SEARCH · Search NASA

Results for “Conditional distributions”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Year End Progress Report on Rattlesnake Improvements

Rattlesnake is a MOOSE-based radiation transport application developed at INL to support modern multi-physics simulations. At the beginning of the last year, Rattlesnake was able to perform steady-state, transient and eigenvalue calculations for the multigroup radiation transport equations. Various discretization schemes, including continuous finite element method (FEM) with discrete ordinates method (SN) and spherical harmonics expansion method (PN) for the self-adjoint angular flux (SAAF) formulation, continuous FEM (CFEM) with SN for the least square (LS) formulation, diffusion approximation with CFEM and discontinuous FEM (DFEM), have been implemented. A separate toolkit, YAKXS, for multigroup cross section management was developed to support Rattlesnake calculations with feedback both from changes in the field variables, such as fuel temperature, coolant density, and etc., and in isotope inventory. The framework for doing nonlinear diffusion acceleration (NDA) within Rattlesnake has been set up, and both NDA calculations with SAAF-SN-CFEM scheme and Monte Carlo with OpenMC have been performed. It was also used for coupling BISON and RELAP-7 for the full-core multiphysics simulations. Within the last fiscal year, significant improvements have been made in Rattlesnake. Rattlesnake development was migrated into our internal GITLAB development environment at the end of year 2014. Since then total 369 merge requests has been accepted into Rattlesnake. It is noted that the MOOSE framework that Rattlesnake is based on is under continuous developments. Improvements made in MOOSE can improve the Rattlesnake. It is acknowledged that MOOSE developers spent efforts on patching Rattlesnake for the improvements made on the framework side. This report will not cover the code restructuring for better readability and modularity and documentation improvements, which we have spent tremendous effort on. It only details some of improvements in the following sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Property Values Associated with the Failure of Individual Links in a System with Multiple Weak and Strong Links.

Representations are developed and illustrated for the distribution of link property values at the time of link failure in the presence of aleatory uncertainty in link properties. The following topics are considered: (i) defining properties for weak links and strong links, (ii) cumulative distribution functions (CDFs) for link failure time, (iii) integral-based derivation of CDFs for link property at time of link failure, (iv) sampling-based approximation of CDFs for link property at time of link failure, (v) verification of integral-based and sampling-based determinations of CDFs for link property at time of link failure, (vi) distributions of link properties conditional on time of link failure, and (vii) equivalence of two different integral-based derivations of CDFs for link property at time of link failure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

A Limited-In-Scope Comparison of Subsidence Scenarios For 3D Vadose Zone PORFLOW Trench Models

This technical memorandum summarizes the results from two separate sequences of 3D PORFLOW vadose zone flow and contaminant transport models that were used to test the impact of different spatial distributions of subsidence boundary conditions. More specifically, the two simulation setups used a general conceptual model for an engineered trench (ET): one with a subsided region specified in the center of the trench and one with a subsided region located at the end of the trench. Both subsided regions had the same geometric specifications (e.g., length, width, orientation), but used water infiltration rate boundary conditions that appropriately accounted for surface runoff and lateral drainage from the adjacent upslope intact regions of the final closure cap. Because of the substantially higher water infiltration rate associated with the subsided region at the end of the trench, this geometry produced higher absolute peak fluxes to the water table for all six radionuclides that were simulated. However, the slower release rate of the centrally located subsided hole geometry produced a higher flux to the water table in the time period subsequent to the absolute peak. A third model was implemented as a control, where the water infiltration rate that corresponds to the centrally located subsided region was applied at the end of the trench to highlight the purely geometric effects. The results show that a higher water infiltration rate produces a sharper peak, while a lower infiltration rate leads to a broader peak. A centrally located hole impacts more of the waste zone, producing a higher peak when an equal infiltration rate is applied. These generalized qualitative differences, and their impacts on the overall modeling workflow (i.e., from vadose zone models to limits and dose calculations), should receive appropriate consideration during the development of conceptual models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Batch Extraction Studies to Evaluate Trace Element Behavior in PUREX Conditions

