Systems Engineering Commons^™

Prognostic Algorithm Development For Plant Monitoring And Maintenance Planning, Them Hill Bui

Doctoral Dissertations

The economic goals in a typical industrial plant are to improve product quality, maximize equipment up-time, reliability, and availability, and minimize spare part inventories and maintenance costs. Modern facilities are comprised of thousands of subsystems with critical unique components. Simple components and more complex engineering systems alike are typically engineered to perform satisfactorily. Their lives can be predicted under normal operation runtime. It should be the same with chronological time lapse from the moment of installation. However, their ages accelerate faster than chronological time lapse if they are operated under unfavorable working conditions, making their remaining life predictions likely not …

Developing An Optimal Model For Infant Home Visitation, Isaac Atuahene

Doctoral Dissertations

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) …

X-Band Dual Polarization Phased-Array Radar For Meteorological Applications, Krzysztof Orzel

Doctoral Dissertations

This dissertation details the development and operation of a novel dual-polarized Phase-Tilt Weather Radar (PTWR) designed for meteorological applications. The use of radar has a well-documented history in detection and classification of weather phenomena, but due to the limited mechanical scanning speed, its usage for severe weather observations remains far from ideal. The PTWR utilizes phased-array technology and provides unique capabilities such as smart scanning, fast scan update, and tracking. This technology is considered a candidate for a replacement and consolidation of the current US weather and surveillance radar networks. The dissertation can be divided into three parts. First, the …

Modeling Supply Chain Interdependent Critical Infrastructure Systems, Varun Ramachandran

Doctoral Dissertations

"While strategies for emergency response to large-scale disasters have been extensively studied, little has been done to map medium- to long-term strategies capable of restoring supply chain infrastructure systems and reconnecting such systems from a local urban area to national supply chain systems. This is, in part, because no comprehensive, data-driven model of supply chain networks exists. Without such models communities cannot re-establish the level of connectivity required for timely restoration of goods and services. This dissertation builds a model of supply chain interdependent critical infrastructure (SCICI) as a complex adaptive systems problem. It defines model elements, data needs/element, the …

Computational Intelligence Based Complex Adaptive System-Of-Systems Architecture Evolution Strategy, Siddharth Agarwal

Doctoral Dissertations

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving …

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 …