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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Simulation and Modeling of Hypersonic Turbulent Boundary Layers Subject to Favorable Pressure Gradients due to Streamline Curvature

Direct numerical simulations (DNS) of favorable-pressure-gradient turbulent boundary layers are presented for a nominal freestream Mach number of 5, with the objective of assessing the limitations of the currently available Reynolds-averaged Navier-Stokes (RANS) models.The wall geometry and flow conditions of the DNS are representative of the experimental data for a Mach 4.9 turbulent boundary layer that was tested on a two-dimensional planar convexwall model in the high-speed blow-down wind tunnel located at the National Aerothermochemistry Laboratory at Texas A&M University. The favorable pressure gradient is induced bythe streamwise surface curvature. The DNS results will be compared with experimental measurements and RANS computations for the same flow conditions and wall geometry. The DNS datasets will also be analyzed to provide an improved physical understanding of hypersonic boundary-layer turbulence subject to mechanical nonequilibrium, including the validity of Morkovin’s hypothesis and the various available compressibility transformations, as well as to obtain turbulence statistics that are relevant to RANS modeling, including the distribution ofeddy viscosity, the budgets of turbulent kinetic energy and Reynolds stresses, and the velocity-temperature correlations. The RANS predictions will be obtained by using both the commonly used one- and two-equation models that assume a constant turbulent Prandtl number and an algebraic, variable Prandtl number model for the turbulent energy flux.

turbulent boundary layers↗
NASA NTRS2005

Development and Testing of Data Mining Algorithms for Earth Observation

The new algorithms developed under this project included a principled procedure for classification of objects, events or circumstances according to a target variable when a very large number of potential predictor variables is available but the number of cases that can be used for training a classifier is relatively small. These "high dimensional" problems require finding a minimal set of variables -called the Markov Blanket-- sufficient for predicting the value of the target variable. An algorithm, the Markov Blanket Fan Search, was developed, implemented and tested on both simulated and real data in conjunction with a graphical model classifier, which was also implemented. Another algorithm developed and implemented in TETRAD IV for time series elaborated on work by C. Granger and N. Swanson, which in turn exploited some of our earlier work. The algorithms in question learn a linear time series model from data. Given such a time series, the simultaneous residual covariances, after factoring out time dependencies, may provide information about causal processes that occur more rapidly than the time series representation allow, so called simultaneous or contemporaneous causal processes. Working with A. Monetta, a graduate student from Italy, we produced the correct statistics for estimating the contemporaneous causal structure from time series data using the TETRAD IV suite of algorithms. Two economists, David Bessler and Kevin Hoover, have independently published applications using TETRAD style algorithms to the same purpose. These implementations and algorithmic developments were separately used in two kinds of studies of climate data: Short time series of geographically proximate climate variables predicting agricultural effects in California, and longer duration climate measurements of temperature teleconnections.

Glymour, Clark↗
NASA NTRS2002

Application of Reconfigurable Computing Technology to Multi-KiloHertz Micro-Laser Altimeter (MMLA) Data Processing