The multilab Intentional Forensics Venture is working to identify which stable elements (i.e., taggants) at trace concentrations relative to U would persist throughout the nuclear fuel cycle in a voluntary fuel tagging scheme. A taggant would provide the nuclear forensics community with a “barcode” to help identify nuclear materials found outside of regulatory control. A portion of this project was focused on reprocessing effects and determining which, if any, elements would coextract with U(VI) in standard Pu–U reduction extraction (PUREX) conditions. Elements with a propensity to coextract could, in theory, be used as taggants from a PUREX perspective. Although retention is not a performance requirement, the taggant signature would need to partition predictably from the U stream after the PUREX process to maintain forensic utility. This report documents results from several batch extraction studies with numerous trace elements from HNO 3 (1.5–5 M), with and without U(VI), into 30% tri-n-butyl phosphate (TBP) in kerosene. Extraction and back-extraction tests were used to evaluate nearly 60 elements in surrogate conditions for PUREX, and distribution coefficients (i.e., D-values) for most species were <0.1, indicating few species are likely to co-extract with U through PUREX. Additional studies are needed to optimize sample volumes and dilutions to dial in these low D-values. The D-values (D) were determined for several of the more promising elements, including Re and Se. Ultimately, we conclude that only a limited number of the ~ 60 elements investigated are extractable in the U stream of PUREX, based on measured D values, meaning most candidate elemental taggants would likely be lost at this stage of the nuclear fuel cycle, even when considering a range of acid concentrations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2026

Characterization of Organosulfates and Organonitrates in Vertically Resolved Aerosols over the Southern Great Plains Field Campaign Report

Aerosol is the largest individual source of uncertainty in assessing the Earth’s radiative balance due to poorly understood aerosol processes and aerosol-cloud interactions. Thus, to constrain aerosol’s climate impacts, it is critical to understand aerosol compositions at high elevations. Organic material accounts for about 20-80% of total aerosol mass in the atmosphere and is known to play a key role in aerosol processes and cloud formation. In prior research, characterization of aerosol molecular composition has been mostly carried out at ground level. In these ground-level measurements, total speciated organosulfates and organonitrates may contribute significantly to organic aerosol mass on the order of 10-40%, most of which are from abundant biogenic volatile organic compounds such as isoprene and monoterpenes. Organosulfates and organonitrates have also been shown to be present in substantial amounts in cloud water, suggesting that they can be transported and/or directly formed at high elevations. On the other hand, the less common and more expensive aircraft studies have performed high-altitude measurements, but were often limited in the number of different altitudes sampled and in sample collection under consistent conditions. Therefore, the vertical distributions of key aerosol components such as organosulfates and organonitrates are not well understood and have not been extensively studied. Nevertheless, it is important to understand how organosulfates and organonitrates in aerosols are distributed, transformed, participate in aqueous-phase processes, and interact with high-altitude clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Legacy Metallic Fuel U(Pu)Zr Data Qualification

The Metallic Fuels Irradiation and Physics Database (FIPD) is an organized collection of legacy metallic fuel U(Pu)Zr data, measurements, and reactor conditions from the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). The database provides a wealth of information and is easily accessed and utilized by the U.S. nuclear industry and the Nuclear Regulatory Commission (NRC). The database contains three categories of data. The first category covers fuel pin fabrication specifications, including fuel slug diameter and length, cladding diameter, smeared density, etc. The second consists of operational conditions, which include axial distributions of power, temperature, fluence, burnup, isotopic density, etc. The third category contains post-irradiation examination (PIE) results, largely collected at facilities now part of the Idaho National Laboratory (INL), formerly part of Argonne National Laboratory -West (ANL-W) and at the Alpha-Gamma Hot Cell Facility (AGHCF) at Argonne National Laboratory, comprising fission gas release and chemistry analysis, profilometry measurements, neutron radiography data, etc. All these data have been organized and preserved in FIPD.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

