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DOE OSTI2023

Visualizing Uranium Crystallization from Melt: Experiment-Informed Phase Field Modeling and Machine Learning

The focus of this project was to observe and simulate the solidification of uranium metal at the crystallographic level from its molten state. Melting experiments were conducted at two different scales to observe microstructural evolution using either a laboratory-scale induction furnace (hundreds of grams of metal) or a microscope heating stage (hundreds of milligrams of metal), respectively. Experimental parameters and characterization data were then used to inform a phase field model of gamma-U crystal growth as dendrites with or without secondary phase impurities in the form of uranium carbide particles. Finally, training datasets were generated by the phase field model as inputs to a neural network, developed with the aim of providing a faster, cheaper surrogate model for microstructural simulations within a given parameter space. Progress is reported herein for each of these task areas. Ultimately, 1) an optical microscope heating stage capability has been stood-up for uranium metal solidification studies, 2) a phase field model was advanced to simulate multiple uranium grains growing in the presence of carbide impurity particles and 3) a neural network was constructed and optimized to predict the microstructure features of individually growing uranium crystals.

36 MATERIALS SCIENCE↗

NASA NTRS2015

Experimental Results of the First Two Stages of an Advanced Transonic Core Compressor Under Isolated and Multi-Stage Conditions

NASA's Environmentally Responsible Aviation (ERA) Program calls for investigation of the technology barriers associated with improved fuel efficiency of large gas turbine engines. Under ERA the task for a High Pressure Ratio Core Technology program calls for a higher overall pressure ratio of 60 to 70. This mean that the HPC would have to almost double in pressure ratio and keep its high level of efficiency. The challenge is how to match the corrected mass flow rate of the front two supersonic high reaction and high corrected tip speed stages with a total pressure ratio of 3.5. NASA and GE teamed to address this challenge by using the initial geometry of an advanced GE compressor design to meet the requirements of the first 2 stages of the very high pressure ratio core compressor. The rig was configured to run as a 2 stage machine, with Strut and IGV, Rotor 1 and Stator 1 run as independent tests which were then followed by adding the second stage. The goal is to fully understand the stage performances under isolated and multi-stage conditions and fully understand any differences and provide a detailed aerodynamic data set for CFD validation. Full use was made of steady and unsteady measurement methods to isolate fluid dynamics loss source mechanisms due to interaction and endwalls. The paper will present the description of the compressor test article, its predicted performance and operability, and the experimental results for both the single stage and two stage configurations. We focus the detailed measurements on 97 and 100 of design speed at 3 vane setting angles.

turbomachinery↗

DOE OSTI2018

Structure of a Deformed Inhomogeneous Material on the Data of Acoustic Emission and X-Ray Computer Microtomography

Accumulation of defects at various stages of the deformation of a structurally inhomogeneous material (granite) has been studied using two nondestructive methods: acoustic emission (AE) and X-ray computer microtomorgaphy (CT). The quasi-static testing of cylindrical samples of a Westerly granite was carried out under uniaxial compression. The control of the defect formation was realized using the real-time monitoring of acoustic emission. For each sample under study, several steps of the loading and tomographic imaging have been performed. We have found that an exponential or power-law function of the energy distribution of the AE signals makes it possible to select a sample region, in which the system of defects has transited into a self-organized criticality state and large cracks have been formed. This result coincides with the data of the X-ray tomography Computer Microtomography.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Testing Rod Seal Leakage of a 700 HP Reciprocating Compressor

Methane emissions from reciprocating compressors in the U.S. natural gas industry account for over 72.4 Bcf per year according to a 2006 statement by the United States Environmental Protection Agency. Methane also has a global warming potential 50 times greater than carbon monoxide. Reciprocating compressors are the machinery type with the highest contribution to methane emissions at natural gas transmissions stations. The largest contributing factor comes from the sealing components in the packing components around the piston rod. SwRI, therefore, designed and setup a test loop to perform baseline packing leakage measurements on a four stage 700 HP JGT/4 compressor. The goal was to improve upon current packing leakage models and to compare new seals vs. used seals. The test loop design is described including the limits of operation. The Data Acquisition System (DAQ), including data measurements, is also fully described. The project shows the results of the commissioning process that verified the operation of all the components. Once the loop was commissioned, SwRI performed baseline packing leakage for multiple pressure ratios on each of the four stages of the compressor. The data was collected to develop an analytical model of the packing leakage. Finally, similar testing was performed after replacing the typical rod seal packing with used packing. The used packing leakage was compared to the baseline packing leakage.

