Two important issues related to nuclear materials safeguards are the continuous monitoring of nuclear processing facilities to verify that undeclared uranium is not processed or enriched and to verify that declared uranium is accounted for. The International Atomic Energy Agency (IAEA) is tasked with ensuring special nuclear facilities are operating as declared and that proper material safeguards have been followed. Traditional safeguards measures have relied on IAEA personnel inspecting each facility and verifying material with authenticated instrumentation. In newer facilities most plant instrumentation data are collected electronically and stored in a central computer. Facilities collect this information for a variety of reasons, most notably for process optimization and monitoring. The field of process monitoring has grown significantly over the past decades, and techniques have been developed to detect and identify changes and to improve reliability and safety. Several of these techniques can also be applied to international and domestic safeguards. This dissertation introduces a safeguards monitoring system developed for both a simulated Uranium blend down facility, and a water-processing facility at the Oak Ridge National Laboratory. For the simulated facility, a safeguards monitoring system is developed using an Auto-Associative Kernel Regression model, and the effects of incorporating facility specific radiation sensors and preprocessing the data are examined. The best safeguards model was able to detect diversions as small as 1.1%. For the ORNL facility, a load cell monitoring system was developed. This monitoring system provides an inspector with an efficient way to identify undeclared activity and to identify atypical facility operation, included diversions as small as 0.1 kg. The system also provides a foundation for an on-line safeguards monitoring approach where inspectors remotely facility data to draw safeguards conclusion, possibly reducing the needed frequency and duration of a traditional inspection.

The proposed cell monitoring unit for sensing voltage, current, and temperature in a 12-cell 18650 lithium-ion battery module aims to be low-power, serving as the core of an energy-efficient battery management system and facilitating battery management functions with cell data. Notable features include a switchable voltage divider, a single op-amp differential amplifier and level shifter, and a high-precision composite amplifier. The proposed circuit is implemented on a printed circuit board. Measurement results show that the highest power dissipation under continuous operation is from the current sensing circuit at 6.03 mW under a 4 A string current, followed by the voltage sensing at 2.52 mW for the top cell and the temperature sensing at 34.9 μW. The measured power figures include the power dissipation from the battery cells in addition to the cell monitoring unit. The maximum output error is 68 mV for cell voltages up to 44.4 V, 36 mA for current up to 4 A, and 0.37 ◦C for temperature up to 73 ◦C. / M.S. / Battery management systems are required in modern rechargeable battery-operated devices to help ensure that the batteries operate within the manufacturer-specified operating range. Otherwise, damage to the batteries or to the device may occur. Battery modules are comprised of smaller energy cells to achieve the specified energy capacity and power output. At the core of a battery management system is a battery cell monitoring unit that interfaces the management system with the battery module by providing data about each of the battery cells, including voltage, current, and temperature. To help minimize the power dissipation of battery-powered devices and prolong the battery life, the power consumed by the battery management system should be small. This project aims to detail the design and results of a low-power cell monitoring unit as the core component of energy-efficient battery management systems. The proposed circuit is designed for a 12-cell lithium-ion battery module and implemented on a printed circuit board. The maximum measured power dissipation under continuous operation is 6.03 mW for the current sensing circuit, followed by the voltage sensing circuit at 2.52 mW and the temperature sensing circuit at 34.9 μW.

The objective of this research is to develop fundamental understanding of cell-substrate (CS) and cell-cell (CC) interactions in the culture space for time evolving cell cultures. Space resolved CC and CS interactions are important indicators of cell-density distribution, localized cellular behavior, and multiple cell-layers which are differentiators of normal and abnormal cell behavior. In this research, CS and CC interactions and the variations therein due to a) Cell growth, 2) cell-drug interaction, and 3) effect of Cytotoxin were studied using multielectrode, multi-frequency Electrochemical Impedance Spectroscopy (EIS). Contemporary impedance based methods sense either CC or CS interaction as a space averaged macroscopic quantity. A major contribution of this research is that, both CC and CS interactions are recorded and analyzed with spatio-temporal resolution. This research led to the development of an automated cell culture monitoring system, namely, CellMap. A planar eight electrode sensor was fabricated on a glass substrate and interfaced with a switching circuit. The switching circuit sequentially selects consecutive electrodes upon input of a 5V trigger pulse which is generated by the frequency response analyzer at the end of each frequency scan, thereby facilitating automated switching and recording of multielectrode dataset. Calibration standards and protocols were developed to null the channel parasitics of individual channels. A set of eight impedance measurements for eight electrodes constitutes a "frame". Frames are recorded at regular time intervals over the desired course of time. Impedance mapping of adhesion, spreading, motility and detachment of OvCa429 ovarian cancer cells was performed over a period of 70 hours. The cell-layer resistance, which indicates cell-cell contact, increased as a function of time until confluence, and decreased thereafter due to cell death and detachment. This was also confirmed by optical microscopy observations. Similarly, the cell layer Constant Phase Element (CPE) parameters, which were found to correlate well with cell density distribution, also increased as a function of time until confluence and decreased thereafter. Additionally, the cell-growth mapping revealed that the CellMap system is able to resolve non-uniform cell distributions in the culture space, which may be useful in differentiating between normal and pathological cells.