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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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DOE OSTI2022

Integration of Superconducting Magnetic Energy Storage (SMES) Systems Optimized with Second-Generation, High-Temperature Superconducting (2G-HTS) Technology with a Major Fossil-Fueled Asset

Utility companies and fossil fueled generation assets are seeking combinations of “hybrid energy storage” to allow power to be provided in advance of, and to otherwise complement, peaking natural gas-fired generation. American Maglev Technology of Florida Inc. (AMT) learned during the Phase I program based on interactions with NRG Energy (NRG) that energy storage such as superconducting magnetic energy storage (SMES) can qualify as a Black Start unit in most markets, ensuring orderly re-start of grid operations and fossil fueled power plants and serving as an important asset of hybrid energy storage technology. In conjunction with the University of Houston (UH), AMT and NRG are working together to scale up low-cost, high- efficiency, second-generation high-temperature superconducting (2G-HTS) technology for deployment across several markets, with a primary focus on the commercial development of utility grid-scale SMES (g-SMES) systems. Ultimately the program confirmed that the novel g-SMES design can meet the performance and financial requirements of the fossil power plant industry, while exhibiting continuous grid-voltage regulation; cost-effective, peak-hour energy storage with almost infinite life; increased input/output efficiency; and the capability to undergo millions of charging cycles, without degradation, representing a significant improvement over lithium ion and other conventional storage technologies. We believe wide scale deployment of this technology is feasible and practical when compared to the higher life cycle cost and relatively short lifespan of chemical batteries. Based on these findings, the future for deployment of SMES at many fossil-fueled power plants exceeding 100MW capability is bright. Further de-risking g-SMES technology would pave the way for the construction of a subscale prototype. Eventually, scaled-down versions of SMES are expected to be competitive with the multi-billion-dollar lithium-ion market for a wide range of commercial, industrial, and transportation uses. There is long-term potential for commercialization and widespread deployment of this disruptive technology, which would spawn a new worldwide supply chain and create domestic, high-tech manufacturing jobs in the green industry.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

An Environmental and Societal Analysis of the US Electrical Energy Industry Based on the Water–Energy Nexus

To meet rising energy demands, power plant operations will expand, influencing the interactions between the water–energy nexus and society. However, a major challenge is integration of social dimensions within electricity generation. To address this, we generate a baseline dataset using US public data (2014–2019) from the Energy Information Administration and US Bureau of Labor Statistics. We identify the rate of energy consumed, CO 2 , SO 2 and NO x emissions generated, and water used per MWh net electricity as well as employee wellbeing per unit MW capacity during electricity generation. Rates of energy consumption (MMBtu/MWh) decreased 4.9%, but water consumption and withdrawal (m 3 /MWh) both increased 0.93% and 0.31%, respectively. Emissions of CO 2 , SO 2 and NO x decreased 22.64%, 75% and 25% MT/MWh, respectively. Thermoelectric cooling withdrawal and consumption is led by natural gas (50.07%, 38.31%), coal (29.61%, 25.07%), and nuclear energies (13.55%, 18.99%). Electric power generation contributes 0.06 injuries–illnesses/TWh and 0.001 fatalities/TWh, of which fossil fuels contributed 70% and 15%, respectively. Fossil fuels led in average annual employment (0.02 employees/MW) with low cost salaries (USD 0.09/MW) likely due to high collective capacity, which is declining. Estimated rates in this study and framework will aid power industry transition and operational decision makers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

DUNE – Simulation Validation of Fermilab Detector Reconstruction

DUNE (Deep Underground Neutrino Experiment) is Fermilab’s flagship international experiment designed to study neutrinos by sending an intense beam from Illinois to detectors located 1,300 kilometers away at the Sanford Underground Research Facility (SURF) in South Dakota. To prepare for such a large-scale experiment, physicists develop detailed simulations to produce mock data sets which are analyzed by the CAFAna framework. During my internship, I developed software using the CAFAna framework to analyze simulated detector data and generated plots to make data trends easier to interpret and identify patterns. My analysis has uncovered inconsistencies in reconstructed neutrino tracks, duplicated reconstructed tracks causing sporadic spikes in the data, and unnatural differences in energy levels between interaction types. These analyses help verify that the improvements to detector simulations do not introduce unintended resolution errors and ensure proper reconstruction performance, supporting DUNE’s goal of making precise neutrino measurements and advancing the Department of Energy’s mission of fundamental scientific discovery.