03 NATURAL GAS↗

DOE OSTI2025

ExINP NSA Ice Nucleating Particle Concentrations

This data set comprises cumulative ambient ice-nucleating particle (INP) concentrations measured at the National Oceanic and Atmospheric Administration's (NOAA’s) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site and ~ 6 km northeast of the town of Utqiaġvik. Our INP abundance data were generated using a combination of online instrument, the Portable Ice Nucleation Experiment chamber ver. 3 (PINE-03), and an offline cold stage, the West Texas Cryogenic Refrigerator Applied to Freezing Test system (WT-CRAFT). Our online INP data are all from the Examining the Ice-Nucleating Particles from NSA (ExINP-NSA) campaign conducted from October 19, 2021 to May 24, 2024. The offline INP concentration analysis was performed at West Texas A&M University for aerosol particle samples collected on polycarbonate filters (with 0.2-micron diameter pores). The PINE-03 measurements, as well as sampling activities for offline INP measurements, were conducted using the BRW site. An inset laminar sampling stack was mounted to the instrument platform, allowing PINE-03 to intake particle-laden air. For most of the campaign period, the semi-autonomous PINE-03 chamber was remotely controlled from West Texas A&M University using the LabView interface through the BeyondTrust remote-access console. PINE-03 was set to conduct an immersion freezing expansion experiment (i.e., simulated adiabatic cooling along with RHw at or above 100%). Except during the scheduled maintenance periods, the time resolution of each expansion experiment was approximately 12 minutes. PINE-03 continuously measured INP concentrations during the entire campaign without any substantial breaks. For most of the campaign period, PINE scanned its set-point vessel air temperatures from -14 °C to -31 °C and back to -14 °C about every 120 minutes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

ExINP NSA Ice Nucleating Particle Concentrations

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2005

Combining MISR and MODIS data to automatically catalogue smoke plumes in North America

We are in the early stages of work on EPA task to investigate the effects of fires on air quality in North America, led by Jennifer Logan of Harvard University. JPL's contribution to this study is to find thousands of smoke plumes in satellite images of North America, and derive statistics about their geographic distribution, extent, orientation, and injection height.

smoke plume↗

NASA NTRS2009

Reefing of Quarter Spherical Ribbon Parachutes used in the Ares I First Stage Deceleration Subsystem

Normalizing drop test reefed drag area for suspension line length with data from Wolf allows best match of test results with Knacke reefing ratio curve. Various sizes and porosities of quarter spherical ribbon parachutes were tested. All appear to fit the published reefing ratio curve-quarter spherical parachutes match.

Schmidt, Jason R.↗

DOE OSTI2024

Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments

In both plant breeding and crop management, interpretability plays a crucial role in instilling trust in AI-driven approaches and enabling the provision of actionable insights. The primary objective of this research is to explore and evaluate the potential contributions of deep learning network architectures that employ stacked LSTM for end-of-season maize grain yield prediction. A secondary aim is to expand the capabilities of these networks by adapting them to better accommodate and leverage the multi-modality properties of remote sensing data. In this study, a multi-modal deep learning architecture that assimilates inputs from heterogeneous data streams, including high-resolution hyperspectral imagery, LiDAR point clouds, and environmental data, is proposed to forecast maize crop yields. The architecture includes attention mechanisms that assign varying levels of importance to different modalities and temporal features that, reflect the dynamics of plant growth and environmental interactions. The interpretability of the attention weights is investigated in multi-modal networks that seek to both improve predictions and attribute crop yield outcomes to genetic and environmental variables. This approach also contributes to increased interpretability of the model's predictions. The temporal attention weight distributions highlighted relevant factors and critical growth stages that contribute to the predictions. The results of this study affirm that the attention weights are consistent with recognized biological growth stages, thereby substantiating the network's capability to learn biologically interpretable features. Accuracies of the model's predictions of yield ranged from 0.82-0.93 R 2 ref in this genetics-focused study, further highlighting the potential of attention-based models. Further, this research facilitates understanding of how multi-modality remote sensing aligns with the physiological stages of maize. The proposed architecture shows promise in improving predictions and offering interpretable insights into the factors affecting maize crop yields, while demonstrating the impact of data collection by different modalities through the growing season. By identifying relevant factors and critical growth stages, the model's attention weights provide valuable information that can be used in both plant breeding and crop management. The consistency of attention weights with biological growth stages reinforces the potential of deep learning networks in agricultural applications, particularly in leveraging remote sensing data for yield prediction. To the best of our knowledge, this is the first study that investigates the use of hyperspectral and LiDAR UAV time series data for explaining/interpreting plant growth stages within deep learning networks and forecasting plot-level maize grain yield using late fusion modalities with attention mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

