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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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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 NTRS2019

Modeling Uncertainty in Time and Fuel Benefit Estimation for TASAR Operational Evaluation

The Traffic Aware Strategic Aircrew Requests concept aims to reduce weather-induced delays, improve route efficiency, and efficiently share route modification options by combining onboard avionics data, Automatic Dependent Surveillance-Broadcast data, and broadband internet data to generate optimal, traffic-compatible trajectory changes based on real-time traffic and weather data. Time and fuel benefits due to use of the Traffic Aware Planner (TAP) software can be estimated by taking the difference in predicted flight time and fuel usage before and after a TAP-inspired trajectory change is completed. Although TAP’s optimization algorithm predicts flight and fuel usage based on the current flight route and weather data, it does not account for possible air traffic controller-initiated trajectory changes, reroutes due to sudden weather changes, or other pilot/controller actions that may occur during flight. This paper introduces an approach for quantifying the uncertainty in estimated time and fuel benefits.

Burris, Joseph↗
NASA NTRSDate not supplied

LOFTID Aeroshell Thermal Response Uncertainty Analysis Utilizing the End-to-End Monte Carlo Approach

A probabilistic thermal margin process has been performed to design the flexible thermal protection system (FTPS) and select entry trajectory constraints given an acceptable risk level for the Low-Earth Orbit Flight Test of and Inflatable Decelerator (LOFTID) project. Uncertainties exist in atmospheric entry aeroheating environments and the predicted thermal response of thermal protection system (TPS) material. Entry vehicle TPS is often over-sized to mitigate uncertainty by combining conservative bounding scenarios together. The probabilistic thermal margin process allows engineers to make informed aeroshell design, flight design, and FTPS performance risk trades while preventing excessive FTPS margin from being applied. This paper describes the uncertainty analysis methodology used to carry out a probabilistic thermal margin process used for LOFTID’s aeroshell and explains how the calculated probability of exceeding flight allowable temperatures is used to design the FTPS and establish nominal flight design constraints. This probabilistic thermal margin process had never been applied to entry, decent, and landing design for a flown entry vehicle and it is one of the LOFTID project’s goals to demonstrate its merits.

Steven Andrew Tobin↗
NASA NTRS2004

Wild2 approach maneuver strategy used for Stardust spacecraft (extended abstract)

Stardust, NASA's first dedicated sample return mission to a comet, successfully flew through the comet dust around Wold2 on January 2, 2004. The spacecraft flew within 236 km of the comet, meeting the mission requirement of 250+/- 50 km on flyby distance. Stardust collected dust particles and took several images of the comet while flying close to Wild2. The spacecraft will return to earth with the comet samples on January 15, 2006. To accomplish the above objective, a large Deep Space Maneuver (DSM#) was implemented during June 17 and 18, 2003 and a series of Trajectory Correction Maneuvers (TCMs) were also implemented during the 30 days prior to encounter. Both maneuver design and executions were influenced by number of factors including the small body ephemeris uncertainty, predictability of small forces arising from 3-axis attitude limit cycling and spacecraft slews. Maneuver design processes, including contingency plans, and maneuver performance characteristics, are discussed in this paper.

dust↗
NASA NTRS2013

Uncertainty Determination for Aeroheating in Uranus and Saturn Probe Entries by the Monte Carlo Method

The 2013-2022 Decaedal survey for planetary exploration has identified probe missions to Uranus and Saturn as high priorities. This work endeavors to examine the uncertainty for determining aeroheating in such entry environments. Representative entry trajectories are constructed using the TRAJ software. Flowfields at selected points on the trajectories are then computed using the Data Parallel Line Relaxation (DPLR) Computational Fluid Dynamics Code. A Monte Carlo study is performed on the DPLR input parameters to determine the uncertainty in the predicted aeroheating, and correlation coefficients are examined to identify which input parameters show the most influence on the uncertainty. A review of the present best practices for input parameters (e.g. transport coefficient and vibrational relaxation time) is also conducted. It is found that the 2(sigma) - uncertainty for heating on Uranus entry is no more than 2.1%, assuming an equilibrium catalytic wall, with the uncertainty being determined primarily by diffusion and H(sub 2) recombination rate within the boundary layer. However, if the wall is assumed to be partially or non-catalytic, this uncertainty may increase to as large as 18%. The catalytic wall model can contribute over 3x change in heat flux and a 20% variation in film coefficient. Therefore, coupled material response/fluid dynamic models are recommended for this problem. It was also found that much of this variability is artificially suppressed when a constant Schmidt number approach is implemented. Because the boundary layer is reacting, it is necessary to employ self-consistent effective binary diffusion to obtain a correct thermal transport solution. For Saturn entries, the 2(sigma) - uncertainty for convective heating was less than 3.7%. The major uncertainty driver was dependent on shock temperature/velocity, changing from boundary layer thermal conductivity to diffusivity and then to shock layer ionization rate as velocity increases. While radiative heating for Uranus entry was negligible, the nominal solution for Saturn computed up to 20% radiative heating at the highest velocity examined. The radiative heating followed a non-normal distribution, with up to a 3x variation in magnitude. This uncertainty is driven by the H(sub 2) dissociation rate, as H(sub 2) that persists in the hot non-equilibrium zone contributes significantly to radiation.

