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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Using Historical Data to Automatically Identify Air-Traffic Control Behavior

This project seeks to develop statistical-based machine learning models to characterize the types of errors present when using current systems to predict future aircraft states. These models will be data-driven - based on large quantities of historical data. Once these models are developed, they will be used to infer situations in the historical data where an air-traffic controller intervened on an aircraft's route, even when there is no direct recording of this action.

trajectory generation↗
NASA NTRS1983

Reconstruction of the shuttle reentry air data parameters using a linearized Kalman filter

This paper presents the reconstruction of the space shuttle's wind-relative reentry trajectory for the orbital flights. The technique uses a linearized Kalman filter (LKF) to merge highand low-frequency inertial and wind-relative data to obtain enhanced high-frequency results that closely follow expected mean levels. Two verifications are presented. First, wind trajectories resulting from the reconstruction are compared with analytically predicted values. There is close comparison. Second, the frequency characteristics are investigated using system identification techniques. The stability and control model generated using the LKF trajectory shows good agreement between measured and predicted spacecraft response for both high and low frequencies.

Whitmore, S. A.↗
DOE OSTI2025

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗
DOE OSTI2024

Using intrahost single nucleotide variant data to predict SARS-CoV-2 detection cycle threshold values

Over the last four years, each successive wave of the COVID-19 pandemic has been caused by variants with mutations that improve the transmissibility of the virus. Despite this, we still lack tools for predicting clinically important features of the virus. In this study, we show that it is possible to predict the PCR cycle threshold (Ct) values from clinical detection assays using sequence data. Ct values often correspond with patient viral load and the epidemiological trajectory of the pandemic. Using a collection of 36,335 high quality genomes, we built models from SARS-CoV-2 intrahost single nucleotide variant (iSNV) data, computing XGBoost models from the frequencies of A, T, G, C, insertions, and deletions at each position relative to the Wuhan-Hu-1 reference genome. Our best model had an R 2 of 0.604 [0.593–0.616, 95% confidence interval] and a Root Mean Square Error (RMSE) of 5.247 [5.156–5.337], demonstrating modest predictive power. Overall, we show that the results are stable relative to an external holdout set of genomes selected from SRA and are robust to patient status and the detection instruments that were used. This study highlights the importance of developing modeling strategies that can be applied to publicly available genome sequence data for use in disease prevention and control.

COVID19↗
NASA NTRS1996

Research concerning the net flux of radiation in the atmosphere of Jupiter

The plan of the NFR (Net Flux of Radiation) team is for the data from the two solar channels (B and E) of NFR to be reduced with the goal of determining the solar heating rate. In order to determine the solar heating rate from the NFR measurements, effects due to the instrument's spatial and spectral response functions, to the temperature variation of the instrument (and associated drift of calibration), to the setting sun, and to the rotation of the probe (initially at a rate comparable to the NFR sampling frequency), all must be well modelled. In the past year, a forward modeling routine was created to simulate NFR data return in the B and E channels. The effects of varying parameters describing the atmospheric model (such as cloud location and thickness) and the descent profile (such as rotation rate) were investigated and an inversion routine was developed. For the forward modeling, existing radiative transfer codes were used to determine intensity fields within the Jovian atmosphere. A routine was developed to determine instantaneous instrument response by integrating the intensity field over the instrument response functions. A second routine was developed to determine the actual output of the NFR by integrating along an arbitrary descent trajectory. Near the top of the atmosphere, the upflux data alone are used to constrain the cloud structure of he atmosphere. To accomplish this, models are used to describe the variation in up flux between consecutive measurements in terms of variations of cloud opacity and variations in known parameters such as the solar zenith angle. This allows us to develop a zero-order model of cloud structure. Lower in the atmosphere, at levels where there is little or no azimuthal structure to the net flux measurements, both the up flux and net flux are used to derive layer transmission and reflection functions, which then determine layer opacity and single scattering albedo. A preliminary analysis of the data began in December 1995. In these data we could see the rapid oscillations expected at the beginning of the data due to probe rotation and the sun passing through the edge of the field of view. In addition, the time when this oscillation stopped was clearly visible. This sets the rough optical depth above the probe at this time.

