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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

TomoPyUI : a user-friendly tool for rapid tomography alignment and reconstruction

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data ( i.e. organizing data/metadata, applying image filters etc. ) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI , a user interface for the well known tomography data processing package TomoPy . This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI , along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI , and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Scalability of Real-time Distribution Models

This work will focus on developing the capabilities and validating the models for a sub transmission network with multiple feeders and microgrids. To achieve this scale of Hardware-in-the-loop (HitL) simulation, it is necessary to federate and collaborate. The work aims to design the large-scale feeder models to allow federation with complementary testbeds in the future. The feeder would be designed to be reconfigurable to put the system into a variety of modes. Aggregators models will be included in each distribution network’s federate to take control actions and interact with the management systems. Lastly, the feeder model will support large scale resilience studies involving complex Distributed Energy Resources (DER) controls, microgrid studies and emulation of complex data flows in future grid architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower (DIVERS-H)

U.S. hydropower plants face potential threats from shrinking water supply, rising demands, and warmer stream temperatures from various causes. Power plant owners, operators, and regulators require new tools to take advantage of and interpret the diverse range of scientific data being produced by both observational methods (for example, satellite, radar, stream gauges) and computer modeling methods that evaluate and predict how earth's dynamic systems (atmosphere, oceans, land surface, and sea ice) are changing and interacting. Combining datasets such as these with AI-based analyses introduces a novel decision support system to help users anticipate and address potential impacts on power generation stations. This new technology has been named DIVERS-H for "Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower." In Phase I, technical feasibility was established with the development and demonstration of all the new technologies that are required. Most notably, DIVERS-H will use new artificial intelligence (AI) methods to capture the complex dynamics of water availability, demand, and environmental changes. In addition, new data management software was developed, and a prototype user interface was implemented as the precursor to a full scale decision support system. With technical research complete, the project focus now shifts to development of a commercial software product to provide users with actionable insight into water availability and the risk/resilience of critical systems at their locations of interest. Although DIVER-H was originally conceived as a tool for hydroelectric power applications, the same underlying technology can be readily applied to other water-consuming systems including coal, natural gas, oil, and nuclear power plants.

Chaudhary, Aashish [Kitware, Inc., Clifton Park, N↗
DOE OSTI2026

Observationally-based relations among water cycle parameters during snowfall events in the Upper Colorado River Basin

Cold-season precipitation predictability within the complex terrain of the Upper Colorado River Basin is vital for water resource management across many western states, as the Colorado River serves as a primary source of water for over 40 million people in the Western United States and Mexico. This study uses the remote sensing measurements of such water cycle parameters as the liquid equivalent snowfall rate, S, and accumulation, A, vertically integrated amounts of supercooled cloud liquid and ice expressed as liquid water path(LWP) and ice water path (IWP), respectively, and vertically integrated water vapor IWV.

Matrosov, Sergey [CIRES University of Colorado Bou↗
DOE OSTI2026

Stakeholder engagement to address agribusiness concerns and opportunities: the circular carbon bioeconomy example

Effective stakeholder engagement in decisions about complex systems involving sustainable agribusiness requires substantial time and resources by both the managers involved in a supply chain and their stakeholders. Therefore, it is important to understand how to design and implement business strategies that integrate stakeholder perspectives as the project develops. The objective of this article is to explore how actors interested in sustainable and resilient agribusinesses can effectively involve stakeholders in supporting strategies to advance a circular carbon bioeconomy. We consider an approach for stakeholder engagement based on six principles: diversity, listening, value, trust, accountability, and flexibility/ adaptability. Practical means for agribusinesses to apply the six principles to the circular carbon bioeconomy are discussed along with challenges encountered when applying them. Managerial choices and engagement designs and practices are specific to each type of agribusiness. Employing this approach can help project developers prioritize, prepare, and sustain stakeholder engagement, and build local capacities for continual improvement and informed decisions aligned with more sustainable business strategies.

Dale, Virginia [University of Tennessee, Knoxville↗
DOE OSTI2024

7-8 GHz Point-to-Point Testing

Wireless spectrum is a limiting resource for continued economic growth in the United States. As discussed in the recent National Spectrum Strategy (NSS), wireless spectrum underpins several aspects of the U.S. economy and the demand for additional spectrum is driving the need for realizing spectrum sharing to enable continued development. At the same time, wireless spectrum is an essential foundation of critical energy infrastructure, including electric, oil, and natural gas resources. In particular, wireless point-to-point (P2P) links are the backbone of vast infrastructure networks that enable the flow of sensor and control information needed to manage critical energy sector infrastructure in the United States. These links will only become more important as the energy sector incorporates more diverse sensing and more efficient control mechanisms, which increases system complexity and data volume requiring more resilient communications. Therefore, the continued economic development of the U.S. depends on determining novel approaches to spectrum management that balance both broad access for advanced wireless technologies and resilience for critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Diagnostics, Prognostics, and Optimization for Lithium-Ion Battery Systems

