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At least 595 records · Page 33

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NASA NTRS2022

Desert Locust Cropland Damage Differentiated from Drought, with Multi-Source Remote Sensing in Ethiopia

In 2020, Ethiopia had the worst desert locust outbreak in 25 years, leading to food insecurity. Locust research has typically focused on predicting the paths and breeding grounds based on ground surveys and remote sensing of outbreak factors. In this study, we hypothesized that it is possible to detect desert locust cropland damage through the analysis of fine-scale (5–10 m) resolution satellite remote sensing datasets. We performed our analysis on 121 swarm point locations on croplands derived from the Food and Agriculture Organization (FAO) of the United Nations, and 94 ‘non-affected’ random cropland sample points generated for this study that are distributed within 20–25 km from the ‘center’ of swarm affected sample locations. Integrated Drought Condition Indices (IDCIs) and Vegetation Health Indices (VHIs) calculated for the affected sample locations for 2000–2020 were strongly correlated (R(exp 2) > 0.90) with that of the corresponding non-affected group of sample sites. Drought indices were strongly correlated with the evaluation Standardized Precipitation Evapotranspiration Indices (SPEIs) and showed that 2020 was the wettest year since 2000. In 2020, the NDVI and backscatter coefficient of cropland phenologies from the affected versus non-affected cropland sample sites showed a slightly wider, but significant gap in March (short growing season) and August-October (long growing season). Thus, slightly wider gaps in cropland phenologies between the affected and non-affected sites were likely induced from the locust damage, not drought, with fine scale data representing a larger gap.

Desert locust↗

DOE OSTI2025

A Refined BISON-Griffin Workflow For Designing Targeted TRISO Transient Experiments In The Transient Reactor Test Facility

U.S. industry is expected to deploy tristructural isotropic (TRISO) particle fuel technologies for commercial reactors within the next decade. In our previous work, we defined a preliminary transient design space for TRISO fuels, identified potential gaps in the available data, and began to develop multiphysics modeling tools that could be applied to design targeted Transient Reactor Test Facility (TREAT) experiments to fill these gaps. This work builds on that foundation by (1) updating BISON fuel performance and Griffin reactor physics models to reflect the current TREAT experiment tube and capsule designs,(2) coupling the codes to improve the accuracy and usability of the transient design analyses, and (3) demonstrating their use over an expanded design space that includes fuel burnup. The simulated mechanical responses of the TRISO particles were complex functions of fission product accumulation, fission gas release, and irradiation-induced dimensional change in the pyrolytic carbon layers. Predicted tangential stresses in particle silicon carbide layers were least compressive for preheated tests involving fresh fuels but remained compressive throughout the ranges of temperature, heat rate, and burnup considered in this work. Finally, comparisons between the potential TREAT transients and historical test reactor irradiations showed that the TREAT tests would produce significantly lower average energy deposition rates, yielding less severe transients with greater relevance to near-term commercial applications. Use of these predictive capabilities has the potential to increase the value of each test, improving the overall efficiency and cost effectiveness of transient testing for TRISO and other advanced fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Technical Gaps in Hanford High-Level Waste Solids Settling Behavior and Settling Time Evaluation for Direct Feed High-Level Waste (DFHLW) Operations

