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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Preliminary prediction of long-term aging and creep behavior of AM 316 SS

This report describes the development of initial mechanism models for the long term behavior of additively manufactured (AM), laser powder-bed fusion 316H stainless steel under the conditions expected in future advanced nuclear reactors. These models focus on key features of the material microstructure and response that differ from the conventionally-manufactured wrought material. Specifically, the report describes the development of models to capture the unique response of the AM material focusing on irradiation creep and swelling, the effect of internal stress, for example caused by dislocation structure, on precipitation, and the effect of the AM grain and dislocation structure on the macroscale creep and thermal aging behavior. This single mechanism models represent progress towards a complete, physics-based model for the long-term material behavior as well as elucidate key differences in the AM material behavior, when compared to the better-understood, conventionally-manufactured 316H.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Short Term Plasticity for Artificial Neural Networks

Achieving efficient learning for AI systems was identified as a major challenge in the DOE's recently released, AI for Science , report. The human brain is capable of efficient and low-powered learning. It is likely that implementing brain-like principles will lead to more efficient AI systems. In this LDRD, I aim to contribute to this goal by creating a foundation for implementing and studying a brain phenomenon termed short term plasticity (STP) in spiking artificial neural networks within Sandia. First, data collected by the Allen Institute for Brain Science (AIBS) was analyzed to see if STP could be classified into types using the data collected. Although the data was inadequate at the time, AIBS has updated their database and created models that could be utilized in the future. Second, I began creating a software package to assess the ability of a Boltzmann machine utilizing STP to sample from national security data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Major Drivers of Long-Term Distribution Transformer Demand

Distribution transformers, used to step-down medium voltage to service-voltage level for end-use electrical consumption, are currently experiencing major shortages. Utilities are experiencing extended lead times for transformers of up to 2 years (a 4x increase on lead times pre-2022) and prices have gone up by as much as 5-6 times in the past 2 years. Current shortages have been attributed to pent-up post-pandemic demand, workforce shortages and low retention rates, component supply chain challenges, and materials shortages (grain-oriented electrical steel, aluminum, and copper). The supply of this equipment is critical for the reliability and growth of the power system, and in meeting administration climate goals in terms of electrification of demand and the growth of renewable energy. This report details some of the initial analysis conducted by the National Renewable Energy Laboratory (NREL), supported by the Department of Energy's Office of Electricity and Office of Policy, in assessing the long-term demand trends for distribution transformers. Expected increased demand is due to a confluence of not only electrification and renewable energy growth, but also in the context of aging electric infrastructure, increased frequency and severity of extreme weather events, and utility-driven investments in reliability and resiliency of the electricity distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Probabilistic Analysis of Long-Term Degradation of Microwave Cavity Flow Sensor

We are investigating a microwave resonant cavity transducer for flow sensing in the vessel of a high temperature fluid advanced reactor (AR), such as a molten salt cooled reactor (MSCR) or a sodium fast reactor (SFR). This transducer is a hollow metallic cylindrical cavity, with the flat wall of the cylinder flexible enough to undergo microscopic deflection due to dynamic fluid pressure. Membrane deflection leads to a shift in the resonant frequency, which can be detected with a spectrum analyzer. We have performed a proof-of-concept experiment of flow sensing with the transducer in liquid sodium at 340°C in impinging liquid jet geometry. The transducer remained in liquid sodium for 70 days. After removal, no structural damage was observed, and the expected transducer response was verified in a water test. Because long-term (multi-year) experimental tests of transducer resilience to harsh environment are not practical, we have developed a probabilistic model of creep to estimate transducer resilience to the harsh environment. The probabilistic model considers diffusion creep under the condition of high temperature and low stress, where the stress and temperature are allowed to be random variables with Gaussian distributions. Using the probabilistic model, we estimate inelastic membrane deflections due to creep for several temperature ranges. We conclude that for temperatures less than 650°C, creep has negligible long-term effect on the transducer performance. Since a yellowish residue was observed on the transducer surface after 70 days of immersion in liquid sodium, we have investigated possible evidence of corrosion. Chromium depletion is a typical indicator of the corrosion process in stainless steel. Scraping off a residue from the transducer and performing scanning electron microscopy (SEM) with energy dispersive analysis (EDS) did not find any chromium in the residue. Approximately 60% of the residue consisted of copper, which can be attributed to contamination of sodium due to powder residue from machining of copper and brass components of the transducer.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