The Multi-KiloHertz Micro-Laser Altimeter (MMLA) is an aircraft based instrument developed by NASA Goddard Space Flight Center with several potential spaceflight applications. This presentation describes how reconfigurable computing technology was employed to perform MMLA signal extraction in real-time under realistic operating constraints. The MMLA is a "single-photon-counting" airborne laser altimeter that is used to measure land surface features such as topography and vegetation canopy height. This instrument has to date flown a number of times aboard the NASA P3 aircraft acquiring data at a number of sites in the Mid-Atlantic region. This instrument pulses a relatively low-powered laser at a very high rate (10 kHz) and then measures the time-of-flight of discrete returns from the target surface. The instrument then bins these measurements into a two-dimensional array (vertical height vs. horizontal ground track) and selects the most likely signal path through the array. Return data that does not correspond to the selected signal path are classified as noise returns and are then discarded. The MMLA signal extraction algorithm is very compute intensive in that a score must be computed for every possible path through the two dimensional array in order to select the most likely signal path. Given a typical array size with 50 x 6, up to 33 arrays must be processed per second. And for each of these arrays, roughly 12,000 individual paths must be scored. Furthermore, the number of paths increases exponentially with the horizontal size of the array, and linearly with the vertical size. Yet, increasing the horizontal and vertical sizes of the array offer science advantages such as improved range, resolution, and noise rejection. Due to the volume of return data and the compute intensive signal extraction algorithm, the existing PC-based MMLA data system has been unable to perform signal extraction in real-time unless the array is limited in size to one column, This limits the ability of the MMLA to operate in environments with sparse signal returns and a high number of noise return. However, under an IR&D project, an FPGA-based, reconfigurable computing data system has been developed that has been demonstrated to perform real-time signal extraction under realistic operating constraints. This reconfigurable data system is based on the commercially available Firebird Board from Annapolis Microsystems. This PCI board consists of a Xilinx Virtex 2000E FPGA along with 36 MB of SRAM arranged in five separately addressable banks. This board is housed in a rackmount PC with dual 850MHz Pentium processors running the Windows 2000 operating system. This data system performs all signal extraction in hardware on the Firebird, but also runs the existing "software based" signal extraction in tandem for comparison purposes. Using a relatively small amount of the Virtex XCV2000E resources, the reconfigurable data system has demonstrated to improve performance improvement over the existing software based data system by an order of magnitude. Performance could be further improved by employing parallelism. Ground testing and a preliminary engineering test flight aboard the NASA P3 has been performed, during which the reconfigurable data system has been demonstrated to match the results of the existing data system.

Powell, Wesley↗
NASA NTRS1983

Subsonic high-angle-of-attack aerodynamic characteristics of a cone and cylinder with triangular cross sections and a cone with a square cross section

Experiments were conducted in the 12-Foot Pressure Wind Tunnel at Ames Research Center on three models with noncircular cross sections: a cone having a square cross section with rounded corners and a cone and cylinder with triangular cross sections and rounded vertices. The cones were tested with both sharp and blunt noses. Surface pressures and force and moment measurements were obtained over an angle of attack range from 30 deg to 90 deg and selected oil-flow experiments were conducted to visualize surface flow patterns. Unit Reynolds numbers ranged from 0.8x1,000,000/m to 13.0x1,000,000/m at a Mach number of 0.25, except for a few low-Reynolds-number runs at a Mach number of 0.17. Pressure data, as well as force data and oil-flow photographs, reveal that the three dimensional flow structure at angles of attack up to 75 deg is very complex and is highly dependent on nose bluntness and Reynolds number. For angles of attack from 75 deg to 90 deg the sectional aerodynamic characteristics are similar to those of a two dimensional cylinder with the same cross section.

Clarkson, M. H.↗
NASA NTRS1992

Internal Shock Interactions in Propulsion/Airframe Integrated Three-Dimensional Sidewall Compression Scramjet Inlets

The advantages and design requirements of propulsion/airframe integration for high Mach number flight have led to extensive study of the three-dimensional sidewall compression scramjet inlet in recent years. Recent research publications have indicated testing over a broad range of Mach number (2 to 18) in a variety of test gases, such as air, helium, and tetrafluoromethane. Multiple experimental techniques have been employed to obtain detailed internal shock interaction data, performance data, and inlet starting limits. Computational fluid dynamics has been effectively used for preliminary parametric studies as well as in parallel with experiments to aid in the explanation of unusual or unexpected flow phenomena. Inlets of this genre afford a relatively simple, generic geometry while producing a highly complex, three-dimensional flow field dominated by shock/shock and shock/boundary layer interactions. While the importance of the viscous effects in high speed inlet interactions is recognized, the present work addresses in a parametric fashion the inviscid effects of leading edge sweep, sidewall compression, and inflow Mach number on the internal shock structure in terms of inlet compression and mass capture. In the process, the source of the of the Mach number invariance with leading edge sweep for a constant sidewall compression class of inlet is identified, and a previously undocumented spillage phenomenon in a constant effective wedge angle class of inlets is discussed.