Settling of high-level waste (HLW) solids in process vessels is a key conceptual process step in providing HLW feed directly to the Hanford Waste Treatment and Immobilization Plant (WTP) HLW Vitrification Facility. Direct Feed High-Level Waste (DFHLW) is a potential approach to initiating HLW vitrification prior to completing of the WTP Pretreatment Facility. Settling would be used with subsequent supernatant decant to concentrate HLW feed. To support planning for DFHLW, Washington River Protection Solutions (WRPS) requested support from the Pacific Northwest National Laboratory to evaluate the current data set available to predict the time needed for HLW solids to settle, to identify gaps in the understanding and predictive capability of HLW solids waste settling times, and to provide scoping estimates of the potential settling time. Eight technical gaps were identified for predicting settling times and characteristics of the formed sediment layers including: Gap 1: In-Tank Settling Rates Faster than Settling of Laboratory Samples, Gap 2: Effect of Sludge Leaching/Washing on Predicted Settling Times, Gap 3: Predicting Waste Settling from Waste Chemistry (Waste Type), Gap 4: Predicting Waste Settling from Particle Size and Density Distributions (PSDDs), Gap 5: Insufficient Laboratory and In-Tank Settling Data to Represent Hanford Waste, Gap 6: Methods for Real-Time, In-Tank Tracking of Settling, Gap 7: Prediction of Sediment Erosion Resistance as a Function of Settling Time, and Gap 8: Prediction of Sediment Solids Content as a Function of Settling Time. In addition to the data gaps, an overarching observation of the settling rate and settled layer data is the significant variation in behavior. At similar solids concentrations, settling rates can vary by as much as 3 orders of magnitude depending on the source waste tank, and significantly different settling rates are noted between laboratory and in situ tests for the same waste tank. The range of average solids concentration in existing HLW sediment, which may have been quiescent for decades, can vary from less than 7 wt% to greater than 74 wt% solids. The shear strengths (or yield stresses) measured on laboratory samples range from less than 27 Pa to greater than 6400 Pa. These variations can challenge process planning for the application of a settle/decant process for DFHLW. This report describes the significance of the gaps to the settle/decant process and presents uncertainties by way of examples. Potential technical approaches for resolving these gaps are described and the estimated difficulty in resolving these gaps is evaluated. Based on the significance of the gap and the difficulty of resolution, recommendations are made to address specific gaps. Scoping estimates of the potential settling times for DFHLW solids have been made based on the existing data set with its associated gaps. Depending on the process vessel depth and final sediment concentration, substantial fractions of the scoping estimate results for settling times for characterized HLW exceed the 2-week period that has been previously assumed for process planning. There is also significant disparity, potentially greater than a factor of 5000 difference, in the estimated settling times depending on process vessel depth and final sediment solid concentration. This variation in results underscores the significance of the identified gaps and uncertainties with respect to process planning for utilizing settle/decant operations for DFHLW.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Magnetic exchange interactions in the van der Waals layered antiferromagnet MnPSe 3

Two-dimensional van der Waals compounds with magnetic ions on a honeycomb lattice are hosts to a variety of exotic behavior. The magnetic interactions in one such compound, MnPSe 3 , are investigated with elastic and inelastic neutron scattering. Magnetic excitations are observed in the magnetically ordered regime and persist to temperatures well above the ordering temperature, T N =74K, consistent with low dimensional magnetic interactions. The inelastic neutron scattering results allow a model spin Hamiltonian to be presented that includes dominant intralayer interactions of J 1ab =0.45 meV, J 2ab =0.03 meV, J 3ab =0.19 meV, consistent with theoretical predictions. Furthermore, despite the quasi-2D behavior, appreciable interlayer interactions of J c =0.031(5) meV are required to model the data. No evidence for anisotropy in the form of a spin gap is observed in the data collected. The measurements on MnPSe 3 are contrasted with those on MnPS 3 and reveal a large increase in the interlayer exchange interaction in MnPSe 3 that may stabilize the similar ordering temperatures in the bulk compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1992

PROS: An IRAF based system for analysis of x ray data

PROS is an IRAF based software package for the reduction and analysis of x-ray data. The use of a standard, portable, integrated environment provides for both multi-frequency and multi-mission analysis. The analysis of x-ray data differs from optical analysis due to the nature of the x-ray data and its acquisition during constantly varying conditions. The scarcity of data, the low signal-to-noise ratio and the large gaps in exposure time make data screening and masking an important part of the analysis. PROS was developed to support the analysis of data from the ROSAT and Einstein missions but many of the tasks have been used on data from other missions. IRAF/PROS provides a complete end-to-end system for x-ray data analysis: (1) a set of tools for importing and exporting data via FITS format -- in particular, IRAF provides a specialized event-list format, QPOE, that is compatible with its IMAGE (2-D array) format; (2) a powerful set of IRAF system capabilities for both temporal and spatial event filtering; (3) full set of imaging and graphics tasks; (4) specialized packages for scientific analysis such as spatial, spectral and timing analysis -- these consist of both general and mission specific tasks; and (5) complete system support including ftp and magnetic tape releases, electronic and conventional mail hotline support, electronic mail distribution of solutions to frequently asked questions and current known bugs. We will discuss the philosophy, architecture and development environment used by PROS to generate a portable, multimission software environment. PROS is available on all platforms that support IRAF, including Sun/Unix, VAX/VMS, HP, and Decstations. It is available on request at no charge.

