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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Method to estimate drag coefficient at the air/ice interface over drifting open pack ice from remotely sensed data

A knowledge in near real time, of the surface drag coefficient for drifting pack ice is vital for predicting its motions. And since this is not routinely available from measurements it must be replaced by estimates. Hence, a method for estimating this variable, as well as the drag coefficient at the water/ice interface and the ice thickness, for drifting open pack ice was developed. These estimates were derived from three-day sequences of LANDSAT-1 MSS images and surface weather charts and from the observed minima and maxima of these variables. The method was tested with four data sets in the southeastern Beaufort sea. Acceptable results were obtained for three data sets. Routine application of the method depends on the availability of data from an all-weather air or spaceborne remote sensing system, producing images with high geometric fidelity and high resolution.

Feldman, U.↗
NASA NTRS1990

A preliminary look at techniques used to obtain airdata from flight at high angles of attack

Flight research at high angles of attack has posed new problems for airdata measurements. New sensors and techniques for measuring the standard airdata quantities of static pressure, dynamic pressure, angle of attack, and angle of sideslip were subsequently developed. The ongoing airdata research supporting NASA's F-18 high alpha research program is updated. Included are the techniques used and the preliminary results. The F-18 aircraft was flown with three research airdata systems: a standard airdata probe on the right wingtip, a self-aligning airdata probe on the left wingtip, and a flush airdata system on the nose cone. The primary research goal was to obtain steady-state calibrations for each airdata system up to an angle of attack of 50 deg. This goal was accomplished and preliminary accuracies of the three airdata systems were assessed and are presented. An effort to improve the fidelity of the airdata measurements during dynamic maneuvering is also discussed. This involved enhancement of the aerodynamic data with data obtained from linear accelerometers, rate gyros, and attitude gyros. Preliminary results of this technique are presented.

Moes, Timothy R.↗
NASA NTRS1992

Crew behavior and performance in space analog environments

The objectives and the current status of the Crew Factors research program conducted at NASA-Ames Research Center are reviewed. The principal objectives of the program are to determine the effects of a broad class of input variables on crew performance and to provide guidance with respect to the design and management of crews assigned to future space missions. A wide range of research environments are utilized, including controlled experimental settings, high fidelity full mission simulator facilities, and fully operational field environments. Key group processes are identified, and preliminary data are presented on the effect of crew size, type, and structure on team performance.

Kanki, Barbara G.↗
NASA NTRS2011

Icing Encounter Duration Sensitivity Study

This paper describes a study performed to investigate how aerodynamic performance degradation progresses with time throughout an exposure to icing conditions. It is one of the first documented studies of the effects of ice contamination on aerodynamic performance at various points in time throughout an icing encounter. Both a 1.5 and 6 ft chord, two-dimensional, NACA-23012 airfoils were subjected to icing conditions in the NASA Icing Research Tunnel for varying lengths of time. At the end of each run, lift, drag, and pitching moment measurements were made. Measurements with the 1.5 ft chord model showed that maximum lift and pitching moment degraded more rapidly early in the exposure and degraded more slowly as time progressed. Drag for the 1.5 ft chord model degraded more linearly with time, although drag for very short exposure durations was slightly higher than expected. Only drag measurements were made with the 6 ft chord airfoil. Here, drag for the long exposures was higher than expected. Novel comparison of drag measurements versus an icing scaling parameter, accumulation parameter times collection efficiency was used to compare the data from the two different size model. The comparisons provided a means of assessing the level of fidelity needed for accurate icing simulation.

