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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Lightweight Inflatable Solar Array: Providing a Flexible, Efficient Solution to Space Power Systems for Small Spacecraft

Affordable and convenient access to electrical power is critical to consumers, spacecraft, military and other applications alike. In the aerospace industry, an increased emphasis on small satellite flights and a move toward CubeSat and NanoSat technologies, the need for systems that could package into a small stowage volume while still being able to power robust space missions has become more critical. As a result, the Marshall Space Flight Center's Advanced Concepts Office identified a need for more efficient, affordable, and smaller space power systems to trade in performing design and feasibility studies. The Lightweight Inflatable Solar Array (LISA), a concept designed, prototyped, and tested at the NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama provides an affordable, lightweight, scalable, and easily manufactured approach for power generation in space or on Earth. This flexible technology has many wide-ranging applications from serving small satellites to soldiers in the field. By using very thin, ultraflexible solar arrays adhered to an inflatable structure, a large area (and thus large amount of power) can be folded and packaged into a relatively small volume (shown in artist rendering in Figure 1 below). The proposed presentation will provide an overview of the progress to date on the LISA project as well as a look at its potential, with continued development, to revolutionize small spacecraft and portable terrestrial power systems.

Johnson, Len↗
NASA NTRS2015

Lightweight Innovative Solar Array (LISA): Providing Higher Power to Small Spacecraft

Affordable and convenient access to electrical power is essential for all spacecraft and is a critical design driver for the next generation of smallsats, including cubesats, which are currently extremely power limited. The Lightweight Innovative Solar Array (LISA), a concept designed, prototyped, and tested at the NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama provides an affordable, lightweight, scalable, and easily manufactured approach for power generation in space. This flexible technology has many wide‐ranging applications from serving small satellites to providing abundant power to large spacecraft in GEO and beyond. By using very thin, ultra‐flexible solar arrays adhered to an inflatable structure, a large area (and thus large amount of power) can be folded and packaged into a relatively small volume. The LISA array comprises a launch‐stowed, orbit‐deployed structure on which lightweight photovoltaic devices and, potentially, transceiver elements are embedded. The system will provide a 2.5 to 5 fold increase in specific power generation (Watts/kilogram) coupled with a >2x enhancement of stowed volume (Watts/cubic‐meter) and a decrease in cost (dollars/Watt) when compared to state‐of‐the‐art solar arrays.

Johnson, Les↗
NASA NTRS2015

Lightweight Integrated Solar Array (LISA): Providing Higher Power to Small Spacecraft

Affordable and convenient access to electrical power is essential for all spacecraft and is a critical design driver for the next generation of smallsats, including CubeSats, which are currently extremely power limited. The Lightweight Integrated Solar Array (LISA), a concept designed, prototyped, and tested at the NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama provides an affordable, lightweight, scalable, and easily manufactured approach for power generation in space. This flexible technology has many wide-ranging applications from serving small satellites to providing abundant power to large spacecraft in GEO and beyond. By using very thin, ultraflexible solar arrays adhered to an inflatable or deployable structure, a large area (and thus large amount of power) can be folded and packaged into a relatively small volume.

Johnson, Les↗
NASA NTRS2006

Recent Advances in Solar Sail Propulsion at NASA

Supporting NASA's Science Mission Directorate, the In-Space Propulsion Technology Program is developing solar sail propulsion for use in robotic science and exploration of the solar system. Solar sail propulsion will provide longer on-station operation, increased scientific payload mass fraction, and access to previously inaccessible orbits for multiple potential science missions. Two different 20-meter solar sail systems were produced and successfully completed functional vacuum testing last year in NASA Glenn's Space Power Facility at Plum Brook Station, Ohio. The sails were designed and developed by ATK Space Systems and L'Garde, respectively. These sail systems consist of a central structure with four deployable booms that support the sails. This sail designs are robust enough for deployments in a one atmosphere, one gravity environment, and are scalable to much larger solar sails-perhaps as much as 150 meters on a side. In addition, computation modeling and analytical simulations have been performed to assess the scalability of the technology to the large sizes (>150 meters) required for first generation solar sails missions. Life and space environmental effects testing of sail and component materials are also nearly complete. This paper will summarize recent technology advancements in solar sails and their successful ambient and vacuum testing.

