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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Lucy Optical Navigation Performance During The (152830) Dinkinesh Encounter

The Lucy Jupiter-Trojan asteroid mission launched in November 2021. Its original mission concept included six small-body encounters over its 12-year primary mission. In the fall of 2022, an additional target of opportunity encounter was proposed to be executed in the fall of 2023. The encounter with (152830) Dinkinesh (previously 1999 VD57) presented myriad imaging, navigation, engineering, and planning challenges, as well as a chance to exercise and further refine the Optical NavigationSystem concept of operations, interfaces, and tools. Dinkinesh would be the smallest and dimmest target Lucy would encounter, with a higher uncertainty in these physical parameters than for other targets. While the Op Nav system and instruments carried a high amount of heritage from the New Horizons and OSIRIS-REx missions, this would be the first use of these systems on Lucy for navigation purposes. Despite these additional challenges, the Lucy Dinkinesh encounter was a resounding success throughout which the navigational system exceeded requirements.1Optical Navigation was successfully performed and fed into the orbit determination and trajectory maneuver activities up to the final knowledge update. The Dinkinesh encounter also proved to be greatly scientifically interesting, if not additionally challenging, as the Dinkinesh system was discovered to be a binary system through imaging during closest approach, and the secondary body was itself found to be a contact binary. This added complexity notwithstanding, the OpNav and OD teams were able to re-construct the close-approach trajectory of Dinkinesh in cooperation and concert with the Lucy Science Team’s shape modelling efforts.

Erik Lessac-Chenen↗
NASA NTRSDate not supplied

Multifunctional End Effector for Regolith Construction, Acquisition, and Transfer (MEERCAT)

Presentation prepared for ASCE Earth and Space. Presentation covers the capabilities of the MEERCAT system with videos demonstrating con ops. The MEERCAT system specs are taken from a previously STRIVES approved flyer on MEERCAT. Presentation will not be part of ASCE Earth and Space but should still be submitted through STRIVES for use with public facing business developments.

meercat↗
NASA NTRS2024

Initial Results of Wyatt EIRP- The Ground Based Power and Ambiguity Function Monitor for P-Band Signals of Opportunity Sources

The Wideband Year-round AmbuguiTy-function Track-ing Effective Isotropic Radiated Power (WYATT EIRP)instrument is designed to support P-Band based Sig-nals of Opportunity (SoOp) remote sensing instrument.SoOp utilizes pre-existing non-cooperative microwavetransmitters as sources of illumination. This remotesensing method requires knowledge of the signals EIRP,position and ambugituty function’s shape.WYATT EIRP is designed to periodically generateEIRP measurements, ambuguity functions and transmit-ter elevation. It uses an array of RHCP and LHCPantennas, mounted on a rotating antenna pedestal togenerate EIRP measurements. A secondary observationantenna is placed to allow time difference of arrival mea-surements for transmitter elevation estimates. Both thepedestal and reference antenana are used to generateamituigyt fionctions. The pedestal will also be used tovalidate existing P-Band background noise temperaturesky maps. WYATT EIRP will be commissioned in thefirst quarter of 2024 and will be used to provide calibra-tion data to the upcoming spaceborne SigNals Of Op-portunity: P-Band Investigation (SNOOPI) instrument.

Remote Sensing↗
NASA NTRSDate not supplied

Towards Sustainable Aviation With Efficient Airspace Operations

In November 2021, the Federal Aviation Administration published the United States Aviation Climate Action Plan to accelerate innovation across the U.S. aviation ecosystem. In response, NASA has established the Sustainable Flight National Partnership to engage with industry, academia, and other agencies to accomplish net-zero carbon emissions by 2050. As part of the SFNP Mission, NASA is conducting a series of real world operational demonstrations in the current National Airspace System with a focus on delivering real world sustainability benefits. This paper presents the current work and future plan for the SFNP Ops Demo Series and describes the cloud based infrastructure used for virtual deployment of decision support tools to flight operators and Air Traffic Controllers to help improve operational efficiency of the National Airspace System. Validation results are shared along with the key sustainability benefits such as jet fuel savings and reduction in CO2 emissions. The operational efficiency metrics such as delay savings are also reported.

Sustainable Flight National Partnership↗
NASA NTRSDate not supplied

Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool

BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.

