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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

High-Efficiency Food Production in a Renewable Energy Based Micro-Grid Power System

Controlled Environment Agriculture (CEA) systems can be used to produce high-quality, desirable food year round, and the fresh produce can positively contribute to the health and well being of residents in communities with difficult supply logistics. While CEA has many positive outcomes for a remote community, the associated high electric demands have prohibited widespread implementation in what is typically already a fully subscribed power generation and distribution system. Recent advances in CEA technologies as well as renewable power generation, storage, and micro-grid management are increasing system efficiency and expanding the possibilities for enhancing community supporting infrastructure without increasing demands for outside supplied fuels. We will present examples of how new lighting, nutrient delivery, and energy management and control systems can enable significant increases in food production efficiency while maintaining high yields in CEA. Examples from Alaskan communities where initial incorporation of renewable power generation, energy storage and grid management techniques have already reduced diesel fuel consumption for electric generation by more than 40% and expanded grid capacity will be presented. We will discuss how renewable power generation, efficient grid management to extract maximum community service per kW, and novel energy storage approaches can expand the food production, water supply, waste treatment, sanitation and other community support services without traditional increases of consumable fuels supplied from outside the community. These capabilities offer communities with a range of choices to enhance their communities. The examples represent a synergy of technology advancement efforts to develop sustainable community support systems for future space-based human habitats and practical implementation of infrastructure components to increase efficiency and enhance health and well being in remote communities today and tomorrow.

Fuel↗
NASA NTRS2017

High-Efficiency Food Production in a Renewable Energy Based Micro-Grid

Controlled Environment Agriculture (CEA) systems can be used to produce high-quality, desirable food year round, and the fresh produce can positively contribute to the health and well being of residents in communities with difficult supply logistics. While CEA has many positive outcomes for a remote community, the associated high electric demands have prohibited widespread implementation in what is typically already a fully subscribed power generation and distribution system. Recent advances in CEA technologies as well as renewable power generation, storage, and micro-grid management are increasing system efficiency and expanding the possibilities for enhancing community supporting infrastructure without increasing demands for outside supplied fuels. We will present examples of how new lighting, nutrient delivery, and energy management and control systems can enable significant increases in food production efficiency while maintaining high yields in CEA.Examples from Alaskan communities where initial incorporation of renewable power generation, energy storage and grid management techniques have already reduced diesel fuel consumption for electric generation by more than 40 and expanded grid capacity will be presented. We will discuss how renewable power generation, efficient grid management to extract maximum community service per kW, and novel energy storage approaches can expand the food production, water supply, waste treatment, sanitation and other community support services without traditional increases of consumable fuels supplied from outside the community. These capabilities offer communities with a range of choices to enhance their communities. The examples represent a synergy of technology advancement efforts to develop sustainable community support systems for future space-based human habitats and practical implementation of infrastructure components to increase efficiency and enhance health and well-being in remote communities today and tomorrow.

Renewable Energy↗
NASA NTRS2019

Assimilation of Sentinel 1 and SMAP – Based Satellite Soil Moisture Retrievals into SWAT Hydrological Model: the Impact of Satellite Revisit Time and Product Spatial Resolution on Flood Simulations in Small Basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR obtained via S1 over ASCAT was small likely due to very challenging areas for S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the soil moisture pre-storm conditions.

Small basins↗
NASA NTRS2019

Assimilation of Sentinel 1 and SMAP–based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins

In runoff generation process, soil moisture plays an important role as it controls the magnitude of the flood events in response to the rainfall inputs. In this study, we investigated the ability of a new era of satellite soil moisture retrievals to improve the Soil & Water Assessment Tool (SWAT) daily discharge simulations via soil moisture data assimilation for two small (< 500 km2) and hydrologically different catchments located in Central Italy. We ingested 1) the Soil Moisture Active and Passive (SMAP) Enhanced L3 Radiometer Global Daily 9 km EASE-Grid soil moisture, 2) the Advanced SCATterometer (ASCAT) H113 soil moisture product released within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (HSAF) which has a nearly daily temporal resolution and sampling of 12.5 km, and 3) a fused ASCAT/Sentinel-1 (S1) satellite soil moisture product named SCATSAR-SWI with temporal and spatial sampling of 1 day and 1 km, respectively into SWAT hydrological model via the Ensemble Kalman Filter (EnKF). Different configurations were tested with the aim of exploring the effect of the hydrological regime, the land use conditions, the spatial sampling and the revisit time of the products (which controls the amount of available data to be potentially ingested). Results show a general improvement of SWAT discharge simulations for all products in terms of error and Nash Sutcliffe efficiency index. In particular, we found a relatively good behavior of both the active and the passive products in terms of low flows improvement especially for the catchment characterized by a higher baseflow component. The benefit of the higher spatial resolution of SCATSAR-SWI obtained via S1 over ASCAT was small, likely due to very challenging areas for the S1 retrieval. Eventually, better performances were obtained for the passive product in the more forested catchment. With the aim of exploring the benefit of having more frequent satellite soil moisture observations to be ingested, we tested the performance of the ASCAT product with a reduced temporal sampling obtained by temporally matching ASCAT observations to that of SMAP. The results show a significant reduction of the performance of ASCAT, suggesting that the correction frequency (due to the higher number of observations available) for small catchments is an important aspect for improving flood forecasting as it helps to adjust more frequently the pre-storm soil moisture conditions.

Shima Azimi↗
DOE OSTI2025

Open Power System Datasets and Open Simulation Engines: A Survey Toward Machine Learning Applications

A major factor behind the success of machine learning (ML) models in multiple domains is the availability and accessibility of large, labeled, and well-organized datasets for training and benchmarking. In comparison, power grid datasets face three major challenges: (i) real-world data is often restricted by regulatory constraints, privacy reasons, or security concerns, making it difficult to obtain and work with; (ii) synthetic datasets, which are created to address these limitations, often have incomplete information and are released using specialized tools, making them inaccessible to the broader community; and, (iii) input-output datasets are difficult to generate through simulation for non-experts because open-source simulators are not known outside the power system community. This survey addresses these challenges by serving as an entry point to publicly available datasets and simulators for researchers venturing in this area. We review the current landscape of open-source power network data, machine models, consumer demand profiles, renewable generation data, and inverter models. We also examine open-source power system simulators, which are crucial for generating high-quality, high-fidelity power grid datasets. We aim to provide a foundation for overcoming data scarcity and advance towards a structured web of datasets and simulators to support the development of ML for power systems.

42 ENGINEERING↗
DOE OSTI2026

A Guide for Public Utility Commissions: Building Internal Technical Capacity and Recruiting Talent for Grid Resilience

This guide offers insight into how PUCs can strategically expand their technical workforce to meet evolving gird resilience demands. It outlines critical skill sets needed to support informed regulatory decision-making around resilience, such as modeling and weather forecasting, electric power systems analysis, and advanced data interpretation. In addition, it provides strategies for developing technical talent both internally and through additional recruitment efforts. Two appendices provide a list of grid resilience training resources and a compendium of sample job descriptions that reflect grid resilience technical expertise for PUC consideration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1998

Current Grid Generation Strategies and Future Requirements in Hypersonic Vehicle Design, Analysis and Testing

Recent advances in computational power enable computational fluid dynamic modeling of increasingly complex configurations. A review of grid generation methodologies implemented in support of the computational work performed for the X-38 and X-33 are presented. In strategizing topological constructs and blocking structures factors considered are the geometric configuration, optimal grid size, numerical algorithms, accuracy requirements, physics of the problem at hand, computational expense, and the available computer hardware. Also addressed are grid refinement strategies, the effects of wall spacing, and convergence. The significance of grid is demonstrated through a comparison of computational and experimental results of the aeroheating environment experienced by the X-38 vehicle. Special topics on grid generation strategies are also addressed to model control surface deflections, and material mapping.

