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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 649 records · Page 36

All sources NASA NTRS DOE OSTI

NASA NTRS2001

Infrared Sensing Aeroheating Flight Experiement: STS-96 Flight Results

Major elements of an experiment called the Infrared Sensing Aeroheating Flight Experiment are discussed. The primary experiment goal is to provide reentry global temperature images from infrared measurements to define the characteristics of hypersonic boundary-layer transition during flight. Specifically, the experiment is to identify, monitor, and quantify hypersonic boundary layer windward surface transition of the X-33 vehicle during flight. In addition, the flight data will serve as a calibration and validation of current boundary layer transition prediction techniques, provide benchmark laminar, transitional, and fully turbulent global aeroheating data in order to validate existing wind tunnel and computational results, and to advance aeroheating technology. Shuttle Orbiter data from STS-96 used to validate the data acquisition and data reduction to global temperatures, in order to mitigate the experiment risks prior to the maiden flight of the X-33, is discussed. STS-96 reentry mid-wave (3-5 Pm) infrared data were collected at the Ballistic Missile Defense Organization/Innovative Sciences and Technology Experimentation Facility site at NASA-Kennedy Space Center and subsequently mapped into global temperature contours using ground calibrations only. A series of image mapping techniques have been developed in order to compare each frame of infrared data with thermocouple data collected during the flight. Comparisons of the ground calibrated global temperature images with the corresponding thermocouple data are discussed. The differences are shown to be generally less than about 5%, which is comparable to the expected accuracy of both types of aeroheating measurements.

Blanchard, Robert C.↗

DOE OSTI2015

ND 2 AV: N-dimensional data analysis and visualization analysis for the National Ignition Campaign

Here, one of the biggest challenges in high-energy physics is to analyze a complex mix of experimental and simulation data to gain new insights into the underlying physics. Currently, this analysis relies primarily on the intuition of trained experts often using nothing more sophisticated than default scatter plots. Many advanced analysis techniques are not easily accessible to scientists and not flexible enough to explore the potentially interesting hypotheses in an intuitive manner. Furthermore, results from individual techniques are often difficult to integrate, leading to a confusing patchwork of analysis snippets too cumbersome for data exploration. This paper presents a case study on how a combination of techniques from statistics, machine learning, topology, and visualization can have a significant impact in the field of inertial confinement fusion. We present the $\mathrm{ND}^2\mathrm{AV}$: N-dimensional data analysis and visualization framework, a user-friendly tool aimed at exploiting the intuition and current workflow of the target users. The system integrates traditional analysis approaches such as dimension reduction and clustering with state-of-the-art techniques such as neighborhood graphs and topological analysis, and custom capabilities such as defining combined metrics on the fly. All components are linked into an interactive environment that enables an intuitive exploration of a wide variety of hypotheses while relating the results to concepts familiar to the users, such as scatter plots. $\mathrm{ND}^2\mathrm{AV}$ uses a modular design providing easy extensibility and customization for different applications. $\mathrm{ND}^2\mathrm{AV}$ is being actively used in the National Ignition Campaign and has already led to a number of unexpected discoveries.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction

In this paper, we propose a variational approach to estimate eddy viscosity using forward sensitivity method (FSM) for closure modeling in nonlinear reduced order models. FSM is a data assimilation technique that blends model's predictions with noisy observations to correct initial state and/or model parameters. We apply this approach on a projection based reduced order model (ROM) of the one-dimensional viscous Burgers equation with a square wave defining a moving shock, and the two-dimensional vorticity transport equation formulating a decay of Kraichnan turbulence. We investigate the capability of the approach to approximate an optimal value for eddy viscosity with different measurement configurations. Specifically, we show that our approach can sufficiently assimilate information either through full field or sparse noisy measurements to estimate eddy viscosity closure to cure standard Galerkin reduced order model (GROM) predictions. Therefore, our approach provides a modular framework to correct forecasting error from a sparse observational network on a latent space. We highlight that the proposed GROM-FSM framework is promising for emerging digital twin applications, where real-time sensor measurements can be used to update and optimize surrogate model's parameters.

