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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ARIC 2019 workshop report: The 2nd ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities: Chicago, IL, USA November 5, 2019

The advancements in sensor technology and ubiquity of connected devices has enabled the generation of large volume of disparate, dynamic and geographically distributed data both by scientific communities and citizens. With astonishing technological innovations and convergence, there have been major changes in peoples daily activities and social interaction. The socio-technological innovations motivate the concept of smart and connected cities. A smart city, however, is subjected to the same challenges as a conventional city, such as environmental damages, hazard impacts, access to services and resources, due to continuous population and economic growth. Therefore, it is imperative to improve our understanding of Resilient and Intelligent Cities in order to leverage technologies and artificial intelligence to tackle the challenges cities face, which range from climate change, public health, traffic congestion, economic growth, to digital divide, social equity, political movements, and cultural conflicts, among others.

Kar, Bandana↗
DOE OSTI2021

MOOSE Framework Meshing Enhancements to Support Reactor Analysis

MOOSE-based physics codes require an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The use of difficult-touse, external licensed software is often required to generate high quality meshes for reactor geometries. High-fidelity geometry modeling also requires elaborate tracking of groups of elements for material property assignment and output reporting which can be considerably complex for the user to identify and maintain. Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, several meshingrelated enhancements have been developed for the MOOSE framework to address user challenges in creating finite element meshes for advanced reactor geometries. MOOSE mesh generators have been developed to mesh hexagonal geometries (pins, ducted assemblies, and cores) commonly found in liquid-metal cooled fast reactor concepts. The mesh generator used for hexagonal pin cells is generic for regular polygons and therefore may also be used for Cartesian pin cells. Hexagonal pin cells can be stitched into ducted assemblies, and assemblies can be stitched together into a core. The user may specify region ids, region names, and other preferences on the mesh. This control is useful for later material mapping in the MOOSE-based physics codes input. A capability was also developed for meshing rotating control drums including determination of material volume fractions in each mesh element as a function of time. Control drum meshes may be stitched to other hexagonal assemblies to create a core configuration. Additional mesh generators were developed that wrap around the hexagonal meshing capabilities and utilize “extra element integer” ID values on each element. In regular Cartesian or hexagonal assemblies or cores, the bookkeeping of element groups for both material assignment and output reporting can now be automated through assignment of pin, assembly, core, axial and depletion id values stored as extra element integers. The extra element tags on the mesh greatly speed the reactor analyst’s efforts to map materials to meshes, track depletion zones, and parse output such as axial pin power distributions. At the highest level, pin, assembly, and core mesh generators (with this reactor terminology) have also been developed to easily generate regular Cartesian and hexagonal cores, including axial extrusion. These reactor geometry builders call upon the previously mentioned capabilities to produce analysis-ready 3D meshes including material assignments. Open source mesh triangulation capabilities were also investigated for integration into the MOOSE framework to address the need for meshing the core periphery region which extends from the irregular outer assembly border to a cylindrical boundary. Options are limited due to licensing constraints, and the recommendation is pursue building a native MOOSE Delaunay triangulator routine with full functionality. Finally, a series of verification problems were performed with NEAMS physics tools. All developed capabilities will be available in the new open-source “Reactor” module of the MOOSE framework, which is accessible to any MOOSE-based NEAMS physics tool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Enhancing the Design of Photocathodes with 90% polarization and QE > 1% for DOE NP (Final Report)

This project’s 3 major goals were the following: 1. Fabricate state-of-the-art spin-polarized photocathodes using MOCVD and develop knowledge of fabrication parameters. 2. Enhance the design of 2 structures of spin-polarized photocathodes (strained-superlattice and strained-superlattice with distributed Bragg reflector) to assess paths to the next generation of spin-polarized photocathodes. 3. Provide a supply of state-of-the-art spin-polarized photocathodes to both Brookhaven National Laboratory and the Thomas Jefferson National Accelerator Facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

ASEAN Technical Exchange Workshop for System Operators, Regulators, and Policymakers

