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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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NASA NTRS2023

Single-Event Effect Testing of the Analog Devices AD8041ARZ Operational Amplifier

This study was undertaken to determine the single event transient distribution of a transimpedance amplifier configuration of the AD8041 Operational Amplifier. The AD8041 is made in a bipolar technology and the application of interest has a bipolar supply of ±5 V. The device was monitored for transient events on the output voltage during exposure to a heavy ion beam at Lawrence Berkeley National Laboratory’s (LBNL) 88-inch Cyclotron.

Matthew B. Joplin↗

NASA NTRS2004

Balanced Expertise Distribution in Remote Ultrasound Imaging Aboard The International Space Station (ISS)

Astronaut training for ISS operations usually ensures independent performance. With small crew size same crews also conduct all science work onboard. With diverse backgrounds, a good "match" between the existing and required skills can only be anecdotal. Furthermore, full proficiency in most of the complex tasks can be attained only through long training and practice, which may not be justified and may be impossible given the scarcity of training time. To enable a number of operational and science advancements, authors have developed a new approach to expertise distribution in time and among the space and ground personnel. Methods: As part of NASA Operational Ultrasound Project (1998-2003) and the NASA-solicited experiment "Advanced Diagnostic Ultrasound in Microgravity-ADUM" (P.I. -S.D., ongoing), the authors have created a "Balanced Expertise Distribution" approach to perform complex ultrasound imaging tasks on ISS for both operational and science use. The four components of expertise are a) any pre-existing pertinent expertise; b) limited preflight training c) adaptive onboard proficiency enhancement tools; d) real-time ' guidance from the ground. Throughout the pre-flight training and flight time preceding the experiments, the four components are shaped in a dynamic fashion to meet in an optimum combination during the experiment sessions. Results: Procedure validation sessions and feasibility studies have given encouraging results. While several successful real-time remote guidance sessions have been conducted on ISS, Expedition 8 is the first to use an "on-orbit proficiency enhancement" tool. Conclusions: In spite of severely limited training time, daring peer-reviewed research and operational enhancements are feasible through a balanced distribution of expertise in time, as well as among the crewmembers and ground personnel. This approach shows great promise for biomedical research, but may be applicable for other areas of micro gravity-based science

Sargsyan, Ashot↗

NASA NTRS2022

Evaluating Network Performance of Containerized Test Framework for Distributed Space Systems

Distributed space systems are a mission architecture consisting of multiple spacecraft as a cohesive system which provide multipoint sampling, increased mission coverage, or improved sample resolution, while reducing mission risk through redundancy. To fully realize the potential of these systems, eventually scaling to hundreds or thousands of spacecraft, distributed space systems need to be operated as a single entity, which will enable a variety of novel scientific space missions. The Distributed Spacecraft Autonomy (DSA) project is a software project which aims to mature the technology needed for those systems, namely autonomous decision-making and swarm networking. The DSA project leverages a containerized swarm test framework to simulate spacecraft software, which can identify emergent behavior early in development. Container virtualization allows distributed spacecraft systems to be simulated entirely in software on a single computer, avoiding the overhead associated with conventional approaches like hardware facsimiles and virtual machines. For this approach to be effective, the simulated system behavior must not be artificially influenced by the swarm test framework itself. To address this, we present a series of benchmarks to quantify virtual network bandwidth available on a single-host computer and contextualize this against the network and application behavior of the DSA swarm test framework.

Distributed Spacecraft Autonomy↗

DOE OSTI2024

Digital Twin + AI: Control Room of the Future [Slides]

The control room functions as the central brain of the grid, essential for balancing supply and demand and ensuring moment-to-moment grid reliability. Like the human brain, which processes sensory data to make decisions, control room operators analyze operational data from power generation, transmission, and distribution to make informed decisions. Currently, decision-making primarily rests with operators due to hardware and software limitations. However, with technological advancements, Digital Twins and AI are becoming high interest points in the control room's decision-making pilot programs. NREL is developing a comprehensive decision-making platform that integrates Digital Twins, AI, and advanced visualization techniques. As this integration progresses, the role of Digital Twins will evolve from conducting automated simulations to serving as a Trustworthy AI enabler, offering verification and validation of AI-generated response for power systems or providing physics-aware synthetic data of AI pre-training.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1998

Simple Automatic File Exchange (SAFE) to Support Low-Cost Spacecraft Operation via the Internet

Various issues associated with Simple Automatic File Exchange (SAFE) are presented in viewgraph form. Specific topics include: 1) Packet telemetry, Internet IP networks and cost reduction; 2) Basic functions and technical features of SAFE; 3) Project goals, including low-cost satellite transmission to data centers to be distributed via an Internet; 4) Operations with a replicated file protocol; 5) File exchange operation; 6) Ground stations as gateways; 7) Lessons learned from demonstrations and tests with SAFE; and 8) Feedback and future initiatives.