Palmer, Grant↗
NASA NTRS1978

Undisturbed heat transfer data analysis on the Space Shuttle External Tank Barrel Section

The paper analyzes the existing continuum undisturbed turbulent heat transfer data on smooth models of the Space Shuttle External Tank and develops a mathematical model for theoretical prediction of heat transfer rates on the External Tank Barrel Section. Experimental data have been obtained from various wind tunnels which simulated the continuum flow regime in the Shuttle flight trajectory. The model data have been compared with theoretical predictions using realistic flow fields and well-known empirical heat transfer relationships. The results show that the predictions are good to within the experimental uncertainties of the measured data.

Praharaj, S. C.↗
NASA NTRS1979

Undisturbed flowfield and turbulent heat-transfer analysis on the Space Shuttle external tank

The paper analyzes the existing undisturbed flowfield and turbulent heat-transfer data on smooth models of the Space Shuttle external tank and extends the mathematical model for theoretical calculation of heat-transfer rates presented in an earlier paper to include both the external tank barrel and ogive sections at zero and nonzero angles of attack. Experimental data have been obtained from various wind tunnels which simulated the continuum flow regime in the Shuttle flight trajectory. The model data have been compared with theoretical predictions using realistic flowfields and well-known empirical heat-transfer relationships. The results show that the predictions are good to within the experimental uncertainties of the measured data.

Praharaj, S. C.↗
NASA NTRS2009

Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

Consiglio, Maria C.↗
NASA NTRS2011

Precision Departure Release Capability (PDRC) Integration, Evaluation and Transition

NASA's Precision Departure Release Capability (PDRC) research activity is assessing the use of surface trajectory-based takeoff (OFF) time estimates for en route domain departure scheduling in Call For Release situations. Current aircraft departure release times computed by an Air Traffic Management decision support tool to meet Call For Release constraints are based on coarse estimates of aircraft OFF times. Uncertainty in OFF time estimates may result in missed opportunities to merge into an overhead stream and lost throughput. However, technology exists to improve OFF time estimates by using more accurate aircraft trajectory predictions available in NextGen airport surface management decision support tools. PDRC findings are expected to be broadly applicable to NextGen integrated arrival/departure/surface implementations. For concept development and evaluation purposes this research activity integrates NASA's Surface Management System (SMS) OFF time prediction capabilities with Traffic Management Advisor (TMA) departure scheduling functions. PDRC field evaluations are being conducted at the North Texas (NTX) Research Station. The NASA/FAA Integrated Arrival/Departure/Surface Research Transition Team is using PDRC as a pathfinder for developing technology transfer mechanisms and procedures.