This presentation provides an in-depth exploration of power system planning, cross-border electricity trading, and battery energy storage systems (BESS), offering actionable insights for system operators, regulators, and policymakers. The first section delves into power system planning and analysis, focusing on capacity expansion models and resource adequacy studies, including their role in optimizing system efficiency, managing emissions, and addressing system reliability risks. Key considerations, such as integration of transmission into generation planning and the forecasting versus optimization of customer distributed energy resources (DER) technologies, are explored. The session highlights critical trade-offs in spatial granularity and model runtimes, as well as the feasibility of aligning distribution investments with capacity expansion efforts. The second section examines cross-border electricity trading, with an emphasis on resource adequacy concepts such as reliability targets, loss of load expectation (LOLE), and planning reserve margins (PRM). Case studies on reserve market design and coordination across US regions provide insights into improving reserve deliverability and managing interregional power balance and congestion. This section also addresses market-to-market congestion management, including advanced strategies for high-voltage direct current (HVDC) optimization and ancillary service delivery. Finally, the presentation covers the rapid evolution of Battery Energy Storage Systems (BESS), highlighting their operational growth, regulatory frameworks, and use cases in grid flexibility, energy storage, and reliability. The discussion focuses on the benefits of BESS for system stability, resilience, and integration of renewable energy, offering insights into its role as a vital component in the transition toward a more sustainable and flexible grid. Key performance parameters, such as throughput, round-trip efficiency, and state of charge, are also examined.

25 ENERGY STORAGE↗
DOE OSTI2025

On Possibilities of Using Edge Radiation for X-ray and Electron Beam Diagnostics at Bending Magnet Beamlines of NSLS-II

Spectral flux density distributions of long-wavelength Edge Radiation, i.e. radiation generated by relativistic electrons at edges of bending magnets in a storage ring are described, both analytically and numerically. Possibilities of using this radiation for the alignment of optical components of bending magnet beamlines at NSLS-II and for non-destructive X-ray and electron beam diagnostics at these beamlines are discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗
DOE OSTI2021

Modeling Kilonova Light Curves: Dependence on Nuclear Inputs

The mergers of binary neutron stars, as well as black hole–neutron star systems, are expected to produce an electromagnetic counterpart that can be analyzed to infer the element synthesis that occurred in these events. We investigate one source of uncertainties pertinent to lanthanide-rich outflows: the nuclear inputs to rapid neutron capture nucleosynthesis calculations. We begin by examining 32 different combinations of nuclear inputs: eight mass models, two types of spontaneous fission rates, and two types of fission daughter product distributions. We find that such nuclear physics uncertainties typically generate at least one order of magnitude uncertainty in key quantities such as the nuclear heating (one and a half orders of magnitude at 1 day post-merger), the bolometric luminosity (one order of magnitude at 5 days post-merger), and the inferred mass of material from the bolometric luminosity (factor of 8 when considering the 8–10 day region). Since particular nuclear processes are critical for determining the electromagnetic signal, we provide tables of key nuclei undergoing β-decay, α-decay, and spontaneous fission important for heating at different times, identifying decays that are common among the many nuclear input combinations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Core Mass Estimates in Strong Lensing Galaxy Clusters Using a Single-halo Lens Model

The core mass of galaxy clusters is an important probe of structure formation. Here we evaluate the use of a single-halo model (SHM) as an efficient method to estimate the strong lensing cluster core mass, testing it with ray-traced images from the Outer Rim simulation. Unlike detailed lens models, the SHM represents the cluster mass distribution with a single halo and can be automatically generated from the measured lensing constraints. In this work we find that the projected core mass estimated with this method, $M_{\text{SHM}}$, has a scatter of 8.52% and a bias of 0.90% compared to the "true" mass within the same aperture. Our analysis shows no systematic correlation between the scatter or bias and the lens-source system properties. The bias and scatter can be reduced to 3.26% and 0.34%, respectively, by excluding models that fail a visual inspection test. We find that the SHM success depends on the lensing geometry, with single giant arc configurations accounting for most of the failed cases due to their limiting constraining power. When excluding such cases, we measure a scatter and bias of 3.88% and 0.84%, respectively. Finally, we find that when the source redshift is unknown, the model-predicted redshifts are overestimated, and the $M_{\text{SHM}}$ is underestimated by a few percent, highlighting the importance of securing spectroscopic redshifts of background sources. Our analysis provides a quantitative characterization of $M_{\text{SHM}}$, enabling its efficient use as a tool to estimate the strong lensing cluster core masses in the large samples, expected from current and future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Stochastic Approach to Reconstruct Gamma-Ray-burst Light Curves