Baker, Paul↗

NASA NTRS1990

Space Station module Power Management And Distribution (PMAD) system

This project consists of several tasks which are unified toward experimentally demonstrating the operation of a highly autonomous, user-supportive power management and distribution system for Space Station Freedom (SSF) habitation/laboratory modules. This goal will be extended to a demonstration of autonomous, cooperative power system operation for the whole SSF power system through a joint effort with NASA's Lewis Research Center, using their Autonomous Power System. Short term goals for the space station module power management and distribution include having an operational breadboard reflecting current plans for SSF, improving performance of the system communications, and improving the organization and mutability of the artificial intelligence (AI) systems. In the middle term, intermediate levels of autonomy will be added, user interfaces will be modified, and enhanced modeling capabilities will be integrated in the system. Long term goals involve conversion of all software into Ada, vigorous verification and validation efforts and, finally, seeing an impact of this research on the operation of SSF. Conversion of the system to a DC Star configuration is now in progress, and should be completed by the end of October, 1989. This configuration reflects the latest SSF module architecture. Hardware is now being procured which will improve system communications significantly. The Knowledge-Based Management System (KBMS) is initially developed and the rules from FRAMES have been implemented in the KBMS. Rules in the other two AI systems are also being grouped modularly, making them more tractable, and easier to eventually move into the KBMS. Adding an intermediate level of autonomy will require development of a planning utility, which will also be built using the KBMS. These changes will require having the user interface for the whole system available from one interface. An Enhanced Model will be developed, which will allow exercise of the system through the interface without requiring all of the power hardware to be operational. The functionality of the AI systems will continue to be advanced, including incipient failure detection. Ada conversion will begin with the lowest level processor (LLP) code. Then selected pieces of the higher level functionality will be recorded in Ada and, where possible, moved to the LLP level. Validation and verification will be done on the Ada code, and will complete sometimes after completion of the Ada conversion.

Walls, Bryan↗

DOE OSTI2024

Performance Evaluation of Multi-Vendor Grid-Forming Inverters for Grid-Connected Operation Through Hardware Experimentation: Preprint

Existing real-world projects of GFM inverters that operate in parallel to power grids typically are sized between dozens and a few hundreds Megawatt (MW) scale according to a recent NERC GFM inverter white paper. These large systems are often difficult to evaluate prior to deployments because of their large size. The performance of smaller GFM inverters (dozens to a few hundreds MW) that operate parallel with power grids (distribution systems) is even less understood. There is an opportunity to better understand these systems through hardware testing under controlled laboratory conditions. Therefore, this paper presents the functional performance evaluation tests of multiple (three) commercial GFM inverters when they operate in parallel with the grid through hardware experiments. The goal of these tests is to explore the GFM inverters' functionalities and dynamic response when in parallel with power grids to eventually develop universal specifications for GFM inverters. Both steady state (changing the inverter's frequency and voltage droop) and transient (adding step change in grid's frequency/voltage) tests are performed for each GFM inverter with the same testing circuit and testing protocol. The experimental results indicate the bench-marked performance that: 1) the GFM inverters can be dispatched through frequency and voltage droop intercepts to output the target power when paralleled to the grid; 2) the GFM inverters automatically respond to system frequency and voltage events to output the needed power, however, the GFM inverters all show stability issues when absorbing reactive power from the grid.

