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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Barriers and Alternatives to Encryption in Critical Nuclear Systems

Over the past decade, cybersecurity researchers have released multiple studies highlighting the insecure nature of I&C system communication protocols. In response, standards bodies have addressed the issue by adding the ability to encrypt communications to some protocols in some cases, while control system engineers have argued that encryption within these kinds of high consequence systems is in fact dangerous. Certainly, control system information between systems should be protected. But encrypting the information may not be the best way to do so. In fact, while in IT systems vendors are concerned with confidentiality, integrity, and availability, frequently in that order, in OT systems engineers are much more concerned with availability and integrity that confidentiality. In this paper, we will counter specific arguments against encrypting control system traffic, and present potential alternatives to encryption that support nuclear OT system needs more strongly that commodity IT system needs while still providing robust integrity and availability guarantees.

42 ENGINEERING↗
DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Trust in News as Moderated by Known Truth Assessments and Source

Disinformation has become a problem in various spaces, from social media to organizations. Given the lack of evidence and transparency surrounding organizational disinformation, we aim to understand issue of information exposure effect and source trust from the lens of traditional information consumption online. Using an online experiment and multi-level mixed-effects modeling, we find that the exposure effect exists even over only two exposures to a headline, as long as participants are not shown fact-checking. Fact-checking can be effective in reducing the impact of the exposure effect. Additionally, we find that participants trusted sources significantly more before seeing the headlines. The possible presence of disinformation reduces trust in sources, even when considered highly neutral and reputable. These findings can inform simulations of agent interactions with misinformation as well as future experimental designs focused on evaluations of belief and trust based on recognizability of a source.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Mobile Sensing for Wind Field Estimation in Wind Farms: Preprint

This paper introduces a novel approach for estimating the wind field over an entire wind farm using a mobile sensor to collect limited amounts of data. The proposed method estimates the boundary conditions of a simplified turbine wake model by computing the model sensitivity matrix and using a recursive least-squares algorithm to recover the model parameters from the wind field measurements. To address the fact that it is not practical to take measurements across the entire wind farm, the proposed method classifies each area on the map based on its sensitivity to parameter variations. This classification is then used to generate a suitable path for a mobile sensor, which is charged with collecting data for the recursive least-squares algorithm. The proposed framework can successfully estimate the model boundary conditions using just the measurements collected along the path of the mobile sensor. This preliminary result paves the way for using real-time wind field estimates for the coordinated control of all the turbines within a wind farm.

estimation↗
DOE OSTI2025

Performance Evaluation of Weather@home2 Simulations over West African Region

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

West Africa↗
DOE OSTI2021

Recovery of Rare Earth Oxides from Flotation Concentrates of Bastnaesite Ore by Ultra-Fine Centrifugal Concentration

Historically, the ability to effectively separate carbonate gangue from bastnaesite via flotation has frequently proven to be challenging without sacrificing significant rare earth oxide (REO) grade or recovery. However, in light of the fact that the rare earth bearing minerals often exhibit higher specific gravities than the carbonate gangue, the possibility exists that the use of gravity separation could be used to achieve such a selective separation. This however is complicated by the fact that, in cases such as this study when the liberation size is finer than 50 microns, most traditional gravity separation methods become increasingly challenging. The aim of this study is to determine the applicability of centrifugal concentrators to beneficiate ultra-fine (UF) bastnaesite and calcite bearing flotation concentrates. By using a UF Falcon, it was possible to achieve initial gravity REO recoveries exceeding 90% while rejecting on the order of 25% to 35% of the total calcium from an assortment of rougher and cleaner flotation concentrates. Additionally, when additional stages of cleaner UF Falcon gravity separation were operated in an open circuit configuration, it was possible, from an original fine feed of 35 microns containing 50.5% REO and 5.5% Ca, to upgrade up to approximately 59% REO and 2.0% calcium. While not the goal of this study, these results also support previous limited data to suggest that UF Falcons are potentially capable of treating a wider range of materials than they were originally designed for, including feeds rich in heavy mineral content.

Norgren, Alex↗
DOE OSTI2021

Ultra-Fine Centrifugal Concentration of Bastnaesite Ore

Historically, the ability to effectively separate carbonate gangue from bastnaesite via flotation has frequently proven to be challenging without sacrificing significant rare earth oxide (REO) grade or recovery. However, in light of the fact that the rare earth bearing minerals often exhibit higher specific gravities than the carbonate gangue, the possibility exists that the use of gravity separation could be used to achieve such a selective separation. This however is complicated by the fact that, in cases such as this study when the liberation size is finer than 50 µm, most traditional gravity separation methods become increasingly challenging. The purposes of this study is to determine the applicability of gravity concentrators to beneficiate bastnaesite from deleterious calcite bearing flotation feed material. Via the use of a UF Falcon, it was possible to achieve rougher gravity REO recoveries approaching the upper 80% range while rejecting on the order of 30% of the total calcium. In terms of purely REO recovery, this represents a significant improvement over results obtained via a traditional Falcon in previously reported studies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Lorentz Symmetry Group, Retardation, Intergalactic Mass Depletion and Mechanisms Leading to Galactic Rotation Curves