Papadopoulos, Periklis↗
DOE OSTI2026

Supporting U.S. National Security Through Cybersecurity Partnerships

At NLR, we're studying energy evolutions and threats to understand the challenges they pose and uncover ways to leverage grid advancements to achieve more secure, defensible, and reliable systems. Our integrated research approach bridges the gap between cyber threats and real-world consequences to deliver actionable solutions that reduce vulnerabilities and help strengthen U.S. national security.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Characterization of MC&A for the Molten Salt Fuel Cycle

Advanced reactor developers are exploring diverse reactor designs, including molten salt reactors (MSRs). These advanced reactors are considered for wider applications and a range of deployment locations, including supporting the integration of renewable energy sources in the grid. There are three main types of MSRs: (1) reactors in which the fuel salt freely circulates within the core; (2) reactors with the fuel salt contained within vented fuel tubes; and (3) reactors that use molten salt solely as a coolant, with the fuel in a separate, solid form. In this document, the term MSR refers specifically to the first two types, which use fuel salt—special nuclear material (enriched uranium, plutonium, and 233 U) in chloride or fluoride form mixed with chloride- or fluoride-based carrier salt in a peritectic mixture—as the primary medium for fission. The composition of fuel salt, both at startup and for makeup or refueling, varies depending on the MSR design and the chosen fuel cycle approach, which can be either once-through or closed. For MSRs, a variety of fuel cycle approaches (e.g., U, U–Pu, U–Pu–TRU, U–Th, U–Pu–Th) are being considered. Fuel in MSRs is much different than traditional solid fuel, including its preparation. The uniqueness warrants investigation into characterizing fuel preparation processes, known as fuel salt synthesis . This effort characterized major fuel preparation and synthesis processes, identifying temperature, equipment, and environmental requirements for uranium-, plutonium-, and thorium-based fuel preparation and synthesis. Because MSR fuel salt synthesis facilities handle special nuclear material in loose, bulk form, a material control and accounting plan will be required for licensing from the US Nuclear Regulatory Commission or under the US Department of Energy authorization. This effort serves as a foundation to investigate material control and accounting approaches for synthesis facilities, including determining measurement points and techniques. Because several MSR developers are planning demonstration facilities in the coming years, this effort will support stakeholders with preparing or reviewing material control and accounting plans for providing assurance that all special nuclear material is accounted for at fuel salt synthesis facilities. This report was produced for Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy (DOE), Office of Nuclear Energy, Nuclear Fuel Cycle and Supply Chain.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Artificial Intelligence for Enhancing Multiscale Analysis: Buildings Focus

This project aims to develop multi-scale building energy data, potentially improving the representation of the U.S. buildings sector in GCAM-USA, an U.S.-focused human-energy-Earth systems model. Existing building energy datasets are typically limited to national or regional levels, which constrains the ability of models to capture fine-scale human-energy-Earth systems interactions and reduces their relevance for decision-making on issues such as energy security, resilience, and energy planning. By leveraging AI and advanced data integration methods, this work fuses multiple existing datasets to enhance the physical and geographic representation of both residential and commercial building energy use. So far, progress includes processing residential building data, designing the data structure for commercial buildings, and testing AI approaches for integrating datasets and addressing spatial-temporal gaps. This effort can not only advances GCAM-USA’s capability in modeling the buildings sector but also supports broader DOE missions, such as developing digital testbeds, enhancing grid resilience analysis, and improving building–energy system modeling at decision-relevant scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗
DOE OSTI2025

A Performance Portable, Fully Implicit Landau Collision Operator with Batched Linear Solvers