Calculation and Correlation of the Unsteady Flowfield in a High Pressure Turbine

Forced vibrations in turbomachinery components can cause blades to crack or fail due to high-cycle fatigue. Such forced response problems will become more pronounced in newer engines with higher pressure ratios and smaller axial gap between blade rows. An accurate numerical prediction of the unsteady aerodynamics phenomena that cause resonant forced vibrations is increasingly important to designers. Validation of the computational fluid dynamics (CFD) codes used to model the unsteady aerodynamic excitations is necessary before these codes can be used with confidence. Recently published benchmark data, including unsteady pressures and vibratory strains, for a high-pressure turbine stage makes such code validation possible. In the present work, a three dimensional, unsteady, multi blade-row, Reynolds-Averaged Navier Stokes code is applied to a turbine stage that was recently tested in a short duration test facility. Two configurations with three operating conditions corresponding to modes 2, 3, and 4 crossings on the Campbell diagram are analyzed. Unsteady pressures on the rotor surface are compared with data.

Bakhle, Milind A.↗

NASA NTRS2010

Processing AIRS Scientific Data Through Level 3

The Atmospheric Infra-Red Sounder (AIRS) Science Processing System (SPS) is a collection of computer programs, known as product generation executives (PGEs). The AIRS SPS PGEs are used for processing measurements received from the AIRS suite of infrared and microwave instruments orbiting the Earth onboard NASA's Aqua spacecraft. Early stages of the AIRS SPS development were described in a prior NASA Tech Briefs article: Initial Processing of Infrared Spectral Data (NPO-35243), Vol. 28, No. 11 (November 2004), page 39. In summary: Starting from Level 0 (representing raw AIRS data), the AIRS SPS PGEs and the data products they produce are identified by alphanumeric labels (1A, 1B, 2, and 3) representing successive stages or levels of processing. The previous NASA Tech Briefs article described processing through Level 2, the output of which comprises geo-located atmospheric data products such as temperature and humidity profiles among others. The AIRS Level 3 PGE samples selected information from the Level 2 standard products to produce a single global gridded product. One Level 3 product is generated for each day s collection of Level 2 data. In addition, daily Level 3 products are aggregated into two multiday products: an eight-day (half the orbital repeat cycle) product and monthly (calendar month) product.

Granger, Stephanie↗

DOE OSTI2016

Comparisons between a priori Uncertainty Quantification and Calculation/Measurement Discrepancies Applied to the MERCI UO{sub 2} Fuel Rod Decay Heat Experiment