Vershaw, Andre [Unlisted, US, IL; Fermilab] (ORCID↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 4: Social and Economic Effects of Marine Renewable Energy

While the 2024 State of the Science report primarily focuses on the interactions between marine renewable energy (MRE) and the environment, to fully account for the effects of MRE development, the social and economic aspects must also be considered. Incorporating how societal elements are altered related to the construction, operation, and maintenance of MRE projects and how MRE development may affect communities on a local, regional, and/or national scale is necessary to understand the suite of effects from the industry.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Thermal and Quantum Melting Phase Diagrams for a Magnetic-Field-Induced Wigner Solid

A sufficiently large perpendicular magnetic field quenches the kinetic (Fermi) energy of an interacting two-dimensional (2D) system of fermions, making them susceptible to the formation of a Wigner solid (WS) phase in which the charged carriers organize themselves in a periodic array in order to minimize their Coulomb repulsion energy. In low-disorder 2D electron systems confined to modulation-doped GaAs heterostructures, signatures of a magnetic-field-induced WS appear at low temperatures and very small Landau level filling factors ($\textit{ν}$ ≃ 1/5). In dilute GaAs 2D hole systems, on the other hand, thanks to the larger hole effective mass and the ensuing Landau level mixing, the WS forms at relatively higher fillings ($\textit{ν}$ ≃ 1/3). Here we report our measurements of the fundamental temperature vs filling phase diagram for the 2D holes’ WS-liquid thermal melting. Moreover, via changing the 2D hole density, we also probe their Landau level mixing vs filling WS-liquid quantum melting phase diagram. In this work, we find our data to be in good agreement with the results of very recent calculations, although intriguing subtleties remain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Hydropower representation in water and energy system models: a review of divergences and call for reconciliation

Abstract Reservoir-based hydropower systems represent key interactions between water and energy systems and are being transformed under policy initiatives driven by increasing water and energy demand, the desire to reduce environmental impacts, and interacting effects of climate change. Such policies are often guided by complex system models, whereby divergence in system representations can potentially translate to incompatible planning outcomes, thereby undermining any planning that may rely on them. We review different approaches and assumptions in hydropower representation in water and energy systems. While the models and issues are relevant globally, the review focuses on applications in California given its extensive development of energy and water models for policy planning, but discusses the extent to which these observations apply to other regions. Structurally, both water-driven and energy-driven management models are similar. However, in energy models, hydropower is often represented as a single-priority output. Water management models typically allocate water for competing priorities, which are generally uninformed by dynamic electricity load demand, and often result in a lower priority for hydropower. In water models, constraints are increasingly resolved for non-energy components (e.g. inflow hydrology and non-energy water demand); few analogues exist for energy models. These limitations may result in inadequate representations of each respective sector, and vastly different planning outcomes for the same facilities between the two different sectors. These divergent modeling approaches manifest themselves in California where poorly reconciled outcomes may affect decisions in hydropower licensing, electricity grid flexibility and decarbonization, and planning for environmental water. Fully integrated water-energy models are computationally intensive and specific to certain regions, but better representation of each domain in respective efforts would help reconcile divergences in planning and management efforts related to hydropower across energy and water systems.

