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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Investigation of new radar-data-reduction techniques used to determine drag characteristics of a free-flight vehicle

An investigation was conducted of new techniques used to determine the complete transonic drag characteristics of a series of free-flight drop-test models using principally radar tracking data. The full capabilities of the radar tracking and meteorological measurement systems were utilized. In addition, preflight trajectory design, exact kinematic equations, and visual-analytical filtering procedures were employed. The results of this study were compared with the results obtained from analysis of the onboard, accelerometer and pressure sensor data of the only drop-test model that was instrumented. The accelerometer-pressure drag curve was approximated by the radar-data drag curve. However, a small amplitude oscillation on the latter curve precluded a precise definition of its drag rise.

Woodbury, G. E.↗
NASA NTRSDate not supplied

Reasoning Service Exemplars for NASA’s Data and Reasoning Fabric

Future operations for Urban and Advanced Air Mobility are enabled by a distributed network of reliable and secured data and reasoning services referred to here as a fabric. In the aggregate, such a system must be all encompassing and mission agnostic, but specific use-cases are still needed to improve understanding and drive design paradigms. For this purpose, three reasoning service exemplars for Target Selection and Routing, Trajectory Generation, and Battery Health Management were developed and integrated into a specific NASA proposed data and reasoning fabric. These services were then used to build a mission reasoning application for lightning strike reconnaissance developed in collaboration with the Civil Air Patrol. Autonomous mission execution was then demonstrated using a multivehicle simulation platform with a full envelope 6 Degree-of-Freedom dynamics model for a concept electric Vertical Takeoff and Landing aircraft.

Autonomy↗
NASA NTRS2018

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Bosson, Christabelle S.↗
NASA NTRS2018

Supervised Learning Applied to Air Traffic Trajectory Classification

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Bosson, Christabelle↗
NASA NTRS2016

Navigation Using Deep-Space Optical Communication Systems

This work investigates the deep-space spacecraft navigation performance achievable from tracking data types obtained using optical communication systems. These optical navigation types include ranging between spacecraft and a station on Earth and astrometric measurements of angular position. Two mission scenarios are analyzed: an interplanetary cruise trajectory for a Mars lander (Mars 2020), and a science orbit for a Mars orbiter (MAVEN). Various data types are simulated using comprehensive measurement models, tracking schedules, and geometrical constraints. Sensitivity analyses are performed to assess the effect of various contributors to measurement accuracy and navigation performance. For both of the mission scenarios studied, the optical navigation types yield equivalent or improved performance as compared to traditional radiometric observables, though radiometric data types slightly outperform optical observables during tracking data gaps in the science orbit scenario.

McCandless, Sarah Elizabeth↗
NASA NTRSDate not supplied

VFR Trajectory Forecasting using Deep Generative Model for Autonomous Airspace Operations

To enable the airspace integration of autonomous operations, such as uncrewed aircraft conducting cargo deliveries, there is a need to forecast the positions of the surrounding traffic with which they may interact. This paper focuses on forecasting Visual Flight Rules traffic, a significant source of uncertainty and risk in the airspace, especially around small regional airports, due to the unplanned and often untracked nature of such flights. A deep generative model is developed, trained on historical traffic data at example towered and non-towered airports, and used to predict flight trajectories. Experimental results are presented comparing the performance of variational autoencoder and classical machine learning forecasting when applied to both the towered and non-towered airports over varying time horizons. The results show the advantages of the variational autoencoder in producing accurate probabilistic forecasts over varying time horizons.

uncrewed aircraft↗
NASA NTRSDate not supplied

VFR Trajectory Forecasting using Deep Generative Model for Autonomous Airspace Operations

To enable the airspace integration of autonomous operations, such as uncrewed aircraft conducting cargo deliveries, there is a need to forecast the positions of the surrounding traffic with which they may interact. This paper focuses on forecasting Visual Flight Rules traffic, a significant source of uncertainty and risk in the airspace, especially around small regional airports, due to the unplanned and often untracked nature of such flights. A deep generative model is developed, trained on historical traffic data at example towered and non-towered airports, and used to predict flight trajectories. Experimental results are presented comparing the performance of variational autoencoder and classical machine learning forecasting when applied to both the towered and non-towered airports over varying time horizons. The results show the advantages of the variational autoencoder in producing accurate probabilistic forecasts over varying time horizons.