WTK-LED: The WIND Toolkit Long-Term Ensemble Dataset

To satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have, we aimed at developing an updated version of the meteorological WIND Toolkit, named WIND Toolkit Long-term Ensemble Dataset (WTK-LED), which is a meteorological dataset providing time series every 5 min and 2 km, including model uncertainty of wind speed at every modeling grid point so that users are provided with a range of possible wind speeds every 2 km. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: 1) Numerical simulations covering the continental United States, Alaska, and Hawaii, with high-resolution data being available for 3 years (2018-2020). 2) Climate simulations from Argonne National Laboratories covering the North American continent, including Alaska, Canada, and most of Mexico and the Caribbean Islands. These simulations complement the new WTK-LED to offer a 4-km dataset covering 20 years, from 2001-2020. 3) Specific long-term,high-resolution offshore simulations have been conducted separately for the US coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind data set. This report focuses on a description of the land-based WTK-LED for CONUS, Hawaii, and Alaska, for the 3-year 2-km/5-min dataset and the 20-year 4-km/hourly dataset, as well as the uncertainty quantification method. We also provide limited validation results. Based on our results to date, we suggest use cases and applications for each dataset of the WTK-LED.

17 WIND ENERGY↗
DOE OSTI2024

Documentation of Air Emissions Source Term for Radionuclide NESHAP Compliance: TA-53 Building 0984 Isotope Production Facility

This paper will document the air emissions source term for the TA-53 Building 0984 Isotope Production Facility (IPF). The facility has historically been managed as a minor source under Radionuclide NESHAP regulations, but began using a wider variety of irradiation targets and a higher beam current. To support expanded generation of actinium-225 for medical diagnostic and therapeutic uses, IPF is now irradiating thorium targets and the beam current is planned to increase from 250 microamperes up to 600 microamperes. These changes merit a review of the anticipated source term under the new proposed operational conditions. The end result of the review indicates the main stack (Exhaust Stack ES-1) needs to be managed as a major source with continuous emissions monitoring. No additional advance notifications or permitting is required as a result of these operational changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aerosol Optical Properties as Part of the Long-Term Aerosol Measurements in Puerto Rico (AOP-LAMP) Field Campaign Report

The University of Puerto Rico-Rio Piedras Campus (UPR-RP) has been measuring aerosol optical, chemical, and microphysical properties at Cape San Juan (CSJ, also known as CPR) since 2004. This site has also hosted several intensive field campaigns, with context provided by the long-term measurements. Hurricane Maria largely destroyed the station on September 20, 2017, forcing a cessation of the measurements. The scientific focus of this intensive operational period was to use a U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) aerosol shelter to enable the resumption of long-term aerosol measurements. This AMF shelter is now the main aerosol shelter for CSJ operations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Near Term Reliability and Resilience: Revisiting Resilience Metrics for the Electric Grid

This report presents the metrics employed in the Near-Term Reliability and Resilience (NTRR) project to study the inter-dependencies between electric and natural gas infrastructures, particularly under challenging conditions. These metrics were developed and applied to evaluate the reliability and resilience of the electric grid and natural gas systems in near-term scenarios (within the next 10 years) involving extreme weather events and major supply disruptions. The report defines the metrics, explains how they are calculated, and describes the process by which they are used to evaluate reliability and resilience across simulated scenarios. It also demonstrates how the resilience metrics integrate with other project activities and summarizes the software tools deployed to calculate and visualize the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Pressurized Water Reactor Containment Aerosol Settling Rate for Accident Source Terms