Rheinheimer, David E. (ORCID:0000000315259069)↗
DOE OSTI2024

Infinitely rugged intra-cage potential energy landscape in metallic glasses caused by many-body interaction

The absence of translational symmetry in glassy materials poses a significant challenge in establishing effective structure-property relationships in real space. Consequently, the potential energy landscape (PEL) in phase space is widely utilized to comprehend the complex phenomena in glasses. The classical PEL features a two-scale profile comprising mega-basins and sub-basins, corresponding to α-relaxations (e.g. glass transition) and β-relaxations (e.g. local cage-breaking atomic rearrangements), respectively. Recent studies, however, reveal that sub-basins are not smooth and contain finer structures, the origins of which remain elusive. Here we probe the smoothness of sub-basin bottoms in glasses' PEL by introducing small intra-cage cyclic loading and then measuring the net changes in atomic-level stresses. Compared to glasses with pair interaction, glasses with many-body interaction exhibit orders-of-magnitude larger and loading-dependent stress changes even before the first cage-breaking event takes place, which reflect much more feature-rich sub-basins. We further demonstrate this stark contrast stems from the spatial distribution of individual atom's constraining force field. Specifically, at vanishing perturbations, many-body interactions disrupt the positive-definite synchrony in energy variations of the perturbed atom and the whole system, causing inherently less confined atomic responses and infinitely rugged sub-basins. The implications of these findings for the selective addition or removal of fine structures in the PEL and the subsequent tuning of glassy materials' responses to external stimuli are also explored.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets

Climate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial–temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy markets and emission reduction scenarios. We find that under SSP5, a “fossil-fueled development” scenario, the effects of sea-ice loss are larger for Arctic offshore oil production than gas. Under SSP5, future extraction of Arctic offshore oil and gas through 2100 adds roughly 0.8–2.6 EJ/year to oil and gas markets but does not have large impacts on global oil and gas markets. Surprisingly, a low-carbon scenario results in greater Arctic offshore oil production to offset the more emissions-intensive unconventional oil production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Supersonically expanded sodium metal-dilute halogen gas interactions. The importance of reaction populated and energy storing reservoir states and population inversion created amplification in Na2

The reactions of Cl, Br, and I with Nan=2,3 produced in a supersonic expansion form Na2* and Na* excited states extending across the visible and ultraviolet regions. Emission in the region extending from 410 to 600 nm indicates selectively formed excited state Na2 emission features. Experimental evidence suggests that this emission is associated with Na3 + X reactions. Broadband (0.5 cm−1) laser measurements demonstrate gain (population inversion) for select features at∼524–528(1%), ∼492(0.3%), and ∼458.7–461(0.8%) nm. Single mode (0.007 cm−1) measurements extending from 528.03 to 527.63 nm demonstrate amplification involving five to six individual rovibronic levels with a maximum gain close to 3% recorded at 527.9 nm. The observed gain is associated with select transitions from levels of the Na2 11Πu state populated, via identified curve crossings, through collision induced transfer from long-lived Na2 21Σg+ and 11Πg reservoir states. Collision induced population buildup in the lowest vibrational levels of these reservoir states and collision induced transfer to the Na2 11Πu state create a population inversion in transitions to the X 1Σg+ state of Na2. The observed amplification is aided by rapid vibrational and rotational relaxation in both the Na2 ground and excited reservoir states producing amplifiers in the visible region like the HF amplifier in the infrared. This study suggests the importance of reaction populated and energy storing long-lived reservoir states in small sodium molecule combustion processes and indicates the potential for providing new short wavelength visible and ultraviolet amplifiers for future laser-based chemical propulsion concepts.