Conroy, M. A.↗

DOE OSTI2022

High temperature stability and transport characteristics of hydrogen in alumina via multiscale computation

Here, the impact of hydrogen charge states on the stability and transport characteristics of hydrogen interstitials in alumina polymorphs is evaluated by multiscale computational methods including density functional theory (DFT), ab initio molecular dynamics (AIMD) and machine learned force fields. Thermodynamic calculations show that the protonic H i +1 interstitial is the most stable defect species for most values of the electronic bandgap in both and amorphous alumina (Al 2 O 3 ). Further, active learned Gaussian approximation potentials (GAP) were developed using AIMD data to study temperature dependent long time proton diffusion in alumina. Diffusivity calculations from GAP-MD simulations are found to be comparable with of the AIMD data, while being ~340 times faster and scalable to larger systems. Comparisons with diffusivity values for other interstitial charge states (H i 0 and H i -1 ) and published experimental literature indicate that H i +1 diffusion is the likely mechanism of hydrogen transport. A good agreement is obtained between H i +1 diffusivity calculated in α-Al 2 O 3 from DFT: 5.05 10 -3 exp(-0.81 eV/k B /T) cm 2 /s and reported experiment: 9.7X10 -4 exp(-0.83 eV/k B /T) cm 2 /s. Computationally and experimentally calculated energy barriers (0.81 and 0.83 eV respectively) only differ by 2.5%. Similarly, the pre-exponential diffusion coefficients only differ by 0.5 orders of magnitude. Moreover, the diffusivity of H i +1 in amorphous Al 2 O 3 in the 1000–2000 K range is calculated to be 2.53X10 -2 exp(-0.89 eV/k B /T), just one order of magnitude higher than the corresponding value in α-Al 2 O 3 . This suggests that local structural disorder does not significantly affect the energy landscape and diffusion behavior of H i +1 in Al 2 O 3 . Overall, these results show promise for the application of alumina polymorphs as hydrogen permeation barriers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗

DOE OSTI2022

Brownian bridge-based speed imputation technique for truck energy consumption and emissions estimation

The available truck Global Positioning System (GPS) data, typically collected with large time gaps, rely on imputation techniques to obtain second-by-second data that are required in models for estimating truck energy consumption and emissions. However, existing speed imputation techniques either require a large amount of high-resolution data for model training or rely on special movement assumptions. Here, to fill the gap and effectively apply the low-resolution truck GPS datasets, this paper proposes a simple imputation technique that adopts the Brownian bridge structure to impute missing speed data. The proposed technique introduces a feasible imputation region and a combined drift into the imputation procedure to capture vehicle acceleration constraint, travel distance constraint, and speed volatility. The calibrated model is applied to a set of low-resolution truck GPS data. The results demonstrate the robustness of the proposed technique in enhancing estimation accuracy when using low-resolution GPS data to estimate fuel consumption and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Complete and Correct Transfer of Information (CACTI)

Many distributed systems, file transfer mechanisms, and message passing systems offer reliability mechanisms such as acknowledgements, retries, and durability. While these tools may be “good enough” for their typical use cases, they may not offer sufficient coverage for the wide range of faults that impact data transfers and communication. A gap in the reliability measures may lead to some small amount of data loss. Some high-consequence systems cannot tolerate the loss or corruption of even a single record. We present seven principles that will counter a wide range of faults and protect against data loss and corruption. These principles bring together lessons learned from a wide range of technologies and can inform appropriate system design and application usage. These principles will help readers reason on how prevent data loss in a multi-hop pipeline and how to properly use tools that may have a deficiency in reliability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Detection and Association of Operational Events using DAS and Seismometers (FY 2025 Mid-Year Report)

This mid-year report summarizes ongoing work to identify anomalous vibration signals indicative of potential containment breaches. This work includes compiling continuous seismic datasets and testing and refining underground detection and geolocation techniques. In the first two quarters of FY25, we have completed two project work plan tasks: (1) creating a database of continuous waveforms and ground truth event data from multiple modalities and (2) refining and implementing a detection and association algorithm to create a catalog of anomalous underground activities. This report contains a summary of the seismic database including the continuous seismic data collected by a dense array of surface seismic stations above Pleasant Gap Mine, and continuous seismic data collected using subsurface distributed acoustic sensing (DAS) in the subsurface at Sanford Underground Research Facility (SURF) and the ground truth information gathered from both sites. This report also includes results from refining and applying a dynamic power spectral density detector to both continuous seismic datasets. Finally, the report provides an initial catalog of subsurface operational events from both sensing modalities.