This report documents results from MELCOR calculations performed to determine the aerosol settling rate in pressurized water reactor containments in support of the Nuclear Regulatory Commission (NRC) Regulatory Guide (RG) 1.183, “Alternative Radiological Source Terms for Evaluating Design Basis Accidents at Nuclear Power Reactors,” which is the methodology for determining alternate source terms in design basis accidents at nuclear power reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Novel and Rugged Electromagnetic Wireless System for Long-Term Subsurface CO₂ Plume Monitoring and Saturation Mapping

Novel and rugged electromagnetic wireless system for long-term subsurface CO₂ plume monitoring and saturation mapping is a Phase I SBIR project led by Cyentech Consulting LLC to develop a permanently installed, outside-casing electromagnetic monitoring system for long-term carbon storage monitoring. The project addresses a major challenge in carbon capture and storage: the need for reliable, cable-free downhole monitoring that can detect CO₂ plume movement and saturation changes without compromising well integrity through casing perforations or external umbilical cables.

58 GEOSCIENCES↗
DOE OSTI2026

Investigating Interference Term in DUNE & SBND Neutrino Interactions with ACHILLES

Understanding neutrino oscillations can help us answer some of the universe’s most fundamental questions like: Why is there more matter than antimatter? Neutrino-nucleus cross-sections (probability of neutrino interactions with nuclei) are a leading uncertainty in the measurements of neutrino oscillations. To meaningfully determine scattering parameters, measurements must be supported by robust theoretical modeling, which can be provided via event generators. In this poster, we use ACHILLES to investigate the interference term of neutrino interactions with both DUNE-ND and SBND flux configurations [1] [2]. The interference term is the quantum amplitude interference resulting from 1p1h or 2p2h neutrino-nucleon interactions, and isn't modeled in current industry standard event generators.

Serumaga, Peera [UC, San Diego (main); Fermilab]↗
DOE OSTI2023

Predicting Short-Term Deformation in the Central Valley Using Machine Learning

Land subsidence caused by excessive groundwater pumping in Central Valley, California, is a major issue that has several negative impacts such as reduced aquifer storage and damaged infrastructures which, in turn, produce an economic loss due to the high reliance on crop production. This is why it is of utmost importance to routinely monitor and assess the surface deformation occurring. Two main goals that this paper attempts to accomplish are deformation characterization and deformation prediction. The first goal is realized through the use of Principal Component Analysis (PCA) applied to a series of Interferomtric Synthetic Aperture Radar (InSAR) images that produces eigenimages displaying the key characteristics of the subsidence. Water storage changes are also directly analyzed by the use of data from the Gravity Recovery and Climate Experiment (GRACE) twin satellites and the Global Land Data Assimilation System (GLDAS). The second goal is accomplished by building a Long Short-Term Memory (LSTM) model to predict short-term deformation after developing an InSAR time series using LiCSBAS, an open-source InSAR time series package. The model is applied to the city of Madera and produces better results than a baseline averaging model and a one dimensional convolutional neural network (CNN) based on a mean squared error metric showing the effectiveness of machine learning in deformation prediction as well as the potential for incorporation in hazard mitigation models. The model results can directly aid policy makers in determining the appropriate rate of groundwater withdrawal while maintaining the safety and well-being of the population as well as the aquifers’ integrity.

58 GEOSCIENCES↗
DOE OSTI2021

A D-term Modeling Code (DMC) for Simultaneous Calibration and Full-Stokes Imaging of Very Long Baseline Interferometric Data

In this paper we present DMC, a model and associated tool for polarimetric imaging of very long baseline interferometry data sets that simultaneously reconstructs the full-Stokes emission structure along with the station-based gain and leakage calibration terms. DMC formulates the imaging problem in terms of posterior exploration, which is achieved using Hamiltonian Monte Carlo sampling. The resulting posterior distribution provides a natural quantification of uncertainty in both the image structure and the data calibration. We run DMC on both synthetic and real data sets, the results of which demonstrate its ability to accurately recover both the image structure and calibration quantities, as well as to assess their corresponding uncertainties. The framework underpinning DMC is flexible, and its specific implementation is under continued development.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Optimizing Long Term Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy Duty Fuel Cell Electric Vehicles