grid-forming inverters↗

NASA NTRS2017

Key Differences in Operating a Rover on the Moon vs. Mars

The command and control model for spacecraft operations, as well as the distribution of tasks between ground assets and in space assets, whether with a crew or solely robotic, is fundamentally constrained by the round trip light time between the space asset and the control facility (presumably on Earth, though not required). For an asset on Mars, the round trip light time varies, from roughly fourteen minutes to up to forty minutes. For a Lunar asset the round-trip light time is measured in only a few seconds, but current communications systems may more than double the latency with system overhead. For a Lunar Asset the total command latency may range from six seconds to more than forty, depending on communications overhead and data rates. Further, these variables are not always predictable, thus complicating operations. There are several differentiating factors for Lunar vs. Mars operations, Round trip light time/Atmosphere/Lighting and ShadowsTerrain type and knowledge/Round trip light time has implications for the distribution of tasks between ground and in space assets. Even at Lunar Distances, the combination of round trip light time plus communications systems overhead does not enable joy stick driving of a rover. The best that can be done, if driving from Earth, is near real time command and control. By 2030, driving from in space may be possible. Productivity on Mars requires either long operational sequences of commands, as is done for current rovers such as Curiosity, significant autonomous capability or, as may be possible by 2030, command and control support from space. Another implication of the long round trip light time from Earth to Mars, is that flight software functions must be resident on the in space asset. On the Moon, there is considerably more flexibility, enabling processing functions, to be resident on Earth or in space. This provides the opportunity to take advantage of the considerable processing power available on the ground, but may be constrained by data rates. On the Moon, for practical operational purposes, there is no atmosphere. Hence there is no scattering of light in the shadows. This has implications for image interpretation and driving near the poles. The Moon has permanently shadowed regions (PSR), unique terrain with unknown surface properties. With no scattering of light in shadows, driving on the Moon, particularly at the poles, where we have strong evidence of water, may prove to be hazardous and complex, requiring non-optical sensors, such as LIDAR.

Trimble, Jay↗

DOE OSTI2026

Grid Topology Discovery Algorithm Evaluation of Suitability for Utility Deployment (CRADA 606 Final Report)

This work presents the results of a field-informed demonstration aimed at evaluating the practical suitability of a topology discovery algorithm for utility environments. We demonstrated an algorithm that uses a graph-theory-informed state estimation approach for model selection. In collaboration with Survalent and Peninsula Light Co., the algorithm was applied to real feeder models and field measurements from supervisory control and data acquisition (SCADA) and advanced metering infrastructure (AMI) systems to identify the operational topology of a power distribution system. The demonstration assessed the algorithm’s performance under realistic data conditions, including sparse and noisy measurements, and examined its ability to identify the most likely network configurations. The results confirmed that the approach can effectively narrow down feasible topologies, providing operators with improved situational awareness of network status. Key lessons learned emphasize the need for systematic data validation and strategic sensor placement to enhance observability. These insights inform future deployment strategies and guide refinements for broader adoption in utility operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2015

The NASA Earth Science Program and Small Satellites

Earth's changing environment impacts every aspect of life on our planet and climate change has profound implications on society. Studying Earth as a single complex system is essential to understanding the causes and consequences of climate change and other global environmental concerns. NASA's Earth Science Division (ESD) shapes an interdisciplinary view of Earth, exploring interactions among the atmosphere, oceans, ice sheets, land surface interior, and life itself. This enables scientists to measure global and climate changes and to inform decisions by Government, other organizations, and people in the United States and around the world. The data collected and results generated are accessible to other agencies and organizations to improve the products and services they provide, including air quality indices, disaster prediction and response, agricultural yield projections, and aviation safety. ESD's Flight Program provides the spacebased observing systems and supporting infrastructure for mission operations and scientific data processing and distribution that support NASA's Earth science research and modeling activities. The Flight Program currently has 21 operating Earth observing space missions, including the recently launched Global Precipitation Measurement (GPM) mission, the Orbiting Carbon Observatory-2 (OCO-2), the Soil Moisture Active Passive (SMAP) mission, and the International Space Station (ISS) RapidSCAT and Cloud-Aerosol Transport System (CATS) instruments. The ESD has 22 more missions and instruments planned for launch over the next decade. These include first and second tier missions from the 2007 Earth Science Decadal Survey, Climate Continuity missions to assure availability of key climate data sets, and small-sized competitively selected orbital missions and instrument missions of opportunity belonging to the Earth Venture (EV) Program. Small satellites (~500 kg or less) are critical contributors to these current and future satellite missions. Some examples are the aforementioned Orbiting Carbon Observatory-2 (OCO-2), the Gravity Recovery and Climate Experiment Follow On (GRACE FO), and the Cyclone Global Navigation Satellite System (CYGNSS) microsatellite constellation. Small satellites also support ESD in space validation and risk reduction of enabling technologies (components and systems). The status of the ESD Flight Program and the role of small satellites will be discussed.