In 2008, an UO{sub 2} fuel rod was irradiated up to ∼ 3.5 GWd/tHL in the CEA/Saclay research reactor Osiris through the MERCI experiment. Some rod's pellets were analysed. Experimental results were obtained: - fuel rod decay heat measurement by calorimetry (cooling times from 27 minutes to 42 days), - evaluation of the amounts of some nuclei (U, Pu, Cs, Nd...) by isotopic dilution mass spectrometry, - nuclide activities. Comparison of type (C - M)/M where C is the calculated decay heat and M the experimentally measured decay heat was reported in reference. Neutronics flux was computed by CEA TRIPOLI-4 Monte-Carlo or APOLLO2 deterministic transport code system. Irradiation and cooling phases were simulated with CEA DARWIN/PEPIN2 code system. Good agreements were globally shown between numerical simulation results and experimental measurements on total decay heat. Uncertainty propagation in this previous work was established from Rebah's studies. These last years, within the framework of supports to its industrial partners EDF and Areva, the CEA/DEN has implemented two different approaches to propagate nuclear data uncertainties to depletion code outputs. A direct forward deterministic perturbation method using sensitivity profiles was implemented in the French industrial depletion code system DARWIN/PEPIN2. Meanwhile, a propagation based on Monte Carlo correlated sampling was achieved using the CEA uncertainty platform URANIE and the new generation depletion code MENDEL. Both methods will be described in this article. Uncertainties on nuclear data (independent fission yields, multigroup microscopic cross sections, radioactive decay constants, radioactive decay branching ratio and radioactive decay energies) are propagated to decay heat and isotopic concentrations. To match MERCI first study, flux computation is realized by APOLLO2. Furthermore, uncertainty quantification (UQ) is re-evaluated by both DARWIN/PEPIN2 and MENDEL codes. It is an important stage in the process of validating both depletion codes with their respective data library. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Pacific Lamprey Translocations to the Snake River Boost Abundance of All Life Stages

Abstract The Pacific Lamprey Entosphenus tridentatus is an anadromous fish that has severely declined in the Snake River basin. In 2007, the Nez Perce Tribe initiated translocation of adults to this region from the main‐stem Columbia River and has continued the translocations to this day. These actions are aimed at restoring larval abundance along with holistic habitat improvements. We performed parentage and sibship analyses with 260 single‐nucleotide polymorphism loci to monitor productivity of translocated lamprey over a decade (2007–2018). These results provide the first direct evidence that translocations boosted larval abundance, increased juvenile production in the interior Columbia River (~3% in 2017 and 2018), and demonstrated successful migration to the Pacific Ocean. Per capita juvenile production from Snake River adult lamprey translocations out‐performed that of their volitionally migrating counterparts in the interior Columbia River, demonstrating that translocating adults to suitable habitats increased overall productivity. We projected that the translocations may eventually return enough adult offspring to the Columbia River to replace the annual take of adults for translocations, despite many adults likely returning to other basins. These translocations are also restoring Pacific Lamprey to historical areas where they had been nearly extirpated, which has impactful benefits both culturally and ecologically. Further, this study provided an unprecedented volume of data that has redefined key biological attributes, including timing of life stage transformation (average of 6.7‐year‐old juveniles), larval growth rates (~22 mm/year for the first 4 years), ocean duration (average of 5.1 years), dispersal (~3% of Snake River‐origin adults that return to the Columbia River will divert to the Willamette River), and life span (median age of postspawn adults was 12.9 years). We even quantified a new biological phenomenon of delayed spawning, which occurs at low rates (~9%) in nature. These data provide an opportunity to monitor ongoing translocation efforts and inform adaptive management to aid species recovery.

Hess, Jon E.↗

NASA NTRS1975

Usefulness of LANDSAT data for monitoring plant development and range conditions in California's annual grassland

A network of sampling sites throughout the annual grassland region of California was established to correlate plant growth stages and forage production to climatic and other environmental factors. Plant growth and range conditions were further related to geographic location and seasonal variations. A sequence of LANDSAT data was obtained covering critical periods in the growth cycle. This was analyzed by both photointerpretation and computer aided techniques. Image characteristics and spectral reflectance data were then related to forage production, range condition, range site and changing growth conditions. It was determined that repeat sequences with LANDSAT color composite images do provide a means for monitoring changes in range condition. Spectral radiance data obtained from magnetic tape can be used to determine quantitatively the critical stages in the forage growth cycle. A computer ratioing technique provided a sensitive indicator of changes in growth stages and an indication of the relative differences in forage production between range sites.

