types of adaptation, adaptive control and learning, will be investigated separately. For adaptive control, the research focuses on second-level adaptation, which is a new multiple-model-based approach; for learning, the multiple model concept is designed and embedded into a type of reinforcement scheme: learning automata.</p><p> The stability, robustness and performance of second-level adaptation will be first investigated in the context of various environments, including time-varying plants and noisy disturbances. Then, a new design of second-level adaptation for general systems and input-output accessible systems will be discussed. The reasons for the improved performance using second-level adaptation are analyzed theoretically. The second part of the thesis contributes to a new method of learning automata using multiple models. The method is first applied to a two-state (binary) reward environment in the simplest case, and it is later extended to the feed-forward case when multiple states or actions are presented. Finally, general reinforcement learning automata for network cases will be discussed. In all cases, simulation studies are given, wherever appropriate, to demonstrate the improvement in performance compared to conventional approaches.</p><p>

<p> Model-Based Systems Engineering and Logistics Engineering are emerging disciplines that offer a synergy for integrating the proactive modeling of prototype R&amp;D acquisition and industrial base sustainment support into a framework that characterizes the most influential phases of the Department of Defense ground vehicle and robotics equipment life cycle. This research enhances situational awareness of upstream factors that drive the capability and capacity constraints to leveraging new technology for sustainment risk mitigation. These capability and capacity constraints include sub-optimal supply chain coordination and limited collaboration between government R&amp;D centers. This research also demonstrates how a new business model called the Defense Mobility Enterprise solves these problems, while offering an incubator for Model-Based Systems Engineering experimentation and continuous productivity improvement. Through the successful application of SysML, the modeling language of systems engineering, this research concludes with multi-model orchestration, using the momentum of commercial-off-the-shelf tools, providing a strategic lens with which to specify, analyze, design, and verify Department of Defense ground vehicle and robotics technology transition opportunities.</p><p>

We consider general-purpose and flexible non-continuous chemical plants under deterministic feedback control. The aim of this research has been to develop hierarchical distributed feedback based control policies to: (1) organize and schedule flow between the different unit operations, (2) ensure the satisfaction of both safety as well as product constraints, and (3) achieve desirable performance. We begin by developing a lower bound on total storage required to meet demand rates. We also develop an upper bound on total storage required by an optimal policy. Next we propose a distributed feedback control scheme to organize flow in flexible non-continuous chemical plants. We show that this control scheme is stable, and can be implemented with fixed and finite storage. The performance of this policy in a limited number of simulations was close to optimal. When there are severe constraints on the size of the intermediate storage, a global supervisor can be implemented to prevent deadlock. We show that when the plant satisfies a sparsity property, the global supervisory control problem is tractable. The overall control system approach that we have developed for non-continuous chemical plants is based on a two-tiered structure--(1) a global supervisor ensures that process and safety constraints are satisfied, and also keeps the plant state trajectory steered away from dead-lock; and (2) local controllers are designed to maximize a distributed performance measure.

Serverless Computing has gained mass popularity by offering lower cost, improved elasticity, and improved ease of use. Driven by the need for efficient low latency computation on resource-constrained infrastructure, it is also becoming a common execution model for edge computing. However, hyperscale cloud mitigations against the serverless cold start problem do not cleanly scale down to tiny 10-100kW edge sites, causing edge deployments of existing VM and container-based serverless runtimes to suffer poor tail latency. This is particularly acute considering that future edge computing workloads are expected to have latency requirements ranging from microseconds to seconds. SledgeEDF is the first runtime to apply the traditional real-time systems techniques of admissions control and deadline-driven scheduling to the serverless execution model. It extends previous research on aWsm, an ahead-of-time (AOT) WebAssembly compiler, and Sledge, a single-process WebAssembly-based serverless runtime designed for the edge, yielding a runtime that targets efficient execution of mixed-criticality edge workloads. Evaluations demonstrate that SledgeEDF prevents backpressure due to excessive client requests and eliminates head-of-line blocking, allowing latency-sensitive high-criticality requests to preempt executing tasks and complete within 10% of their optimal execution time. Taken together, SledgeEDF's admissions controller and deadline-driven scheduler enable it to provide limited guarantees around latency deadlines defined by client service level objectives.