Ariana M Nelson↗
NASA NTRS2024

System Engineering & Integration (SE&I) In-Situ Resource Utilization (ISRU) Modeling and Analysis (SIMA)

NASA developed a flexible system modeling framework of integrated ISRU and ISRU related subsystem models: MAIT (Mission Analysis & Integration Tool) that enables point solutions, optimization, and/or parametric studies at the system level to predict mission architecture mass, power, and volume and provides accessible consolidated database that categorizes specific ISRU and ISRU related subsystem variables common between NASA & industry. Directly and indirectly addresses multiple STMD shortfalls: - ISRU-581 - ‘ISRU System Modeling’: Establish a modular end-to-end ISRU system modeling & analysis capability by leveraging and evolving prior, on-going, and future investments - More than an ISRU system modeling tool, MAIT integrates power, excavation, Environmental Control & Life Support System (ECLSS), Cryogenic Fluid Management (CFM) liquification, & compares surface ops & environments, to assist in the closure of other related ISRU shortfalls Adheres to governing NASA procedures for Models & Simulations (NASA-HDBK-7009) & AIAA standards for Mass Properties Control for Space Systems.

Modeling↗
DOE OSTI2020

Eurycea lucifuga (Cave Salamander). Diet.

Eurycea lucifuga is a common and widespread facultative inhabitant of caves and springs in the southeastern and central United States (Powell et al. 2016. Peterson Field Guide to Reptiles and Amphibians of Eastern and Central North America. Houghton Mifflin Harcourt, Boston, Massachusetts. 512 pp.). This species is known to feed on a variety of invertebrates, such as snails, crustaceans, beetles, and flies (Peck 1974. Nat. Speleol. Soc. Bull. 36:7–10). Although several millipede species also can serve as prey for E. lucifuga, some are presumably avoided due to the presence of defensive secretions (e.g., Abacionidae, Paradoxosomatidae). Captive feeding trials and field study show that E. lucifuga do not actively prey upon cave-obligate Tetracion millipedes, which produce defensive secretions comprised primarily of the compound p-cresol (Peck and Richardson 1976. Annales de Speleologie 31:175–182). On the other hand, Pseudotremia millipedes, which do not possess chemical defenses, are a significant component of the diet of cave-dwelling E. lucifuga (Peck and Richardson 1976, op. cit.)

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Two-Stage Gauss-Seidel Preconditioners and Smoothers for Krylov Solvers on a GPU Cluster: Preprint

Gauss-Seidel (GS) relaxation is often employed as a preconditioner for a Krylov solver or as a smoother for Algebraic Multigrid (AMG). However, the requisite sparse triangular solve is difficult to parallelize on many-core architectures such as graphics processing units (GPUs). In the present study, the performance of the sequential GS relaxation based on a triangular solve is compared with two-stage variants, replacing the direct triangular solve with a fixed number of inner Jacobi-Richardson (JR) iterations. When a small number of inner iterations is sufficient to maintain the Krylov convergence rate, the two-stage GS (GS2) often outperforms the sequential algorithm on many-core architectures. The GS2 algorithm is also compared with JR. When they perform the same number of ops for SpMV (e.g. three JR sweeps compared to two GS sweeps with one inner JR sweep), the GS2 iterations, and the Krylov solver preconditioned with GS2, may converge faster than the JR iterations. Moreover, for some problems (e.g. elasticity), it was found that JR may diverge with a damping factor of one, whereas two-stage GS may improve the convergence with more inner iterations. Finally, to study the performance of the two-stage smoother and preconditioner for a practical problem, these were applied to incompressible uid ow simulations on GPUs.

algebraic multigrid↗
DOE OSTI2022

Quantum metrology of low frequency electromagnetic modes with frequency upconverters

We describe the RF Quantum Upconverter (RQU) and describe its application to quantum metrology of electromagnetic modes between dc and the Very High Frequency band (VHF) (≲300MHz). The RQU uses a Josephson interferometer made up of superconducting loops and Josephson junctions to implement a parametric interaction between a low-frequency electromagnetic mode (between dc and VHF) and a mode in the microwave C Band (~ 5GHz), analogous to the radiation pressure interaction between electromagnetic and mechanical modes in cavity optomechanics. The RQU can operate as a quantum-limited op-amp, or use protocols from optomechanics to implement non-classical measurement protocols equivalent to those used in cavity optomechanics, including back-action evading (BAE) measurements, sideband cooling, and two-mode squeezing. Furthermore, these protocols enable experiments using dc-VHF electromagnetic modes as quantum sensors.