Carneggie, D. M.↗

DOE OSTI2021

Groundwater regulates interannual variations in evapotranspiration in a riparian semiarid ecosystem

Dryland ecosystems are an important component of Earth’s carbon, water, and energy budgets. Changes in hydroclimatic conditions can significantly alter land surface fluxes in these ecosystems. In regions with groundwater-river water exchange, land surface fluxes are strongly modulated by groundwater table fluctuations in response to river stage variations; however, interactions between fluxes and groundwater remain poorly understood in drylands. Here, we use eddy covariance data collected in paired upland and riparian semiarid ecosystems during two years with contrasting river flow conditions to examine interactions among river stage conditions, water table dynamics, meteorological drivers, and ecosystem fluxes. Elevated groundwater availability resulting from groundwater-surface water exchange at the riparian site enhanced the latent heat flux (LE, the energy form of evapotranspiration), which was sustained longer in the growing season during both years. At the upland site, mean LE during the dry season differed by less than 2% between the two years. In contrast, at the riparian site contrasting river flow conditions resulted in a 41% difference in peak monthly LE between the two years. The two-year mean LE in the summer at the riparian site was twice that at the upland site. Carbon uptake (NEP) and LE were well correlated at the upland site during both years, but at the riparian site enhanced summertime LE during the high river flow year did not correspond t enhanced NEP. Our results demonstrate that enhanced groundwater availability modulated by river stage variability is a critical driver of land surface fluxes in semiarid riparian ecosystems.

Missik, Justine E.↗

DOE OSTI2016

SkyMine Beneficial CO 2 Use Project

This Final Report addresses accomplishments achieved during Phase 1 and Phase 2 of the SkyMine® Carbon Mineralization Commercial Scale Pilot Project. The primary objectives of this project were to design, construct, and operate a system to capture CO₂ from a slipstream of flue gas from a commercial coal-fired cement kiln, convert that CO₂ into products having commercial value as an example of Carbon Capture and Beneficial Re-Use, show the economic viability of the CO₂ capture and conversion process, and thereby advance the technology to a level of commercial scale completion with the ability for further proliferation. The project also substantiates market opportunities for the technology by sales of chemicals into existing markets, and has identified opportunities to improve technology performance and reduce costs during the normal course of operations. The primary objectives of Phase 1 of the project were to elaborate proven SkyMine® process chemistry to commercial pilot-scale operation and complete the preliminary design for the pilot plant to be built and operated in Phase 2. During Phase 2, Pilot System Engineering Design, Construction and Testing, supporting research and development was conducted at a field test unit to collect data that aided in detailed designs of the commercial scale pilot unit; final detailed designs were completed; the commercial scale pilot plant is in its final stages of construction; and a test program has been designed and will be implemented to collect data from the facility to evaluate the technical viability of the process for resulting in an overall net reduction in CO 2 emitted into the atmosphere through a process that is run and conducted in a carbon negative manner. The objective of Phase 2b was to build the commercial scale pilot plant to be operated and tested in Phase 2c. By June 30, 2015, the plant was +99% constructed and completed.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Synthetic aperture radar signal processing on the MPP

Satellite-borne Synthetic Aperture Radars (SAR) sense areas of several thousand square kilometers in seconds and transmit phase history signal data several tens of megabits per second. The Shuttle Imaging Radar-B (SIR-B) has a variable swath of 20 to 50 km and acquired data over 100 kms along track in about 13 seconds. With the simplification of separability of the reference function, the processing still requires considerable resources; high speed I/O, large memory and fast computation. Processing systems with regular hardware take hours to process one Seasat image and about one hour for a SIR-B image. Bringing this processing time closer to acquisition times requires an end-to-end system solution. For the purpose of demonstration, software was implemented on the present Massively Parallel Processor (MPP) configuration for processing Seasat and SIR-B data. The software takes advantage of the high processing speed offered by the MPP, the large Staging Buffer, and the high speed I/O between the MPP array unit and the Staging Buffer. It was found that with unoptimized Parallel Pascal code, the processing time on the MPP for a 4096 x 4096 sample subset of signal data ranges between 18 and 30.2 seconds depending on options.

Ramapriyan, H. K.↗

DOE OSTI2018

Managing Data on Tiered Storage for Scientific Workflows (MaDaTS) v1.1.2

MaDaTS provides an integrated data management and workflow execution framework on multi-tiered storage systems. Users of MaDaTS can execute a workflow by either specifying the workflow stages in a YAML description file, or use the API to manage the workflow through a Virtual Data Space (VDS) abstraction.

Ramakrishnan, Lavanya↗