The general theory of relativity (GR) is symmetric under smooth coordinate transformations, also known as diffeomorphisms. The general coordinate transformation group has a linear subgroup denoted as the Lorentz group of symmetry, which is also maintained in the weak field approximation to GR. The dominant operator in the weak field equation of GR is thus the d’Alembert (wave) operator, which has a retarded potential solution. Galaxies are huge physical systems with dimensions of many tens of thousands of light years. Thus, any change at the galactic center will be noticed at the rim only tens of thousands of years later. Those retardation effects are neglected in the present day galactic modelling used to calculate rotational velocities of matter in the rims of the galaxy and surrounding gas. The significant differences between the predictions of Newtonian instantaneous action at a distance and observed velocities are usually explained by either assuming dark matter or by modifying the laws of gravity (MOND). In this paper, we will show that, by taking general relativity seriously without neglecting retardation effects, one can explain the radial velocities of galactic matter in the M33 galaxy without postulating dark matter. It should be stressed that the current approach does not require that velocities v are high; in fact, the vast majority of galactic bodies (stars, gas) are substantially subluminal—in other words, the ratio of $\frac{v}{c} \ll 1$. Typical velocities in galaxies are 100 km/s, which makes this ratio 0.001 or smaller. However, one should consider the fact that every gravitational system, even if it is made of subluminal bodies, has a retardation distance, beyond which the retardation effect cannot be neglected. Every natural system, such as stars and galaxies and even galactic clusters, exchanges mass with its environment, for example, the sun loses mass through solar wind and galaxies accrete gas from the intergalactic medium. This means that all natural gravitational systems have a finite retardation distance. The question is thus quantitative: how large is the retardation distance? For the M33 galaxy, the velocity curve indicates that the retardation effects cannot be neglected beyond a certain distance, which was calculated to be roughly 14,000 light years; similar analysis for other galaxies of different types has shown similar results. We demonstrate, using a detailed model, that this does not require a high velocity of gas or stars in or out of the galaxy and is perfectly consistent with the current observational knowledge of galactic and extra galactic material content and dynamics

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The Metal-weak Milky Way Stellar Disk Hidden in the Gaia–Sausage–Enceladus Debris: The APOGEE DR17 View

We have for the first time identified the early stellar disk in the Milky Way by using a combination of elemental abundances and kinematics. Using data from APOGEE DR17 and Gaia we select stars in the Mg–Mn–Al–Fe plane with elemental abundances indicative of an accreted origin and find stars with both halo-like and disk-like kinematics. The stars with halo-like kinematics lie along a lower sequence in [Mg/Fe], while the stars with disk-like kinematics lie along a higher sequence. Combined with astroseismic observations, we determine that the stars with halo-like kinematics are old, 9–11 Gyr, and that the more evolved stellar disk is about 1–2 Gyr younger. We show that the in situ fraction of stars on deeply bound orbits is not small, in fact the inner Galaxy likely harbors a genuine in situ population together with an accreted one. In addition, we show that the selection of the Gaia–Sausage–Enceladus in the E n -L z plane is not very robust. In fact, radically different selection criteria give almost identical elemental abundance signatures for the accreted stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling

Abstract. Uncertainties in an output of interest that depends on the solution of a complex system (e.g., of partial differential equations with random inputs) are often, if not nearly ubiquitously, determined in practice using Monte Carlo (MC) estimation. While simple to implement, MC estimation fails to provide reliable information about statistical quantities (such as the expected value of the output of interest) in application settings such as climate modeling, for which obtaining a single realization of the output of interest is a costly endeavor. Specifically, the dilemma encountered is that many samples of the output of interest have to be collected in order to obtain an MC estimator that has sufficient accuracy – so many, in fact, that the available computational budget is not large enough to effect the number of samples needed. To circumvent this dilemma, we consider using multifidelity Monte Carlo (MFMC) estimation which leverages the use of less costly and less accurate surrogate models (such as coarser grids, reduced-order models, simplified physics, and/or interpolants) to achieve, for the same computational budget, higher accuracy compared to that obtained by an MC estimator – or, looking at it another way, an MFMC estimator obtains the same accuracy as the MC estimator at lower computational cost. The key to the efficacy of MFMC estimation is the fact that most of the required computational budget is loaded onto the less costly surrogate models so that very few samples are taken of the more expensive model of interest. We first provide a more detailed discussion about the need to consider an alternative to MC estimation for uncertainty quantification. Subsequently, we present a review, in an abstract setting, of the MFMC approach along with its application to three climate-related benchmark problems as a proof-of-concept exercise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Best Practices for Energy Management Information Systems Metadata Schemas

The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of Energy Management Information Systems (EMIS) at federal facilities. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. The use of standard naming conventions and a metadata schema, which may be referred to as 'data tags,' improves the ability of the EMIS to consistently analyze, visualize, and derive value from operational data. To help address these issues, this fact sheet highlights best practices for use of metadata in an EMIS stack, which can significantly reduce the initial time required to deploy an EMIS.

