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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Nonlinear least squares - An aid to thermal property determination.

Nonlinear least squares techniques can be used to determine effective thermal conductivity values from experimental data. Comparisons between measured and predicted conductivity values indicate that the analytically determined values can be used with confidence in performing thermal protection system analyses. A study was performed to compare the relative efficiencies of different minimizing techniques; the method of Peckham was the most efficient.

Curry, D. M.↗
NASA NTRS1973

Theoretical studies of tone noise from a fan rotor

An analytical study was made of some possible rotor alone noise sources of dipole, quadrapole and monopole characters which generate discrete tone noise. Particular emphasis is given to the tone noise caused by fan inlet flow distortion and turbulence. Analytical models are developed to allow prediction of absolute levels. Experimental data measured on a small scale fan is presented which indicates inlet turbulence interaction with a fan rotor can be a source of tone noise. Predicted and measured tone noise for the small scale rotor are shown to be in reasonable agreement.

Rao, G. V. R.↗
NASA NTRS1973

Radiated sound field measurements from an annular flow duct facility

A series of measured radiated field patterns correlated with defined in-duct conditions is presented, along with a second series of radiation measurements for multiple mode propagation, with individual mode amplitudes and phases at duct termination as well as with angular positions of higher-order stationary duct modes relative to the plane of the radiated field measurement. Though incomplete, these experimental data should prove useful for comparisons with theoretical predictions in testing analytical procedures and prediction techniques.

Plumblee, H. E.↗
NASA NTRS1980

Effect of bipropellant plume exhaust effluents on spaceborne optical instruments

Analytical tools together with a good data base are necessary to predict the transport of plume contaminants and their effects on spacecraft surfaces. The present paper describes an assessment of bipropellant thrusters, the production and transport of plume contaminants from these thrusters, and the use of the JPL contamination analysis program to assess the effects of plume contamination on the Galileo spacecraft. It is shown that, in the case of the Galileo mission, contamination from the liquid engines has been effectively reduced to nothing by the use of predictive tools. Plume shields together with precise scan platform stowage have been designed to protect the optical instruments.

Maag, C. R.↗
NASA NTRS1981

The viscoelastic response of a graphite/epoxy laminate

An accelerated characterization procedure has been developed for time-dependent compliances and strengths of resin-matrix composites. The procedure, which is based on a time-temperature-stress superposition principle, is applied to a graphite/epoxy laminate T300/934. Creep rupture analytical models are discussed, and model predictions are compared with experimental data. Master curves for the creep compliances are given.

Brinson, H. F.↗
NASA NTRS1987

Cellular automatons applied to gas dynamic problems

This paper compares the results of a relatively new computational fluid dynamics method, cellular automatons, with experimental data and analytical results. This technique has been shown to qualitatively predict fluidlike behavior; however, there have been few published comparisons with experiment or other theories. Comparisons are made for a one-dimensional supersonic piston problem, Stokes first problem, and the flow past a normal flat plate. These comparisons are used to assess the ability of the method to accurately model fluid dynamic behavior and to point out its limitations. Reasonable results were obtained for all three test cases, but the fundamental limitations of cellular automatons are numerous. It may be misleading, at this time, to say that cellular automatons are a computationally efficient technique. Other methods, based on continuum or kinetic theory, would also be very efficient if as little of the physics were included.

Long, Lyle N.↗
NASA NTRS1988

Analytical ice shape predictions for flight in natural icing conditions

LEWICE is an analytical ice prediction code that has been evaluated against icing tunnel data, but on a more limited basis against flight data. Ice shapes predicted by LEWICE is compared with experimental ice shapes accreted on the NASA Lewis Icing Research Aircraft. The flight data selected for comparison includes liquid water content recorded using a hot wire device and droplet distribution data from a laser spectrometer; the ice shape is recorded using stereo photography. The main findings are as follows: (1) An equivalent sand grain roughness correlation different from that used for LEWICE tunnel comparisons must be employed to obtain satisfactory results for flight; (2) Using this correlation and making no other changes in the code, the comparisons to ice shapes accreted in flight are in general as good as the comparisons to ice shapes accreted in the tunnel (as in the case of tunnel ice shapes, agreement is least reliable for large glaze ice shapes at high angles of attack); (3) In some cases comparisons can be somewhat improved by utilizing the code so as to take account of the variation of parameters such as liquid water content, which may vary significantly in flight.