Gamma-ray bursts (GRBs), as they are observed at high redshift ( z = 9.4), are vital to cosmological studies and investigating Population III stars. To tackle these studies, we need correlations among relevant GRB variables with the requirement of small uncertainties on their variables. Thus, we must have good coverage of GRB light curves (LCs). However, gaps in the LC hinder the precise determination of GRB properties and are often unavoidable. Therefore, extensive categorization of GRB LCs remains a hurdle. We address LC gaps using a stochastic reconstruction, wherein we fit two preexisting models (the Willingale model; W07; and a broken power law; BPL) to the observed LC, then use the distribution of flux residuals from the original data to generate data to fill in the temporal gaps. We also demonstrate a model-independent LC reconstruction via Gaussian processes. At 10% noise, the uncertainty of the end time of the plateau, its correspondent flux, and the temporal decay index after the plateau decreases by 33.3%, 35.03%, and 43.32% on average for the W07, and by 33.3%, 30.78%, 43.9% for the BPL, respectively. The uncertainty of the slope of the plateau decreases by 14.76% in the BPL. After using the Gaussian process technique, we see similar trends of a decrease in uncertainty for all model parameters for both the W07 and BPL models. These improvements are essential for the application of GRBs as standard candles in cosmology, for the investigation of theoretical models, and for inferring the redshift of GRBs with future machine-learning analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Distributed reinforcement learning and consensus control of energy systems

Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

King, Jennifer Rose Rose↗
DOE OSTI2024

Explained: Maintaining a Reliable Future Grid with More Wind and Solar

Since the early 2000s, maintaining grid reliability has become more complex due to a variety of factors, including the changing generation mix, the creation of wholesale energy markets, and a growing number of extreme weather events. Parts of the U.S. grid are already operating with significant amounts of wind and solar generation - with 2022 annual wind and solar generation in the range of 25% to 40%. Even without considering the effects of extreme weather, maintaining reliability will require new capacity to address both growth in electric demand and retiring capacity. Based on the 2022 North American Electric Reliability Corporation (NERC) Long-Term Reliability Assessment, the combination of both growth in peak demand and retirements suggests a need for more than 100 gigawatts (GW) of new capacity by 2032. In general, there are a five categories of resources that are expected to be deployed and used to meet the challenge of maintaining an adequate source of supply in the coming decades: new wind and solar resources (accounting for their reliability contributions), energy storage, demand response resources, expanded transmission, and continued use of thermal generators.

power grid↗
DOE OSTI2024

South Asia Group for Energy - Bhutan

Bhutan's electricity system is already low-carbon through the use of hydropower. However, generation from hydroelectric plants is reduced during the dry winter months and will be impacted by climate change and other extreme weather events. Bhutan is mitigating these risks by diversifying their energy mix with clean energy resources. Bhutan is exploring photovoltaic (PV) solar energy development to enhance its energy system's overall resilience. To ensure efficient grid planning and solar integration, Bhutan's power generator, Druk Green Power Corporation, and the transmission and distribution utility, Bhutan Power Corporation, are partnering with the South Asia Group for Energy (SAGE) to develop their solar capabilities, integrate solar energy into the grid, and strengthen Bhutan's energy infrastructure and efficiency.