EMIS↗
DOE OSTI2022

Best Practices for Energy Management Information Systems Metadata Schemas

Fact sheet highlights best practices for metadata schemas and standard naming conventions, which improve the ability of an energy management information system (EMIS) to consistently analyze, visualize, and derive value from operational data. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. It provides an overview of best practices for using metadata in an EMIS stack, which can significantly reduce the initial time required to deploy an EMIS.

data tags↗
DOE OSTI2023

Wind as a Distributed Energy Resource

Distributed wind can be installed in a wide range of locations and wind conditions, supporting millions of systems and thousands of gigawatts of power production capacity. As a result, utilities, communities, and nations are looking to distributed generation as an effective way to meet future energy needs. This fact sheet provides an overview of distributed wind, including where distributed wind projects can be located, and how U.S. and international research supports distributed wind applications. This fact sheet was produced as a resource for the International Energy Agency Task 41 members to use as an educational resource.

behind-the-meter wind energy↗
DOE OSTI2020

Technical Evaluation of the Department of Energy Research and Development Activities in Underground Research Laboratories - 20287

Congress created the U.S. Nuclear Waste Technical Review Board (NWTRB) in the 1987 Nuclear Waste Policy Amendments Act (Public Law 100-203) to evaluate the technical and scientific validity of activities undertaken by the Secretary of Energy to implement the Nuclear Waste Policy Act. Since 2012, DOE has collaborated in research conducted in several underground research laboratories (URLs) located in Europe and Asia. According to DOE, these international collaborations have been beneficial to its spent nuclear fuel (SNF) and high-level waste radioactive (HLW) disposal research program, particularly after the termination of the Yucca Mountain repository program when DOE began generic research on alternative host rocks (crystalline, clay, and salt) and repository environments very different from those at Yucca Mountain. In accordance with its mandate, the NWTRB is reviewing the DOE research and development (R and D) activities related to URLs. The NWTRB's review is documented in a report to Congress and the Secretary of Energy that will be released in January 2020, and this paper summarizes the NWTRB review and findings. The NWTRB held a fact-finding meeting with DOE and subsequently held a workshop on international URL collaborations in April of 2019. Based on the presentations and discussions at the workshop and at the fact-finding meeting, as well as information from reports published by DOE and others, there are four principal findings related to DoE's URL-related R and D activities. First, DOE participation in URL-related international research greatly benefits the U.S. geologic disposal R and D program by furthering its understanding of generic and site-specific disposal issues relevant to alternative repository host rocks and environments. DOE-funded R and D activities also are benefiting the URL-related research of other countries, especially in the area of complex analytical and numerical model/software development. Second, the more developed repository programs in other countries have focused on creating and strengthening their safety cases and making them transparent to the public. Repository programs in other countries use URLs to explain the technical bases underlying their safety cases, periodically reassess knowledge gaps and define new activities to strengthen the technical bases, and demonstrate the technology that will allow implementation of the proposed safety concept. Third, countries with more developed geologic disposal programs have found domestic URLs essential to their repository programs. DOE needs domestic URLs to advance geologic disposal efforts over the next decades and further its ability to train the next generation of scientists, engineers, and skilled technical workers. Fourth, DoE's international URL collaborations have advanced its generic disposal R and D program, including development of modeling capabilities recognized internationally as state-of-the-art, but further work on its coupled thermal-hydrological-mechanical-chemical models and URL- and laboratory-based research can strengthen its program. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Environmental Life Cycle Assessment of Electricity from PV Systems

PV Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying and assessing material and energy flows and their associated emissions from manufacturing, transport, installation, use and end of life. This is the first version of the Fact Sheet, published in 2021 based on the Task 12 LCA Report from 2020 (and based on the 2018 update of the LCA database). A newer version of this Fact Sheet has been published in 2022.

carbon emissions↗
DOE OSTI2024

Energy Efficiency and Renewable Energy for New Home Construction in Maui

For residential property owners preparing to rebuild homes in Maui, this fact sheet, produced by the National Renewable Energy Laboratory (NREL), a national laboratory of the U.S. Department of Energy (DOE), provides a brief introduction to the topics of renewable energy and energy efficiency for new residential construction, presents a few high-level considerations and key concepts, and provides a sampling of information on rebates, incentives, certification programs, standards, and relevant policies. This fact sheet is not intended to be comprehensive nor to replace local resources.

appliances↗