Johnson, Les↗
NASA NTRS2010

New Technology for Microfabrication and Testing of a Thermoelectric Device for Generating Mobile Electrical Power

We report the results of fabrication and testing of a thermoelectric power generation module. The module was fabricated using a new "flip-chip" module assembly technique that is scalable and modular. This technique results in a low value of contact resistivity ( < or = 10(exp 5) Ohms-sq cm). It can be used to leverage new advances in thin-film and nanostructured materials for the fabrication of new miniature thermoelectric devices. It may also enable monolithic integration of large devices or tandem arrays of devices on flexible or curved surfaces. Under mild testing, a power of 22 mW/sq cm was obtained from small (<100 K) temperature differences. At higher, more realistic temperature differences, approx.500 K, where the efficiency of these materials greatly improves, this power density would scale to between 0.5 and 1 Watt/cm2. These results highlight the excellent potential for the generation and scavenging of electrical power of practical and usable magnitude for remote applications using thermoelectric power generation technologies.

Prasad, Narashimha S.↗
DOE OSTI2020

Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme

Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory.

Li, Sibo↗
DOE OSTI2021

Test Points for Online Monitoring of Quantum Circuits

Noisy Intermediate-Scale Quantum (NISQ) computers consisting of tens of inherently noisy quantum bits (qubits) suffer from reliability problems. Qubits and their gates are susceptible to various types of errors. Due to limited numbers of qubits and high error rates, quantum error correction cannot be applied. Physical constraints of quantum hardware including the error rates are used to guide the design and the layout of quantum circuits. The error rates determine the selection of qubits and their operations. The resulting circuit is executed on the quantum computer. This study explores the risk of unexpected changes in the error rates of NISQ computers post-calibration. We show that unexpected changes in error rates can alter the output state of a quantum circuit. To detect these changes, we propose the insertion of test points into the quantum circuit to enable online monitoring of the physical qubit behavior. We utilize classical, superposition, and uncompute test points. Furthermore, we use a gate error coverage metric to assess the quality of the tests. We verify the effectiveness of the proposed scheme on different IBM quantum computers (IBM Q), in addition to a noisy simulation that shows the scalability of the proposed approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High-order multirate explicit time-stepping schemes for the baroclinic-barotropic split dynamics in primitive equations

In order to treat the multiple time scales of ocean dynamics in an efficient manner, the baroclinic-barotropic splitting technique has been widely used for solving the primitive equations for ocean modeling. Based on the framework of strong stability-preserving Runge-Kutta approach, we propose two high-order multirate explicit time-stepping schemes (SSPRK2-SE and SSPRK3-SE) for the resulting split system in this paper. The proposed schemes allow for a large time step to be used for the three-dimensional baroclinic (slow) mode and a small time step for the two-dimensional barotropic (fast) mode, in which each of the two mode solves just need to satisfy their respective CFL conditions for numerical stability. Specifically, at each time step, the baroclinic velocity is first computed by advancing the baroclinic mode and fluid thickness of the system with the large time-step and the assistance of some intermediate approximations of the barotropicmode obtained by substepping with the small time step; then the barotropic velocity is corrected by using the small time step to re-advance the barotropic mode un-der an improved barotropic forcing produced by interpolation of the forcing terms from the preceding baroclinic mode solves; lastly, the fluid thickness is updated by coupling the baroclinic and barotropic velocities. Additionally, numerical inconsistencies on the discretized sea surface height caused by the mode splitting are relieved via a reconciliation process with carefully calculated flux deficits. Here, two benchmark tests from the “MPAS-Ocean” platform are carried out to numerically demonstrate the performance and parallel scalability of the proposed SSPRK-SE schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Anomaly Detection in Electronic Health Records Across Hospital Networks: Integrating Machine Learning With Graph Algorithms

In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, the dependability of the health information technology (HIT) systems responsible for collecting EHR data is of utmost importance for patient safety. Recently, novel methods and tools aimed at identifying anomalies in EHR data to bolster the reliability of HIT systems have been introduced. However, these existing methods and tools primarily concentrate on individual hospitals, which limits our understanding of system-wide anomalous events and their potential impact on patient safety across multiple hospitals. In this article, we introduce a new approach to detecting anomalies in EHR data within a network of hospitals. This is achieved by combining advanced machine learning techniques with graph algorithms to create a tool capable of swiftly identifying and responding to deviations. Our proposed approach employs a combination of five machine learning models, harnessing the unique strengths of each model to provide a more robust detection system. The detected anomalies are then represented as graphs, allowing us to recognize patterns across the hospital network. This aids in identifying anomalies that span multiple medical facilities, potentially indicating broader system-level risks. Extensive real-world testing of our approach demonstrated its ability to offer actionable insights compared to existing methods. Additionally, its scalable design ensures seamless integration into existing HIT infrastructures.

