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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

EXPLORING THE USE OF COGNITIVE MODELS FOR NUCLEAR POWER PLANT HUMAN-SYSTEM INTERFACE EVALUATION

Much of the United States commercial nuclear power plant fleet is approaching the end of their operating licenses. To extend the life of these plants, advanced human-system interface (HSI) technologies are being researched to address aging and reliability concerns with the existing legacy instrumentation and controls. Human factors engineering (HFE) has a crucial role in ensuring these technologies are designed in a way that does not introduce new failure modes and promote optimal human-system performance. An important focus of HFE in NPP modernization is the early involvement to inform the design of the HSI. Here, traditional formative evaluations are done to collect design feedback. While these evaluations are absolutely useful, they are limited in providing convincing quantitative data for efficiency of use. This paper discusses the use of cognitive models to provide such quantitative data early in the HSI design process. A comparison of three open-source and readily accessible cognitive modeling tools are discussed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Near-Field Corrosion Interactions between Glass and Corrosion Resistant Alloys

This study explores the corrosion interactions between model nuclear waste glass materials and corrosion resistant alloys, under conditions that simulate the near field of a nuclear waste repository. The interactions between the corrosion of stainless steel (SS) 316, alloy G30, or alloy 625, and international simple glass or soda-lime silica glass are systematically studied. The dissimilar materials were exposed in close proximity to each other in different electrolytes at 90 oC. After exposure, the glass surface exposed near metals showed different regimes of corrosion, with distinct surface morphologies and chemistries that were likely affected by the local environment created by the localized corrosion of metals. Surface and solution analyses showed that the corrosion rate of glass was enhanced by the presence of metals. Infrared spectroscopy data suggested the local build-up of stresses in the contact area of glass, which may lead to the mechanical instability of the glass alteration layer. On the other hand, the effect of glass on metal corrosion is strongly dependent on the leaching solution. In electrolytes containing abundant aggressive anions such as Cl-, glass seems to suppress the localized corrosion of SS by the precipitation of a Si-rich surface film that protects the SS substrate from solutions. However, in less aggressive electrolytes, the corrosion rate of SS was increased by the presence of glass corrosion products. Overall, our study showed that the hidden and localized damage on glass in contact with metals may enhance the release of incorporated radionuclides compared to typical uniform glass corrosion. Therefore, more attention should be paid to the corrosion interactions between metals and glass under repository conditions.

Guo, Xiaolei↗
DOE OSTI2024

Updated uranium reference material 231 Pa/ 235 U consensus model ages for nuclear forensics

Radiochronometry provides the model age of nuclear materials, which is useful for understanding the production history of materials found outside of regulatory control. Certified reference materials (CRMs) are important for radiochronometry to increase confidence in measurement quality; however, the absence of 231 Pa/ 235 U CRMs necessitates that nuclear forensic laboratories measure the 231 Pa/ 235 U model ages of preexisting uranium reference materials. Here, in this work, new consensus 231 Pa/ 235 U model ages are reported from three nuclear forensic laboratories for three reference materials using current analytical methods. These updated consensus values can be used for quality control of 231 Pa/ 235 U model age measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Improvement of low energy atmospheric neutrino flux calculation using the JAM nuclear interaction model

We present the calculation of the atmospheric neutrino fluxes with an interaction model named JAM, which is used in PHITS (Particle and Heavy-Ion Transport code System) [K. Niita et al., Radiation Measurements 41, 1080 (2006).]. The JAM interaction model agrees with the HARP experiment [H. Collaboration, Astropart. Phys. 30, 124 (2008).] a little better than DPMJET-III[S. Roesler, R. Engel, and J. Ranft, arXiv:hep-ph/0012252.]. After some modifications, it reproduces the muon flux below 1 GeV/c at balloon altitudes better than the modified DPMJET-III, which we used for the calculation of atmospheric neutrino flux in previous works [T. Sanuki, M. Honda, T. Kajita, K. Kasahara, and S. Midorikawa, Phys. Rev. D 75, 043005 (2007).][M. Honda, T. Kajita, K. Kasahara, S. Midorikawa, and T. Sanuki, Phys. Rev. D 75, 043006 (2007).]. Some improvements in the calculation of atmospheric neutrino flux are also reported.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Intelligent Modeling for Nuclear Power Plant Accident Management