Earth Science Prog & Small Sat↗

DOE OSTI2025

Enabling Efficient Sparse Computations using Linear Algebra Aware Compilers

This project developed the LAPIS compiler framework, built on the Multilevel Intermediate Representation (MLIR), to optimize sparse linear algebra operations and support performance portability across diverse architectures. The main innovation of LAPIS is the Kokkos dialect, which allows for lowering codes from a high productivity language to different architectures in an elegant way. The dialect also allows the conversion of lower-level MLIR code to C++ Kokkos code, facilitating the integration of scientific machine learning (SciML) models into applications. To extend LAPIS for distributed memory architectures, a new partition dialect was created to manage the distribution of sparse tensors and express communication patterns for sparse linear algebra operations. This dialect also supports the distributed execution of operators and includes algorithmic optimizations to minimize communication to improve performance. The project also demonstrates that MLIR can enable effective linear algebra-level optimizations, improving performance on different GPUs for both sparse and dense linear algebra kernels. Key applications of LAPIS include sparse linear algebra and graph kernels, TenSQL, a relational database management solution built on GraphBLAS, and the development of subgraph isomorphism and monomorphism kernels, showcasing performance portability. In summary, the LAPIS framework supports productivity, performance, portability, and distributed memory execution, while also enabling linear algebra-level optimizations that are challenging in traditional programming languages, with successful applications ranging from simple sparse linear algebra to complex graph kernels.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1976

Design evolution of a low shock release nut

Design improvements and detailed functional analyses are reviewed to trace the development of a pyroactuated release device with segmented thread design from its intermediate design into one that reduces the levels of shock spectra generated during its operation by 50%. Comparisons of shock output and internal load distribution are presented, along with descriptions of mechanical operation for both designs. Results also show the potential areas where design development activity can gain further progress in lowering actuation shock levels.

Otth, D. H.↗

NASA NTRS2019

Small Satellites for NASA Earth Science

NASA’s Earth Science Division (ESD) seeks to develop a scientific understanding of Earth and its response to natural and human-induced changes. Earth is a system comprised of diverse components interacting in complex ways. Understanding Earth’s atmosphere, surface and interior, oceans and surface water, ice and snow, and life as a single connected system is necessary in order to improve our predictions of climate, weather, and natural hazards. The ESD’s Flight Program consists of a coordinated series of satellite and airborne systems providing long and short-term, global and regional observations. In addition, the Flight Program provides infrastructure for operating these missions, processing their scientific data, and distributing them on a free and open basis to researchers, operational users, and the public. The Flight Program currently has 24 operating Earth observing space missions and instruments. There are 18 more missions and instruments planned for launch over the next five years. These comprise missions recommended by the National Academies 2017 Earth Science Decadal Survey, missions and selected instruments to ensure availability of key climate data sets, operational missions to sustain the land imaging provided by the Landsat system, and small-sized competitively selected orbital and instrument missions of opportunity belonging to the Earth Venture (EV) program. The Earth Science Decadal Survey, released in early 2018, recommended four new Flight Program elements in addition to the above activities that comprise the Program of Record (POR). Small satellites (~500 kg or less) are essential components of these activities. Presently, there is an increasing use of micro and nanosatellites (or CubeSats) in constellations to support NASA ESD’s scientific objectives. These include the Cyclone Global Navigation Satellite System (CYGNSS) for observing tropical cyclone intensification and genesis factors, the Timed-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, and the Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) CubeSat mission. ESD small satellite initiatives like the Small Satellite Constellation Data Buy and Venture Class Launch Services (VCLS) are also underway. The Earth Science Technology Office’s (ESTO) In-Space Validation of Earth Science Technologies (InVEST) and the Venture Technology program elements have launched seven 3U and 6U CubeSat missions to validate advanced instruments and related technologies. An equivalent number of InVEST and other technology demonstration CubeSats are being prepared for launch in the next year. An overview of plans and current status including topics related to small satellite enabling activities will be presented.

