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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Applications of Displacement Transfer Functions to Deformed Shape Predictions of the GIII Swept-Wing Structure

The displacement transfer functions (DTFs) were applied to the GIII swept wing for the deformed shape prediction. The calculated deformed shapes are very close to the correlated finite element results as well as the measured data. The convergence study showed that using 17 strain stations, the wing-tip displacement prediction error was 1.6 percent, and that there is no need to use a large number of strain stations for G-III wing shape predictions.

on board string sensing system↗
NASA NTRS2016

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

trajectory prediction uncertainty↗
NASA NTRS2015

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors: An Interrupted Time-Series Analysis of Controller Behavior

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASAs Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlantas Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the studys trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 20-knot over-predictions and 20-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

human-automation interaction↗
NASA NTRSDate not supplied

USM3D Simulations for the Third Sonic Boom Prediction Workshop (SBPW-3)

The NASA USM3D flow solver was used to compute test cases for the Third AIAA Sonic Boom Prediction Workshop (SBPW3). The test cases include a nearfield biconvex shock-plume interaction wind tunnel model, and the C608 Low Boom Flight Demonstrator. Numerical simulations were conducted on the mixed-element and tetrahedral grids provided by the workshop committee, as well as a family of grids generated by an in-house approach for sonic boom analyses known as BoomGrid. The near-field pressure signatures were extracted, propagated to the ground and the perceived loudness levels on the ground were computed. The USM3D near-field pressure signatures, corresponding ground signatures, and loudness levels on the ground are compared with that of mean values from other workshop participants. The effect of three flux-limiters on the accuracy of near-field pressure signatures prediction was investigated and results are compared with that of mean values from other workshop participants. The effect of using wall function grids in accurately predicting near-field pressure signatures was also evaluated.

Supersonics↗
NASA NTRS2021

The Efficacy of Seasonal Terrestrial Water Storage Forecasts for Predicting Vegetation Activity Over Africa

Terrestrial water storage (TWS) provides important information on terrestrial hydroclimate and may have value for seasonal forecasting because of its strong persistence. We use the NASA Hydrological Forecast and Analysis System (NHyFAS) to investigate TWS forecast skill over Africa and assess its value for predicting vegetation activity from satellite estimates of leaf area index (LAI). Forecast skill is high over East and Southern Africa, extending up to 3–6 months in some cases, with more modest skill over West Africa. Highest skill generally occurs during the dry season or beginning of the wet season when TWS anomalies from the previous wet season are most likely to carry forward in time. In East Africa, this occurs prior to and during the transition into the spring “Long Rains” from January–March, while in Southern Africa this period of highest skill starts at the beginning of the dry season in April and extends through to the start of the wet season in October. TWS is highly and positively correlated with LAI, and a logistic regression model shows high cross-validation skill in predicting above or below normal LAI using TWS. Combining the LAI regression model with the NHyFAS forecasts, 1-month lead LAI predictions have high accuracy over East and Southern Africa, with reduced but significant skill at 3-month leads over smaller sub-regions. This highlights the potential value of TWS as an additional source of information for seasonal forecasts over Africa, with direct applications to some of the most vulnerable agricultural regions on the continent.

Terrestrial water shortage↗
NASA NTRS2022

USM3D Simulations for the Third AIAA Sonic Boom Prediction Workshop

The NASA USM3D flow solver was used to compute test cases for the Third AIAA Sonic Boom Prediction Workshop (SBPW3). The test cases included a nearfield biconvex shock-plume interaction wind tunnel model and the C608 Low Boom Flight Demonstrator. Numerical simulations were conducted on the mixed-element and tetrahedral grids provided by the workshop committee, as well as a family of grids generated by an in-house approach known as BoomGrid. The nearfield pressure signatures were extracted and propagated to the ground, and the perceived loudness levels on the ground were computed. The USM3D nearfield pressure signatures, corresponding ground signatures, and loudness levels on the ground were compared with that of mean values from other workshop participants. The effect of three flux-limiters on the accuracy of nearfield pressure signature prediction was investigated and results were compared with that of mean values from other workshop participants. The effect of using wall-function models for predicting nearfield pressure signatures was also evaluated. Results showed that the overpressure signatures extracted from the wall-modeled simulations and the wall-resolved simulations are in good agreement. The use of wall functions (wall-modeled simulations) allowed for approximately 23% savings in the time to solution and yielded comparable perceived loudness levels on the ground to the wall-resolved Reynolds-averaged Navier Stokes simulations.

