No description available.

The purpose of this work is to investigate the implementation of nitride fuels containing little or no uranium in a fast-spectrum nuclear reactor to reduce the amount of plutonium and minor actinides in spent nuclear fuel destined for the Yucca Mountain Repository. A two tier recycling strategy is proposed. Thermal spectrum transmutation systems converted from the existing LWR fleet were modeled for the first tier, and the Japanese fast reactor MONJU was used for the fast-spectrum transmutation. The modeling was performed with the Monteburns code. Transmutation performance was investigated as well as delayed neutron fraction, heat generation rates, and radioactivity of the spent material in the short and long term for the different transmutation fuel cycles. A two-tier recycling strategy incorporating fast and thermal transmutation with uranium-free nitride fuel was shown to reduce the long-term heat generation rates and radioactivity of the spent nuclear fuel inventory.

The Multi-Isotope Process Monitor is being developed at Pacific Northwest National Laboratory as a method to verify the process conditions within a nuclear fuel reprocessing facility using the gamma spectra of various process streams. The technique uses multivariate analysis techniques such as principal component analysis and partial least squares regression applied to gamma spectra collected of a process stream in order to classify the contents as belonging to a normal versus off-normal chemistry process. This approach to process monitoring is designed to function automatically, nondestructively, and in near real-time. To extend the Multi-Isotope Process Monitor, an analysis method to char- acterize spent nuclear fuel based on the reactor of origin, either pressurized or boiling water reactor, and burnup of the fuel using nuclide concentrations as input data has been developed. While the Multi-Isotope Process Monitor uses gamma spectra as input data, nuclide activities were used in this work as an initial step before Nuclide composition information was generated using ORIGEN-ARP for different fuel assembly types, initial 235U enrichments, burnup values, and cooling times. This data was used to train, tune, and test several multivariate analysis algorithms in order to compare their performance and identify the technique most suited for the analysis. To perform the classification based on reactor type, four methods were considered: k-nearest neighbors, linear and quadratic discriminant analysis, and support vector machines. Each method was optimized, and its performance on a validation set was used to determine the best method for classifying the fuel reactor class. Partial least squares was used to make burnup predictions. Three models were generated and tested: one trained on all the data, one trained for just pressurized water reactors, and one trained for boiling water reactors. Quadratic discriminant analysis was chosen as the best classifier of reactor class because of its simplicity and its potential to be extended to classify spent nuclear fuel’s fuel assembly type, i.e, more specific classes, using nuclide concentrations as input data. In the case of predicting the burnup of spent fuel using partial least squares, it was determined that making reactor-specific partial least squares models, one trained for pressurized water reactors and one trained for boiling water reactors, performed better than a single, general model that was trained for all light water reactors. Thus, the the classifier, regression algorithm, and all the necessary intermediate data processing steps were combined into a single analysis method and implemented as a Matlab function called “burnup.” This function was used to test the analysis routine on an additional set of data generated in ORIGEN-ARP. This dataset included samples with parameters that were not represented in the development data in order to ascertain the analysis method’s ability to analyze data for which it has not been explicitly trained. The algorithm was able to achieve perfect binary classification of the reactor as being a pressurized or boiling water reactor on the dataset and made burnup predictions with an average error of 0.0297%. / text

No description available.

The purpose of this work is to investigate the implementation of nitride fuels containing little or no uranium in a fast-spectrum nuclear reactor to reduce the amount of plutonium and minor actinides in spent nuclear fuel destined for the Yucca Mountain Repository. A two tier recycling strategy is proposed. Thermal spectrum transmutation systems converted from the existing LWR fleet were modeled for the first tier, and the Japanese fast reactor MONJU was used for the fast-spectrum transmutation. The modeling was performed with the Monteburns code. Transmutation performance was investigated as well as delayed neutron fraction, heat generation rates, and radioactivity of the spent material in the short and long term for the different transmutation fuel cycles. A two-tier recycling strategy incorporating fast and thermal transmutation with uranium-free nitride fuel was shown to reduce the long-term heat generation rates and radioactivity of the spent nuclear fuel inventory.

No description available.

No description available.

Thesis. 1976. Ph.D.--Massachusetts Institute of Technology. Dept. of Nuclear Engineering. / Microfiche copy available in Archives and Science. / Vita. / Includes bibliographical references. / by George Charman Allen, Jr. / Ph.D.

No description available.

Ceramic and refractory metal foams have a potential for use in extreme environments, such as in fuel elements within nuclear reactors both in space and terrestrial applications. In addition, infiltrating an open-cell ceramic foam with a continuous second phase can create an interpenetrating phase composite (IPC), consisting of a three-dimensional reinforcement structure. One aspect of investigation within this study was the influence of foam pore/strut size, foam composition, and foam density on neutronic and mechanical properties. Neutron transmission through open-cell tantalum carbide foams was measured using experimental techniques and modeled with Monte Carlo N-Particle (MCNP) transport code. Neutron transmission decreased linearly within tantalum carbide (TaC)/reticulated vitreous carbon (RVC) foams as areal TaC density increased. All MCNP modeling runs predicted slightly higher neutron transmission than what was experimentally measured, potentially indicating that the foam structure had a small influence on neutron transmission. Compressive strength and Young's moduli of tantalum carbide foams were measured for foam specimens that were exposed to thermal cycling and thermal shock, as well as for baseline specimens. Extensive micro-cracking was observed in the foams after 18 thermal cycles to 2100°C. However, thermal shock in liquid nitrogen did not produce observable micro-cracking in the TaC foams. The average strengths of baseline TaC/RVC foams ranged from 1.97 MPa - 3.82 MPa. The baseline TaC/PyC/RVC foams exhibited strengths ranging from 4.57 MPa - 12.60 MPa. The compressive strength of thermally cycled foams tended to be 1/3-1/2 that of baseline specimens. Another aspect of this study investigated the infiltration of RVC foams with tungsten powder in an attempt to form a tungsten-ceramic foam interpenetrating phase composite (IPC). It was found that tungsten particle size influenced infiltrated densities more than foam pore size. Significantly lower infiltrated densities were obtained using sub-micron tungsten than with 5-10 micron tungsten as a result of particle agglomeration. Infiltrated 5-10 micron tungsten achieved densities ranging from 23-25% theoretical within RVC foams, whereas sub-micron tungsten densities ranged from 11-16% theoretical. Constrained densification was observed during sintering of tungsten-infiltrated foams. / Ph. D.