Kuenstner, Stephen E.↗
DOE OSTI2024

Rural Hybrid Generation & Microgrids: National Labs are Here to Help

Hear about the tools and technical assistance National Labs can offer to co-ops and other rural utilities seeking to build or enhance hybrid generation projects combining multiple technologies including wind, solar, battery storage, and others resources. These hybrids can deliver additional value by combining complimentary resources and by increasing reliability and resilience, including as part of a microgrid to serve a local load or community. Experienced cooperative and lab experts will share their perspectives on the opportunities there are to make use of their advanced modeling capabilities and expertise to scope, design, and implement these emerging hybrid solutions. Key takeaways for participants will include better understanding of the resilience benefits distributed hybrid systems provide, awareness of National Laboratory assistance programs and resources, tips for successful federal funding applications for these types of projects, and peer-to-peer learning through shared experiences and discussion.

14 SOLAR ENERGY↗
DOE OSTI2026

An AI-driven framework for evaluating local and state authorities’ permitting processes

The demand for new energy infrastructure is increasing across the United States, but heterogenous permitting processes and embedded requirements across different local jurisdictions can cause project delays, increase “soft costs,” and hinder developer expansion. This study analyzes the variability in local permitting requirements across the U.S. and develops a quantitative approach to describe their clarity and effectiveness in enabling infrastructure project development. By using an Energy Language Model (ELM), a large language model (LLM) for energy technologies, we systematically gathered permitting information from nearly 300 state-, county-, and city-level documents, creating a structured dataset of requirements and procedures on an unprecedented scale and speed. Our analysis revealed that local (city and county) permitting requirement documents are underrepresented compared to state-level guidance documents, which can impede timely and cost-effective installation of new electric infrastructure. Our validation process showed that the final database has an accuracy of approximately 95%. We, further, created a new quantitative method to score permitting requirements for clarity and efficiency, with electric vehicle supply equipment as an initial use case. The average local permitting document scored a 1.8 out of 5, which we interpret as meaning that half of the requirements developers face when installing electric infrastructure are ambiguous, increasing both cost and time. We also created a “Generalized Permit Process”, highlighting common procedural steps and identifying specific opportunities for municipalities to improve their documentation. This research establishes a systematic and scalable framework for evaluating the complexities of local infrastructure permitting processes by combining LLM-powered data collection and quantitative scoring. The framework enables policymakers and developers to identify and mitigate procedural bottlenecks, with the expectation that these improvements can accelerate application review and approval, reduce project costs, and expedite connection to utility distribution grids. As a foundational approach for streamlining local project development processes, this study’s methods are intended to be extended to a wide range of energy applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

In-plane selective area InSb–Al nanowire quantum networks

Abstract Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2 e -periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Planning for Equitable Solar Deployment with Electric Cooperatives

The goal of the study was to understand how electric cooperatives can design equitable solar photovoltaic (PV) projects consistent with the goals of their organizations. To understand the possibilities for equitable solar deployment, the project team carefully defined cross-subsidy by delving into the multi-level structure of electric cooperatives. Understanding that utilities and analysts apply different cost-categorization perspectives was key to developing a transparent analytic model that traces the economic value flows of new solar PV projects across the tiers of a cooperative system.

14 SOLAR ENERGY↗
DOE OSTI2024

X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr −1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr −1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×10 3 ± 0.9×10 3 km 3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Nelson, Jacob A.↗
NASA NTRS1996

On-Orbit Calibration of a Multi-Spectral Satellite Satellite Sensor Using a High Altitude Airborne Imaging Spectrometer

Earth-looking satellites must be calibrated in order to quantitatively measure and monitor components of land, water and atmosphere of the Earth system. The inevitable change in performance due to the stress of satellite launch requires that the calibration of a satellite sensor be established and validated on-orbit. A new approach to on-orbit satellite sensor calibration has been developed using the flight of a high altitude calibrated airborne imaging spectrometer below a multi-spectral satellite sensor.

sensor calibration calibration Earth-looking satel↗