Modern accelerators use hierarchical parallel programming models that enable massive multithreading within a processing element (PE), with multiple PEs per device driven by traditional processes. Batching is a technique for exposing PE-level parallelism in algorithms that have traditionally run on MPI processes or multiple threads within a single process. Opportunities for batching arise in, for example, kinetic discretizations of magnetized plasmas where collisions are advanced in velocity space at each spatial point independently. This paper builds on previous work on a high-performance, fully nonlinear, Landau collision operator by batching the linear solver, as well as batching the spatial point problems and adding new support for multiple grids for multiscale, multispecies problems. An anisotropic relaxation verification test that agrees well with previously published results and analytical models is presented. The performance results from NVIDIA A100 and AMD MI250X nodes are presented with hardware utilization analysis for each architecture. Finally, the entire implicit Landau operator time advance is implemented in Kokkos for performance portability, running entirely on the device and is available in the PETSc numerical library.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Model-Specific Metadata for Enhancing Space Science Models

The Space Weather and Heliophysics modeling community, supported by the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov), provides a collaborative platform for space weather models and data. Flexible metadata is vital for advancing scientific research and fostering collaboration. Our work in expressing complex simulations of the Space Weather Modeling Framework (SWMF), particularly Global Magnetosphere (GM) grid components, in terms of simple metadata records shows great promise in creating searchable and reusable units of knowledge. Such records can be readily utilized to support the process of scientific discovery, closely aligning with the goals outlined in the Open Science initiative. Our primary goal is to show the scalability and benefits of metadata-focused methodologies. This presentation highlights the potential for applying metadata methodologies to other complex models, improving usability, supplying efficient documentation and fostering interdisciplinary research.

space weather↗
NASA NTRS1979

Advanced development of atmospheric models

A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.

Kesel, P. G.↗
DOE OSTI2026

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗
DOE OSTI2024

Technical Learning and Integration of Interns in Advanced Protection Lab Space: Enhancements to Testbed and Experiments to Improve Workflows for Producing Datasets

This report presents a successful technical learning integration of student interns in the Advanced Protection Laboratory space, located in the Grid Research Integration and Deployment Center (GRID-C) at the Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL). The Advanced Protection Laboratory was created for the primary goal of supporting DOE’s research projects and technical staff at ORNL. As a secondary goal, the space was used for collaborating with ORNL’s intern programs, providing support to the lab’s mentors and student interns. In 2024, three student interns spent a summer in the Advanced Protection lab space and were involved in the DarkNet Distributed Ledger Technology (DLT) project. The students had a great opportunity to gain hands-on experience with communication and protective relay equipment focused on information technology, data analytics, and cybersecurity. Experiences in the lab space with real equipment and software integration offer education and professional development for students, which is especially important because of a need in the energy industry to recruit highly skilled power and communication engineers.

42 ENGINEERING↗
DOE OSTI2025

LLGoMAX : Enhancing Industry-Standard Tools for AC Optimal Unit Commitment

In 2018, the Advanced Research Project Agency – Energy (ARPA-E) launched the Grid Optimization Competition (GOC) [1], a series of competitive challenges intended to accelerate innovation in decision support software used to schedule power grid operations, making them as efficient as possible, while respecting operational constraints of power equipment and operational security. This report covers the participation of the LLGoMAX team—a collaboration of the Lawrence Livermore National Laboratory (LLNL) and ECCO International, Inc.—in Challenge 3 of the competition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Energy Systems Integration Facility Stewardship Summary: Fiscal Year 2024

A summary of NREL's good stewardship of the nationally unique Energy Systems Integration Facility (ESIF) highlighting performance metrics, infrastructure upgrades, and examples of R&D impact. In fiscal year 2024, we developed advanced energy security and resilience capabilities as we built a new test bed for power electronics and completed a 1-megawatt platform for studying energy systems with grid-forming inverters. Researchers collaborated with utilities, manufacturers, and communities to solve their pressing questions, such as a control architecture that heralds a new direction for distributed energy management systems. With support from the U.S Department of Energy (DOE), the work in the ESIF laboratories continues to advance national goals for resilient and affordable energy.

annual report↗