Berkowitz, Brian M.↗
NASA NTRS1993

Acoustic radiation damping of flat rectangular plates subjected to subsonic flows

The acoustic radiation damping for various isotropic and laminated composite plates and semi-infinite strips subjected to a uniform, subsonic and steady flow has been predicted. The predictions are based on the linear vibration of a flat plate. The fluid loading is characterized as the perturbation pressure derived from the linearized Bernoulli and continuity equations. Parameters varied in the analysis include Mach number, mode number and plate size, aspect ratio and mass. The predictions are compared with existing theoretical results and experimental data. The analytical results show that the fluid loading can significantly affect realistic plate responses. Generally, graphite/epoxy and carbon/carbon plates have higher acoustic radiation damping values than similar aluminum plates, except near plate divergence conditions resulting from aeroelastic instability. Universal curves are presented where the acoustic radiation damping normalized by the mass ratio is a linear function of the reduced frequency. A separate curve is required for each Mach number and plate aspect ratio. In addition, acoustic radiation damping values can be greater than or equal to the structural component of the modal critical damping ratio (assumed as 0.01) for the higher subsonic Mach numbers. New experimental data were acquired for comparison with the analytical results.

Lyle, Karen Heitman↗
NASA NTRS2001

Insights into Airframe Aerodynamics and Rotor-on-Wing Interactions from a 0.25-Scale Tiltrotor Wind Tunnel Model

A recent experimental investigation into tiltrotor aerodynamics and acoustics has resulted in the acquisition of a set of data related to tiltrotor airframe aerodynamics and rotor and wing interactional aerodynamics. This work was conducted in the National Full-scale Aerodynamics Complex's (NFAC) 40-by-80 Foot Wind Tunnel, at NASA Ames Research Center, on the Full-Span Tilt Rotor Aeroacoustic Model (TRAM). The full-span TRAM wind tunnel test stand is nominally based on a quarter-scale representation of the V-22 aircraft. The data acquired will enable the refinement of analytical tools for the prediction of tiltrotor aeromechanics and aeroacoustics.

Young, L. A.↗
NASA NTRS2011

Infrared Imagery of Solid Rocket Exhaust Plumes

The Ares I Scale Model Acoustic Test program consisted of a series of 18 solid rocket motor static firings, simulating the liftoff conditions of the Ares I five-segment Reusable Solid Rocket Motor Vehicle. Primary test objectives included acquiring acoustic and pressure data which will be used to validate analytical models for the prediction of Ares 1 liftoff acoustics and ignition overpressure environments. The test article consisted of a 5% scale Ares I vehicle and launch tower mounted on the Mobile Launch Pad. The testing also incorporated several Water Sound Suppression Systems. Infrared imagery was employed during the solid rocket testing to support the validation or improvement of analytical models, and identify corollaries between rocket plume size or shape and the accompanying measured level of noise suppression obtained by water sound suppression systems.

Moran, Robert P.↗
NASA NTRS2013

LADEE Propulsion System Cold Flow Test

Lunar Atmosphere and Dust Environment Explorer (LADEE) is a NASA mission that will orbit the Moon. Its main objective is to characterize the atmosphere and lunar dust environment. The spacecraft development is being led by NASA Ames Research Center and scheduled for launch in 2013. The LADEE spacecraft will be operated with a bi-propellant hypergolic propulsion system using MMH and NTO as the fuel and oxidizer, respectively. The propulsion system utilizes flight-proven hardware on major components. The propulsion layout is composed of one 100-lbf main thruster and four 5-lbf RCS thrusters. The propellants are stored in four tanks (two parallel-connected tanks per propellant component). The propellants will be pressurized by regulated helium. A simulated propulsion system has been built for conducting cold flow test series to characterize the transient fluid flow of the propulsion system feed lines and to verify the critical operation modes, such as system priming, waterhammer, and crucial mission duty cycles. Propellant drainage differential between propellant tanks will also be assessed. Since the oxidizer feed line system has a higher flow demand than the fuel system does, the cold flow test focuses on the oxidizer system. The objective of the cold flow test is to simulate the LADEE propulsion fluid flow operation through water cold flow test and to obtain data for anchoring analytical models. The models will be used to predict the transient and steady state flow behaviors in the actual flight operations. The test activities, including the simulated propulsion test article, cold flow test, and analytical modeling, are being performed at NASA Marshall Space Flight Center. At the time of the abstract submission, the test article checkout is being performed. The test series will be completed by November, 2012