Supersonics↗
NASA NTRSDate not supplied

Prediction of Quadrotor Acoustics Using RVLT Toolchain

The NASA Revolutionary Vertical Lift Technology (RVLT) Project toolchain is used to predict the acoustics of the NASA 6-passenger quadrotor concept vehicle. A qualitative study of the blade vertical loading to understand noise trends with tip speed and number of blades was performed. Trends of the individual rotor noise sources (thickness, loading, and broadband) are studied. Noise is predicted and analyzed for three flight conditions: approach (6-deg descent), level flight flyover, and takeoff. Three quadrotor designs are considered: tip speed=700 ft/sec, 3 blades (“700/3”), “550/3”, and “375/7”. The qualitative study shows that during approach multiple, strong BVIs occur on the advancing and retreating sides for “700/3” and “550/3”, but for “375/7” only weak BVIs are present. Consistent with this BVI scenario, the quadrotor noise results show that “700/3” has the highest loading noise (and EPNL) and “375/7” the lowest loading noise (and EPNL), with “550/3” falling in between. Broadband noise during approach and flyover is roughly the same for all three designs. Takeoff broadband noise is much lower, especially for “375/7”. The bulk of the results have been obtained with a rigid uniform blade model, with a flap hinge and a pitch bearing. For “550/3”, noise predictions with elastic nonuniform blades have been initiated and are ongoing.

Quadrotor↗
NASA NTRS2022

An ODE-Fitting Approach to Estimate Critical Aircraft Performance Parameters for Trajectory Prediction

Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM) parameters, but some or all of these parameters might not be readily available. In particular, the three critical parameters required for trajectory prediction are the thrust setting, drag coefficients, and takeoff weight of the aircraft. Unfortunately, these parameters are coupled and appear together in physics-based kinetic models. Past approaches utilize data from a specific phase of flight (climb, level flight or descent), where one or more of the parameters are assumed to be known and estimate the remaining unknown parameters. This approach introduces bias/errors and also does not extend to scenarios where all of the above parameters are not known with sufficient accuracy. This paper is the first of its kind to propose a generalized framework for simultaneous estimation of all three critical APM parameters (thrust, drag, and mass). The proposed approach utilizes data from both the climb and descent phases and fits the ordinary differential equation for altitude in each phase using historical trajectory data available from radar tracks or ADS-B. The approach yields a set of optimized APM parameters that are best suited to fit each historical flight record. The methodology is applied on on sample flights from three different aircraft types, and the results demonstrate low fit error and consequently will yield a high level of prediction accuracy.

trajectory prediction, aircraft performance model,↗
NASA NTRSDate not supplied

An ODE-Fitting Approach to Estimate Critical Aircraft Performance Parameters for Trajectory Prediction

Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM) parameters, but some or all of these parameters might not be readily available. In particular, the three critical parameters required for trajectory prediction are the thrust setting, drag coefficients, and takeoff weight of the aircraft. Unfortunately, these parameters are coupled and appear together in physics-based kinetic models. Past approaches utilize data from a specific phase of flight (climb, level flight or descent), where one or more of the parameters are assumed to be known and estimate the remaining unknown parameters. This approach introduces bias/errors and also does not extend to scenarios where all of the above parameters are not known with sufficient accuracy. This paper is the first of its kind to propose a generalized framework for simultaneous estimation of all three critical APM parameters (thrust, drag, and mass). The proposed approach utilizes data from both the climb and descent phases and fits the ordinary differential equation for altitude in each phase using historical trajectory data available from radar tracks or ADS-B. The approach yields a set of optimized APM parameters that are best suited to fit each historical flight record. The methodology is applied on on sample flights from three different aircraft types, and the results demonstrate low fit error and consequently will yield a high level of prediction accuracy.