Holland, Scott D.↗
NASA NTRS1991

Standard test case for a low-speed, turbulent junction vortex flow

The mean flow structure upstream, around within, and in the near wake of a turbulent junction or horseshoe vortex is reported for an incompressible subsonic flow. Measurements of the primitive variables of velocity and pressure are reported on all surfaces bounding the region of the vortex flow and on three transverse and one streamwise plane within the flowfield itself for comparisons between the measured and any calculated flow variables. Detailed surface flow visualizations and some direct force measurements of surface shear stress are also available. The data is a highly detailed, coherent, self-consistent set offered to the computational fluid mechanics community as a standard test case for the evaluation of the capability of numerical solvers intended for predicting the flowfield in such a complex, separated, three-dimensional turbulent flow. This data base is available for copying to user supplied tapes or for transmission via BITNET, as well as in two National Technical Information Service (NTIS) reports.

Pierce, F. J.↗
DOE OSTI2026

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

High-lift aerodynamics: Trends, trades, and options

The trend toward the utilization of higher maximum lift coefficient with increased aircraft size and cruise velocities is discussed. The impact of this trend on the need for tradeoffs between cruise performance and takeoff, climb, and landing performance is examined. Theoretical methods for the analysis of the two-dimensional characteristics of flap systems are described and compared with experimental data. Four powered-lift concepts are described to outline some of the options currently being developed. Two jet-flap theories are described which provide analytical methods for estimation of the three-dimensional aerodynamic high-lift performance characteristics of powered lift systems.

Margason, R. J.↗
NASA NTRS1978

Wake vortex measurements of bodies at high angle of attack

Three-dimensional laser velocimeter measurements have been made of the wake vortices of a slender tangent-ogive body which had nose and body fineness ratios of 3.5 and 12, respectively. Data were obtained for an angle of attack to seminose angle ratio of 2.3 at a free-stream Mach number of 0.6 and unit Reynolds number of 2 million/ft. Details of the mean flow field are presented and features of the turbulent and unsteady nature of the vortex flow field are discussed. Problems associated with obtaining meaningful vortex measurements in high-speed flows are addressed.

Owen, F. K.↗
NASA NTRS2016

Digital Image Correlation Techniques Applied to Large Scale Rocket Engine Testing

Rocket engine hot-fire ground testing is necessary to understand component performance, reliability and engine system interactions during development. The J-2X upper stage engine completed a series of developmental hot-fire tests that derived performance of the engine and components, validated analytical models and provided the necessary data to identify where design changes, process improvements and technology development were needed. The J-2X development engines were heavily instrumented to provide the data necessary to support these activities which enabled the team to investigate any anomalies experienced during the test program. This paper describes the development of an optical digital image correlation technique to augment the data provided by traditional strain gauges which are prone to debonding at elevated temperatures and limited to localized measurements. The feasibility of this optical measurement system was demonstrated during full scale hot-fire testing of J-2X, during which a digital image correlation system, incorporating a pair of high speed cameras to measure three-dimensional, real-time displacements and strains was installed and operated under the extreme environments present on the test stand. The camera and facility setup, pre-test calibrations, data collection, hot-fire test data collection and post-test analysis and results are presented in this paper.

Gradl, Paul R.↗
NASA NTRS2004

Exhaust Simulation Testing of a Hypersonic Airbreathing Model at Transonic Speeds

An experimental study was performed to examine jet-effects for an airframe-integrated, scramjet-rocket combined-cycle vehicle configuration at transonic test conditions. This investigation was performed by testing an existing exhaust simulation wind tunnel model, known as Model 5B, in the NASA Langley 16-Ft. Transonic Tunnel. Tests were conducted at freestream Mach numbers from 0.7 to 1.2, at angles of attack from 2 to +14 degrees, and at up to seven nozzle static pressure ratio values for a set of horizontal-tail and body-flap deflections. The model aftbody, horizontal tails, and body flaps were extensively pressure instrumented to provide an understanding of jet-effects and control-surface/plume interactions, as well as for the development of analytical methodologies and calibration of computational fluid dynamic codes to predict this type of flow phenomenon. At all transonic test conditions examined, the exhaust flow at the exit of the internal nozzle was over-expanded, generating an exhaust plume that turned toward the aftbody. Pressure contour plots for the aftbody of Model 5B are presented for freestream transonic Mach numbers of 0.70, 0.95, and 1.20. These pressure data, along with shadowgraph images, indicated the impingement of an internal plume shock and at least one reflected shock onto the aftbody for all transonic conditions tested. These results also provided evidence of the highly three-dimensional nature of the aftbody exhaust flowfield. Parametric testing showed that angle-of-attack, static nozzle pressure ratio, and freestream Mach number all affected the exhaust-plume size, exhaust-flowfield shock structure, and the aftbody-pressure distribution, with Mach number having the largest effect. Integration of the aftbody pressure data showed large variations in the pitching moment throughout the transonic regime.