uncrewed aircraft↗
NASA NTRS2017

Experimental Study of Hypersonic Inflatable Aerodynamic Decelerator (HIAD) Aeroshell with Axisymmetric Surface Deflection Patterns

A wind tunnel test program was conducted to obtain aeroheating environment data on Hypersonic Inflatable Aerodynamic Decelerator aeroshells with flexible thermal protection systems. Data were obtained on a set of rigid wind tunnel models with surface deflection patterns of various heights that simulated a range of potential in-flight aeroshell deformations. Wind tunnel testing was conducted at Mach 6 at unit Reynolds numbers from 2.1 × 10(exp 6)/ft to 8.3 × 10(exp 6)/ft and angles of attack from 0 deg to 18 deg. Boundary-layer transition onset and global surface heating distribution measurements were performed using phosphor thermography and flow field images were obtained through schlieren photography. Surface deflections were found to both promote early transition of the boundary layer and to augment heating levels for both laminar and turbulent flows. A complimentary computational flow field study was also performed to provide heating predictions for comparison with the measurements as well as boundary layer flow field properties for use in correlating the data. Correlations of the wind tunnel data were developed to predict deflection effects on boundary layer transition and surface heating and were applied to both the wind tunnel test conditions and to the trajectory of NASA's successful IRVE-3 flight test. In general, the correlations produced at least qualitative agreement with the wind tunnel data, although the heating levels were underpredicted for some of the larger surface deflections. For the flight conditions, the correlations suggested that peak heating levels on the leeward side conical flank of the IRVE-3 vehicle may have exceeded those at nose for times late in the trajectory after the peak heating time point. However, the flight estimates were based on a conservative assumption of surface deflection magnitude (i.e., larger) than likely was produced in flight.

Hollis, Brian R.↗
NASA NTRS2001

Role of Stratospheric Air in a Severe Weather Event: Analysis of Potential Vorticity and Total Ozone

The role of dry stratospheric air descending to low and middle tropospheric levels in a severe weather outbreak in the midwestern United States is examined using ACCEPT Eta model output, Rapid Update Cycle (RUC) analyses, and Earth probe Total Ozone Mapping Spectrometer (EP/TOMS) total ozone data. While stratospheric air was not found to play a direct role in the convection, backward trajectories show stratospheric air descended to 800 hPa just west of the convection. Damaging surface winds not associated with thunderstorms also occurred in the region of greatest stratospheric descent. Small-scale features in the high-resolution total ozone data compare favorably with geopotential heights and potential vorticity fields, supporting the notion that stratospheric air descended to near the surface. A detailed vertical structure in the potential vorticity appears to be captured by small-scale total ozone variations. The capability of the total ozone to identify mesoscale features assists model verification. The total ozone data suggest biases in the RUC analysis and Eta forecast of this event. The total ozone is also useful in determining whether potential vorticity is of stratospheric origin or is diabatically generated in the troposphere.

Goering, Melissa A.↗
NASA NTRS2018

Interplanetary Trajectory Design for NASA's Common Probe Study

The Galileo Probe, Pioneer-Venus probes, and SPRITE concept all share a number of common characteristics. They all follow a similar entry and descent sequence, using an aeroshell to protect against entry environments, and parachutes to aid in extrusion and descent speed control of the descent vehicle containing the science instruments. The descent vehicles all contained similar instruments (e.g. mass spectrometers and atmosphere structure sensors), and data was either relayed back to a carrier spacecraft (Galileo Probe, SPRITE) or transmitted direct to Earth (Pioneer-Venus). Based on these similar characteristics, NASA initiated a study to investigate a “common probe' that might be designed to perform similar science in a variety of planetary environments. This concept would leverage a common aeroshell design, and descent vehicle designs that could be made as similar as possible (the primary exception being that Venus will require a pressure vessel due to the extreme pressures and temperatures seen in the lower portion of the descent). To support the Common Probe study, GSFC and JPL performed a series of interplanetary trajectory analyses to help develop the mission designs for Venus, Jupiter, Saturn, Uranus, and Neptune. Primary considerations in the trajectory modeling included: a maximum of 12-year time of flight (for outer planet destinations), generation of both steep and shallow entry trajectories to each destination (where steep and shallow resulted in approximately 150 g and 50 g peak deceleration during entry at each location), and consideration of the data relay. Gravity assists and trajectories with low delta-V requirements (typically much less than 500 m/s) were also incorporated into the design process to enable launch on existing vehicles such as the Atlas V.

Hughes, Kyle M.↗
DOE OSTI2014

TRAJECTORY SENSITIVITY ANALYSIS FOR DYNAMIC SECURITY ASSESSMENT AND OTHER APPLICATIONS IN POWER SYSTEMS

Real time stability evaluation and preventive scheduling in power systems offer many challenges in a stressed power system. Trajectory sensitivity analysis (TSA) is a useful tool for this and other applications in the emerging smart grid area. In this chapter we outline the basic approach of TSA, to extract suitable information from the data and develop reliable metrics or indices to evaluate proximity of the system to an unstable condition. Trajectory sensitivities can be used to compute critical parameters such as clearing time of circuit breakers, tie line flow, etc. in a power system by developing suitable norms for ease of interpretation. The TSA technique has the advantage that model complexity is not a limitation, and the sensitivities can be computed numerically. Suitable metrics are developed from these sensitivities. The TSA technique can be extended to do preventive rescheduling. A brief discussion of other applications of TSA in placement of distributed generation is indicated.

critical parameter computation↗
NASA NTRS2003

Ultraviolet and Visible Emission Mechanisms in Astrophysics

The project involved the study of ultraviolet (UV) and visible emission mechanisms in astrophysical and atmospheric environments. In many situations, the emission is a direct consequence of a charge transferring collision of an ion with a neutral with capture of an electron to an excited state of the product ion. The process is also important in establishing the ionization and thermal balance of an astrophysical plasma. As little of the necessary collision data are available, the main thrust of the project was the calculation of total and state-selective charge transfer cross sections and rate coefficients for a very large number of collision systems. The data was computed using modern explicit techniques including the molecular-orbital close-coupling (MOCC), classical trajectory Monte Carlo (CTMC), and continuum distorted wave (CDW) methods. Estimates were also made in some instances using the multichannel Landau-Zener (MCLZ) and classical over-the-barrier (COB) models. Much of the data which has been computed has been formatted for inclusion in a charge transfer database on the World Wide Web (cfadc.phy.ornl.gov/astro/ps/data/). A considerable amount of data has been generated during the lifetime of the grant. Some of it has not been analyzed, but it will be as soon as possible, the data placed on our website, and papers ultimately written.

Stancil, Phillip C.↗
NASA NTRS1986

Ascent/descent ancillary data production user's guide

The Ascent/Descent Ancillary Data Product, also called the A/D BET because it contains a Best Estimate of the Trajectory (BET), is a collection of trajectory, attitude, and atmospheric related parameters computed for the ascent and descent phases of each Shuttle Mission. These computations are executed shortly after the event in a post-flight environment. A collection of several routines including some stand-alone routines constitute what is called the Ascent/Descent Ancillary Data Production Program. A User's Guide for that program is given. It is intended to provide the reader with all the information necessary to generate an Ascent or a Descent Ancillary Data Product. It includes descriptions of the input data and output data for each routine, and contains explicit instructions on how to run each routine. A description of the final output product is given.

Brans, H. R.↗
NASA NTRS2010

Definition and Demonstration of a Methodology for Validating Aircraft Trajectory Predictors

This paper presents a new methodology for validating an aircraft trajectory predictor, inspired by the lessons learned from a number of field trials, flight tests and simulation experiments for the development of trajectory-predictor-based automation. The methodology introduces new techniques and a new multi-staged approach to reduce the effort in identifying and resolving validation failures, avoiding the potentially large costs associated with failures during a single-stage, pass/fail approach. As a case study, the validation effort performed by the Federal Aviation Administration for its En Route Automation Modernization (ERAM) system is analyzed to illustrate the real-world applicability of this methodology. During this validation effort, ERAM initially failed to achieve six of its eight requirements associated with trajectory prediction and conflict probe. The ERAM validation issues have since been addressed, but to illustrate how the methodology could have benefited the FAA effort, additional techniques are presented that could have been used to resolve some of these issues. Using data from the ERAM validation effort, it is demonstrated that these new techniques could have identified trajectory prediction error sources that contributed to several of the unmet ERAM requirements.

Vivona, Robert A.↗
DOE OSTI2017

Baryon properties in the relativistic quark model

Properties of heavy and strange baryons are investigated in the framework of the relativistic quark-diquark picture. It is based on the relativistic quark model of hadrons, which was previously successfully applied for the calculation of meson properties. It is assumed that two quarks in a baryon form a diquark and baryon is considered as the bound quark-diquark system. The relativistic effects and diquark internal structure are consistently taken into account. Calculations are performed up to rather high orbital and radial excitations of heavy and strange baryons. On this basis the Regge trajectories are constructed. The rates of semileptonic decays of heavy baryons are calculated. The obtained results agree well with available experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Transit timing variations for planets co-orbiting in the horseshoe regime

Although not yet detected, pairs of exoplanets in 1:1 mean motion resonance probably exist. Low eccentricity, near-planar orbits, which in the comoving frame follow horseshoe trajectories, are one of the possible stable configurations. Here we study transit timing variations (TTVs) produced by mutual gravitational interaction of planets in this orbital architecture, with the goal to develop methods that can be used to recognize this case in observational data. In particular, we use a semi-analytic model to derive parametric constraints that should facilitate data analysis. We show that characteristic traits of the TTVs can directly constrain the (1) ratio of planetary masses and (2) their total mass (divided by that of the central star) as a function of the minimum angular separation as seen from the star. In an ideal case, when transits of both planets are observed and well characterized, the minimum angular separation can also be inferred from the data. As a result, parameters derived from the observed transit timing series alone can directly provide both planetary masses scaled to the central star mass.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1996

Air Traffic Complexity Measurement Environment (ACME): Software User's Guide

A user's guide for the Air Traffic Complexity Measurement Environment (ACME) software is presented. The ACME consists of two major components, a complexity analysis tool and user interface. The Complexity Analysis Tool (CAT) analyzes complexity off-line, producing data files which may be examined interactively via the Complexity Data Analysis Tool (CDAT). The Complexity Analysis Tool is composed of three independently executing processes that communicate via PVM (Parallel Virtual Machine) and Unix sockets. The Runtime Data Management and Control process (RUNDMC) extracts flight plan and track information from a SAR input file, and sends the information to GARP (Generate Aircraft Routes Process) and CAT (Complexity Analysis Task). GARP in turn generates aircraft trajectories, which are utilized by CAT to calculate sector complexity. CAT writes flight plan, track and complexity data to an output file, which can be examined interactively. The Complexity Data Analysis Tool (CDAT) provides an interactive graphic environment for examining the complexity data produced by the Complexity Analysis Tool (CAT). CDAT can also play back track data extracted from System Analysis Recording (SAR) tapes. The CDAT user interface consists of a primary window, a controls window, and miscellaneous pop-ups. Aircraft track and position data is displayed in the main viewing area of the primary window. The controls window contains miscellaneous control and display items. Complexity data is displayed in pop-up windows. CDAT plays back sector complexity and aircraft track and position data as a function of time. Controls are provided to start and stop playback, adjust the playback rate, and reposition the display to a specified time.

Source record↗
DOE OSTI2022

Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference

Operator inference learns low-dimensional dynamical-system models with polynomial nonlinear terms from trajectories of high-dimensional physical systems (non-intrusive model reduction). Here, this work focuses on the large class of physical systems that can be well described by models with quadratic and cubic nonlinear terms and proposes a regularizer for operator inference that induces a stability bias onto learned models. The proposed regularizer is physics informed in the sense that it penalizes higher-order terms with large norms and so explicitly leverages the polynomial model form that is given by the underlying physics. This means that the proposed approach judiciously learns from data and physical insights combined, rather than from either data or physics alone. Additionally, a formulation of operator inference is proposed that enforces model constraints for preserving structure such as symmetry and definiteness in linear terms. Numerical results demonstrate that models learned with operator inference and the proposed regularizer and structure preservation are accurate and stable even in cases where using no regularization and Tikhonov regularization leads to models that are unstable.

97 MATHEMATICS AND COMPUTING↗