An Inventory of AI-ready Benchmark Data for US Fires, Heatwaves, and Droughts

Extreme weather events, including fires, heatwaves, and droughts, have significant impacts on earth, environmental, and energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning for, and responding to these extremes. Records of extreme weather events provide an important data source for understanding present and future extremes, but the existing data needs preprocessing before it can be used for analysis. Moreover, there are many nonstandard metrics defining the levels of severity or impacts of extremes. In this study, we compile a comprehensive benchmark data inventory of extreme weather events, including fires, heatwaves, and droughts. The dataset covers the period from 2001 to 2020 with a daily temporal resolution and a spatial resolution of 0.5°×0.5° (~55km×55km) over the continental United States (CONUS), and a spatial resolution of 1km × 1km over the Pacific Northwest (PNW) region, together with the co-located and relevant meteorological variables. By exploring and summarizing the spatial and temporal patterns of these extremes in various forms of marginal, conditional, and joint probability distributions, we gain a better understanding of the characteristics of climate extremes. The resulting AI/ML-ready data products can be readily applied to ML-based research, fostering and encouraging AI/ML research in the field of extreme weather. This study can contribute significantly to the advancement of extreme weather research, aiding researchers, policymakers, and practitioners in developing improved preparedness and response strategies to protect communities and ecosystems from the adverse impacts of extreme weather events. Usage Notes We presented a long term (2001-2020) and comprehensive data inventory of historical extreme events with daily temporal resolution covering the separate spatial extents of CONUS (0.5°×0.5°) and PNW(1km×1km) for various applications and studies. The dataset with 0.5°×0.5° resolution for CONUS can be used to help build more accurate climate models for the entire CONUS, which can help in understanding long-term climate trends, including changes in the frequency and intensity of extreme events, predicting future extreme events as well as understanding the implications of extreme events on society and the environment. The data can also be applied for risk accessment of the extremes. For example, ML/AI models can be developed to predict wildfire risk or forecast HWs by analyzing historical weather data, and past fires or heateave , allowing for early warnings and risk mitigation strategies. Using this dataset, AI-driven risk assessment models can also be built to identify vulnerable energy and utilities infrastructure, imrpove grid resilience and suggest adaptations to withstand extreme weather events. The high-resolution 1km×1km dataset ove PNW are advantageous for real-time, localized and detailed applications. It can enhance the accuracy of early warning systems for extreme weather events, helping authorities and communities prepare for and respond to disasters more effectively. For example, ML models can be developed to provide localized HW predictions for specific neighborhoods or cities, enabling residents and local emergency services to take targeted actions; the assessment of drought severity in specific communities or watersheds within the PNW can help local authorities manage water resources more effectively.

Lin, Xinming↗

DOE OSTI2023

Power Density Distributions in Electron Beams

Measuring and controlling the power density distribution of electron beams used for welding is critical for producing repeatable welds and for transferring welding parameters between different machines. On any given machine, the power density distribution is controlled by defocusing the beam relative to its sharpest focused condition. However, measuring the power density distribution can be difficult due to the intense nature of welding beams and is further complicated by imperfect electron optics that can distort the beam, making it difficult to quantify. The enhanced modified Faraday cup (EMFC) diagnostic method was used here for beam analysis that utilizes computed tomography to reconstruct the beam’s power density distribution. These results were compared to the International Standards Organization (ISO) method for characterizing laser beams using a second-moment D4σ calculation. For ideal Gaussian-shaped beams, both methods would give the same result. However, for imperfect beams, the calculated D4σ diameter was shown to be about 25% larger relative to the FWe2 diameter measured by the EMFC due to the heavier weighting of data in the tails of the beam by D4σ. Finally, although both methods produce repeatable welds, it is important to understand the differences in the reported beam diameters, divergence angles, and beam parameter products when transferring parameters between machines.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Four-Stage Multi-Physics Simulations to Assist Temperature Sensor Design for Industrial-Scale Coal-Fired Boiler

The growth of renewable energy sources presents a pressing challenge to the operation and maintenance of existing fossil fuel power plants, given that fossil fuel remains the predominant fuel source, responsible for over 60% of electricity generation in the United States. One of the main concerns within these fossil fuel power plants is the unpredictable failure of boiler tubes, resulting in emergency maintenance with significant economic and societal consequences. A reliable high-temperature sensor is necessary for in situ monitoring of boiler tubes and the safety of fossil fuel power plants. In this study, a comprehensive four-stage multi-physics computational framework is developed to assist the design, optimization installation, and operation of the high-temperature stainless-steel and quartz coaxial cable sensor (SSQ-CCS) for coal-fired boiler applications. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. With the simulation-guided sensor installation plan, the newly designed SSQ-CCSs have been employed for field testing for more than 430 days. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

42 ENGINEERING↗

DOE OSTI2025

Dual-band Ion-scale Waves in the Solar Wind: Statistical Properties and Comparison with Single-band Ion-scale Waves

We present a comprehensive statistical analysis of ion-scale waves including dual-band ion-scale waves (DBIWs) observed by the Parker Solar Probe in the solar wind. DBIWs are characterized by the simultaneous occurrence of distinct left- and right-handed polarized wave packets at higher and lower frequencies, respectively, in the spacecraft frame, implying the presence of bidirectionally propagating L-mode waves. We identify and compare DBIWs to single-band ion-scale waves (SBIWs) and investigate their spatial distributions, background magnetic field conditions, and associated inertial range turbulence characteristics. We find that DBIWs exhibit a strong preferential occurrence at heliocentric distances between 0.2 and 0.25 au (equivalently 43 and 54 R S ) in contrast to SBIWs, the occurrence rate of which peaks closer to the Sun and decreases with the heliocentric distance. DBIWs are also preferentially observed under conditions of strong Alfvénic turbulence, characterized by low magnetic compressibility and perpendicular-dominant fluctuations. These findings support a scenario in which stochastic ion heating via sufficiently large perpendicular Alfvénic fluctuation generates the ion temperature anisotropies required to excite bidirectional ion cyclotron waves. This work advances our understanding of kinetic wave generation in the solar wind and its connection to large-scale turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