Williams, Jonathan Hunter↗
NASA NTRS2015

Resource Prospector Propulsion System Cold Flow Testing

Resource Prospector (RP) is a NASA mission being led by NASA Ames Research Center with current plans to deliver a scientific payload package aboard a rover to the lunar surface. As part of an early risk reduction activity, Marshall Space Flight Center (MSFC) and Johnson Space Flight Center (JSC) have jointly developed a government-version concept of a lunar lander for the mission. The spacecraft consists of two parts, the lander and the rover which carries the scientific instruments. The lander holds the rover during launch, cruise, and landing on the surface. Following terminal descent and landing the lander portion of the spacecraft become dormant after the rover embarks on the science mission. The lander will be equipped with a propulsion system for lunar descent and landing, as well as trajectory correction and attitude control maneuvers during transit to the moon. Hypergolic propellants monomethyl hydrazine and nitrogen tetroxide will be used to fuel sixteen 70-lbf descent thrusters and twelve 5-lbf attitude control thrusters. A total of four metal-diaphragm tanks, two per propellant, will be used along with a high-pressure composite-overwrapped pressure vessel for the helium pressurant gas. Many of the major propulsion system components are heritage missile hardware obtained by NASA from the Air Force. In parallel with the flight system design activities, a simulated propulsion system based on flight drawings was built for conducting a series of water flow tests to characterize the transient fluid flow of the propulsion system feed lines and to verify the critical operation modes such as system priming, waterhammer, and crucial mission duty cycles. The primary objective of the cold flow testing was to simulate the RP propulsion system fluid flow operation through water flow testing and to obtain data for anchoring analytical models. The models will be used to predict the transient and steady state flow behaviors in the actual flight operations. All design and build efforts, including the analytical modeling, have been performed. The cold flow testing of the propulsion system was set up and conducted at a NASA MSFC test facility. All testing was completed in the summer of 2014, and this paper documents the results of that testing and the associated fluid system modeling efforts.

Williams, Hunter↗
NASA NTRS1988

Measurement and prediction of propeller flow field on the PTA aircraft at speeds of up to Mach 0.85

High speed subsonic transports powered by advanced propellers provide significant fuel savings compared to turbofan powered transports. Unfortunately, however, propfans must operate in aircraft-induced nonuniform flow fields which can lead to high blade cyclic stresses, vibration and noise. To optimize the design and installation of these advanced propellers, therefore, detailed knowledge of the complex flow field is required. As part of the NASA Propfan Test Assessment (PTA) program, a 1/9 scale semispan model of the Gulfstream II propfan test-bed aircraft was tested in the NASA-Lewis 8 x 6 supersonic wind tunnel to obtain propeller flow field data. Detailed radial and azimuthal surveys were made to obtain the total pressure in the flow and the three components of velocity. Data was acquired for Mach numbers ranging from 0.6 to 0.85. Analytical predictions were also made using a subsonic panel method, QUADPAN. Comparison of wind-tunnel measurements and analytical predictions show good agreement throughout the Mach range.

Aljabri, Abdullah S.↗
DOE OSTI2023

Spatiotemporal measurements of striations in a glow discharge’s positive column using laser-collisional induced fluorescence

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n e , and the ratios of LCIF emission states that can be correlated with T e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n e in DC striations. The n e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n e , allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

42 ENGINEERING↗
NASA NTRS2019

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and automation, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Tong, Michael T.↗
NASA NTRS2019

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and data science, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Core Size↗
DOE OSTI2021

An AI-Enabled MODEX Framework for Improving Predictability of Subsurface Water Storage across Local and Continental Scales

Focal Area: (2) Predictive modeling through the use of AI techniques and AI-derived model components. (3) Insight gleaned from complex data using AI, big data analytics, and other advanced methods. We propose an AI-enabled model-experiment (MODEX) framework to improve the predictability of subsurface water storage (SWS) from local to conus scales in a changing environment by taking advantage of DOE’s observation and simulation capabilities, as well as to inform the model and the observation development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Method for simultaneous characterization and expansion of reference libraries for small molecule identification

A variational autoencoder (VAE) has been developed to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. The VAE has been extended to include a chemical property decoder, trained as a multitask network, to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, focused on properties that are obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involves a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training. Finally, the network is further refined by being trained with the experimental data. The trained network is used to predict chemical properties directly from structure and generate candidate structures with desired chemical properties. The network is extensible to other training data and molecular representations, and for use with other analytical platforms, for both chemical property and feature prediction as well as molecular structure generation.

Colby, Sean M.↗