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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Performance considerations in long-term spaceflight

Maintenance of skilled performance during extended space flight is of critical importance to both the health and safety of crew members and to the overall success of mission goals. An examination of long term effects and performance requirements is therefore a factor of immense importance to the planning of future missions. Factors that were investigated include: definition of performance categories to be investigated; methods for assessing and predicting performance levels; in-flight factors which can affect performance; and factors pertinent to the maintenance of skilled performance.

Akins, F. R.↗
NASA NTRS1982

JPL antenna technology development

Systems-level technology for evolving cost-effective, STS compatible antennas that will be automatically deployed in orbit to perform a variety of missions in the 1985 to 2000 time period is discussed. For large space-based antenna systems, the LSST program has selected deployable antennas for development. The maturity of this class of antenna, demonstrated by the success of smaller size apertures, provides a potential capability for satisfying a significant number of near-term, space-based applications. The offset wrap-rib concept development is the basis of the JPL LSST antenna technology development program. Supporting technology to the antenna concept development include analytical performance prediction, the capability for measuring and evaluating mechanical antenna performance in the intended service environment, and the development of candidate system-level configurations for potential applications utilizing the offset wrap-rib antenna concept.

Freeland, R. E.↗
NASA NTRS1985

Onboard rendezvous navigation for the Space Shuttle

The onboard rendezvous navigation software for Shuttle flight 41-C are described. Particular attention is given to the inputs, models, and outputs of the software. The performance of the rendezvous navigation system is compared to predicted performance profiles in connection with the relative vehicle geometry, as well as the location of the navigation sensor tracking arcs. The methods used to process navigational sensor measurements in order to update the state vector are also summarized. A table listing the sources of maneuver targeting errors is provided.

Wylie, A. D.↗
NASA NTRS1925

The estimation of airplane performance from wind tunnel tests on conventional airplane models

Calculations of the magnitude of the correction factors and the range of their variations for wind tunnel models used in making aircraft performance predictions were made for 23 wind tunnel models. Calculated performances were compared with those actually determined for such airplanes as have been built and put through flight test. Except as otherwise noted, all the models have interplane struts and diagonal struts formed to streamwise shape. Wires were omitted in all cases. All the models were about 18 inches in span and were tested in a 4-foot wind tunnel. Results are given in tabular form.

Warner, Edward P↗
DOE OSTI2024

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗
NASA NTRS1978

Comparison of theoretical and experimental solar cell performance

This paper presents the results of a detailed comparison between the theoretically predicted performance of silicon solar cells and the experimentally observed performance. The comparison has included the dark I-V characteristics, the spectral response characteristics and the I-V characteristics under AM0 illumination. In general it has been found that the agreement between theory and experimental behavior is very good. This good agreement has been obtained for a variety of cells fabricated with junction depths ranging from 0.1 micron to more than 1 micron and for base layer resistivities from 10 to 0.1 ohm-cm.

Fang, C. R.↗
DOE OSTI2021

Information-Theoretic Bounds on Quantum Advantage in Machine Learning

We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2 Ω(n) copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1991

Evaluation of GPS/UTC steering performance

The Global Positioning System (GPS) is required to maintain GPS time to Universal Coordinated Time (UTC) to an accuracy of one microsecond and broadcast to the user the offset between GPS and UTC to an accuracy of 100 nanoseconds (1 sigma). On 25 Jun. 1990, an automatic steering algorithm was implemented to control GPS time to synchronize it with UTC. The description of the steering laws and predicted performance results were presented at the 1989 Precise Time and Time Interval (PTTI) conference, while preliminary performance results were presented at the 1990 PTTI conference. The initial performance was not as predicted, resulting in an in-depth analysis of the observed performance and a more thorough sensitivity analysis. In addition, responses to anomalies were investigated. This paper will describe these analyses and results, and evaluate actual steering performance from Jun. 1990 to Nov. 1991. Although anomalies were observed during the initial phase of steering, recent experience is more in line with expectations.

W. A. Feess↗
DOE OSTI2026

Predicting core transport in ITER baseline discharges with neon injections

Achieving self-consistent performance predictions for ITER requires integrated modeling of core transport and divertor power exhaust under realistic impurity conditions. We present results from a systematic power-flow and impurity-content study for the ITER 15 MA baseline scenario constrained directly by existing SOLPS-ITER neon-seeded divertor solutions. Using the OMFIT STEP workflow, stationary temperature and density profiles are predicted with TGYRO for $1.5 \unicode{x2A7D} Z_\textrm{eff} \unicode{x2A7D} 2.5$, and the corresponding power crossing the separatrix $P_\textrm{sep}$ is evaluated. We find that $P_\textrm{sep}$ varies by more than a factor of 1.7 across this scan and matches the ${\sim}100$ MW SOLPS-ITER prediction when $Z_\textrm{eff} \simeq 1.6$ or when auxiliary heating is reduced to ${\sim}75\%$ of nominal. Rotation-sensitivity studies show that plausible variations in toroidal flow magnitude modify $P_\textrm{sep}$ by $\lesssim 20\%$, while AURORA modeling confirms that charge-exchange radiation inside the separatrix is dynamically negligible under predicted ITER neutral densities. These results identify a restricted compatibility window, $Z_\textrm{eff} \approx 1.6$ –1.75 and $0.75 \lesssim f_{P_\textrm{aux}} \unicode{x2A7D} 1.0$, in which core transport predictions remain aligned with neon-seeded divertor protection targets. This self-consistent, model-constrained framework provides actionable guidance for impurity control and auxiliary-heating scheduling in early ITER operation and supports future whole-device scenario optimization.

ITER↗
NASA NTRS1975

Prediction of oxidation performance of reinforced carbon-carbon material for Space Shuttle leading edges

A method was developed for predicting oxidation performance, in an earth atmospheric entry environment, of reinforced carbon-carbon material, coated for oxidation resistance. A model was developed which describes oxidation control mechanisms, and the equations defining these mechanisms were derived. These relations were used to correlate oxidation test data, and to infer pertinent rate constants. Predictions were made of material oxidation performance in a representative entry environment, and the predictions were compared with ground test data. Results indicate that the method can be successfully used for predicting material oxidation performance.

Medford, J. E.↗
DOE OSTI2023

Predicting Kyasanur forest disease in resource-limited settings using event-based surveillance and transfer learning

In recent years, the reports of Kyasanur forest disease (KFD) breaking endemic barriers by spreading to new regions and crossing state boundaries is alarming. Effective disease surveillance and reporting systems are lacking for this emerging zoonosis, hence hindering control and prevention efforts. We compared time-series models using weather data with and without Event-Based Surveillance (EBS) information, i.e., news media reports and internet search trends, to predict monthly KFD cases in humans. We fitted Extreme Gradient Boosting (XGB) and Long Short-Term Memory models at the national and regional levels. We utilized the rich epidemiological data from endemic regions by applying Transfer Learning (TL) techniques to predict KFD cases in new outbreak regions where disease surveillance information was scarce. Overall, the inclusion of EBS data, in addition to the weather data, substantially increased the prediction performance across all models. The XGB method produced the best predictions at the national and regional levels. The TL techniques outperformed baseline models in predicting KFD in new outbreak regions. Novel sources of data and advanced machine-learning approaches, e.g., EBS and TL, show great potential towards increasing disease prediction capabilities in data-scarce scenarios and/or resource-limited settings, for better-informed decisions in the face of emerging zoonotic threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗
NASA NTRS1984

Estimating Pump Blockage

Blockage predicted for all components including inducers, impellers and diffusers. Pump performance predicted by semiempirical method shows excellent agreement with test results in Space Shuttle main-engine highpressure fuel turbopump. Comparisons of pump efficiency show equally good agreement of calculated values with experimental ones. Method improves current estimation methods based solely on subjective engineering judgment.

Chung, W.↗
NASA NTRS1988

Composite transport wing technology development: Design development tests and advanced structural concepts

Numerous design concepts, materials, and manufacturing methods were investigated for the covers and spars of a transport box wing. Cover panels and spar segments were fabricated and tested to verify the structural integrity of design concepts and fabrication techniques. Compression tests on stiffened panels demonstrated the ability of graphite/epoxy wing upper cover designs to achieve a 35 percent weight savings compared to the aluminum baseline. The impact damage tolerance of the designs and materials used for these panels limits the allowable compression strain and therefore the maximum achievable weight savings. Bending and shear tests on various spar designs verified an average weight savings of 37 percent compared to the aluminum baseline. Impact damage to spar webs did not significantly degrade structural performance. Predictions of spar web shear instability correlated well with measured performance. The structural integrity of spars manufactured by filament winding equalled or exceeded those fabricated by hand lay-up. The information obtained will be applied to the design, fabrication, and test of a full-scale section of a wing box. When completed, the tests on the technology integration box beam will demonstrate the structural integrity of an advanced composite wing design which is 25 percent lighter than the metal baseline.

Griffin, Charles F.↗
NASA NTRSDate not supplied

Optical Time Transfer for Bistatic SAR Spacecraft

A spacecraft-to-spacecraft optical time-transfer simulation has been developed as a tool for informing NASA’s Surface Deformation and Change (SDC) mission architecture. The SDC mission will combine radar images from multiple spacecraft to improve understanding of the Earth’s sea-level and landscape changes. Spacecraft must be precisely synchronized in order to create sharp radar images. Simulation of multiple spacecraft time-synchronizing via laser communication can inform technology choices of a mission by providing a picosecond-precision level estimate of clock error. This timing and ranging simulation has been combined with a radar system performance analysis pipeline. The simulated timing errors are used to predict performance of bistatic SAR systems in the presence of oscillator noise and time synchronization in accuracy. This analysis includes both analytic approximation equations from existing literature, and a numerical radar simulation to extract key system performance parameters like phase error and signal-to-noise ratio (SNR)degradation. Precision time-transfer techniques facilitate the accurate synchronization of clocks between any combination of terminals. Most time-transfer technology for comparing two clocks at different terminals use radio frequencies (RF) to measure the time delay between the sending and receiving of signals. Laser technology offers the capability to transmit high data rates with systems that are of smaller size and lower power than comparable RF systems. The clocks on independent spacecraft will have some phase and frequency errors between them that result in clock drift. The two clock models that are included in this bi-directional MATLAB simulation are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC). The CSAC has flown as hardware for small satellite missions such as the University of Florida’s CHOMPTT mission. A study of example orbits, including that of NASA NASA-ISRO Synthetic Aperture Radar Mission (NISAR) mission, and lasing rates demonstrate the impact of flight configuration parameters on the synchronization error between two spacecraft. The MATLAB timing simulation uses a Runge-Kutta 4th-order method to propagate spacecraft orbits and computes the light-travel time estimate between them. The simulation outputs the estimated range and estimated clock error based on a user-defined spacecraft cluster configuration. The radar simulation and analytic approximations are applied to evaluate a potential future NASA bistatic SAR constellation architecture. In the proposed architecture, satellites follow each other in the same orbit at 800 km altitude, with a 210 km baseline. We also baseline the CSAC as an ultra stable oscillator, and use NASA’s NISAR for baseline radar system parameters to compute a clock-system introduced phase error of 5.6 degrees without synchronization by frequent time transfer. We build on this base case with a sensitivity analysis of radar performance over a proposed range of constellation and radar system parameters. With this analysis pipeline, we comment on which radar parameters should or should not be changed to minimize synchronization requirements. This analysis technique could be extended or modified to evaluate the timing requirements of other geometries for other future multistatic SAR missions, or other interferometric satellite missions.

Surface Deformation and Change↗
DOE OSTI2024

STFM: Accurate Spatio-Temporal Fusion Model for Weather Forecasting

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

54 ENVIRONMENTAL SCIENCES↗