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This paper develops a long-term plan for refueling infrastructure deployment using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional specific vehicle fuel economy and weight, vehicle origin and destination (OD), vehicle volume by class and infrastructure costs to characterize in-mission refueling requirements for a given freight corridor. The authors applied this framework to determine the ideal long term public access locations for hydrogen refueling (constrained by existing fueling stations and dispensing technology), the minimal viable cost to deploy sufficient hydrogen fuel dispensers, and associated equipment, to accommodate a growing population of hydrogen fuel cell trucks. So the framework discussed in this paper can be expanded and applied to additional electrified powertrains as well as a larger interstate system, expanded regional corridor, or other transportation networks.

08 HYDROGEN↗
DOE OSTI2024

Long-Term Performance of Ag/AgCl Reference Electrodes for Corrosion Potential Monitoring in Radioactive Tank Waste at the Hanford Site

This work studied the exposure effects of radioactive tank waste on the long-term performance of single junction Ag/AgCl reference electrodes for corrosion potential monitoring at the Hanford Site. Electrodes from three manufacturers with very different designs were studied using open-circuit potential and electrochemical impedance measurements in radioactive tank waste. Post-test analyses were conducted on some failed electrodes using destructive and nondestructive techniques. The intrusion of the aggressive and radioactive chemicals in tank waste through the porous frit materials was the primary mechanism that led to the clogging of frit, physical and chemical degradation of AgCl bonded to Ag wire, and alteration of the internal electrolyte. Radiolytic chemical species such as H2O2 and HNO3 may have also induced the degradation of the Ag wire. The extent of electrode degradation and failure probability highly depended on the electrode design and environmental conditions. Chemicals in tank waste had stronger effects than radiation on the long-term performance of the Ag/AgCl reference electrodes.

Materials Science↗
DOE OSTI2023

New Absolute Cavity Pyrgeometer equation by application of Kirchhoff's law and adding a convection term

An equation for the Absolute Cavity Pyrgeometer (ACP) is derived from application of Kirchhoff's law and the addition of a convection term to account for the thermopile being open to the environment, unlike a domed radiometer. The equation is then used to investigate four methods to characterise key instrumental parameters using laboratory and field measurements. The first uses solar irradiance to estimate the thermopile responsivity, the second uses a minimisation method that solves for the thermopile responsivity and transmission of the cavity, and the third and fourth revisit the Reda et al. (2012) linear least squares calibration technique. Data were collected between January and November 2020, when the ACP96 and two IRIS radiometers monitoring terrestrial irradiances were available. The results indicate good agreement with IRIS irradiances using the new equation. The analysis also indicates that while the thermopile responsivity, concentrator transmission and emissivity of an ACP can be determined independently, as an open instrument, the impact of the convection term is minor in steady-state conditions but significant when the base of the instrument is being subjected to rapid artificial cooling or heating. Using laboratory characterisation of the transmission and emissivity, together with use of an estimated solar calibration of the thermopile, generated mean differences of less than 1.5 Wm -2 to the two IRIS radiometers. A minimisation method using each IRIS radiometer as the reference also provided similar results, and the derived thermopile responsivity was within 0.3 µV W -1 m 2 of the solar-calibration-derived infrared responsivity estimate of 10.5 µV W -1 m 2 estimated using a nominal solar calibration and provide irradiances within ±2 % of the terrestrial irradiance measured by the reference pyrgeometers traceable to the International System of Units (SI). The calibration method using linear least squares regression introduced by Reda et al. (2012) that relies on rapid cooling of the ACP base but utilising the new equation was found to produce consistent results but was dependent on the assumed temperature of the air above the thermopile. This study demonstrates the potential of the ACP as another independent reference radiometer for terrestrial irradiance once the magnitude of the convection coefficient and any potential variations in it have been resolved.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