A synthesis dataset of permafrost-affected soil thermal conditions for Alaska, USA

Recent observations of near-surface soil temperatures over the circumpolar Arctic show accelerated warming of permafrost-affected soils. The availability of a comprehensive near-surface permafrost and active layer dataset is critical to better understanding climate impacts and to constraining permafrost thermal conditions and its spatial distribution in land system models. We compiled a soil temperature dataset from 72 monitoring stations in Alaska using data collected by the U.S. Geological Survey, the National Park Service, and the University of Alaska Fairbanks permafrost monitoring networks. The array of monitoring stations spans a large range of latitudes from 60.9 to 71.3°N and elevations from near sea level to ~1300 m, comprising tundra and boreal forest regions. This dataset consists of monthly ground temperatures at depths up to 1 m, volumetric soil water content, snow depth, and air temperature during 1997–2016. These data have been quality controlled in collection and processing. Meanwhile, we implemented data harmonization evaluation for the processed dataset. The final product (PF-AK, v0.1) is available at the Arctic Data Center (https://doi.org/10.18739/A2KG55).

58 GEOSCIENCES↗

DOE OSTI2021

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1969

Whistler instability characteristics in a hot plasma

Whistler mode instability due to anisotropic charged particle velocity distribution, establishing general onset conditions for variable density cold plasma containing hot electrons

Crawford, F. W.↗

NASA NTRS1971

Computer program for design of two-dimensional supersonic turbine rotor blades with boundary-layer correction

A FORTRAN 4 computer program for the design of two-dimensional supersonic rotor blade sections corrected for boundary-layer displacement thickness is presented. The ideal rotor is designed by the method of characteristics to produce vortex flow within the blade passage. The boundary-layer parameters are calculated by Cohen and Reshotoko's method for laminar flow and Sasman and Cresci's method for turbulent flow. The program input consists essentially of the blade surface Mach number distribution and total flow conditions. The primary output is the corrected blade profile and the boundary-layer parameters.

Goldman, L. J.↗

NASA NTRS1972

Nonlinear actuator disk theory.

Results obtained from a recent investigation of the flowfield induced by a heavily loaded actuator disk. First, the governing nonlinear integral equations are formulated from two different points of view, and the iterative solution is briefly outlined. Calculated flow patterns are presented for representative advance ratios and blade circulation distributions. For the static condition, the experimentally observed lingering of the tip vortices in the propeller plane, and the insensitivity of the streamline pattern to thrust coefficient are both accounted for, and a 'dividing streamline' - apparently not previously discussed in the literature, is predicted for the nonstatic case. Finally, the relationship between the actuator disk flow and the zero harmonic of the flowfield induced by a finite-bladed propeller is considered.

Greenberg, M. D.↗

NASA NTRS1972

Whistler side-band growth due to nonlinear wave-particle interaction.

The distortion caused by a large-amplitude whistler (with wave normal parallel to the static magnetic field) on the energetic-electron velocity distribution of a predominantly cold magnetoplasma is derived analytically. Whistler test waves impressed on the perturbed magnetoplasma and within two narrow bands centered on the frequency of the original wave may experience large consecutive growth at the early stages of the wave-particle interaction if the unperturbed energetic-electron distribution satisfies two specified conditions. The relevance of these whistler side bands to magnetospheric phenomena is assessed; in particular, an identification of the onset of artificially stimulated emissions with the creation of whistler side bands gives good agreement with observations.

Brinca, A. L.↗

NASA NTRS1974

Measurement and correlation of aerodynamic heating to surface corrugation stiffened structures in thick turbulent boundary layers

The flow conditions for which heating distributions were measured on corrugated surfaces and wavy walls in turbulent boundary layers are shown, along with the ratio of the displacement thickness to the roughness height versus the local edge Mach number for an equivalent smooth surface. The present data are seen to greatly extend the range of data available on corrugated surfaces in turbulent boundary layers. These data were obtained by testing fullscale corrugation roughened panels in the wall boundary layer of a supersonic and hypersonic wind tunnel. The experimental program used to obtain the data is described. The data are analyzed and correlated in terms of the pertinent flow and geometric parameters. The developed correlations are compared with the available thin boundary layer data, as well as with previously published correlation techniques.

Brandon, H. J.↗