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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 307 records · Page 17

Case Study: Hybridizing Nuclear Energy Systems in the U.S.

This case study was presented at the ICTP-IAEA VIRTUAL Course on Nuclear-Renewable Integrated Energy Systems: Phenomenology, Research and Development. It provides preliminary results on an analysis of hybridizing the two nuclear power plants owned by Xcel Energy and located in Minnesota. The analysis extends previous analyses that provided only price-taker results. Those assume adjusting the generation sold to the grid does not impact locational marginal electricity prices nor do they estimate impacts on the total net cost to serve the load. This presentation summarizes the new technique that was developed to both optimize the size and operations of the hybridized system and the resulting impacts on the grid when it is operated optimally.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Revenue Analysis of Stationary and Transportable Battery Storage for Power Systems: A Market Participant Perspective

The power system faces a growing need for increased transmission capacity and reliability with the rising integration of renewable energy resources. To tackle this challenge, Battery Energy Storage Systems (BESSs) prove effective in enhancing grid capacity and relieving transmission congestion. This paper focuses on the PJM market, conducting a thorough revenue analysis to identify and characterize highly profitable nodes for BESS market participants. A comparison between stationary and transportable BESSs reveals that the transportable BESSs can generate higher potential revenue in energy and regulation markets. Based on these findings, we propose an optimal placement algorithm to support market participants in selecting strategic sites for BESS installation, validated with real PJM market data. This paper provides valuable insights for navigating market-based power system participants and promoting the effective integration of BESSs.

25 ENERGY STORAGE↗

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

Iodine imaging using spectral analysis

Existing radiographic imaging systems provide images which represent an integration or averaging over the energy spectrum. In order to provide noninvasive angiography it is necessary to image the relatively small amounts of iodine which are available following an intravenous administration. This is accomplished by making use of the special spectral characteristics of iodine. Two methods will be presented. One involves a special grating for encoding the iodine information in the form of a fine line pattern. This is subsequently decoded to provide images of iodinated structures which are otherwise almost invisible. The second method utilizes a scanned X-ray beam which is rapidly switched in the high energy region. In this region, iodine experiences significant variations in the attenuation coefficient while bone and soft tissue do not. An efficient and accurate X-ray detector can be used with scanned X-ray beams. This provides a high degree of sensitivity enabling the visualization of small vessels containing relatively dilute iodine.

Macovski, A.↗

Integrated techno-economic framework for nuclear hydrogen production: assessing the role of high temperature steam electrolysis and safety considerations

This manuscript presents a comprehensive techno-economic assessment of nuclear integrated hydrogen production through high-temperature steam electrolysis (HTSE) in the U.S. Gulf Coast region. Given the significant role of hydrogen as an energy carrier and chemical feedstock, the research evaluates the feasibility of co-locating HTSE facilities with existing nuclear power plants (NPPs) to enhance hydrogen production efficiency and cost-effectiveness. Here, the study highlights the advantages of HTSE over traditional low-temperature electrolysis, particularly in leveraging thermal and electrical energy from NPPs. A novel framework for hydrogen deployment is introduced, integrating hydrogen market analysis, techno-economic evaluation (TEA), and safety assessments. The findings underscore the economic viability of hydrogen production in light of current market conditions, including fluctuating natural gas prices and the impact of production tax credits under the Inflation Reduction Act. A case study in the Gulf Coast region demonstrates the potential for strategic hydrogen production to meet growing industrial demand while ensuring safety and regulatory compliance. Overall, this research contributes to the advancement of nuclear integrated hydrogen production as a sustainable energy solution.