58 GEOSCIENCES↗

NASA NTRS2003

Sensor Web in Antarctica: Developing an Intelligent, Autonomous Platform for Locating Biological Flourishes in Cryogenic Environments

The most rigorous tests of the ability to detect extant life will occur where biotic activity is limited by severe environmental conditions. Cryogenic environments are among the most severe-the energy and nutrients needed for biological activity are in short supply while the climate itself is actively destructive to biological mechanisms. In such settings biological activity is often limited to brief flourishes, occurring only when and where conditions are at their most favorable. The closer that typical regional conditions approach conditions that are actively hostile , the more widely distributed biological blooms will be in both time and space. On a spatial dimension of a few meters or a time dimension of a few days, biological activity becomes much more difficult to detect. One way to overcome this difficulty is to establish a Sensor Web that can monitor microclimates over appropriate scales of time and distance, allowing a continuous virtual presence for instant recognition of favorable conditions. A more sophisticated Sensor Web, incorporating metabolic sensors, can effectively meet the challenge to be in "the right place in the right time". This is particularly of value in planetary surface missions, where limited mobility and mission timelines require extremely efficient sample and data acquisition. Sensor Webs can be an effective way to fill the gap between broad scale orbital data collection and fine-scale surface lander science. We are in the process of developing an intelligent, distributed and autonomous Sensor Web that will allow us to monitor microclimate under severe cryogenic conditions, approaching those extant on the surface of Mars. Ultimately this Sensor Web will include the ability to detect and/or establish limits on extant microbiological activity through incorporation of novel metabolic gas sensors. Here we report the results of our first deployment of a Sensor Web prototype in a previously unexplored high altitude East Antarctic Plateau "micro-oasis" at the MacAlpine Hills, Law Glacier, Antarctica.

Delin, K. A.↗

DOE OSTI2022

NXREFINE

NXRefine implements a complete workflow for both data acquisition and reduction of single crystal diffuse x-ray scattering collected as a series of area detector frames during continuous sample rotation. The data are stored in HDF5 files, which conform to the NeXus data format standard. These files contain a comprehensive set of metadata, including the incident wavelength, powder calibration scans used to define detector distances, beam centers, and yaw, pitch, and roll corrections. Automated peak searches of the three-dimensional data arrays define a set of Bragg peaks that are used to define an orientation matrix, defined according to Busing and Levy, which is then used to transform the data from angular coordinates to reciprocal space coordinates using the CCTW program. Multiple rotations at different detector translations and offset rotation axes are combined to ensure that there are no gaps in the reconstructed data, and allow the construction of masks to eliminate detector artifacts due to Compton scattering within the sensor layers. Finally, the data can be transformed into 3D-ΔPDF maps using the punch-and-fill method after symmetrization.

OSBORN, RAYMOND↗

NASA NTRS2016

A Comparison of Van Allen Belt Radiation Environment Modeling Programs: AE8/AP8 Legacy, AE9/AP9, and SPENVIS

In the space surrounding Earth there exists an active radiation environment consisting mostly of electrons and protons that have been trapped by Earths magnetic field. This radiation, also known as the Van Allen Belts, has the potential to damage man-made satellites in orbit; thus, proper precautions must be taken to shield NASA assets from this phenomenon. Data on the Van Allen Belts has been collected continuously by a multitude of space-based instruments since the beginning of space exploration. Subsequently, using theory to fill in the gaps in the collected data, computer models have been developed that take in the orbital information of a hypothetical mission and output the expected particle fluence and flux for that orbit. However, as new versions of the modeling system are released, users are left wondering how the new version differs from the old. Therefore, we performed a comparison of three different editions of the modeling system: AE8/AP8 (legacy), which is included in the model 9 graphical user interface as an option for ones calculations, AE9/AP9, and the Space Environment Information System (SPENVIS), which is an online-based form of AE8/AP8 developed by NASA and the European Space Agency that changed the code to allow the program to extrapolate data to predict fluence and flux at higher energies. Although this evaluation is still ongoing, it is predicted that the model 8 (legacy) and SPENVIS version will have identical outputs with the exception of the extended energy levels from SPENVIS, while model 9 will provide different fluences than model 8 based on additional magnetic field descriptions and on-orbit data.

Modeling Programs↗

DOE OSTI2022

Machine learning for ultrasonic nondestructive examination of welding defects: A systematic review

Recent years have seen a substantial increase in the application of machine learning (ML) for automated analysis of nondestructive examination (NDE) data. One of the applications of interest is the use of ML for the analysis of data from in-service inspection of welds in nuclear power and other industries. These types of inspections are performed in accordance with criteria described in the ASME Boiler and Pressure Vessel Code and require the use of reliable NDE techniques. The rapid growth in ML methods and the diversity of possible approaches indicate a need to assess the current capabilities of ML and automated data analysis for NDE and identify any gaps or shortcomings in current ML technologies as applied to the automated analysis of NDE data. In particular, there is a need to determine the impact of ML on the NDE reliability. This paper discusses the findings from a literature survey on the current state of ML for the automated analysis of data from ultrasonic NDE of weld flaws. It discusses an overview of ultrasonic NDE as used for weld inspections in nuclear power and other industries. Herein, data sets and ML models used in the literature are summarized, along with a generally applicable workflow for ML. Findings on the capabilities, limitations and potential gaps in feature selection, data selection, and ML model optimization are discussed. The paper identified several needs for quantifying and validating the performance of ML methods for ultrasonic NDE, including the need for common data sets.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Optimizing Error-Bounded Lossy Compression for Scientific Data by Dynamic Spline Interpolation

