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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 1,189 records · Page 66

Experiment to Investigate the On-set of Transient Fission Gas Release Under Simulated LOCA Conditions

Continuing efforts to better understand the phenomenon of transient fission gas release in irradiated commercial light water reactor fuel undergoing a simulated loss of coolant accident (LOCA) will be discussed in this work. During heating associated with LOCA conditions there is an additional release of fission gas beyond what is typically released during steady state operation. The exact timing of this release could impact the cladding balloon and rupture as the LOCA progresses in an actual accident. Recent experiments performed on the upgraded Severe Accident Test Station at Oak Ridge National Laboratory have expanded the current assessment of transient fission gas release. This system evaluates fission gas release by sweeping fission gas out of the LOCA test furnace and into cryogenically cooled cold traps where radioactive noble gas fission products are measured by gamma spectrometry. Additionally, the sweep gas can be monitored by a gas mass spectrometer to provide additional data on noble gas release and changes in the sweep gas atmosphere during heating. Several different conditions have been evaluated that explored the response of irradiated fuel to different thermal ramp conditions and different overpressure conditions. This further confirmed the impact of an overpressure in suppressing transient fission gas release. Further experiments are planned to evaluate the on-set temperature of transient fission gas release under a known overpressure. This test will progressively step through different temperature conditions while maintaining hydrostatic pressure on the fuel that is representative of high burnup fuel conditions. The available results from this type of testing will be discussed. Post-test microscopy will be compared to other transient fission gas release and standard LOCA tests to further understand the microstructural source of transient fission gas release.

Harp, Jason [ORNL] (ORCID:0000000253458440)↗

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

59 BASIC BIOLOGICAL SCIENCES↗

Heating effects on pyrogenic organic matter mass loss and temperature in a sand matrix in a lab setting from 2022

This dataset contains data associated with the preprint “A laboratory method for simulating the effects of subsequent fires on pyrogenic organic matter at different exposure depths in a sand matrix” (https://doi.org/10.1101/2024.07.30.605814), which has been accepted for publication in the International Journal of Wildland Fire. The dataset was generated to investigate the effects of subsequent fires on preexisting pyrogenic organic matter (PyOM) at different soil depths. Specifically, we designed a laboratory method to simulate soil heating from above, applying realistic heat flux profiles (High, Low, Control) derived from jack pine (Pinus banksiana Lamb.) log burns. Using a cone calorimeter, these profiles were applied to buried jack pine PyOM (produced at 350°C) in a sand matrix pyrocosm to examine PyOM mass loss at different depths (surface, 1 cm, 5 cm). Each treatment (e.g., High heat flux at 1 cm depth) was applied once to five replicates in a pyrocosm.The dataset includes mass loss fraction of PyOM and time-series temperature profiles (measured with type K thermocouples). Additionally, calibration datasets for high and low heat flux profiles are provided, including programmed heat flux profile data and three sets of calibration results. All datasets are in .csv format and were analyzed in R using code found at https://github.com/MengmengLuo/Reburning-pyrogenic-organic-matter-A-laboratory-method-for-dosing-dynamic-heat-fluxes-from-above. This dataset supports research on PyOM transformations during subsequent fires, and methodological advancements in simulating soil heating. It can be used to explore fire-induced PyOM alterations across different fire intensities and soil depths.

54 ENVIRONMENTAL SCIENCES↗

Public Data Set: On Virial Analysis at Low Aspect Ratio

This public data set contains openly-documented, machine readable digital research data published in M.W. Bongard, et al., 'On Virial Analysis at Low Aspect Ratio,' Phys. Plasmas 23, 072508 (2016).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Public Data Set: Erratum: "Multi-point, high-speed passive ion velocity distribution diagnostic on the Pegasus Toroidal Experiment" [Rev. Sci. Instrum. 83, 10D516 (2012)]

This data set contains openly-documented, machine readable digital research data corresponding to figures published in M.G. Burke et al., 'Erratum: "Multi-point, high-speed passive ion velocity distribution diagnostic on the Pegasus Toroidal Experiment" [Rev. Sci. Instrum. 83, 10D516 (2012)],' Rev. Sci. Instrum. 87, 079902 (2016).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Public Data Set: Spatial Heterodyne Spectroscopy for High Speed Measurements of Stark Split Neutral Beam Emission in a High Temperature Plasma

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in M.G. Burke et al., 'Spatial Heterodyne Spectroscopy for High Speed Measurements of Stark Split Neutral Beam Emission in a High Temperature Plasma,' Review of Scientific Instruments 89, 10D114 (2018).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