Health management of lithium-ion battery systems presents a host of challenges due to their complex physics, large numbers of components, and a wide variety of degradation behaviors across different battery types. Dr. Paul Gasper will present on research from the Electrochemical Energy Storage Group on Lithium-ion battery diagnostics, prognostics, and optimization. Diagnostics research, including state-estimation via machine-learning from electrochemical impedance spectroscopy and DC pulses as well as continuous state-estimation via Kalman filters, will highlight the ongoing challenges for accurately measuring the state of batteries without performing time-consuming characterization tests. NLR's industry-recognized battery prognostics work, which predicts real-world battery degradation by identifying degradation rate models from accelerated aging data using statistical modeling and machine-learning, will be used to demonstrate the critical impact of battery controls, thermal management, and operating strategy on durability and lifetime. Finally, the use of prognostic models for financial or lifetime optimization will be discussed.

25 ENERGY STORAGE↗
DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) Software for Depletion and Fuel Management

The Advanced Dimensional Depletion for Engineering of Reactors (ADDER) software is being developed in the Research and Test Reactor (RTR) Program at Argonne National Laboratory to meet the reactor design and analysis needs of the Conversion Program. ADDER is a flexible tool that (1) provides a depletion capability through coupling external neutronics codes with a built-in CRAM solver or external depletion code and (2) provides a user-friendly interface to perform fuel management and criticality search operations. The ADDER software is a Python 3 application written using modern software development practices subject to a compliant implementation of NQA-1 and applicable Department of Energy software quality assurance standards. This report is the user guide for the software release referred to as ADDER v1.1.0. The motivation for a software to have flexible capabilities that ADDER possesses is the need to support a wide variety of geometries that are commonly required in analysis of research and test reactors. These reactors can have complex fuel, experiment, or control material shuffling patterns that persist over several years with many fuel management and partial refueling intervals. The scale of fuel management analysis can require tracking of an inventory that is multiple times the core loading. Many reactors, both power and non-power reactors of various types, will find the features of ADDER useful to facilitate key tasks that a fuel or core design engineer must perform with the convenience of concise input and validated functionality.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multipolymer Matrix

Additive manufacturing (AM) techniques to directly integrate phase change materials (PCMs) are of interest for efficient thermal energy storage (TES) architectures. Complex, high surface-to-volume ratio composites embedded with PCM can improve thermal management with reduced material waste for customizable device fabrication. Reducing feature sizes of TES-integrated heat exchangers using AM can increase heat transfer without thermal conductivity enhancement. Here, composite AM materials containing 60 wt% microencapsulated phase change materials (MEPCM) are fabricated using off-the-shelf printers at common speeds and resolutions. High MEPCM loading in filaments is achieved with powder extrusion using two polymers, thermoplastic-polyurethane (TPU) and polycaprolactone (PCL), that mediate flexibility and rigidity for effective extrusion and printing without filament fracture or buckling. Furthermore, with PCL and TPU at 20 wt% each and 60 wt% MEPCM (P 20 T 20 M 60 ), smooth, form-stable filaments are consistently printed. Powder-based extrusion displays negligible damaging effects on the MEPCM. Printed P 20 T 20 M 60 demonstrates 105 J/g of energy storage with no degradation through 250 thermal cycles, within 5% of the theoretical storage enthalpy. Combining PCL/TPU shows good interfacial adhesion between print layers and produces high surface area objects, like 15% gyroids, and dense, 100% infilled pucks. Prints are also scalable to a 900 cm 3 honeycomb heat exchanger with an estimated 9 Wh energy storage.

25 ENERGY STORAGE↗
DOE OSTI2026

Analyzing historical snow trends in interior Alaska

Study region The Chena River watershed in Interior Alaska, USA Study focus This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD). New hydrological insights for the region Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: −5.2, −5.0, and −4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10°C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Incorporation of Ion Transport Chains into Multivariate MOF for Improved Water Oxidation

The climate crisis demands clean energy technologies to cut CO 2 emissions from fossil fuels. Hydrogen fuel cells and solar-driven CO 2 reduction are promising, but both rely on efficient water oxidation. Polypyridyl ruthenium complexes are active catalysts for water oxidation; however, they exhibit poor stability and recyclability. Our group improved performance by embedding these complexes into metal−organic frameworks (MOFs). As water oxidation is pH-dependent, proton management further enhances reactivity. To address the issue, we introduced proton transfer pathways into the MOF structure. Specifically, we incorporated −SO 3 H groups onto the biphenyl linkers of UiO-67 loaded with [Ru(tpy)(dcbpy)OH 2 ]PF 6 catalyst (where tpy = 2,2′:6′,2″-terpyridine; dcbpy = 5,5-dicarboxy-2,2′- bipyridine). The sulfonated MOF exhibited a 2.5-fold increase in oxygen evolution compared to the nonsulfonated analogue. After 1 h of electrolysis, the sulfonated MOF exhibited a turnover number of 25 for oxygen evolution reaction compared to 10 for the native MOF, demonstrating the benefits of built-in proton management.

