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Energy Efficiency/Renewable Energy Impact in the Texas Emissions Reduction Plan (TERP), Volume I - ��� Technical Appendix, Annual Report to the Texas Commission on Environmental Quality January 2023 - December 2023
Get PDFThe Energy Systems Laboratory (ESL) at the Texas A&M Engineering Experiment Station of the Texas A&M University System is pleased to provide its annual report, "Energy Efficiency/Renewable Energy Impact in the Texas Emissions Reduction Plan (TERP)," as required under Texas Health and Safety Code 386.205, 386.252, 388.006, 389.003 (e), and under Texas Utilities Code Sec. 39.9051 (g) (h), and Sec. 39.9052 (c) (d)
Proliferation Resistance Analysis of Multiple Recycling of Re-Enriched Reprocessed Uranium Fuel in Commercial Light Water Reactors
No full textThe rapidly growing demand for electricity, combined with the limitations of renewable energy sources such as wind and solar, and excessive CO2 emissions from fossil fuels, makes nuclear power an increasingly attractive option as a significant supply of energy. However, to develop a robust nuclear energy framework, one of the aspects that must be considered is nuclear non-proliferation. The aspects of nuclear fuel cycles sensitive to nuclear proliferation, such as the reprocessing of spent nuclear fuel (SNF), have been the subject of numerous studies over the years. This study analyzes the proliferation resistance (PR) of re-enriched reprocessed uranium fuel discharged from a light water reactor (LWR), which is the Vodo-Vodyanoi Enyergeticheskiy Reactor (VVER-1000MWe). This analysis involves estimating the growth in the desired amounts of even-numbered uranium (U) and plutonium (Pu) isotopes, specifically 236-U and 238-Pu, to render the SNF less viable for military purposes. During fuel burnup, in addition to the presence of 235-U, 234-U, and 238-U isotopes, a non-fissionable minor isotope, 236-U, which is considered a signature isotope for reprocessed uranium (RepU), is generated through successive neutron capture from its precursor, 235-U. Subsequently, 236-U absorbs a neutron to transmute into 237-U, which then decays through beta emission into the long-lived minor actinide, 237-Np. Then 237-Np absorbs a neutron to transmute into 238-Np, which then decays through beta emission into 238-Pu. In summary, a fraction of 235-U gets converted to 236U and fraction of 236-U gets converted to 238-Pu. The presence of both 236-U and 238-Pu isotopes supports PR against weaponization of SNF.
Through multiple recycling of U in SNF with the concurrent re-enrichment, the concentration of 236-U continues to increase contributing to the enhanced production of 238-Pu in the SNF. The presence of 238-Pu is important as it reduces the quality of Pu for military purposes due to its high spontaneous fission neutron emission rate and decay heat (DH).
Simulation of VVER fuel assembly burnup was carried out using the Monte Carlo radiation transport code, MCNP6.2. Geometry data for the fuel assembly was collected from literature to conduct simulations of fuel burnup, aimed at exploring the feasibility of multiple recycling of re-enriched RepU discharged from VVER reactor. Subsequent to the fuel burnup simulation, the Matched Abundance Cascade Ratio (MARC) model, which permits computational co-enrichment of 235-U and 236-U, is utilized to re-enrich the RepU material. Fuel burnup simulation using MCNP6.2 code and multi-isotope re-enrichment using the MARC model allowed to estimate the amount of 236-U and 238-Pu in multi-recycled VVER SNF. These estimated values showed that these two isotopes help support the enhancement of PR
Digital Resource 6: Black authors in Norton PWAM (1979, 1985, 1989, 1994, 1998, 2003, 2007, 2012, 2017, 2022), as a percentage normalized, zoom
No full textReferenced in Chapter 4 of the book "Digital Literary Redlining: African American Anthologies, Digital Humanities, and the Canon.
Graph Clustering Algorithms in GraphBLAS
Get PDFGraph theory has long served as a cornerstone for computational problems among various domains. Hence, the development of graph algorithms has proved to be one of the most pronounced focuses in the field of computer science. Among the most recent developments in this field is the emergence of linear algebra as a tool for addressing graph related problems. GraphBLAS, an open-source API specification, realizes this intrinsic connection by providing a framework for constructing graph algorithms in the language of linear algebra. Graph clustering is the process of determining natural groups of nodes with relatively high connectivity in a graph structure. The Peer Pressure and Markov Cluster algorithms are two unsupervised processes which capitalize on linear algebraic principles to efficiently identify clusters within graphs. This paper aims to walk through the development and implementation of both algorithms using the SuiteSparse:GraphBLAS C API, with the additional goal of fostering intuition for crafting graph algorithms from a linear algebraic perspective. Our implementations will be added to the LAGraph repository, a collection of algorithms implemented using GraphBLAS. Additionally, we provide a suite of metrics which can be used to quantitatively measure the quality of a graph clustering. We demonstrate that our quality metrics surpass the speed of existing implementations and our clustering algorithms yield reasonable clusterings efficiently, even on large graphs
Examples of birds mounted by Sammy Ray, 1937-1940
No full text31 slide Power Point presentation. Created 2004, modified in 2010Bird collection is currently housed in the Fish and Game Museum, Jackson, Mississippi. These birds were originally collected and mounted by Sammy Ray between 1937 and 1940. Those are slide 2-8; slides 9-31 are of birds and circumstances of collecting in the Pacific theater of World War II (1943-1945) while Dr. Ray was serving in the U.S. Arm