Bhutan↗
DOE OSTI2025

Investigating the weak charge of 48 Ca using a dispersive optical model

A new nonlocal dispersive-optical-model analysis has been carried out for neutrons and protons in 48 Ca that reproduces the weak-form-factor measurement of CREX. In addition to elastic-scattering angular distributions, total and reaction cross sections, single-particle energies, the neutron and proton numbers, and the charge distribution, the CREX-measured weak form factor has been fit to extract the neutron and proton self-energies both above and below the Fermi energy. The resulting single-particle propagators yield a weak form factor of F w = 0.125 ± 0.05 and a neutron skin of R skin = 0.152 ± 0.05 fm, in good agreement with CREX. The rearrangement of the neutron distribution to accommodate such a thin neutron skin results in the high-momentum content of the neutrons exceeding that of the protons, in contrast to what is expected from high-energy two-nucleon knockout measurements by the CLAS collaboration and ab initio asymmetric matter calculations. The present analysis also emphasizes the importance of neutron experimental data in constraining weak charge observables necessary for a precise description of neutron densities. Notably, the neutron reaction cross section and further parity-violating experiments weak form factor measurements are essential to generate a unique way to determine the 48 Ca neutron distribution in this framework.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Energy, Exergy, Entropy Generation Minimization, and Exergoenvironmental Analyses of Energy Systems-A Mini-Review

Meeting the growing energy demands has become a crucial challenge, which should employ energy integration and benefit from the extraction of the maximum thermodynamic potential of the resources consumed. This brief review presents an overview of the essential elements of the methods of energy, exergy, entropy generation minimization, and exergoenvironmental analyses. In combination, these methodologies constitute a powerful toolbox for the design, analysis, and optimization of energy systems. The quantification of energy and environmental impacts provided by them is essential in guiding toward system designs that are consistent with current energy and environmental needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Understanding Line Losses and Transformer Losses in Rural Isolated Distribution Systems

Rural, isolated power systems in the mainland U.S. and in states like Alaska and Hawaii are powered by assets like diesel generators. These rural, isolated power systems also cannot operate at the higher band of medium voltage (like 69kV). They are primarily in the 12 to 14 kV range to keep the cost of the distribution investments lower. Because of this mid-band medium voltage range, the line losses and distribution transformers losses consume significant diesel consumption (almost 10 percent of the peak load). This work considers one such power system powering an isolated system and presents key findings online losses, and transformer losses. Understanding and documenting the impacts is critical for these communities operating their power systems and take actions to reduce expensive diesel consumption. In this paper, we will present one such typical grid and model it in electromagnetic transients (EMT) domain. We used the tower structure, under ground cabling installation to develop high fidelity models of lines. We also used high fidelity models of distribution transformers to present the no-load losses and full load loses. We will also present technical solutions available commercially off-the-shelf to reduce these losses and reduce diesel consumption. This work will be a primer for communities to understand the technical challenges and to understand the possible solution available to solve such challenges for rural, isolated power system operators.

blackstart↗
DOE OSTI2021

Quantifying the time‐specific kinetic energy of simulated rainfall using a dynamic rain gauge system

Abstract Raindrop impact derives from the kinetic energy of falling raindrops. Determining the kinetic energy of rainfall requires the size distribution and terminal velocity of raindrops, which necessitates complex instrumentation. To avoid this, empirical relations have been developed that relate rainfall intensity and the rate of kinetic energy, i.e., time‐specific kinetic energy (KE time ). In this study, a dynamic rain gauge system (DRGS) was used to quantify the KE time generated by a rainfall simulator without need of measuring raindrop size distributions or impact velocities. In a series of 10 rainfall tests, the KE time and rainfall intensity were 860.9 (±88.6) J m 2 h −1 and 72.1 (±1.9) mm h −1 , respectively. Estimated KE time was found to agree well with the power‐law relation presented by Petrů and Kalibová for high‐intensity simulated rainfall, which are the conditions when higher deviations occur. The DRGS may be a useful tool in quantifying the KE time of rainfall simulators in hopes to better understand raindrop impact mechanisms.

Wacha, Kenneth M.↗
DOE OSTI2023

A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks

As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution system planners can use to prepare for future extreme events is to plan multiple microgrids which can use local generation as much as possible to supply critical loads. But partitioning an existing distribution system such that multiple feasible islands are planned and which are capable of supporting critical loads is still challenging for distribution systems - first, because of the size of the network graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithm based approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems - node allocation and edge elimination - and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, United States.

genetic algorithm↗
DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