This study explores the viability of using counterfactual reasoning for impact analyses when understanding and responding to “beyond-design-basis” nuclear power plant accidents. Currently, when a severe nuclear power plant accident occurs, plant operators rely on Severe Accident Management Guidelines. However, the current guidelines are limited in scope and depth: for certain types of accidents, plant operators would have to work to mitigate the damage with limited experience and guidance for the particular situation. We aim to fill the need for comprehensive accident support by using a dynamic Bayesian network to aid in the diagnosis of a nuclear reactor’s state and to analyze the impact of possible response measures.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Screening evaluation of radionuclide groundwater concentrations for the end state basement fill model Zion Nuclear Power Station decommissioning project

ZionSolutions is in the process of decommissioning the Zion Nuclear Power Plant. The site contains two reactor Containment Buildings, a Fuel Building, an Auxiliary Building, and a Turbine Building that may be contaminated. The current decommissioning plan involves removing all above grade structures to a depth of 3 feet below grade. The remaining underground structures will be backfilled with clean material. The final selection of fill material has not been made.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Time-of-flight experiments for nuclear structure and astrophysics

Neutron-rich isotopes are atomic nuclei with a large neutron excess compared to their stable counter parts. Their study provides essential information to understand the properties of the nuclear interaction, and to model nuclear processes in extreme astrophysical environments where neutron-rich isotopes drive the chains of nuclear reactions. Experimentally, these unstable isotopes are difficult to study because of their short half-lives and low production yields at particle accelerator laboratories. The TOF-Bρ technique is a mass measurement technique specialized for experiments with fast beams of short-lived radioactive isotopes. In this project we used the technique for two experiments performed at the National Superconducting Cyclotron Laboratory to measure new masses of isotopes in the region of 112 Mo and 46 S. The experiments at the NSCL were complemented by the development of new timing radiation detectors and experimental techniques to improve the performance and reach of mass measurements on neutron-rich isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Toward Global Regional Seismic Moment Tensor Inversion with Three-Dimensional Earth Models for Nuclear Explosion Monitoring with Sparse Networks: Demonstration of Reciprocity for Strain Greens Tensor Database Simulation with Salvus

Seismic source characterization is an essential function of global nuclear explosion monitoring (NEM). While large events (roughly with moment magnitude, M w , greater than 5.0) can often be easily detected, located and identified with high signal-to-noise ratios at teleseismic distances (> 20°), trends in NEM research require confident source characterization at much lower magnitudes (say down to 3.0) and exploitation of sparse observations (from only a few stations) at regional distance (< 20°). Regional distance waveform inversion to characterize sources is now widely used and effective (e.g. Ford et al., 2009; Alvizuri and Tape, 2018; Alvizuri et al., 2018; Chiang et al., 2018; Ford et al., 2022). These methods obtain the magnitude, depth and seismic moment tensor, which represents the forces that excited the observed seismic waves (slip on an earthquake fault, explosion, collapse or a combination of various forces). Common to many problems in seismology, the isolation of the source 2 properties requires removal of path propagation effects that waves experience while traveling through the three-dimensional (3D) Earth (the structure exists due to different rock types, material properties, temperature and tectonic processes).

58 GEOSCIENCES↗
DOE OSTI2022

Building surrogate models of nuclear density functional theory with Gaussian processes and autoencoders

From the lightest Hydrogen isotopes up to the recently synthesized Oganesson (Z = 118), it is estimated that as many as about 8,000 atomic nuclei could exist in nature. Most of these nuclei are too short-lived to be occurring on Earth, but they play an essential role in astrophysical events such as supernova explosions or neutron star mergers that are presumed to be at the origin of most heavy elements in the Universe. Understanding the structure, reactions, and decays of nuclei across the entire chart of nuclides is an enormous challenge because of the experimental difficulties in measuring properties of interest in such fleeting objects and the theoretical and computational issues of simulating strongly-interacting quantum many-body systems. Nuclear density functional theory (DFT) is a fully microscopic theoretical framework which has the potential of providing such a quantitatively accurate description of nuclear properties for every nucleus in the chart of nuclides. Thanks to high-performance computing facilities, it has already been successfully applied to predict nuclear masses, global patterns of radioactive decay like β or γ decay, and several aspects of the nuclear fission process such as, e.g., spontaneous fission half-lives. Yet, predictive simulations of nuclear spectroscopy—the low-lying excited states and transitions between them—or of nuclear fission, or the quantification of theoretical uncertainties and their propagation to basic or applied nuclear science applications, would require several orders of magnitude more calculations than currently possible. However, most of this computational effort would be spent into generating a suitable basis of DFT wavefunctions. Such a task could potentially be considerably accelerated by borrowing tools from the field of machine learning and artificial intelligence. In this paper, we review different approaches to applying supervised and unsupervised learning techniques to nuclear DFT.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