Catalysts↗
DOE OSTI2026

Design of Controller Hardware-In-the-Loop Model of Microgrid with Modular Building Blocks and Automated Design Script

The scalability of controller hardware-in-the-loop (CHIL) simulation is critical for validating control coordination and energy management in microgrids with distributed energy resources, especially as these modern systems become more complex and decentralized. This paper presents a CHIL modeling methodology that combines modular building blocks with an automated design script to streamline the development of high-fidelity microgrid models. Standardized subsystem templates for resources, converters, and buses are integrated with a Python-based script that compiles structured JSON configuration files into simulation-ready initialization code. The proposed approach reduces development time, improves model consistency, and enhances simulation fidelity. The methodology is validated on a Typhoon HIL604 platform and is broadly applicable to real-time simulation of complex, networked microgrid systems. This framework establishes a foundation for automated, scalable CHIL validation and accelerates the design of next-generation distributed energy systems.

Kim, Namwon [ORNL] (ORCID:0000000200438489)↗
DOE OSTI2024

Self-aligned fabrication of vertical, fin-based structures

Modern power devices rely on complex, three-dimensional, vertical designs to increase their power density, ease their thermal management, and improve their reliability. However, fabrication techniques have historically relied on 2D processes for patterning lateral features. This work presents a new technology that uses multiple steps of angled depositions to fabricate self-aligned vertical, fin-based devices that avoid fundamental lithography resolution and alignment limitations. The fabrication flows of two devices, the self-aligned vertical finFET and the high-κ dielectric fin diode, are presented to demonstrate how angled depositions can readily achieve transistors with submicrometer, vertical gates in a source-first process and also create high-aspect ratio GaN fins with a record 70:1 aspect ratio.

Perozek, Joshua (ORCID:0000000251519131)↗
DOE OSTI2024

The Digital Assurance for High Consequence Systems (DAHCS) Mission Campaign Whitepaper

The DAHCS (pronounced “Dax”) MC is a 7-year, $\$$45 million research portfolio within Sandia’s Laboratory Directed Research and Development program. The DAHCS MC arose in response to a great need: to ensure that the use of digital technologies does not weaken our nation’s high consequence systems. Digital technologies offer many benefits in speed, cost, and flexibility, and we seek to reap those benefits without introducing new system failures. However, digital technologies cannot be evaluated the same way as analog technologies. Initiatives across the nation highlight the capability gap that prevents efficient, effective digital assurance. The Challenge Today’s digital assurance tools, techniques, and methods are inadequate to confidently characterize, assess, and manage digital risk; they are ad hoc, slow, costly, and rarely scalable to increasingly complex digital technologies. The rapidly evolving cyber threat landscape exacerbates this problem because digital assurance now must secure against digital risks now and in the future, including those introduced by rapidly evolving technologies, adversaries, and systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Detection and Screening of Organic Contaminants in A Riverine System of Georgia Using Non-Targeted Analysis

Numerous organic chemicals exist within aquatic environments, yet effectively screening and prioritizing them is a huge challenge. This study provides a comprehensive investigation into the ecological dynamics of the North Oconee River within Athens-Clarke County, Georgia, with a specific focus on the distribution of 33 identified compounds, including a prominent pesticide. The research, conducted in the riverine ecosystems proximal to the Firefly trail, employs advanced analytical techniques to elucidate potential contamination sources arising from agricultural and urban runoff. Intriguingly, the study reveals North Oconee River near the Firefly Trail as a notable site for heightened pesticide contamination, warranting a meticulous exploration of its origins. Furthermore, the investigation unveils the intricate microbial degradation processes of malathion within the North Oconee River, elucidating the pivotal role played by microbial activity in river water. The detection of degradant byproducts prompts the considerations of bioavailability and toxicity, associating potential implications for the river’s overall ecological health. Ongoing research endeavors to precisely quantify environmental risks and unravel indigenous microbial degradation pathways, presenting pivotal contributions to the scientific community’s understanding of complex riverine ecosystems. This research serves as a foundational piece in informing sustainable environmental management practices and emphasizes the urgency of comprehensive stewardship in safeguarding aquatic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Managing Increased Electric Vehicle Shares on Decarbonized Bulk Power Systems

Transportation electrification and power sector decarbonization - the convergence of these two trends present a complex planning problem requiring realistic, region-specific modeling and analysis to ensure that both can happen rapidly and cost effectively. This project, funded through the U.S. Department of Energy's Vehicle Technologies Office, models the evolution of the U.S. bulk power system (through 2050) in response to large-scale EV charging across all on-road vehicle segments. We will assess the opportunity and value of demand-side flexibility (i.e., "smart" charging) for reducing energy costs, increasing renewable generation shares, and managing future EV loads on the bulk power system. Overall, this study aims to provide an improved understanding of least-cost solutions for managing EV load growth on the grid and will make high-resolution EV load data sets publicly available for further analysis.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