08 - HYDROGEN↗

Neutrino Analysis of the September 2010 Crab Nebula Flare and Time-Integrated Constraints on Neutrino Emission from the Crab Using IceCube

We present the results for a search of high-energy muon neutrinos with the IceCube detector in coincidence with the Crab nebula flare reported on September 2010 by various experiments. Due to the unusual flaring state of the otherwise steady source we performed a prompt analysis of the 79-string configuration data to search for neutrinos that might be emitted along with the observed gamma-rays. We performed two different and complementary data selections of neutrino events in the time window of 10 days around the flare. One event selection is optimized for discovery of E(sub v)(sup -2) neutrino spectrum typical of 1st order Fermi acceleration. A similar event selection has also been applied to the 40-string data to derive the time-integrated limits to the neutrino emission from the Crab [35]. The other event selection was optimized for discovery of neutrino spectra with softer spectral index and TeV energy cut-offs as observed for various galactic sources in gamma-rays. The 90% CL best upper limits on the Crab flux during the 10 day flare are 4.73 x 10(exp -11) per square centimeter per second TeV(sup -1) for an E(sub v)(sup -2) neutrino spectrum and 2.50 x 10(exp -10) per square centimeter per second TeV(sup -1) for a softer neutrino spectra of E(sub v)(sup -2.7), as indicated by Fermi measurements during the flare. IceCube has also set a time-integrated limit on the neutrino emission of the Crab using 375.5 days of livetime of the 40-string configuration data. This limit is compared to existing models of neutrino production from the Crab and its impact on astrophysical parameters is discussed. The most optimistic predictions of some models are already rejected by the IceCube neutrino telescope with more than 90% CL.

Abbasi, R.↗

Neutrino Analysis of the September 2010 Crab Nebula Flare and Time-integrated Constraints on Neutrino Emission From the Crab Using IceCube

We present the results for a search of high-energy muon neutrinos with the IceCube detector in coincidence with the Crab nebula flare reported on September 2010 by various experiments. Due to the unusual flaring state of the otherwise steady source we performed a prompt analysis of the 79-string configuration data to search for neutrinos that might be emitted along with the observed gamma-rays. We performed two different and complementary data selections of neutrino events in the time window of 10 days around the flare. One event selection is optimized for discovery of E(sub nu)(sup -2) neutrino spectrum typical of 1st order Fermi acceleration. A similar event selection has also been applied to the 40-string data to derive the time-integrated limits to the neutrino emission from the Crab [35]. The other event selection was optimized for discovery of neutrino spectra with softer spectral index and TeV energy cut-offs as observed for various galactic sources in gamma-rays. The 90% CL best upper limits on the Crab flux during the 10 day flare are 4.73 x 10(exp -11) per square centimeter per second TeV (sup -1) for an E(sub nu) (sup -2) neutrino spectrum and 2.50 x 10(exp -10) per square centimeter per second TeV(sup -1) for a softer neutrino spectra of E(sub nu)(sup -2.7), as indicated by Fermi measurements during the flare. IceCube has also set a time-integrated limit on the neutrino emission of the Crab using 375.5 days of livetime of the 40-string configuration data. This limit is compared to existing models of neutrino production from the Crab and its impact on astrophysical parameters is discussed. The most optimistic predictions of some models are already rejected by the IceCube neutrino telescope with more than 90% CL.

Stamatikos, M.↗

Ionization of multielectron atoms by fast charged particles.

Using plane waves to describe the incident and scattered particles, and screened hydrogenic and Coulomb functions to describe the atomic electrons before and after ejections, we have calculated the differential and total ionization cross sections of 11 atoms and one ion by electron impact, and ionization of helium by proton impact. The effective charges of the screened hydrogenic functions are fixed by the Hartree-Fock calculations. Calculations have been carried out for the atomic s, p, and d electrons. For low atomic numbers, we find reasonable agreement with the experimental data. For intermediate atomic numbers, we expect our results to overestimate the actual cross sections, since our choice of a unit charge for the Coulomb function of the ejected electrons will overestimate the atomic dipole potential strength, and in turn the high-energy cross sections. The advantage of the method presented here is that the ionization amplitude is given in analytic form. This may allow further analysis on this amplitude, and facilitates extension of the numerical integration for the cross section to high impact energies.

Omidvar, K.↗

Negative-energy states in the Dirac-Hartree-Fock problem - The effect of omission of two-electron integrals involving the small component

The effect of omission of two-electron integrals involving basis functions for the small component of the wavefunction on the eigenvalue spectrum in the Dirac-Hartree-Fock problem is studied. From an analysis of the Fock matrix it is shown that omission of these integrals moves the negative-energy states down, not up. Their complete omission does not give rise to intruder states. The appearance of intruder states occurs when only some of the core integrals are omitted, due to the nature of particular contraction schemes used for the core basis functions. Use of radially localized functions rather than atomic functions alleviates the intruder state problem.

Dyall, Kenneth G.↗

Using Co-Simulation to Model Interconnect-Scale Power Systems from Loads to Generators

Co-simulation is a modeling technique that allows analysts to combine simulation tools and their corresponding models to exchange data during run-time, allowing the creation of larger and more complex models across heterogeneous domains. HELICS is a co-simulation platform developed over the past six years that has been shown to be effective for these multi-domain analysis. Recently, a HELICS-based analysis was completed where the ERCOT electrical interconnect in the United States was modeled in high detail from bulk power system generation to individual customer loads. This model was used to evaluate a flat-rate and transactive energy tariff with integrated wholesale and retail real-time and day-ahead energy markets. This modeling allows detailed analysis showing how the operations of the power system under these tariffs impact all actors in the power system, from individual customers to bulk power system operators.

co-simulation, HELICS, transactive energy system, ↗

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗

Roadmap to reach global net-zero emissions for developing regions by 2085

As climate change intensifies, determining a developing region’s role in achieving net-zero emissions worldwide is crucial. However, regional efforts, considering historical emissions, remain underexplored. Here, we assess energy system changes, technology adoption, and investments needed for developing regions, including five major- and minor-emitting nations. Our analysis, using an integrated assessment model, shows a large gap in regional efforts toward global net-zero emissions, stemming from the necessary shift of energy systems to low-carbon resources. The use of new technologies, like electric vehicles, hydrogen, and carbon capture, varies by region, with the highest adoption required between 2020 and 2030. Financing this shift needs an average gross domestic product (GDP) investment rise of 0.464% in minor-emitting regions and up to 2.1% in major-emitting regions by 2085. Our results could guide policies and support setting quantifiable targets for developing nations. The findings are key to facilitating strategic technology use and finance mobilization to achieve a carbon-neutral future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Comprehensive Life Cycle Analysis of Methanol Production and Methanol-to-Diesel Conversion

Methanol is a strategic chemical and intermediate in the manufacture of synthetic diesel, due to its versatility, diesel’s compatibility with existing infrastructure, and their role in industrial and transport applications. Conventional production methods for methanol, primarily steam methane reforming (SMR), rely on natural gas and are subject to the price variability due to market conditions and geopolitical events. They are also associated with greenhouse gas (GHG) emissions. Methanol and synthetic diesel production could be integrated with nuclear energy to stabilize fuel prices and insulate pricing from outside geopolitical events due to the relative stability of nuclear fuel as compared to natural gas. This could lead to increased transportation fuel security, reliability and resilience. An added benefit is the abatement of emissions when substituting nuclear energy for conventional energy from natural gas. This report presents a comprehensive life cycle analysis(LCA) framework which was developed to evaluate the GHG emissions reduction potential associated with nuclear integrated methanol production, methanol-to-diesel upgrading, and end-use combustion. Gate-to-gate methanol production and cradle-to-grave emissions were evaluated in, starting with a business-as-usual (BAU) SMR-based methanol plant, and then considering stepwise nuclear integration. Methanol-to-diesel (MTD) conversion was evaluated accounting for nuclear energy integration and hydrogen production via high-temperature steam electrolysis (HTSE) using electricity either from the grid or from a dedicated nuclear power system. This multi-step process diverts stable and reliable nuclear energy into the transportation sector by upgrading low energy dense natural gas into liquid fuels fully compatible with existing infrastructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

GIS-Based Graphical User Interface Tools for Analyzing Solar Thermal Desalination Systems & High-Potential Implementation

This project developed a user-friendly, open-source, software that enables a comparative evaluation of solar thermal desalination technology options and employs geospatial data layers to identify regions of high-potential for solar thermal desalination. This was accomplished by integrating solar models with desalination models and enhancing their utility by providing GIS-based data inputs. The developed Solar Energy Desalination Analysis Tool (SEDAT) enables techno-economical evaluation of desalination technologies and selection of regions with the highest potential for using solar energy to power desalination plants. It simplifies the planning, design, and valuation of solar thermal and solar hybrid desalination systems in the U.S. and worldwide. SEDAT uses Dash for integrating various layers of large volumes of GIS data with Python-based models of solar energy generation and desalination technologies. It derives time-series of energy generation and water production, with details of plant performance and suggestions for improving the solar-desalination coupling. It is a one of-a-kind tool of analysis representing a definitive advancement in the state-of-the-art. Of solar desalination modeling This report summarizes the various phases of the tool’s development, and presents examples of the results.

14 SOLAR ENERGY↗

Amplitude analysis and branching-fraction measurement of $\mathrm{D}^+_s$ → $π^+π^oη'$

Using data collected with the BESIII detector in $e^+e^-$ collisions at center-of-mass energies between 4.178 and 4.226 GeV and corresponding to 6.32 fb -1 of integrated luminosity, we report the amplitude analysis and branching-fraction measurement of the $\mathrm{D}^+_s$ → $π^+π^oη'$ decay. We find that the dominant intermediate process is $\mathrm{D}^+_s$ →$ρ^+η'$ and the significances of other resonant and nonresonant processes are all less than 3σ. The upper limits on the branching fractions of S-wave and P-wave nonresonant components are set to 0.10% and 0.74% at the 90% confidence level, respectively. In addition, the branching fraction of the $\mathrm{D}^+_s$ → $π^+π^oη'$ decay is measured to be (6.15 ± 0.25(stat.) ± 0.18(syst.))%, which receives significant contribution only from $\mathrm{D}^+_s$ →$ρ^+η'$ according to the amplitude analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

OEDI—Solar Grid Integration Data and Analytics Library

As a part of the Open Energy Data Initiative, this effort aims to develop and demonstrate novel distribution state estimation, control optimization, and transient analysis as well as provide access to data, data integration, and mapping information. More specifically, the focus of the effort will be on physics-based distribution system state estimation, hybrid (physics-based and machine learning) distribution optimal power flow, and event detection/analysis for solar integration and analytics. This work will enable reproducible, robust, replicable, and generalizable R&D in simulation and emulation of solar system integration. These test models and datasets will provide an integrated library for developing and testing power system operation technologies. To make the library user-friendly, this project will provide data curation tools such as data translators, mapping scripts and APIs, database schemas and metadata, interfaces and user dashboard, source code for the reference algorithms, description of the use-cases/scenarios, and comprehensive information on all the assumptions.

14 SOLAR ENERGY↗

Community-Centric Microgrid Feasibility Analysis Framework to Accelerate Resilience of Island Communities

Marine energy offers a reliable energy solution for island and coastal communities, which often lack traditional local generation, to support their transition to energy independence and reduce reliance on externally imported fuels. Successful deployment of new technologies in these isolated locations requires community acceptance and approval from the outset, as these communities typically lack the financial and technical resources to operate and maintain new systems. This report presents a community-centric microgrid planning framework for remote coastal and island communities. Community engagement is integrated as the first step in the planning process, incorporating community profiles and visions into energy development scenarios. A case study was conducted in St. George, Pribilof Islands, Alaska, which relies entirely on diesel yet has significant wind and wave energy potential. Community engagement revealed a unique history and current economic status, with an interest in adopting advanced energy technologies despite past failures. Various microgrid configurations were optimized, considering different technologies to meet current and future energy needs while balancing cost and energy resilience. Wave energy converters (WECs) were a key component, integrated with other energy sources using the Xendee optimization tool. The Marine Energy Microgrid Toolkit, developed as part of this work, uses commercial power system analysis tools to optimize and analyze microgrid scenarios. The developed framework and toolkit can be applied to island and coastal communities to enhance resilience and support microgrid deployments. Future enhancements will include incorporating new marine resources, developing dynamic models, and automating the integration of Xendee and PowerFactory simulations.

02 PETROLEUM↗