Addy, Harold E., Jr.↗
NASA NTRS2013

Acceptability of Flight Deck-Based Interval Management Crew Procedures

The Interval Management for Near-term Operations Validation of Acceptability (IM-NOVA) experiment was conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) in support of the NASA Next Generation Air Transportation System (NextGen) Airspace Systems Program's Air Traffic Management Technology Demonstration - 1 (ATD-1). ATD-1 is intended to showcase an integrated set of technologies that provide an efficient arrival solution for managing aircraft using NextGen surveillance, navigation, procedures, and automation for both airborne and ground-based systems. The goal of the IM-NOVA experiment was to assess if procedures outlined by the ATD-1 Concept of Operations, when used with a minimum set of Flight deck-based Interval Management (FIM) equipment and a prototype crew interface, were acceptable to and feasible for use by flight crews in a voice communications environment. To investigate an integrated arrival solution using ground-based air traffic control tools and aircraft automatic dependent surveillance broadcast (ADS-B) tools, the LaRC FIM system and the Traffic Management Advisor with Terminal Metering and Controller Managed Spacing tools developed at the NASA Ames Research Center (ARC) were integrated in LaRC's Air Traffic Operations Laboratory. Data were collected from 10 crews of current, qualified 757/767 pilots asked to fly a high-fidelity, fixed based simulator during scenarios conducted within an airspace environment modeled on the Dallas-Fort Worth (DFW) Terminal Radar Approach Control area. The aircraft simulator was equipped with the Airborne Spacing for Terminal Area Routes algorithm and a FIM crew interface consisting of electronic flight bags and ADS-B guidance displays. Researchers used "pseudo-pilot" stations to control 24 simulated aircraft that provided multiple air traffic flows into DFW, and recently retired DFW air traffic controllers served as confederate Center, Feeder, Final, and Tower controllers. Pilot participant feedback indicated that the procedures used by flight crews to receive and execute interval management (IM) clearances in a voice communications environment were logical, easy to follow, did not contain any missing or extraneous steps, and required the use of an acceptable level of workload. The majority of the pilot participants found the IM concept, in addition to the proposed FIM crew procedures, to be acceptable and indicated that the ATD-1 procedures can be successfully executed in a near-term NextGen environment.

Murdock, Jennifer L.↗
NASA NTRS2015

Experimental Evaluation of Tuned Chamber Core Panels for Payload Fairing Noise Control

Analytical models have been developed to predict the sound absorption and sound transmission loss of tuned chamber core panels. The panels are constructed of two facesheets sandwiching a corrugated core. When ports are introduced through one facesheet, the long chambers within the core can be used as an array of low-frequency acoustic resonators. To evaluate the accuracy of the analytical models, absorption and sound transmission loss tests were performed on flat panels. Measurements show that the acoustic resonators embedded in the panels improve both the absorption and transmission loss of the sandwich structure at frequencies near the natural frequency of the resonators. Analytical predictions for absorption closely match measured data. However, transmission loss predictions miss important features observed in the measurements. This suggests that higher-fidelity analytical or numerical models will be needed to supplement transmission loss predictions in the future.

Schiller, Noah H.↗
NASA NTRS2016

Results of the Lunar Exploration Analysis Group (LEAG) Gap Review: Specific Action Team (SAT), Examination of Strategic Knowledge Gaps (SKGs) for Human Exploration of the Moon

The Lunar Exploration Analysis Group (LEAG) was tasked by the Human Exploration Operations Mission Directorate (HEOMD) to establish a Specific Action Team (SAT) to review lunar Strategic Knowledge Gaps (SKGs) within the context of new lunar data and some specific human mission scenarios. Within this review, the SAT was to identify the SKGs that have been fully or partially retired, identify new SKGs resulting from new data and observations, and review quantitative descriptions of measurements that are required to fill knowledge gaps, the fidelity of the measurements needed, and if relevant, provide examples of existing instruments or potential missions capable of filling the SKGs.

Shearer, C. K.↗
NASA NTRS2017

The Lander Vision System for Mars 2020 Entry Descent and Landing

In January 2016, the Mars 2020 project added Terrain Relative Navigation to the project baseline. This new capability helps the mission avoid large hazards in the landing ellipse, which enables the consideration of landing sites that more geologically diverse than before. This diversity should improve the quality of the samples collected by Mars 2020 for possible future return to earth. The Lander Vision System (LVS) is the sensor that provides the position fix that is used to determine where to land between hazards identified in orbital data prior to landing. This paper describes the LVS flight design for Mars 2020, a high-fidelity simulation used as a design tool and the expected LVS performance for Mars 2020.

Johnson, Andrew↗
NASA NTRSDate not supplied

UASs Optimization - An evaluation of multiple mode vehicles in monitoring and communication

This presentation will describe the author's experience as Co-I in the NASA/USFS Project: "Strategic Tac Radio and Tac Overwatch (STRATO): Last Mile Communications and Realtime Observation Stratospheric Platforms for wildland fire". This project utilizes an uncrewed Stratospheric (> 70Kft) lighter than air Uninhabited Aerial System (UAS), carries 50 Kg of sensor and communications equipment, and remains on station over a wildfire for up to 30 days. The air vehicle is capable of in excess of 180 days on station, but while the full duration capabilities were not utilized in this project, they could, and would, be used in monitoring a feature like a volcano. In addition to duration, the ability of these Stratospheric Platforms to persistently monitor an area, while carrying "smart" sensors - generating information products, rather than just data - is game changing. Utilizing technologies such as LoRa, the platform can now be the nexus of an ad-hoc sensor web, receiving LoRa based data from low power in-situ sensors in the area being monitored, combining it with high fidelity information gained from on-board sensors, and sending the information product to a remote research facility, using Satellite communication, in real time. The author will relate the evolution of information collection, derivation and delivery mechanisms in the entire range of NASA's UAS fleet, to today's world, where information products conventionally derived in desk top computational environments, and made available to the Science Community in weeks or months, are now being generated and delivered in near real time.

UASs↗
NASA NTRSDate not supplied

Improving Quantification of Medical Evacuation Risk for Human Spaceflight in the IMPACT Model

Traditionally, mission planners have used a heuristic and qualitative approach to design medical systems based on prior experience however this approach may result in high variability and implicit bias to design and could put missions and crewmembers at risk. The Informing Mission Planning through Analysis of Complex Tradespaces (IMPACT) tool is a probabilistic risk assessment tool designed by NASA to model medical risk in long duration missions outside of low earth orbit (LEO). This tool can quantify risk metrics such as risk of crewmember death, loss of crew task time, and the need for medical evacuation to better inform and augment the more traditional approach to medical system design. The risk metric of Return to Definitive Care (RTDC) represents the likelihood of requiring medical evacuation and has been difficult to quantify in a reliable and standardized manner. Initial development of the RTDC metric was constrained due to the complexity of a medical evacuation decision and the lack of prior spaceflight data and this presentation will discuss the review and improvement process used to increase model accuracy and fidelity.

Prashant Parmar↗
NASA NTRS2005

AOCS Performance and Stability Validation for a 160-m Solar Sail with Control-Structure Interactions

Future solar sail missions, such as NASA's Solar Polar Imager Vision, will require sails with dimensions on the order of 50-500 m. We are examining a square sail design with moving mass (trim control mass, TCM) and quadrant rotation primary actuators plus pulsed plasma thrusters (PPTs) at the mast tips for backup attitude control. Quadrant rotation is achieved via roll stabilizer bars (RSB) at the mast tips. At these sizes, given the gossamer nature of the sail supporting structures, flexible modes may be low enough to interact with the control system, especially as these actuators are located on the flexible structure itself and not on the rigid core. This paper develops a practical analysis of the flexible interactions using state-space systems and modal data from finite element models of the system. Torsion and bending of the masts during maneuvers could significantly affect the function of the actuators while activation of the membrane modes could adversely affect the thrust vector direction and magnitude. Analysis of the RSB and TCM dynamics for developing high-fidelity simulations is included. For control analysis of the flexible system, standard finite-element models of the flexible sail body are loaded and the modal data is used to create a modal coordinate state-space system. Key parameters include which modes to include, which nodes are of interest for force inputs and displacement outputs, connecting nodes through which external forces and torques are applied from the flex body to the core, any nominal momentum in the system, and any steady rates. The system is linearized about the nominal attitude and rate. The state-space plant can then be analyzed with a state-space controller, and Bode, Nyquist, step and impulse responses generated. The approach is general for any rigid core with a flexible appendage. This paper develops a compensator for a simple two-mass flex system and extrapolates the results to the solar sail. A finite element model of the 20 m solar sail by ATK Space Systems, recently validated in ground tests, is used to demonstrate the sail analysis approach.

Wie, Bong↗
DOE OSTI2026

Neural entropy-stable conservative flux form neural networks for learning hyperbolic conservation laws

We propose a neural entropy-stable conservative flux form neural network (NESCFN) for learning hyperbolic conservation laws and their associated entropy functions directly from solution trajectories, without requiring any predefined numerical discretization. While recent neural network architectures have successfully integrated classical numerical principles into learned models, most rely on prior knowledge of the governing equations or assume a fixed discretization. Our approach removes this dependency by embedding entropy-stable design principles into the learning process itself, enabling the discovery of physically consistent dynamics in a fully data-driven setting. By jointly learning both the flux function and a corresponding entropy, NESCFN promotes conservation and entropy dissipation, which is critical for long-term stability and fidelity in the system of hyperbolic conservation laws. Furthermore, numerical results demonstrate that the method achieves stability and conservation over extended time horizons and accurately captures shock propagation speeds, even without oracle access to future-time solution profiles in the training data.

Conservative flux form↗
DOE OSTI2023

A Neural Differential Equation Formulation for Modeling Atmospheric Effects in Hyperspectral Images

Atmospheric correction is the process for removing atmospheric effects from spectral data; a necessary step for recovering salient spectral properties. The complex interactions between the atmosphere and light are dominated by absorbance and scattering physics. Existing methods for modeling atmospheric interactions typically rely on deep knowledge of relevant environmental conditions and high-fidelity numerical simulations of the governing physics in order to obtain accurate estimates of these effects. Additionally, existing approaches often require a subject matter expert for pre/post-processing of the data. Model-based approaches for removing atmospheric effects struggle in situations where such domain expertise is not available, and require significant human effort and computational power even when that expertise is available. In contrast, we propose a data-driven approach the uses Neural Differential Equations (NDEs) to accurately learn the interactions between electromagnetic radiation and the atmospheric without access to location specific environmental information. Once trained, the NDE can be applied bi-directionally; to apply or remove atmospheric effects. We demonstrate the effectiveness and utility of these techniques on an example multi-spectral scene.

Koch, James V.↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2019

Investigation of Reduced-Order Modeling for Aircraft Stability and Control Prediction

High-fidelity computational fluid dynamics tools offer the potential to approximate increments for ground-to-flight scaling effects, as well as to augment the dynamic damping derivative data for motion-based flight simulators. Unfortunately, the computational expense is currently prohibitive for populating a complete simulator database. This work investigates an existing surrogate-based, indicial response reduced-order model methodology as a means to efficiently augment a flight simulator database with high-fidelity nonlinear aerodynamic damping derivatives. Creation of the reduced-order model is based on the superposition integrals of the step response with the derivative of its corresponding input signal. Step responses are calculated using a computational grid motion approach that separates the effects of angle of attack and sideslip angle from angular rates, and rates from angle of attack and sideslip. It is demonstrated that the transients produced during the start of a forced-oscillation motion are captured by the reduced-order model to the level of fidelity of a comparable computational solution. Aerodynamic coefficients computed within minutes by the reduced-order model for an aircraft undergoing an 18-second half Lazy-8 maneuver and a 25-second Immelmann turn maneuver are compared with those from full computational flight solutions that required days to complete. Finally, a cost-benefit assessment is included that demonstrates a compelling advantage for this approach. d for maneuvering, flexible vehicles.

Frink, Neal T.↗
DOE OSTI2021

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Thermal scattering law for structure-dependent-Doppler broadening in FLASSH

Traditional Doppler broadening methods assume that target nuclei velocities follow a Maxwell-Boltzmann distribution which inherently assumes that the atoms are a free gas or that their velocities are independent of each other. This approximation is reasonable at high target temperatures and high neutron energies. However, nuclei are not independent: the lattice temperature and chemical binding will define the atomic motion. The thermal scattering law (i.e., TSL or S(α,β)) is a material property which describes the chemical binding and temperature response in terms of available momentum and energy states. In the thermal energy range, this TSL will define the thermal scattering cross sections. In the resonance region, the TSL offers a first-principles description of the probability distribution function for the velocity of the target nuclei. Using the TSL in Doppler broadening captures the structure of the material consistently from the thermal range into the resonance cross sections. In this work, both traditional free-gas and precise TSL Doppler broadening methods for resonance cross section evaluation have been implemented within the Full Law Analysis Scattering System Hub (FLASSH). This framework provides a generalized formulation for evaluating low-lying resonance data and streamlines nuclear data processing methods. TSL data generated using ab initio lattice dynamics (AILD) can be used to broaden cross section libraries in ENDF format for high-fidelity input into reactor physics calculations. These capabilities are demonstrated for the lowest absorption resonances of {sup 238}U in UO{sub 2}, UC and UN. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1986

The design and fabrication of the Centaur neutral buoyancy trainer and related hardware

Two full scale mockups of the Centaur upper stage were designed, fabricated and delivered to NASA. One was the Centaur Weightless Environment Training Facility (WETF) trainer and the other was the Centaur 1-G mockup. The Centaur upper stage booster is designed to carry the spacecraft Galileo to Jupiter, and the spacecraft Ulysses to an orbit around the Sun after launch from the Space Shuttle. The flight vehicle has several Extravehicular Activity (EVA) contingency tasks that require crew training. This need for crew training generated the requirement for the Centaur WETF crew trainer, which is high fidelity in areas of expected crew interface. During the production of the Centaur WETF crew trainer, the need for a jumper cable from Centaur to the Orbiter was identified. This EVA contingency task would be the installation of a cable from the Orbiter cargo bay sill to various command data boxes on Centaur to allow crew control deployment should a failure occur. This task required the upgrading of volumetric boxes on the trainer to a high fidelity configuration including electrical connector installation and cable routing.

Ware, Alan S.↗