Chemistry↗
DOE OSTI2022

Ratios of collective flow observables in high-energy isobar collisions are insensitive to final-state interactions

The ratios of bulk observables, such as harmonic flow v 2 and v 3 , between high-energy 96 Ru + 96 Ru and 96 Zr + 96 Zr collisions were recently argued to be a clean probe of the nuclear structure differences between 96 Ru and 96 Zr . Using a transport model simulation of isobar collisions, we quantify this claim from the dependence of the ratios v 2,Ru /v 2, Zr and v 3,Ru /v 3,Zr on various final-state effects, such as the shear viscosity, hadronization, and hadronic cascade. Although the v 2 and v 3 change by more than 50% when varying the final-state effects, the ratios are unchanged. In addition, these ratios are independent of the transverse momentum p T and hadron species, despite of up to a factor of 2 change in v n . Further, the ratio of mean transverse momentum $\langle$p T $\rangle$ is found to be controlled by the nuclear skin and nuclear radius but is only slightly impacted by the final-state effects. Therefore, these isobar ratios serve as a clean probe of the initial condition of the quark-gluon plasma, which, in turn, is controlled by the collective structure of the colliding nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Chapter 10 Supplement. Environmental Monitoring Technologies and Techniques for Detecting Interactions of Marine Animals with Marine Renewable Energy Devices

The Chapter 10 Supplementary Material provides information on instrument classes used for monitoring marine renewable energy devices such as passive acoustics, active acoustics, and video cameras. It also describes the applications and challenges of video cameras, and provides a technical glossary related to monitoring terminologies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Measurement of Charged-Current $ν_μ$ and $ν_e$ Interactions Towards a Search for Low-Energy $ν_Ε$ Excess Using Wire-Cell In Microboone

This technote summarizes the existing work in searching for $ν_e$ low-energy excess (eLEE) in MicroBooNE Booster Neutrino Beam (BNB) data stream based on the Wire-Cell event reconstruction paradigm. The charged-current $ν_μ$ and $ν_e$ events are selected from the 5.3e19 POT open data from the BNB beam, 6.37e20 POT far sideband from the BNB beam data, and 2.10e20 POT data from Neutrinos at the Main Injector (NuMI) beam. The charged-current $ν_e$ selection results from the BNB data that are sensitive to the eLEE search are not included. Various comparisons between data and Monte Carlo predictions are performed to validate the overall model and demonstrate the power of the analysis techniques. Physics sensitivities in terms of the exclusion and the discovery potential are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Measurements of Nuclear Effects and the $\bar \nu_\mu +H \to \mu^+ + n$ Cross Section in MINERνA with Neutron Tagging

MINERνA, or Main INjector ExpeRiment for ν-A, at Fermilab, is an experimentdedicated to the study of neutrino-nucleus interactions in the GeV regime. Itsgoal is to illustrate the interplay between hadronic and nuclear physics and measure intranuclear dynamics crucial for the present and future neutrino oscillationmeasurements. We first measure a set of variables sensitive to how Monte Carlo(MC) simulations of neutrino-nucleus interactions implement binding energy andthen move on to measure the antineutrino CCQE cross section on the hydrogentargets in MINERνA’s CH detector. We have developed a method to preferentially select events on the hydrogen by comparing outgoing neutrons’ directions totheoretical neutron directions assuming two-body interactions. We measured thecross section, extracted the axial form factor, and performed a Z-expansion fit. Weobserve larger values in the axial form factor at high Q2than current best fits. Finally, we show a preliminary selection of events with both protons and neutrons toinvestigate nuclear processes responsible for producing these final states.

Cai, Tejin↗
DOE OSTI2021

High Energy Physics Network Requirements Review (Final Report, July-October 2020)

Throughout 2020, ESnet and the Office of High Energy Physics (HEP) of the DOE SC organized an ESnet requirements review of HEP-supported activities. Preparation for this event included identification of key stakeholders: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents about their relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Microreactors for a Changing Energy Landscape

Join us for a discussion on the role of microreactors within our sustainable energy future. This interactive session will invite attendees to engage directly with nuclear industry trailblazers. Together, we'll uncover the promise of microreactors in meeting nuclear data needs, powering remote locations, and overcoming the challenges of regulatory landscapes. Your participation will help shape a dialogue on how diverse perspectives can unite to transform our energy infrastructure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