Engelland, Shawn A.↗
NASA NTRS2011

Base Flow Investigation of the Apollo AS-202 Command Module

In recent years, both Europe and the US are developing hypersonic research and operational vehicles. These include (re)entry capsules (both ballistic and lifting) and lifting bodies such as ExoMars, EXPERT, ARV, CEV and IXV. The research programs are meant to enable technology and engineering capabilities to support during the next decade the development of affordable (possibly reusable) space transportation systems as well as hypersonic weapons systems for time critical targets. These programs have a broad range of goals, ranging from the qualification of thermal protection systems, the assessment of RCS performances, the development of GNC algorithms, to the full demonstration of the performance and operability of the integrated vehicles. Since the aerothermodynamic characteristics influence nearly all elements of the vehicle design, the accurate prediction of the aerothermal environment is a prerequisite for the design of efficient hypersonic systems. Significant uncertainties in the prediction of the hypersonic aerodynamic and the aerothermal loads can lead to conservative margins in the design of the vehicle including its Outer Mould Line (OML), thermal protection system, structure, and required control system robustness. The current level of aerothermal prediction uncertainties results therefore in reduced vehicle performances (e.g., sub-optimal payload to mass ratio, increased operational constraints). On the other hand, present computational capabilities enable the simulation of three dimensional flow fields with complex thermo-chemical models over complete trajectories and ease the validation of these tools by, e.g., reconstruction of detailed wind tunnel tests performed under identified and controlled conditions (flow properties and vehicle attitude in particular). These controlled conditions are typically difficult to achieve when performing in flight measurements which in turn results in large associated measurement uncertainties. Similar problems arise when attempting to rebuild measurements performed in "hot" ground facilities, where the difficulty level is increased by the addition of the free-flow characterization itself. The implementation of ever more sophisticated thermochemical models is no obvious cure to the aforementioned problems since their effect is often overwhelmed by the large measurement uncertainties incurred in both flight and ground high enthalpy facilities. Concurrent to the previous considerations, a major contributor to the overall vehicle mass of re-entry vehicles is the afterbody thermal protection system. This is due to the large acreage (equal or bigger than that of the forebody) to be protected. The present predictive capabilities for base flows are comparatively lower than those for windward flowfields and offer therefore a substantial potential for improving the design of future re-entry vehicles. To that end, it is essential to address the accuracy of high fidelity CFD tools exercised in the US and EU, which motivates a thorough investigation of the present status of hypersonic flight afterbody heating. This paper addresses the predictive capabilities of after body flow fields of re-entry vehicles investigated in the frame of the NATO/RTO - RTG-043 Task Group and is structured as follows: First, the verification of base flow topologies on the basis of available wind-tunnel results performed under controlled supersonic conditions (i.e., cold flows devoid of reactive effects) is performed. Such tests address the detailed characterization of the base flow with particular emphasis on separation/reattachment and their relation to Mach number effects. The tests have been performed on an Apollo-like re-entry capsule configuration. Second, the tools validated in the frame of the previous effort are exercised and appraised against flight-test data collected during the Apollo AS-202 re-entry.

Walpot, Louis M. G.↗
NASA NTRS2018

The Effects of Uncertainty in Initial CME Input Parameters on Deflection, Rotation, Bz, and Arrival Time Predictions

Understanding the effects of coronal mass ejections (CMEs) requires knowing if and when they will impact and their properties upon impact. Of particular importance is the strength of a CME's southward magnetic field component (Bz ). Kay et al. (2013, https://doi:10.1088/0004-637X/775/1/5, 2015, https://doi:10.1088/948 0004-637X/805/2/168) have shown that the simplified analytic model Forecasting a CME's Altered Trajectory (ForeCAT) can reproduce the deflection and rotation of CMEs. Kay, Gopalswamy, Reinard, and Opher (2017, https://doi.org/10.3847/1538-4357/835/2/117) introduced ForeCAT In situ Data Observer, which uses ForeCAT results to simulate magnetic field profiles. ForeCAT In situ Data Observer reproduces the in situ observations on roughly hourly time scales, suggesting that these models could be extremely useful for predictions of Bz . However, as with all models, both models are sensitive to their input parameters, which may not be precisely known for predictions. We explore this sensitivity using ensembles having small changes in the initial latitude, longitude, and orientation of the erupting CME. We explore the effects of different background magnetic field models and find that the changes in deflection and rotation resulting from the uncertainty in the initial parameters tend to exceed the changes from dierent magnetic backgrounds. The range in the in situ proles tends to scale with the range in the deflection and rotation. We also consider a simple arrival time model using ForeCAT results and nd an average absolute error of only 3 hr. We show that an uncertainty in the CME position of 8.1 ± 6.9 leads to variations of 6 hr in the arrival time. This measure depends strongly on the location of impact within the CME with the arrival time changing less for impacts near the nose.

Kay, Christina D.↗
NASA NTRS1989

Aerobrake heating rate sensitivity study for the Aeroassist Flight Experiment (AFE)

The sensitivities associated with the prediction of the Aeroassist Flight Experiment (AFE) vehicle's aerothermodynamic environment are presently evaluated in order to assess the heating-rate uncertainties of the AFE's aerobrake component, as a function of time in various trajectories, and as a function of distance around the aerobrake. Relative importance is evaluated by means of the Boundary Layer Integral Matrix Procedure for such areas of uncertainty as the trajectory parameters, the catalycity of the thermal-protection tiles, the nose radius variation/surface pressure distribution, and viscous interaction effects.

