Statistical Modeling and Optimization of Nuclear Waste Vitrification

This thesis describes the development of a methodology to minimize the cost of vitrifying nuclear waste. Pacific Northwest Laboratory (PNL) regression models are used as baseline equations for modeling glass properties such as viscosity, electrical conductivity, and two types of durability. Revised PNL regression models are developed that eliminate insignificant variables from the original models. The Revised PNL regression model for electrical conductivity is shown to better predict electrical conductivity than the original PNL regression model. Neural networks are developed for viscosity and the two types of durability, PCT-B and MCC-1 B. The neural network models are shown to outperform every PNL and Revised PNL regression model in terms of predicting property values for viscosity, PCT-B, and MCC-1 B. The combined Neural Network/Revised PNL 2nd order electrical conductivity models are shown to be the best classifiers of nuclear waste glass, i.e. they have the highest probability of classifying a vitrified waste form as glass when it actually did produce glass in the laboratory. Finally, five nonlinear programs are developed with constraints containing: (1) the PNL original 1st order models, (2) the PNL original 2nd order models, (3) the Revised PNL 1st order models, (4) the Revised PNL 2nd order models, and (5) the Neural Network/Revised PNL 2nd order electrical conductivity models. The Neural Network/Revised PNL 2nd order electrical conductivity nonlinear program is shown to minimize the total expected cost of vitrifying nuclear waste glass. This nonlinear program allows DOE to minimize its risk and cost of high-level nuclear waste vitrification

A Combined Adaptive Tabu Search and Set Partitioning Approach for the Crew Scheduling Problem with an Air Tanker Crew Application

This research develops the first metaheuristic approach to the complete air crew scheduling problem. It develops the first dynamic, integrated, set-partitioning based vocabulary scheme for metaheuristic search. Since no benchmark flight schedules exist for the tanker crew scheduling problem, this research defines and develops a Java™ based flight schedule generator. The robustness of the tabu search algorithms is judged by testing them using designed experiments. An integer program is developed to calculate lower bounds for the tanker crew scheduling problem objectives and to measure the overall quality of solutions produced by the developed algorithms

Synaptic Connections of the Neurokinin 1 Receptor-Like Immunoreactive Neurons in the Rat Medullary Dorsal Horn

The synaptic connections between neurokinin 1 (NK1) receptor-like immunoreactive (LI) neurons and γ-aminobutyric acid (GABA)-, glycine (Gly)-, serotonin (5-HT)- or dopamine-β-hydroxylase (DBH, a specific marker for norepinephrinergic neuronal structures)-LI axon terminals in the rat medullary dorsal horn (MDH) were examined under electron microscope by using a pre-embedding immunohistochemical double-staining technique. NK1 receptor-LI neurons were observed principally in laminae I and III, only a few of them were found in lamina II of the MDH. GABA-, Gly-, 5-HT-, or DBH-LI axon terminals were densely encountered in laminae I and II, and sparsely in lamina III of the MDH. Some of these GABA-, Gly-, 5-HT-, or DBH-LI axon terminals were observed to make principally symmetric synapses with NK1 receptor-LI neuronal cell bodies and dendritic processes in laminae I, II and III of the MDH. The present results suggest that neurons expressing NK1 receptor within the MDH might be modulated by GABAergic and glycinergic inhibitory intrinsic neurons located in the MDH and 5-HT- or norepinephrine (NE)-containing descending fibers originated from structures in the brainstem

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead