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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 145 records · Page 8

Discovery of X-Ray Emission from the Galactic Supernova Remnant G32.8-0.1 with Suzaku

We present the first dedicated X-ray study of the supernova remnant (SNR) G32.8-0.1 (Kes 78) with Suzaku. X-ray emission from the whole SNR shell has been detected for the first time. The X-ray morphology is well correlated with the emission from the radio shell, while anti-correlated with the molecular cloud found in the SNR field. The X-ray spectrum shows not only conventional low-temperature (kT approximately 0.6 kiloelectronvolts) thermal emission in a nonequilibrium ionization state, but also a very high-temperature (approximately 3.4 kiloelectronvolts) component with a very low ionization timescale (approximately 2.7 times 10 (sup 9) per cubic centimeter per second), or a hard nonthermal component with a photon index Gamma approximately equal to 2.3. The average density of the low-temperature plasma is rather low, of the order of 10 (sup -3) - 10 (sup -2) per cubic centimeter, implying that this SNR is expanding into a low-density cavity. We discuss the X-ray emission of the SNR, also detected in teraelectronvolts with H.E.S.S. (High Energy Stereoscopic System), together with multi-wavelength studies of the remnant and other gamma-ray emitting SNRs, such as W28 and RCW 86. Analysis of a time-variable source, 2XMM J185114.3-000004, found in the northern part of the SNR, is also reported for the first time. Rapid time variability and a heavily absorbed hard-X-ray spectrum suggest that this source could be a new supergiant fast X-ray transient.

Petre, Robert↗

New Tools for Tour Design: Swiss Cheese Plot, Invariant Funnel, and Resonant Encounter Map

We define a new set of tools for tour design introduced in previous work: the”Swiss Cheese Plot,” ”Invariant Funnel,” and ”Resonant Encounter Map.” These tools promise to be useful in designing, analyzing, and navigating low-energy trajectories through multi-body systems. We review and clarify methods for generating the swiss cheese plot and invariant funnels in the Circular Restricted Three-Body Problem. We introduce the resonant encounter map as a graphical representation of the three-body design space, similar to the pork-chop plot for the two-body problem. We also discuss some interesting characteristics of the resonant encounter map and its connection to the invariant manifolds of periodic libration orbit

Close, Sigrid↗

Resonant Landau-Zener conversion in multi-axion systems

Multiple axions may emerge in the low-energy effective theory of Nature. Generically, the potentials describing these axion fields are non-diagonal, leading to mass mixing between axion states which can be temperature-dependent due to QCD instanton effects. As the temperature of the Universe drops, level crossing can occur, causing resonant conversion between axion states. In this work, we present an analytic study of the cosmological evolution of multi-axion systems including adiabatic and non-adiabatic resonant conversion from one axion state into another during the misalignment process. We show how the Landau-Zener formalism accurately captures the non-adiabatic resonant conversion, permitting an analytic description of the relic abundances of each axion field for nearly any arbitrary two-state axion mass matrix. As an application, we study the mixing of a QCD axion with an axion-like-particle for specific potentials to identify the predictions for haloscope experiments. We conclude that the detection of an axion off the expected QCD mass-coupling line predicts other haloscope targets if it mixes with the QCD axion.

Axions and ALPs↗

Quantum computing hardware for HEP algorithms and sensing

Quantum information science harnesses the principles of quantum mechanics to realize computational algorithms with complexities vastly intractable by current computer platforms. Typical applications range from quantum chemistry to optimization problems and also include simulations for high energy physics. The recent maturing of quantum hardware has triggered preliminary explorations by several institutions (including Fermilab) of quantum hardware capable of demonstrating quantum advantage in multiple domains, from quantum computing to communications, to sensing. The Superconducting Quantum Materials and Systems (SQMS) Center, led by Fermilab, is dedicated to providing breakthroughs in quantum computing and sensing, mediating quantum engineering and HEP based material science. The main goal of the Center is to deploy quantum systems with superior performance tailored to the algorithms used in high energy physics. In this Snowmass paper, we discuss the two most promising superconducting quantum architectures for HEP algorithms, i.e. three-level systems (qutrits) supported by transmon devices coupled to planar devices and multi-level systems (qudits with arbitrary N energy levels) supported by superconducting 3D cavities. For each architecture, we demonstrate exemplary HEP algorithms and identify the current challenges, ongoing work and future opportunities. Furthermore, we discuss the prospects and complexities of interconnecting the different architectures and individual computational nodes. Finally, we review several different strategies of error protection and correction and discuss their potential to improve the performance of the two architectures. This whitepaper seeks to reach out to the HEP community and drive progress in both HEP research and QIS hardware.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Resilient U.S. Land Ports of Entry

The continued operation of Land Ports of Entry (LPOE), managed by the Customs and Border Protection (CBP) and General Services Administration% is vital to the U.S. economy and security. Border faculties are included in the Department of Homeland Security (DHS) Government Facilities Sector2, one of the 16 critical infrastructures "whose assets, systems, and networks, whether physical or virtual, are considered so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.'" Specifically, disruptions to the flow of border crossing traffic, in the form of closures or increased border crossing wait times, impact the economy and security of all countries involved. This paper describes a process for analyzing and improving the resilience of U.S. Land Ports of Entry. For LPOE, the team believes that energy resilience is the primary objective due to the complete reliance on the e-manifest system and the increasing use of Multi-Energy Portals (MEPs). Emanifests are part of CPB's Automated Commercial Environment (ACE). They document several key pieces of information about cargo vehicles wishing to cross the border into the United States and are submitted before arriving at the port. Vehicles can be flagged for more invasive inspection based on the content of the e-manifest. MEPs are a non-intrusive inspection (NII) technology used to scan the contents of the cargo. Together MEPs and ACE serve an important role in aiding CBP with their mission to protect "the public from dangerous people and materials", and "enabling legitimate trade and travel.'" To analyze resilience of a port, the team would need to understand the port's current energy usage, which systems depend on energy and what backup systems exist, and any emergency operation plans that dictate how systems are operated in the event of a power outage. The team would also need to determine the design basis threats (DBTs) for the LPOE which could include natural disasters, manmade events, and accidents. The magnitudes of the DBTs are calculated and are then translated to expected impacts on the infrastructure and systems at the port. With this information gathered, existing LPOE models developed here at Sandia National Laboratories could be extended to support decisions about resilience. Current models are implemented in FlexSim, a 3rd party discrete event simulator. FlexSim provides 3-D visuals of physical layout that can reveal valuable insights, allows input to be variable (e.g. time it takes to interact with the CBP officer at primary inspection can vary) so that a whole range of possibilities can be captured in the results, and can be used to collect user-defined output metrics. Current LPOE models focus on cargo vehicle traffic, and process changes caused by the installation of new drive-through MEPs. Extending them to address resilience questions would require the addition of key pieces of information learned during the resilience analysis including critical systems, failure rates, and process changes for when failures occur. The primary output metric for current models is border crossing wait time. Additional metrics would also be added to the model to gain a more complete understanding of impacts related to resilience, for example, MEP scan rate. Once complete, the model could be used to analyze the effectiveness of mitigation strategies representing some future state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Experimental investigation of Multi-Mode heat transfer to a Free-Falling dilute particle cloud in a heated vertical tube

The development of dilute particle heat exchangers and reactors for advanced energy systems requires an understanding of the multi-mode heat transfer from a heated wall to falling particles. This study presents experimental results of the overall heat transfer coefficient for a free-falling, dilute flow of particles with solid volume fraction from 0.0005 to 0.006 corresponding to feed rates from 3.7 kg s -1 m -2 to 44 kg s -1 m -2 in a vertical, heated tube containing quiescent air at atmospheric pressure. Tube wall temperatures are varied between 300°C to 900°C while keeping the particle inlet temperature constant. The experimental results show that the overall heat transfer coefficient is a strong function of particle feed rate and surface temperature. Good agreement was obtained with prior studies conducted at comparable temperatures but lower particle feed rates (< 4 kg m -2 s -1 ). The established correlations for particle-to-wall radiation and particle-to-gas convection were used to estimate the wall-to-gas convective contribution from the measured overall heat transfer coefficient. The experimental results indicated a 4 to 6 times improvement in the wall convection in the solid-gas mixture compared to that expected from natural convection in a single-phase gas. Furthermore, the data presented here are applicable to characterize heat transfer in dilute particle heat exchangers, furnaces, and solar receivers.

14 SOLAR ENERGY↗

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma-facing component (PFC) operating lifetime and the impact of the evolving surface morphology of tungsten-based PFCs on plasma contamination, including the dynamic recycling of fuel species and tritium retention, in future magnetic fusion devices. Establishing a fundamental physical understanding and developing predictive capabilities of plasma-surface interactions (PSI) requires simultaneously addressing complex and diverse physics occurring over a wide range of length (Angstroms to meters) and time (femtoseconds to years) scales, as well as integrating extensive physical processes across the plasma–surface interface. This requires development of not only detailed physics models and computational strategies at each scale, but also algorithms and methods to couple them effectively in a way that can be robustly validated. Deploying these tools requires the continued development and coupling of leadership-scale computational codes to describe the boundary plasma and the evolving PFC surface, as well as a host of simulations that bridge disparate scales to address complex physical and computational issues at the plasma–surface interface in multi-component materials systems for magnetic fusion energy development beyond ITER.

36 MATERIALS SCIENCE↗

Advanced Solar-propelled Cargo Spacecraft for Mars Missions

Three concepts for an unmanned, solar powered, cargo spacecraft for Mars support missions were investigated. These spacecraft are designed to carry a 50,000 kg payload from a low Earth orbit to a low Mars orbit. Each design uses a distinctly different propulsion system: A Solar Radiation Absorption (SRA) system, a Solar-Pumped Laser (SPL) system and a solar powered magnetoplasmadynamic (MPD) arc system. The SRA directly converts solar energy to thermal energy in the propellant through a novel process. In the SPL system, a pair of solar-pumped, multi-megawatt, CO2 lasers in sunsynchronous Earth orbit converts solar energy to laser energy. The MPD system used indium phosphide solar cells to convert sunlight to electricity, which powers the propulsion system. Various orbital transfer options are examined for these concepts. In the SRA system, the mother ship transfers the payload into a very high Earth orbit and a small auxiliary propulsion system boosts the payload into a Hohmann transfer to Mars. The SPL spacecraft and the SPL powered spacecraft return to Earth for subsequent missions. The MPD propelled spacecraft, however, remains at Mars as an orbiting space station. A patched conic approximation was used to determine a heliocentric interplanetary transfer orbit for the MPD propelled spacecraft. All three solar-powered spacecraft use an aerobrake procedure to place the payload into a low Mars parking orbit. The payload delivery times range from 160 days to 873 days (2.39 years).

Auziasdeturenne, Jacqueline↗

Multi-layered Energy Management Framework for Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, and Forecast Uncertainties

To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy and yields optimal scheduling of the energy resources on a rolling horizon basis, thereby considering the long-term forecast errors. A lower dispatch layer (LDL) takes the short-term forecast errors into account during the real-time operation of the XFCS. Per the latest research, monthly demand charges can be as high as 90% of the total monthly bills for EV fast charging stations; to this end, this paper takes the first attempt at the reduction of demand charges cost by considering the trade-off between the energy cost and monthly demand charges. Contrasting literature, this work allocates an energy reserve in the BESS stored energy to deal with the impact of short-term forecast errors on the optimized real-time operation of the XFCS. Moreover, degradation modeling considers the trade-off between short-term benefits and long-term BESS life degradation. As a result, case studies and a comparative analysis prove the efficacy of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-objective sizing and dispatch for building thermal and battery storage towards economic and environmental synergy

The role of building thermal and battery storage is pivotal in advancing smart cities and achieving sustainability goals through effective energy management. Despite their significance, there are several limitations in the sizing approach and value stream analysis with various objectives for their widespread adoption in buildings. This work proposes a flexible and scalable multi-objective optimization framework for optimal sizing and dispatch of building thermal and battery storage, addressing conflicting objectives simultaneously using mixed-integer linear programming. The weighted-sum method is adapted, combining multiple objectives into a single function. The two-stage procedure iterates over different weights, generating optimal solutions and forming the Pareto front. Case studies are performed to assess the energy, economic, and environmental benefits of building energy storage systems for a large office building in three climate locations. The results demonstrate that the proposed framework efficiently determines optimal sizing and dispatch strategies, addressing the balance between economic viability and emission reduction. The dynamic relationship between time-of-use energy charges and emission factors leads to significantly different strategies based on whether economic or environmental concerns are prioritized. This research enhances our understanding of the benefits of TES and BES systems in buildings, providing valuable guidance to stakeholders.

25 ENERGY STORAGE↗

Stochastic Continuous-time Flexibility Scheduling and Pricing in Wholesale Electricity Markets

Large-scale integration of intermittent renewable energy sources (RES) is calling for additional flexibility resources as well as more advanced modeling and optimization techniques to account for the increasing uncertainty and variability in power systems operation. As the RES integration gains momentum, the magnitude and frequency of their variations increase, which may trigger ramping scarcity events in real-time power systems operation. This necessitates revisiting the present definition of power systems flexibility and reserve services to reflect their robustness and adequacy towards sub-interval variations of the load and RES, as well as adjusting the operation models to accommodate the new reserve services. This project took a fundamental approach and aimed at developing continuous-time scheduling and pricing model that accurately models the continuous-time variations of load and RES and efficiently deploys the ramping capability of flexible resources to compensate the sources of variability and uncertainty in the market. In this regard, this project pursued the following goals: Developing stochastic multi-fidelity continuous-time optimization models for scheduling of energy storage (ES) systems and flexible loads in wholesale energy markets; Developing the theory and practices of continuous-time locational marginal pricing for valuating energy storage systems and flexible loads in wholesale energy markets; Developing function space solution approach to convert the proposed stochastic multi-fidelity continuous-time optimization models into tractable mixed-integer linear optimization models; and Defining flexibility reserve as a new type of reserve in markets that would enable ultimate participation of energy storage devices in provision of services to compensate the variability and uncertainty of RES in electricity markets. This project successfully completed all five major tasks defined in the SOPO, and produced 8 high-impact journal papers, 6 conference papers, 3 published U.S. patents, and one web-based software for continuous-time operation optimization of power systems. The application of the proposed flexibility reserve and the stochastic multi-fidelity continuous-time operation scheduling models would modify the forward commitment and schedule of generating units, ES devices and flexible loads, and would line up the resources in such a way that the composition of available resources is better prepared to respond to the sub-hourly variations of the load and renewable resources in real-time operation. Therefore, this project paves the way to sustainable, reliable, and economic integration of renewable energy resources in power system, supporting the progress towards reaching the national targets on energy independence. Even if the proposed models offers a radically different point of view as compared to existing models, it does not alter fundamentally the architecture of power systems operations, nor the complexity of the scheduling problem, so the integration of this project in power systems is extremely practical.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Peak Demand Limiting and Optimization of HVAC Systems for Common Areas in High-Rise Multi-Family Housing (CRADA 518)

This project aims to create an innovative energy saving solution that is affordable and easy to implement. Initially, the proposed solution will fulfill an existing need for HVAC systems that serve multi-family housing. However, the solution can be easily expanded to other markets such as large hospitals, hotels, and commercial buildings. The proposed solution will be creatively packaged so that it can work where peak demand charge is high or where goal is to conserve energy and reduce carbon footprint. Of course, both Peak Demand Limiting (PDL) and Set-point optimization (SPO) can also operate simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Simulation of Compound Flooding Using River‐Ocean Two‐Way Coupled E3SM Ensemble on Variable‐Resolution Meshes

Abstract Coastal zone compound flooding (CF) can be caused by the interactive fluvial and oceanic processes, particularly when coastal backwater propagates upstream and interacts with high river discharge. The modeling of CF is limited in existing Earth System Models (ESMs) due to coarse mesh resolutions and one‐way coupled river‐ocean components. In this study, we present a novel multi‐scale coupling framework within the Energy Exascale Earth System Model (E3SM), integrating global atmosphere and land with interactively coupled river and ocean models using different meshes with refined resolutions near the coastline. To evaluate this framework, we conducted ensemble simulations of a CF event (Hurricane Irene in 2011) in a Mid‐Atlantic estuary. The results demonstrate that the novel E3SM configuration can reasonably reproduce river discharge and sea surface height variations. The two‐way river‐ocean coupling improves the representation of coastal backwater effects at the terrestrial‐aquatic interface that are caused by the combined actions of tide and storm surge during the CF event, thus providing a valuable modeling tool for better understanding the river‐estuary‐ocean dynamics in extreme events under climate change. Notably, our results show that the most significant CF impacts occur when the highest storm surge generated by a tropical cyclone meets with a moderate river discharge. This study highlights the state‐of‐the‐art advancements developed within E3SM for simulating multi‐scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗

Demonstrating Distribution System Resiliency through Grid-Edge Microgrids, on a Multi-Site Networked Hardware-in-Loop Platform

With the increasing penetration of Distributed Energy Resources (DERs) at the grid-edge, power systems include more energy storage, remote switches, relays, voltage regulators, and other intelligent electronic devices (IED). Effective control of these grid-edge devices by using Advanced Distribution Management Systems (ADMS) can yield substantial improvements to the resiliency and power quality of distribution systems. In this paper, improvements to the resiliency of a distribution system are demonstrated using a multi-site evaluation environment consisting of a real-time Hardware-in-Loop (HIL) setup in which DERs and other IEDs are modeled; and an ADMS which monitors and is able to control the distribution system assets. The HIL model and the ADMS are located 2400 km away, with communication between the sites enabled by a data manager using Distributed Network Protocol 3 (DNP3), demonstrating the system's capabilities even over long distances. After a simulated transmission system failure in the HIL demonstration setup, DERs and other devices are operated to restore critical loads and node voltage profile (to within the 'nominal +/-5%' band) in the distribution system.

ADMS↗

An Efficient Distributed Reinforcement Learning for Enhanced Multi-Microgrid Management

Economic dispatch in multi-microgrid (MMG) systems requires coordinating distributed energy resources (DERs) of different microgrids, which leads to a significant increase in the number of states for energy management. In these cases, traditional reinforcement learning (RL) approaches become computationally expensive or output a solution that causes extra-operating costs for the system. This paper proposes an RL approach that employs local learning agents to interact with microgrid environments in a distributed manner and aggregates the outcomes to train the global agent to learn the policy for the MMG system. This distributed exploration and aggregation process provides an effective solution and guides the global agent to learn the dispatch policy efficiently. Case studies are performed on a system with three microgrids with different types of DERs. Results obtained using the proposed RL and comparisons with conventional methods substantiate the effectiveness of the proposed approach in terms of operation costs, computation time, and peak-to-average ratio.

Das, Avijit↗

Feasibility of Multi-Use Ocean Thermal Energy Conversion (OTEC) Platforms

Tropical islands and coastal communities in the United States and internationally suffer from high energy costs, unreliable electrical supplies, poverty, and underemployment, which are all being exacerbated by climate change. Multi-use Ocean Thermal Energy Conversion (OTEC) systems could align with the goals and values of these underserved and remote communities as scalable platforms that can provide baseload power, freshwater, and food, as well as potentially support new industries. The cold, nutrient-rich deep seawater needed for OTEC’s power cycles has many promising byproduct applications such as seawater air conditioning (SWAC) for residential and industrial cooling, enhancing aquaculture farms (e.g., cooling and nutrients for seaweed, shellfish, finfish), producing freshwater through desalination, and generating efuels such as ammonia and hydrogen.

16 TIDAL AND WAVE POWER↗