Rochelle, W. C.↗
NASA NTRS2011

Impact of Tactical and Strategic Weather Avoidance on Separation Assurance

The ability to keep flights away from weather hazards while maintaining aircraft-to-aircraft separation is critically important. The Advanced Airspace Concept is an automation concept that implements a ground-based strategic conflict resolution algorithm for management of aircraft separation. The impact of dynamic and uncertain weather avoidance on this concept is investigated. A strategic weather rerouting system is integrated with the Advanced Airspace Concept, which also provides a tactical weather avoidance algorithm, in a fast time simulation of the Air Transportation System. Strategic weather rerouting is used to plan routes around weather in the 20 minute to two-hour time horizon. To address forecast uncertainty, flight routes are revised at 15 minute intervals. Tactical weather avoidance is used for short term trajectory adjustments (30 minute planning horizon) that are updated every minute to address any weather conflicts (instances where aircraft are predicted to pass through weather cells) that are left unresolved by strategic weather rerouting. The fast time simulation is used to assess the impact of tactical weather avoidance on the performance of automated conflict resolution as well as the impact of strategic weather rerouting on both conflict resolution and tactical weather avoidance. The results demonstrate that both tactical weather avoidance and strategic weather rerouting increase the algorithm complexity required to find aircraft conflict resolutions. Results also demonstrate that tactical weather avoidance is prone to higher airborne delay than strategic weather rerouting. Adding strategic weather rerouting to tactical weather avoidance reduces total airborne delays for the reported scenario by 18% and reduces the number of remaining weather violations by 13%. Finally, two features are identified that have proven important for strategic weather rerouting to realize these benefits; namely, the ability to revise reroutes and the use of maneuvers that start far ahead of encountering a weather cell when rerouting around weather.

Refai, Mohamad S.↗
NASA NTRS1986

ICE navigation support

The International Cometary Explorer (ICE) encounter with Comet Giacobini-Zinner took place 7 years after the spacecraft's original launch on 12 August 1978 as the International Sun Earth Explorer 3 (ISEE-3), part of a three-spacecraft project to study the interaction between the solar wind and the Earth's magnetosphere. Transfer to an interplanetary trajectory was performed via a 119-km-altitute, gravity-assist, lunar swingby on December 1983. Navigation support during interplanetary cruise and comet encounter was provided by orbit determination utilizing radio metric data from the DSN 64-meter antennas in Goldstone, California and Madrid, Spain. Orbit solutions yielding predictions of 50-km geocentric delivery accuracy in the target aim plane were achieved during interplanetary cruise and at comet encounter using 6-to-12-week data arcs between periodic attitude-change maneuvers. One-sigma two-way range and range rate residuals were consistently 40 meters and 0.2 mm/s or better, respectively. Non-gravitational forces affected the comet's motion during late August and early September 1985 and caused a 2300-km shift in the orbit of the comet relative to the spacecraft. This necessitated a final ICE orbit trim maneuver 3 days prior to encounter. Near-real-time assessment of two-way 2-GHz (S-band) Doppler pseudo-residuals during the June and July 1985 trajectory change maneuvers aided in calibration of the spacecraft's thrusters in preparation for this final critical maneuver. Post-flight analysis indicates tail centerline passage was achieved within 10 seconds of the predicted time and geocentric position uncertainty at encounter was less than 40 km.

Efron, L.↗
NASA NTRS2017

Orbit Determination Covariance Analyses for the Parker Solar Probe Mission

This paper details pre-launch navigation covariance analyses for the Parker Solar Probe mission. Baseline models and error assumptions are outlined. The results demonstrate how navigation will satisfy requirements and are used to define operational plans. A few sensitivities are identified and the accompanying investigations are described. Predicted state uncertainty results show that most requirements are met with substantial margin. Moreover, navigation sensitivities may be accommodated operationally and this has been incorporated into project planning. Detailed results are presented only for select launch dates, however twenty unique trajectories (one per launch opportunity) have been assessed.

Jones, Drew Ryan↗
NASA NTRS2011

Use of Smoothed Measured Winds to Predict and Assess Launch Environments

Since many of the larger launch vehicles are operated near their design limits during the ascent phase of flight to optimize payload to orbit, it often becomes necessary to verify that the vehicle will remain within certification limits during the ascent phase as part of the go/no-go review made prior to launch. This paper describes the approach used to predict Ares I-X launch vehicle structural air loads and controllability prior to launch which represents a distinct departure from the methodology of the Space Shuttle and Evolved Expendable Launch Vehicle (EELV) programs. Protection for uncertainty of key environment and trajectory parameters is added to the nominal assessment of launch capability to ensure that critical launch trajectory variables would be within the integrated vehicle certification envelopes. This process was applied by the launch team as a key element of the launch day go/no-go recommendation. Pre-launch assessments of vehicle launch capability for NASA's Space Shuttle and the EELV heavy lift versions require the use of a high-resolution wind profile measurements, which have relatively small sample size compared with low-resolution profile databases (which include low-resolution balloons and radar wind profilers). The approach described in this paper has the potential to allow the pre-launch assessment team to use larger samples of wind measurements from low-resolution wind profile databases that will improve the accuracy of pre-launch assessments of launch availability with no degradation of mission assurance or launch safety.

Cordova, Henry S.↗