Huebner, Lawrence D.↗
DOE OSTI2024

Time projection chamber for GADGET II

The established Gaseous Detector with Germanium Tagging (GADGET) detection system is used to measure weak, low-energy 𝛽-delayed proton decays. It consists of the Gaseous Proton Detector equipped with a MICROMEGAS (MM) readout to detect protons and other charged particles calorimetrically, surrounded by the Segmented Germanium Array (SeGA) for high-resolution detection of prompt 𝛾 rays. To upgrade GADGET's Proton Detector to operate as a compact time projection chamber (TPC) for the detection, three-dimensional imaging and identification of low-energy 𝛽-delayed single- and multiparticle emissions mainly of interest to astrophysical studies. A new high granularity MM board with 1024 pads has been designed, fabricated, installed, and tested. A high-density data acquisition system based on generic electronics for TPCs (GET) has been installed and optimized to record and process the gas avalanche signals collected on the readout pads. The TPC's performance has been tested using a 220 Rn 𝛼-particle source and cosmic-ray muons. In addition, decay events in the TPC have been simulated by adapting the attpcroot data analysis framework. Furthermore, a novel application of two-dimensional convolutional neural networks for GADGET II event classification is introduced. The optimization of data throughput is also addressed. The GADGET II TPC is capable of detecting and identifying 𝛼 particles as well as measuring their track direction, range, and energy. The extracted energy resolution of the GADGET II TPC using P10 gas is about 5.4% at 6.288 MeV ( 220 Rn 𝛼 events), computed using charge integration. Based on a systematic simulation study, we estimated the detection efficiency of the GADGET II TPC for protons and 𝛼 particles, respectively. It has also been demonstrated that the GADGET II TPC is capable of tracking minimum-ionizing particles (i.e., cosmic-ray muons). From these measurements, the electron drift velocity was measured under typical operating conditions. In addition to being one of the first generation of micropattern gaseous detectors (MPGDs) to utilize a resistive anode applied to low-energy nuclear physics, the GADGET II TPC will also be the first TPC surrounded by a high-efficiency array of high-purity germanium 𝛾-ray detectors. As a result, the TPC of GADGET II has been designed, fabricated, and tested and is ready for operation at the Facility for Rare Isotope Beams for radioactive-beam-line experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design

Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML training. In this study, we report a data-efficient, deep-learning framework for molecular discovery that integrates a coarse-grained functional-group representation with a self-attention mechanism to capture intricate chemical interactions. Our approach exploits group-contribution concepts to create a graph-based intermediate representation of molecules, serving as a low-dimensional embedding that substantially reduces the data demands typically required for training. Using a self-attention mechanism to learn the subtle but highly relevant chemical context of functional groups, the method proposed here consistently outperforms existing approaches for predictions of multiple thermophysical properties. In a case study focused on adhesive polymer monomers, we train on a limited dataset comprising only 6,000 unlabeled and 600 labeled monomers. The resulting chemistry prediction model achieves over 92% accuracy in forecasting properties directly from SMILES strings, exceeding the performance of current state-of-the-art techniques. Furthermore, the latent molecular embedding is invertible, enabling the design pipeline to automatically generate new monomers from the learned chemical subspace. We illustrate this functionality by targeting several properties, including high and low glass transition temperatures (Tg), and demonstrate that our model can identify new candidates with values that surpass those in the training set. The ease with which the proposed framework navigates both chemical diversity and data scarcity offers a promising route to accelerate and broaden the search for functional materials.