Neeck, Steven P.↗

DOE OSTI2026

Artificial Intelligence-Driven Management of Sustainable Energy Resources: Visibility, Operation, and Control

The rapid global transition toward sustainable energy resources (SERs) is reshaping how modern power systems are observed, optimized, and controlled. While SERs have significantly advanced decarbonization, their weather dependence, variability, and inverter-dominated characteristics challenge traditional, centralized, and deterministic grid operation. At the same time, the proliferation of high-resolution data from inverters, smart meters, and sensors offers unprecedented visibility into system dynamics. Yet, it also exceeds the analytical capability of conventional model-based approaches. Artificial intelligence (AI) provides a new foundation for addressing these challenges by bridging physical laws with data-driven learning, enabling accurate state awareness, adaptive operation, and coordinated control across distributed assets. This article examines how AI transforms the management of SER-rich power systems along three critical dimensions: 1) enhancing visibility by inferring behind-the-meter (BTM) activities, assessing SER flexibility, and reconstructing system states from sparse or noisy measurements; 2) improving operation through AI-enhanced SER service provision, volt/var control (VVC), and dynamic operating envelopes (DOE) for efficiency and security; and 3) advancing control by embedding learning-based intelligence into inverter coordination, voltage and frequency regulation, and long-term dispatch. Together, these developments reveal how AI can convert the variability of SERs from an operational challenge into a source of flexibility, resilience, and intelligence, paving the way toward sustainable, adaptive, and self-optimizing power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2017

Cooling of Electric Motors Used for Propulsion on SCEPTOR

NASA is developing a suite of hybrid-electric propulsion technologies for aircraft. These technologies have the benefit of lower emissions, diminished noise, increased efficiency, and reduced fuel burn. These will provide lower operating costs for aircraft operators. Replacing internal combustion engines with distributed electric propulsion is a keystone of this technology suite, but presents many new problems to aircraft system designers. One of the problems is how to cool these electric motors without adding significant aerodynamic drag, cooling system weight or fan power. This paper discusses the options evaluated for cooling the motors on SCEPTOR (Scalable Convergent Electric Propulsion Technology and Operations Research): a project that will demonstrate Distributed Electric Propulsion technology in flight. Options for external and internal cooling, inlet and exhaust locations, ducting and adjustable cowling, and axial and centrifugal fans were evaluated. The final design was based on a trade between effectiveness, simplicity, robustness, mass and performance over a range of ground and flight operation environments.

Propulsion↗

NASA NTRS1995

Parallel automated adaptive procedures for unstructured meshes

Consideration is given to the techniques required to support adaptive analysis of automatically generated unstructured meshes on distributed memory MIMD parallel computers. The key areas of new development are focused on the support of effective parallel computations when the structure of the numerical discretization, the mesh, is evolving, and in fact constructed, during the computation. All the procedures presented operate in parallel on already distributed mesh information. Starting from a mesh definition in terms of a topological hierarchy, techniques to support the distribution, redistribution and communication among the mesh entities over the processors is given, and algorithms to dynamically balance processor workload based on the migration of mesh entities are given. A procedure to automatically generate meshes in parallel, starting from CAD geometric models, is given. Parallel procedures to enrich the mesh through local mesh modifications are also given. Finally, the combination of these techniques to produce a parallel automated finite element analysis procedure for rotorcraft aerodynamics calculations is discussed and demonstrated.

Shephard, M. S.↗

NASA NTRS2023

Distributed Ground Sensor Fusion Based Object Tracking for Autonomous Advanced Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Advanced Air Mobility and other emerging aviation markets. In order to enable this autonomy, an accurate and detailed understanding of the positions of the various vehicles in the air is necessary. Full localization independent of on-board sensors makes the system suitable for noncooperative vehicles. This paper focuses on the object tracking part that relies on distributed ground-based sensor fusion, considering specific properties and limitations of different sensor types. Results show satisfactory performance in nominal scenarios with full coverage. Dropouts of individual sensors affect the accuracy of the tracking results, which agrees with expectations for partial coverage, when full localization is not achievable anymore. Finally, a study is performed to identify which parameters have the largest impact on the fit error.

Autonomous↗