trajectory prediction↗
NASA NTRSDate not supplied

Comparisons of Impedance Prediction Models for Perforate-over-Honeycomb Liners

A large dataset is used to evaluate the efficacy of multiple impedance prediction models for perforate-over-honeycomb liners. Two-factorial analysis is used to explore the relative importance of the key parameters used in these models. Tests are conducted in the NASALangley Normal Incidence Tube and Grazing Flow Impedance Tube with over eighty perforate facesheets at multiple source sound pressure levels, Mach numbers and frequencies. Each prediction model is then compared with this dataset to determine how well each method predicts the measured data. Finally, an optimizer is used to further improve the ability of one of these models to reproduce the measured results.

acoustic↗
NASA NTRSDate not supplied

Comparisons of Impedance Prediction Models for Perforate-over-Honeycomb Liners

A large dataset is used to evaluate the efficacy of multiple impedance prediction models for perforate-over-honeycomb liners. Two-factorial analysis is used to explore the relative importance of the key parameters used in these models. Tests are conducted in the NASALangley Normal Incidence Tube and Grazing Flow Impedance Tube with over eighty perforate facesheets at multiple source sound pressure levels, Mach numbers and frequencies. Each prediction model is then compared with this dataset to determine how well each method predicts the measured data. Finally, an optimizer is used to further improve the ability of one of these models to reproduce the measured results.

acoustic↗
NASA NTRS2023

New Transient Finite Energy Shock Prediction Methodology

Shock prediction is one of the top loads and dynamics discipline technical challenges identified within NASA and industry programs and projects. The physics-based Transient Finite Energy (TFE) shock prediction methodology has been developed and compared favorably against test results. TFE can provide another approach to develop predictions of shock response spectra (SRS) for use in the analysis of structural margins.

NESC Technical Bulletin No. 23-03↗
NASA NTRSDate not supplied

Best Practices for Predicting Acoustics of a Single Rotor Using the NASA RVLT Conceptual Design Toolchain

To facilitate the development of the Urban Air Mobility (UAM) market, the NASA Revolutionary Vertical Lift Technology Project has created the Conceptual Design Toolchain, a suite of tools developed and/or selected to assist rotorcraft designers in all stages of rotorcraft design. Of particular interest to the UAM noise community are the following two steps in this toolchain: comprehensive analysis and acoustic prediction. Since the UAM application is relatively new, there is a need for a systematic study on how best to utilize these codes. To this end, the current study documents best practices for using the comprehensive analysis codes, CAMRAD II and CHARM, along with the acoustic code AARON. Two single rotors are considered: i) a simple rotor and ii) a rotor that is more exemplary of what UAM designers might use. Best practices are presented for the prediction of both tonal and broadband self-noise, along with the corresponding results. The goal is to provide conceptual designers the tools to conduct accurate noise prediction using the RVLT Conceptual Design Toolchain.

Acoustics↗
NASA NTRSDate not supplied

Acoustic Predictions of the Moog S-250 in Hover

Acoustic predictions were made on the Moog S-250 vehicle to assess one of NASA’s mid-fidelity prediction toolchains for Urban Air Mobility-type vehicles. Experimental data from a 60-foot hover test is used for comparison. The S-250 is an RPM-controlled vehicle in a quadcopter-type configuration with four sets of contra-rotating rotors and powered by eight independently controlled electric motors. The same type of rotor blade used on the S-250 was 3D laser scanned to enable the development of custom-made airfoil tables and more accurate blade loadings. Noise predictions at the first couple of blade-pass frequencies indicate a good comparison to experimental data.

