The ADM version of GR at Sixty: a brief account for historians
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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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This work applies a multiscale mechanistic damage model developed for brittle ceramics and implemented in commercial finite element (FE) packages via user subroutines to study progressive damage in solid oxide fuel cells (SOFC) subjected to thermomechanical loading under normal operating and shutdown conditions including redox effects. The damage model captures the micromechanics of stiffness reduction due to material porosity change and microcracking and integrates the as-obtained stiffness reduction law into a continuum damage mechanics (CDM) formulation for the evolution of microcracks up to fracture. The volumetric “swelling” that occurs during redox is treated in constitutive modeling similarly to thermal expansion, but swelling strains are irreversible. Furthermore, this damage model was first validated through predictions of strength and stress-strain response for the SOFC electrode materials. Next, it has been applied to predict the potential for degradation in a generic planar SOFC stack with large active area cells. Multicell stack models were simulated in both co-flow and counter-flow configurations. In addition, a constant temperature redox cycle was also simulated to capture overall cell electrode damage due to volumetric swelling of the nickel (Ni)-based anode in the anode-supported cells.
Identifying the source of beam loss events in the CE-BAF accelerator can be a challenging task. However, with our new prototype system, this task becomes more effi-cient. The system, developed in the fall of 2022, utilizes a dispersive beam position monitor (BPM) and the exist-ing switched electrode electronics BPM hardware. Previ-ously a commercial off-the-shelf data acquisition (DAQ) system was employed to capture BPM wire signals at a sample rate of 20 kS/s. The fast shutdown signal triggered the system, which disables the beam at the injector. Analysis of beam position and energy variation before a beam loss event was used to determine if the beam loss event was associated with an energy transient. The proto-type system, implemented using National Instruments hardware and LabVIEW® software, relied on a software trigger. Manual post-processing was required to ascertain whether the fault was due to an un-tripped cavity with a gradient or phase transient. This work focuses on deploying a Fast DAQ Chassis to monitor BPM hardware in real time and during beam loss events. This system was originally developed and in-stalled in CEBAF to monitor the time-domain RF control signals in the legacy analog RF systems. This technology was leveraged to also monitor BPM signals. As the new system employs a hardware trigger, developing tools to automatically identify faults linked to energy transients unrelated to cavity faults will be straightforward. This paper will discuss the project's initial updates, underlin-ing the crucial role of each member of our team in this achievement
Conference paper presented at 17th International Conference on Greenhouse Gas Control Technologies (GHGT-17), Calgary, Alberta, Canada, October 20–24, 2024. This paper presents the results of a detailed study into the potential atmospheric leakage risks associated with the geologic storage of CO 2 in saline aquifers. This study included a detailed literature review, a re-creation of existing CO 2 leakage models put forth by other authors and, lastly, the development of an enhanced model that can be utilized for assessing the potential losses to the atmosphere of stored CO 2 across a variety of potential project parameters. The results of this study indicate that, across broad ranges of input parameters for mechanisms that have the potential for CO 2 loss from the storage complex to the atmosphere, there is an extremely low risk of CO 2 leakage to the atmosphere, with the median leakage risk estimated to be 0.1% of total injected CO 2 . The risk of leakage from real-world storage projects is likely to be even lower than those estimated through this study.
Deep learning tools can incorporate all of the available information into a search for new particles, thus making the best use of the available data. This paper reviews how to optimally integrate information with deep learning and explicitly describes the corresponding sources of uncertainty. Simple illustrative examples show how these concepts can be applied in practice.
Molten salt reactors (MSRs) are a class of nuclear reactor designs with features and operational characteristics that vary significantly more than the class of light water reactors (LWRs). MSR design concepts can be broadly categorized as solid-fueled reactors with molten salt as the coolant, liquid-fueled reactors with fuel dissolved in molten salt coolant and liquid-fueled reactors with fuel dissolved in molten salt that is contained in distinct fuel tubes with a nonfissile coolant. Proposed MSR concepts include features that are specific to each design. MSR concepts vary widely across these design features, including the physical, chemical, and isotopic composition of fresh and irradiated fuel. Operational neutron energy spectrums and breeding ratios also vary significantly across design concepts. Some concepts are burner reactors designed to transmute the spent nuclear fuel from LWRs or pressurized heavy water reactors (PHWRs), while others are breeder reactors designed to breed fissile 233 U from naturally occurring fertile 232 Th. Some MSR concepts are designed to be a part of a once-through fuel cycle, while others involve chemical separation. Those that include plans to recycle the fuel differ by whether the chemical processing would be done onsite, as a process connected to the fuel salt itself, or offsite at a reprocessing facility similar to how LWR or PHWR spent fuel is reprocessed in some countries. Each overall design concept contains various aspects of each of these features to produce a unique facility
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This report was prepared by Oak Ridge National Laboratory (ORNL) for Flibe Energy Inc. (FEI), a US-based advanced reactor company founded in 2011 and headquartered in Huntsville, Alabama. FEI is developing the lithium-fluoride thorium reactor (LFTR), which is a modern two-fluid molten salt reactor (MSR) design operating on a thorium/ 233 U fuel cycle. FEI intends for LFTR to become a self-sustaining clean energy source that can create or breed its own fuel from thorium. Each LFTR is intended to breed enough fissile material to compensate for the amount it consumes. Consequently it would not require fissile replenishment during its operational lifetime. This self-sustaining nature would eliminate the need for uranium enrichment infrastructure to support LFTRs after the first generation.
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Here we present a detailed analysis of the error sensitivities of the LLNL temperature analysis package used in analyzing streak spectrometer data. These sensitivities include noise, temperature, wavelength, emissivity, missing bands, and missing data points. The analysis package was tested for its ability to accurately reconstruct randomly generated noisy data and found to perform within specifications.
The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. Incorporation of more physics-based models in BISON for the accident tolerant fuel applications motivated this study. This document details integration of new modeling capabilities in BISON, including: a tensile strength model for uranium dioxide (UO 2 ) fuel to incorporate the microstructural effects (e.g., grain size, fabrication pore size, and porosity), and atomistic-informed creep model for UO 2 fuel that is developed by Los Alamos National Laboratory. Sensitivity analyses are conducted on these models separately as well as a two-dimensional full rod application under normal operating conditions. Lastly, these new modeling capabilities in BISON are exercised in Halden IFA-677.1 and IFA-716.1 assessment cases.
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