Today's scientific simulations are producing vast volumes of data that cannot be stored and transferred efficiently because of limited storage capacity, parallel I/O bandwidth, and network bandwidth. The situation is getting worse over time because of the ever-increasing gap between relatively slow data transfer speed and fast-growing computation power in modern supercomputers. Error-bounded lossy compression is becoming one of the most critical techniques for resolving the big scientific data issue, in that it can significantly reduce the scientific data volume while guaranteeing that the reconstructed data is valid for users because of its compression-error-bounding feature. In this paper, we present a novel error-bounded lossy compressor based on a state-of-the-art prediction-based compression framework. Our solution exhibits substantially better compression quality than all of the existing error-bounded lossy compressors, with comparable compression speed. Specifically, our contribution is threefold. (1) We provide an in-depth analysis of why the best-existing prediction-based lossy compressor can only minimally improve the compression quality. (2) We propose a dynamic spline interpolation approach with a series of optimization strategies that can significantly improve the data prediction accuracy, substantially improving the compression quality in turn. (3) We perform a thorough evaluation using six real-world scientific simulation datasets across different science domains to evaluate our solution vs. all other related works. Experiments show that the compression ratio of our solution is higher than that of the second-best lossy compressor by 20%similar to 460% with the same error bound in most of the cases.

Zhao, Kai↗

NASA NTRS1989

Experiments and scaling laws for catastrophic collisions

The existing data on shattering impacts are reviewed using natural silicate, ice, and cement-mortar targets. A comprehensive data base containing the most important parameters describing these experiments was prepared. The collisional energy needed to shatter consolidated homogeneous targets and the ensuing fragment size distributions have been well studied experimentally. However, major gaps exist in the data on fragment velocity and rotational distributions, as well as collisional energy partitioning for these targets. Current scaling laws lead to predicted outcomes of asteroid collisions that are inconsistent with interpretations of astronomical data.

Fujiwara, A.↗

DOE OSTI2021

Uranium carbide properties for advanced fuel modeling – A review

Uranium carbides are receiving renewed interest as a preferred nuclear fuel composition for advanced reactors due to their numerous favorable properties. Like many other refractory and transition metal carbides these compounds exist in both hypo- and hyper-stoichiometric compositions which results in significant variations in physical, thermal, and mechanical properties. This manuscript surveys both historic and recent literature to compile important properties data mainly as a function of temperature and carbon content to support fuel performance modeling. Expressions and fits for such properties are also suggested when allowed by complete data sets. Finally, the manuscript also attempts to highlight gaps and discrepancies in the reported data to assist the nuclear fuels community identify key areas that may require further attention in terms of future research and development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2005

Characterization of the Space Shuttle Ascent Debris using CFD Methods

After video analysis of space shuttle flight STS-107's ascent showed that an object shed from the bipod-ramp region impacted the left wing, a transport analysis was initiated to determine a credible flight path and impact velocity for the piece of debris. This debris transport analysis was performed both during orbit, and after the subsequent re-entry accident. The analysis provided an accurate prediction of the velocity a large piece of foam bipod ramp would have as it impacted the wing leading edge. This prediction was corroborated by video analysis and fully-coupled CFD/six degree of freedom (DOF) simulations. While the prediction of impact velocity was accurate enough to predict critical damage in this case, one of the recommendations of the Columbia Accident Investigation Board (CAIB) for return-to-flight (RTF) was to analyze the complete debris environment experienced by the shuttle stack on ascent. This includes categorizing all possible debris sources, their probable geometric and aerodynamic characteristics, and their potential for damage. This paper is chiefly concerned with predicting the aerodynamic characteristics of a variety of potential debris sources (insulating foam and cork, nose-cone ablator, ice, ...) for the shuttle ascent configuration using CFD methods. These aerodynamic characteristics are used in the debris transport analysis to predict flight path, impact velocity and angle, and provide statistical variation to perform risk analyses where appropriate. The debris aerodynamic characteristics are difficult to determine using traditional methods, such as static or dynamic test data, due to the scaling requirements of simulating a typical debris event. The use of CFD methods has been a critical element for building confidence in the accuracy of the debris transport code by bridging the gap between existing aerodynamic data and the dynamics of full-scale, in-flight events.

Murman, Scott M.↗