Tomasko, M. G.↗
NASA NTRS1976

Flight characteristics of probes in the atmospheres of Mars, Venus, and the outer planets

Density, pressure, and temperature profiles of an unknown planetary atmosphere can be obtained from the high-speed entry of a probe provided the aerodynamic characteristics of the probe in this atmosphere are accurately known. An investigation of the effect of gas composition on probe aerodynamics has been conducted in the Ames Hypersonic Free Flight Facility by gun launching small-scale models into atmospheres representative of Mars, Venus, Jupiter, and Saturn. Aerodynamic data at conditions matching the velocity and Reynolds number at a number of points on the Viking trajectory (Mars) were obtained in both air and carbon dioxide and significant differences were noted. Aerodynamic data are also presented from tests in hydrogen and hydrogen-helium mixtures, gases which characterize the atmospheres of the outer planets.

Intrieri, P. F.↗
NASA NTRS1978

GEOS-3 coherent C-band tracking data reduction and analysis

The availability of a coherent C-Band transponder on an orbiting vehicle has permitted the development of calibration techniques for C-Band radars. Prior coherent tracking was limited to test vehicles in powered flight or skin tracking of orbiting spacecraft. The pulse Doppler range rate data available concurrently and independently with normal range and angle data provides an extremely useful data set for assessing the internal consistency of the radars measurements, particularly when coupled with a trajectory well constrained by orbit dynamics. In order to further assess the precision of the range rate data, a technique was developed to numerically integrate the rate measurements into a pseudo-range data set showing extremely low noise and high sensitivity to systematic radar errors. Evaluation of integrated range data led to improvements in calibration of both the rate and conventional range data. In particular, proper evaluation of the very sensitive integrated ranges required the development of a processing correction for beacon delay variation with signal strength, a significant error in the conventional ranging data.

Krabill, W. B.↗
NASA NTRS1986

Measurement of angular distribution of sound emission from training projectiles in subsonic flight

Training projectiles with nose ring cavities that produce intense whistles in stationary free-jet tests were shot in a relatively straight-line trajectory. A ground based microphone was used to obtain the angular distribution of sound intensity produced from the subsonically flying projectile. Data reduction required calculation of Doppler and attenuation factors which were determined based on a non-linear trajectory. Also, the directional sensitivity of the microphone was measured and used in the data reduction. Significant angular variation of sound intensity produced from the projectile was found which can be used to plot an intensity contour map on the ground. A full-scale field test confirmed the validity of the aeroacoustic concept of producing a relatively intense whistle from the projectile, and the usefulness of a real-time data acquisition system.

Cho, Y. I.↗
NASA NTRS2010

Design of Quiet Rotorcraft Approach Trajectories: Verification Phase

Flight testing that is planned for October 2010 will provide an opportunity to evaluate rotorcraft trajectory optimization techniques. The flight test will involve a fully instrumented MD-902 helicopter, which will be flown over an array of microphones. In this work, the helicopter approach trajectory is optimized via a multiobjective genetic algorithm to improve community noise, passenger comfort, and pilot acceptance. Previously developed optimization strategies are modified to accommodate new helicopter data and to increase pilot acceptance. This paper describes the MD-902 trajectory optimization plus general optimization strategies and modifications that are needed to reduce the uncertainty in noise predictions. The constraints that are imposed by the flight test conditions and characteristics of the MD-902 helicopter limit the testing possibilities. However, the insights that will be gained through this research will prove highly valuable.

Padula, Sharon L.↗
NASA NTRS2019

Increasing Pilot’s Understanding of Future Automation State – an Evaluation of an Automation State and Trajectory Prediction System

A pilot in the loop flight simulation study was conducted at NASA Langley Research Center to evaluate a trajectory prediction system. The trajectory prediction system computes a five-minute prediction of the lateral and vertical path of the aircraft given the current and intent state of the automation. The prediction is shown as a graphical representation so the pilots can form an accurate mental model of the future state. Otherwise, many automation changes and triggers are hidden from the flight crew or need to be consolidated to understand if a change will occur and the exact timing of the change. Varying dynamic conditions like deceleration can obscure the future trajectory and the ability to meet constraints, especially in the vertical dimension. Current flight deck indications of flight path assume constant conditions and do not adequately support the flight crew to make correct judgments regarding constraints. The study was conducted using ten commercial airline crews from multiple airlines, paired by airline to minimize procedural effects. Scenarios spanned a range of conditions that provided evaluation in a realistic environment with complex traffic and weather conditions. In particular, scenarios probed automation state and loss of state awareness. The technology was evaluated and contrasted with current state-of-the-art flight deck capabilities modeled from the Boeing 787. Objective and subjective data were collected from aircraft parameters, questionnaires, audio/video recordings, head/eye tracking data, and observations. This paper details findings about the trajectory prediction system including recommendations about further study.

Etherington, Timothy J.↗
NASA NTRS2011

Evolution of Space Shuttle Range Safety Ascent Flight Envelope Design

For every space vehicle launch from the Eastern Range in Florida, the range user must provide specific Range Safety (RS) data products to the Air Force's 45th Space Wing in order to obtain flight plan approval. One of these data products is a set of RS ascent flight envelope trajectories that define the normal operating region of the vehicle during powered flight. With the Shuttle Program launching 135 manned missions over a 30-year period, 135 envelope sets were delivered to the range. During this time, the envelope methodology and design process evolved to support mission changes, maintain high data quality, and reduce costs. The purpose of this document is to outline the shuttle envelope design evolution and capture the lessons learned that could apply to future spaceflight endeavors.

Brewer, Joan↗
NASA NTRS1992

MIRACAL: A mission radiation calculation program for analysis of lunar and interplanetary missions

A computational procedure and data base are developed for manned space exploration missions for which estimates are made for the energetic particle fluences encountered and the resulting dose equivalent incurred. The data base includes the following options: statistical or continuum model for ordinary solar proton events, selection of up to six large proton flare spectra, and galactic cosmic ray fluxes for elemental nuclei of charge numbers 1 through 92. The program requires an input trajectory definition information and specifications of optional parameters, which include desired spectral data and nominal shield thickness. The procedure may be implemented as an independent program or as a subroutine in trajectory codes. This code should be most useful in mission optimization and selection studies for which radiation exposure is of special importance.

Nealy, John E.↗
DOE OSTI2019

Nonlocal Flocking Dynamics: Learning the Fractional Order of PDEs from Particle Simulations

Flocking refers to collective behavior of a large number of interacting entities, where the interactions between discrete individuals produce collective motion on the large scale. We employ an agent-based model to describe the microscopic dynamics of each individual in a flock, and use a fractional partial differential equation (fPDE) to model the evolution of macroscopic quantities of interest. The macroscopic models with phenomenological interaction functions are derived by applying the continuum hypothesis to the microscopic model. Instead of specifying the fPDEs with an ad hoc fractional order for nonlocal flocking dynamics, we learn the effective nonlocal influence function in fPDEs directly from particle trajectories generated by the agent-based simulations. We demonstrate how the learning framework is used to connect the discrete agent-based model to the continuum fPDEs in one- and two-dimensional nonlocal flocking dynamics. In particular, a Cucker–Smale particle model is employed to describe the microscale dynamics of each individual, while Euler equations with nonlocal interaction terms are used to compute the evolution of macroscale quantities. The trajectories generated by the particle simulations mimic the field data of tracking logs that can be obtained experimentally. They can be used to learn the fractional order of the influence function using a Gaussian process regression model implemented with the Bayesian optimization. We show in one- and two-dimensional benchmarks that the numerical solution of the learned Euler equations solved by the finite volume scheme can yield correct density distributions consistent with the collective behavior of the agent-based system solved by the particle method. Furthermore, the proposed method offers new insights into how to scale the discrete agent-based models to the continuum-based PDE models, and could serve as a paradigm on extracting effective governing equations for nonlocal flocking dynamics directly from particle trajectories.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Dynamic Stability Analysis Using Free-Flight CFD

Blunt body probes are the primary design for atmospheric entry. The blunted capsule shape, while desirable for the decreased forebody heating, typically experiences dynamic instability at low supersonic and transonic flight. At moderate to low supersonic conditions, the unsteady wake begins to adversely interact with the vehicle in free-flight resulting in attitude oscillations which can grow in time and result in tumbling. Understanding vehicle dynamics is thus important when considering vehicle entry design and guidance navigation and control (GN&C) considerations. Historically, dynamic stability has been carried out exclusively using experimental techniques. The wide range of experimental approaches provide reasonable coverage in Mach and dynamic pressure space for a given trajectory, however achieving flight similitude is often difficult or impossible. Advancements in Computational Fluid Dynamics (CFD) techniques allow for dynamic motion of the vehicle surface during the simulation with either forced/prescribed motion or free motion in response to fluid forces. Several examples of CFD software with the ability to simulate fluid dynamics and vehicle motion are available in literature. The Free-Flight CFD (FF-CFD) capability developed by NASA Ames within the US3D flow solver has shown extensive validation and verification (V&V) efforts from moderate to low supersonic flow across a range of vehicle architectures. The solver is able to simulate full rotational and translation motion resulting in full 6 degrees-of-freedom (DoF) motion. The validation and verification efforts the solver's ability to predict the motion of a ballistic range model as compared to experimental results. Similar to other computational capabilities in literature, FF-CFD relied on heritage data reduction methodologies and processes for reducing dynamic data into aerodynamic coefficients intended for use in design and trajectory codes. These heritage approaches, initially developed with the assumptions (and restrictions) of ground test facilities, resulted in the significant culling of the full 6-DoF dynamic data set to discrete values which are then fit using an aerodynamic model. Recent development of simulation and data reduction methodologies has resulted in an improved approach to FF-CFD simulations of vehicle dynamics which leverage the control of dynamic constraints within a simulation set-up. The presentation of this work will cover the constrained dynamic simulation approach for deriving dynamic coefficients for a Genesis capsule. The methodology will be outlined and a discussion of implications in motion restriction will be discussed. Finally, reconstructed vehicle trajectories using FF-CFD derived aerodynamic coefficients will be presented.

Joseph M Brock↗
DOE OSTI2025

Differentially Private Map Matching (DPMM) v1.0

Human mobility trajectories provide valuable information for developing mobility applications, as they contain diverse and rich information about the users. User mobility data is valuable for various applications such as intelligent transportation systems (ITS), commercial business models, and disease-spread models. However, such spatio-temporal traces may pose a threat to user privacy. GPS trajectories in their raw form are not suitable for transportation studies, as they require matching locations with nearest road links — a process called map-matching. This software implements a differential privacy (DP)-based map-matching algorithm, called DPMM, that generates link-level location trajectories in a privacy-preserving manner to protect users' origin destinations (OD) and travel paths. OD privacy is achieved by injecting Planar Laplace noise to the user OD GPS points. Travel-path privacy is provided with randomized travel path construction using exponential DP mechanism. The injected noise level is selected adaptively, by considering the link density of the location and the functional category of the localized links. For path privacy, our mechanism samples waypoints and selects candidate paths between waypoints. DPMM provides privacy effectively with respect to link density instead of other trajectory samples in the database compared to other privacy mechanisms. Compared to the different baseline models our DP-based privacy model offers closer query responses to the raw data in terms of individual and aggregate trajectory-level statistics with an average at absolute deviation from the baseline for individual statistics on ϵ = 1.0. Beyond individual trajectory statistics, the DPMM outperforms the other benchmark DP-based mechanisms on different aggregate statistics with up to 8x improvement in utility.

Peisert, Sean [Lawrence Berkeley National Laborato↗
NASA NTRS1981

Crop identification and leaf area index calculations with Landsat multitemporal data

Formulas are given to convert land-based vegetative canopy spectral reflectance measurements into Landsat digital counts in the four channels for a clear standard atmosphere. These formulas are shown to predict the curves found by plotting multitemporal Landsat trajectories. With correct interpretation, plots of channel 3 versus channel 4 Landsat data for crops are shown to yield information on both crop identification and crop leaf area index.

Chance, J. E.↗
NASA NTRS1988

Confined turbulent fluid-particle flow modeling using multiple-realization particle trajectory schemes

A multiple-realization particle trajectory scheme has been developed and applied to the numerical prediction of confined turbulent fluid-particle flows. The example flows investigated include the vertical pipe upflow experimental data of Tsuji et al. and the experimental data of Leavitt for a coaxial jet flow, comprising a particle-laden central jet and a clean annular jet, into a large recirculation chamber. The results obtained from the numerical scheme agree well with the experimental data, lending confidence to the modeling approach. The multiple-realization particle trajectory turbulent flow modeling scheme is believed to be a more elegant and accurate approach to the extension of single-particle hydrodynamics to dilute multi-particle systems than the more commonly employed two-fluid modeling approach. It is also better able to incorporate additional force items such as lift, virtual mass and Bassett history terms directly into the particle equation of motion as appropriate. This makes it a suitable candidate for particle migration studies and an extension to situations involving liquid particulate phases with possible propulsion applications, such as in spray combustion, follows naturally.

Adeniji-Fashola, A. A.↗