Niu, Haoran [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2021

Influence of Diffuse and Ground-Reflected Irradiance on the Spectral Modeling of Solar Reference Cells

Thermal Energy Storage (TES) is a key component for solar thermal applications to bridge the gap between the demand for thermal energy and the supply of solar energy, whose availability depends on the time of day and season. Thus, cost-effective packed-bed thermal containers filled with a solid storage medium have been proposed for high-temperature sensible heat storage as materials are abundant and relatively cheap. Thus, it is necessary to investigate their performance and temperature profiles during the charge-discharge cycle. Several models are available for this purpose. Typically, the more detailed a model, the greater the computational effort required to solve it, and hence a time-efficient model is needed to prevent excessively long computation times for long-term analysis. At the more basic level, the common Hughes E-NTU model and the less realistic simplified Infinite-NTU model are very important for their less time and computational effort. In this paper, the appropriateness of employing the Infinite-NTU model was evaluated to investigate the performance of a typical and scalable rock-bed TES as a case study. The results presented provide a methodology to quickly test the validity of the model and predict the temperature profile for the case under study. Accordingly, such simple charge-discharge cycle thermal performance predictions are important to plan, design, and rapidly deploy a reliable and economical solar thermal system for the supply of valuable heat to high-temperature demanding applications of power generation and industrial processes as part of a rapid shift towards non-polluting renewable energy. Keywords: Solar Thermal, TES, Packed-bed, NTU model, Temperature profile

PV modeling↗
NASA NTRS2005

Preliminary Analysis of the 30-m UltraBoom Flight Test

Future NASA missions require long, ultra-lightweight booms to enable solar sails, large sunshields, and other gossamer-type spacecraft structures. The space experiment discussed in this paper will flight validate the non-traditional ultra lightweight rigidizable, inflatable, isogrid structure utilizing graphite shape memory polymer (GR/SMP) called UltraBoom(TradeMark). The focus of this paper is the analysis of the 3-m ground test article. The primary objective of the mission is to show that a combination of ground testing and analysis can predict the on-orbit performance of an ultra lightweight boom that is scalable, predictable, and thermomechanically stable.

UltraBoom↗
NASA NTRS2013

Hydrogen-Enhanced Lunar Oxygen Extraction and Storage Using Only Solar Power

The innovation consists of a thermodynamic system for extracting in situ oxygen vapor from lunar regolith using a solar photovoltaic power source in a reactor, a method for thermally insulating the reactor, a method for protecting the reactor internal components from oxidation by the extracted oxygen, a method for removing unwanted chemical species produced in the reactor from the oxygen vapor, a method for passively storing the oxygen, and a method for releasing high-purity oxygen from storage for lunar use. Lunar oxygen exists in various types of minerals, mostly silicates. The energy required to extract the oxygen from the minerals is 30 to 60 MJ/kg O. Using simple heating, the extraction rate depends on temperature. The minimum temperature is approximately 2,500 K, which is at the upper end of available oven temperatures. The oxygen is released from storage in a purified state, as needed, especially if for human consumption. This method extracts oxygen from regolith by treating the problem as a closed batch cycle system. The innovation works equally well in Earth or Lunar gravity fields, at low partial pressure of oxygen, and makes use of in situ regolith for system insulation. The innovation extracts oxygen from lunar regolith using a method similar to vacuum pyrolysis, but with hydrogen cover gas added stoichiometrically to react with the oxygen as it is produced by radiatively heating regolith to 2,500 K. The hydrogen flows over and through the heating element (HE), protecting it from released oxygen. The H2 O2 heat of reaction is regeneratively recovered to assist the heating process. Lunar regolith is loaded into a large-diameter, low-height pancake reactor powered by photovoltaic cells. The reactor lid contains a 2,500 K HE that radiates downward onto the regolith to heat it and extract oxygen, and is shielded above by a multi-layer tungsten radiation shield. Hydrogen cover gas percolates through the perforated tungsten shielding and HE, preventing oxidation of the shielding and HE, and reacting with the oxygen to form water vapor. The water vapor is filtered through solid regolith to remove unwanted extraction byproducts, and then condensed to a liquid state and stored at 300 to 325 K. Conversion to usable oxygen is achieved by pumping liquid water into a high-pressure electrolyzer, storing the gaseous oxygen at high pressure for use, and diverting the hydrogen back to the reactor or to storage. The results from this design effort show that this oxygen-generating concept can be developed in an efficient system with low specific mass. Advantages include use of regolith as an oxygen source, filter, and thermal insulator. The system can be tested in Earth gravity and can be expected to operate similarly in lunar gravity. The system is scalable, either by increasing the power level and output of a standard module, or by employing multiple modules.

Burton, rodney↗
DOE OSTI2024

Reduced-Order Modeling of Multigroup Neutron Cross Sections for High-Temperature Gas-cooled Reactors

Abstract – Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗
DOE OSTI2024

Advanced Cross Section Library Generation using Reduced Order Models

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗
DOE OSTI2023

Facile and Scalable Synthesis of Metal- and Nitrogen-Doped Carbon Nanotubes for Efficient Electrochemical CO 2 Reduction

Metal- and nitrogen-doped carbon (M–N–C) is a promising material to catalyze electrochemical CO 2 reduction reaction (CO 2 RR). However, most M–N–C catalysts in the literature require complicated synthesis procedures and produce small quantities per batch, limiting the commercialization potential. In this work, we developed a simple and scalable synthesis method to convert metal-impurity-containing commercial carbon nanotubes (CNTs) and nitrogen-containing organic precursors into M–N–C via one-step moderate-temperature (650 °C) pyrolysis without any other treatment nor the need to add metal precursors. Batches of catalysts in varied mass up to 10 g (150 mL in volume) per batch were synthesized, and repeatable catalytic performances were demonstrated. To the best of our knowledge, the 10 g batch is one of the largest batches of CO2RR catalysts synthesized in the literature while requiring minimal synthesis steps. The catalyst possessed single-atomic iron–nitrogen (Fe–N) sites, enabling a high performance of >95% CO product selectivity at a high current density of 400 mA/cm 2 and high stability for 45 h at 100 mA/cm 2 in a flow cell testing. The catalyst outperformed a benchmark noble-metal nanoparticle catalyst and achieved longer stability than many other reported M–N–C catalysts in the literature. The scalable and cost-effective synthesis developed in this work paves a pathway toward practical CO 2 RR applications. The direct utilization of metal impurities from raw CNTs for efficient catalyst synthesis with minimal treatment is a green and sustainable engineering approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Privacy-Preserving Real-Time Action Detection in Intelligent Vehicles Using Federated Learning-Based Temporal Recurrent Network

This study introduces a privacy-preserving approach for the real-time action detection in intelligent vehicles using a federated learning (FL)-based temporal recurrent network (TRN). This approach enables edge devices to independently train models, enhancing data privacy and scalability by eliminating central data consolidation. Our FL-based TRN effectively captures temporal dependencies, anticipating future actions with high precision. Extensive testing on the Honda HDD and TVSeries datasets demonstrated robust performance in centralized and decentralized settings, with competitive mean average precision (mAP) scores. The experimental results highlighted that our FL-based TRN achieved an mAP of 40.0% in decentralized settings, closely matching the 40.1% in centralized configurations. Notably, the model excelled in detecting complex driving maneuvers, with mAPs of 80.7% for intersection passing and 78.1% for right turns. These outcomes affirm the model’s accuracy in action localization and identification. The system showed significant scalability and adaptability, maintaining robust performance across increased client device counts. The integration of a temporal decoder enabled predictions of future actions up to 2 s ahead, enhancing the responsiveness. Our research advances intelligent vehicle technology, promoting safety and efficiency while maintaining strict privacy standards.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2010

Status of Solar Sail Technology Within NASA

In the early 2000s, NASA made substantial progress in the development of solar sail propulsion systems for use in robotic science and exploration of the solar system. Two different 20-m solar sail systems were produced and they successfully completed functional vacuum testing in NASA Glenn Research Center's (GRC's) Space Power Facility at Plum Brook Station, Ohio. The sails were designed and developed by ATK Space Systems and L Garde, respectively. The sail systems consist of a central structure with four deployable booms that support the sails. These sail designs are robust enough for deployment in a one-atmosphere, one-gravity environment and were scalable to much larger solar sails perhaps as large as 150 m on a side. Computation modeling and analytical simulations were also performed to assess the scalability of the technology to the large sizes required to implement the first generation of missions using solar sails. Life and space environmental effects testing of sail and component materials were also conducted. NASA terminated funding for solar sails and other advanced space propulsion technologies shortly after these ground demonstrations were completed. In order to capitalize on the $30M investment made in solar sail technology to that point, NASA Marshall Space Flight Center (MSFC) funded the NanoSail-D, a subscale solar sail system designed for possible small spacecraft applications. The NanoSail-D mission flew on board the ill-fated Falcon-1 Rocket launched August 2, 2008, and due to the failure of that rocket, never achieved orbit. The NanoSail-D flight spare will be flown in the Fall of 2010. This paper will summarize NASA's investment in solar sail technology to-date and discuss future opportunities

Johnson, Les↗