Acoustic prediction↗
NASA NTRSDate not supplied

Results of the NASA Prediction Uncertainty Reduction Tech Challenge

In January 2021 the Advanced Air Vehicles Program approved a new Tech Challenge (TC) to be run out of the Commercial Supersonic Technology (CST) Project. The objective of the TC was to bring uncertainties in the empirical noise modeling for civilian supersonic aircraft into the same range as that of conventional aircraft. The TC goal statement was to “Produce data and demonstrate tools that reduce the uncertainty in predicting Landing & Takeoff Noise levels of supersonic-relevant designs by 5 EPNdB and are ready for use in studies to inform FAA rule-making.” To make the required improvements in noise prediction methods for supersonic aircraft, NASA decided to validate and use high-fidelity numerical simulations to acquire the needed noise data on supersonic propulsion configurations. High-fidelity component designs were developed, such as a two-stage propulsor behind a supersonic inlet designed by General Electric Aviation and variable area exhaust systems using input from recent contracts with GE and Rolls Royce. A noise database was generated as a function of geometric and flow parameters, providing corrections to the empirical noise models and added new input variables to describe the complexities created by the supersonic-specific design features. Statistically, the new models were able to predict the acoustic impact of supersonic-specific features, the reduction in uncertainty being reduced from the baseline 7.8 EPNdB at the beginning of the TC to 2.0 EPNdB at the end.

noise prediction↗
NASA NTRS2025

PSE-Based Aerodynamic Flow Transition Prediction Using Automated Unstructured CFD Integration

Accurate, robust, and efficient prediction of transition in viscous flows is a significant challenge in computational fluid dynamics. We present a coupled, high-fidelity, iterative approach that leverages the FUN3D flow solver and the LASTRAC stability code to predict transition in low-disturbance environments, initiated by the linear growth of boundary-layer instability modes. Our method integrates the ability of FUN3D to compute mixed laminar-transitional-turbulent mean flows via transition-sensitized Reynolds-Averaged Navier-Stokes equations with the ability of LASTRAC to perform linear stability analysis, all within an automated framework that requires no intermediate user involvement. Unlike conventional frameworks that rely on classical stability theory or reduced-order metamodels, our approach employs the parabolized stability equations to provide more accurate and reliable estimates of disturbance growth for multiple instability mechanisms, including Tollmien-Schlichting, Kelvin-Helmholtz, and crossflow modes. By accounting for the effects of mean-flow nonparallelism as well as the surface curvature, this approach lays the foundation for improved N-factor correlations for transition onset prediction in a broad class of flows. We apply this method to three distinct flow configurations: 1) flow over a zero-pressure-gradient flat plate, 2) the NLF-0416 airfoil with both natural and separation-induced transitions, and 3) a 6:1 prolate spheroid, where transition is primarily driven by crossflow instability. For the two-dimensional cases, a formulated intermittency distribution is used to model the transition zone in between the laminar and fully turbulent flows. The results include comparisons with experimental measurements, similar numerical approaches, and transport-equations-based models, demonstrating good agreement in surface pressure coefficients, transition onset locations, and skin-friction coefficients for all three configurations. Besides contributing a couple of new insights into boundary-layer transition in these canonical cases, this study provides a powerful tool for transition modeling in both research and design applications in aerodynamics.

Transition Prediction↗
NASA NTRS1969

ABTRAJ on-site tracking prediction program

Computer program, ABTRAJ, provides Deep Space Network tracking stations with the capability of generating spacecraft predictions with on-site computers. The program is comprised of two major sections - the main prediction portion and a trajectory subroutine which spans the desired predict interval with spacecraft ephemeris data written on magnetic tapes.

Berman, A. L.↗
NASA NTRS1970

Analytical prediction of reverse buckling pressure for thin shells

Analytical technique is developed for prediction of reverse buckling in thin curved shells. Test data indicate technique predicts actual reverse buckling pressure within 10 percent, and should be useful for analytical prediction of reversed condition failure for problems such as explosive decomposition through vacuum failure.

Martindale, D. L.↗