Han, Ming [Univ. of Chicago, IL (United States)]↗
DOE OSTI2024

Designing Remote Monitoring for Smart Manufacturing Facilities: Hazard Identification and Classification

This study investigates the process of hazard identification in complex manufacturing environments during the design phase, emphasizing the significance of the design process in developing designs that effectively mitigate hazards in contexts with numerous variables, such as a variety of machines, sensors, actuators, and agents. Through a mixed-methods approach, the objective of this work is to understand how the evolution of design outcomes across various stages might influence a designer’s ability to recognize both standard and novel hazards. To achieve this understanding, an experimental design task was conducted with six designers from a national lab specializing in manufacturing technologies. This approach combined qualitative and quantitative data analysis from a one-hour virtual session with participants. Findings suggest that the complexity of identifying hazards in a high-dimensional design space is challenging within a limited time frame and that the identification of hazards is significantly influenced by the stage of the design task and the initial design decisions, indicating the need for extended time and strategic initial planning in the design process to enhance hazard identification.

Ballestas, Caseysimone↗
NASA NTRS1975

Light aircraft lift, drag, and moment prediction: A review and analysis

The historical development of analytical methods for predicting the lift, drag, and pitching moment of complete light aircraft configurations in cruising flight is reviewed. Theoretical methods, based in part on techniques described in the literature and in part on original work, are developed. These methods form the basis for understanding the computer programs given to: (1) compute the lift, drag, and moment of conventional airfoils, (2) extend these two-dimensional characteristics to three dimensions for moderate-to-high aspect ratio unswept wings, (3) plot complete configurations, (4) convert the fuselage geometric data to the correct input format, (5) compute the fuselage lift and drag, (6) compute the lift and moment of symmetrical airfoils to M = 1.0 by a simplified semi-empirical procedure, and (7) compute, in closed form, the pressure distribution over a prolate spheroid at alpha = 0. Comparisons of the predictions with experiment indicate excellent lift and drag agreement for conventional airfoils and wings. Limited comparisons of body-alone drag characteristics yield reasonable agreement. Also included are discussions for interference effects and techniques for summing the results above to obtain predictions for complete configurations.

Smetana, F. O.↗
NASA NTRS1975

Pressure gradient effects on heat transfer to reusable surface insulation tile-array gaps

An experimental investigation was performed to determine the effect of pressure gradient on the heat transfer within space shuttle reusable surface insulation (RSI) tile-array gaps under thick, turbulent boundary-layer conditions. Heat-transfer and pressure measurements were obtained on a curved array of full-scale simulated RSI tiles in a tunnel-wall boundary layer at a nominal free-stream Mach number and free-stream Reynolds numbers. Transverse pressure gradients of varying degree were induced over the model surface by rotating the curved array with respect to the flow. Definition of the tunnel-wall boundary-layer flow was obtained by measurement of boundary-layer pitot pressure profiles, wall pressure, and heat transfer. Flat-plate heat-transfer data were correlated and a method was derived for prediction of heat transfer to a smooth curved surface in the highly three-dimensional tunnel-wall boundary-layer flow. Pressure on the floor of the RSI tile-array gap followed the trends of the external surface pressure. Heat transfer to the surface immediately downstream of a transverse gap is higher than that for a smooth surface at the same location. Heating to the wall of a transverse gap, and immediately downstream of it, at its intersection with a longitudinal gap is significantly greater than that for the simple transverse gap.

Throckmorton, D. A.↗
NASA NTRS1975

Radar derived spatial statistics of summer rain. Volume 1: Experiment description

An experiment was performed at Wallops Island, Virginia, to obtain a statistical description of summer rainstorms. Its purpose was to obtain information needed for design of earth and space communications systems in which precipitation in the earth's atmosphere scatters or attenuates the radio signal. Rainstorms were monitored with the high resolution SPANDAR radar and the 3-dimensional structures of the storms were recorded on digital tape. The equipment, the experiment, and tabulated data obtained during the experiment are described.

Katz, I.↗
NASA NTRS1986

Laser velocimetry in highly three-dimensional and vortical flows

The need for experimentally determined 3-D velocity information is crucial to the understanding of highly 3-dimensional and vortical flow fields. In addition to gaining an understanding of the physics of flow fields, a correlation of velocity data is needed for advanced computational modelling. A double pass method for acquiring 3-D flow field information using a 2-D laser velocimeter (LV) is described. The design and implementation of a 3-D LV with expanded capabilities to acquire real-time 3-D flow field information are also described. Finally, the use of such an instrument in a wind tunnel study of a generic fighter configuration is described. The results of the wind tunnel study highlight the complexities of 3-D flow fields, particularly when the vortex behavior is examined over a range of angles of attack.

Novak, C. J.↗