42 ENGINEERING↗

DOE OSTI2023

Machine-learning-assisted automation of single-crystal neutron diffraction

Neutron scattering is a powerful but expensive technique to study materials and discover new matter. Advanced detector technology has significantly improved the efficiency of neutron experiments, increasing the complexity of neutron data reduction and analysis. Machine learning (ML) brings new directions for neutron diffraction data reduction and experiment operation. Here, this work presents an ML-assisted data reduction and analysis method for precise recognition of Bragg peaks and the corresponding regions of interest; it can then automatically screen and align a measured crystal using the recognized peaks, and subsequently plan and optimize the data collection with user-provided information and uncertainty quantification values of detected peaks. This method shows robust performance in different complex sample environments and enables automated single-crystal neutron diffraction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

Numerical simulations of wave propagation in long bars with application to Kolsky bar testing

Material testing using the Kolsky bar, or split Hopkinson bar, technique has proven instrumental to conduct measurements of material behavior at strain rates in the order of 10 3 s -1 . Test design and data reduction, however, remain empirical endeavors based on the experimentalist's experience. Issues such as wave propagation across discontinuities, the effect of the deformation of the bar surfaces in contact with the specimen, the effect of geometric features in tensile specimens (dog-bone shape), wave dispersion in the bars and other particulars are generally treated using simplified models. The work presented here was conducted in Q3 and Q4 of FY14. The objective was to demonstrate the feasibility of numerical simulations of Kolsky bar tests, which was done successfully.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Science-Driven Data Management for Multi-Tiered Storage (Final Report)

Scientific discovery at the exascale will not be possible without significant new research in the management, storage and retrieval over the long lifespan of the extreme amounts of data that will be produced. Our thesis is that adding application level knowledge about data to guide the actions of the storage system provides substantial benefits to the organization, storage, and access to extreme scale data, resulting in improved productivity for computational science. In this project we will demonstrate novel techniques to facilitate efficient mapping of data objects, even partitioning individual variables, from the user space onto multiple storage tiers, and enable application-guided data reductions and transformations to address capacity and bandwidth bottlenecks. Our goal is to address the associated Input/ Output (I/O) and storage challenges in the context of current and emerging storage landscapes, and expedite insights into mission critical scientific processes.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2019

Unsupervised discovery of temporal sequences in high-dimensional datasets, with applications to neuroscience

Identifying low-dimensional features that describe large-scale neural recordings is a major challenge in neuroscience. Repeated temporal patterns (sequences) are thought to be a salient feature of neural dynamics, but are not succinctly captured by traditional dimensionality reduction techniques. Here, we describe a software toolbox—called seqNMF—with new methods for extracting informative, non-redundant, sequences from high-dimensional neural data, testing the significance of these extracted patterns, and assessing the prevalence of sequential structure in data. We test these methods on simulated data under multiple noise conditions, and on several real neural and behavioral data sets. In hippocampal data, seqNMF identifies neural sequences that match those calculated manually by reference to behavioral events. In songbird data, seqNMF discovers neural sequences in untutored birds that lack stereotyped songs. Thus, by identifying temporal structure directly from neural data, seqNMF enables dissection of complex neural circuits without relying on temporal references from stimuli or behavioral outputs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1979

Local atomic and electronic structure of oxide/GaAs and SiO2/Si interfaces using high-resolution XPS

The chemical structures of thin SiO2 films, thin native oxides of GaAs (20-30 A), and the respective oxide-semiconductor interfaces, have been investigated using high-resolution X-ray photoelectron spectroscopy. Depth profiles of these structures have been obtained using argon ion bombardment and wet chemical etching techniques. The chemical destruction induced by the ion profiling method is shown by direct comparison of these methods for identical samples. Fourier transform data-reduction methods based on linear prediction with maximum entropy constraints are used to analyze the discrete structure in oxides and substrates. This discrete structure is interpreted by means of a structure-induced charge-transfer model.

Grunthaner, F. J.↗

NASA NTRS2016

Simulation of Thermographic Responses of Delaminations in Composites with Quadrupole Method

The application of the quadrupole method for simulating thermal responses of delaminations in carbon fiber reinforced epoxy composites materials is presented. The method solves for the flux at the interface containing the delamination. From the interface flux, the temperature at the surface is calculated. While the results presented are for single sided measurements, with ash heating, expansion of the technique to arbitrary temporal flux heating or through transmission measurements is simple. The quadrupole method is shown to have two distinct advantages relative to finite element or finite difference techniques. First, it is straight forward to incorporate arbitrary shaped delaminations into the simulation. Second, the quadrupole method enables calculation of the thermal response at only the times of interest. This, combined with a significant reduction in the number of degrees of freedom for the same simulation quality, results in a reduction of the computation time by at least an order of magnitude. Therefore, it is a more viable technique for model based inversion of thermographic data. Results for simulations of delaminations in composites are presented and compared to measurements and finite element method results.

Winfree, William P.↗

NASA NTRS2016

Hybrid Propulsion In-Situ Resource Utilization Test Facility Results for Performance Characterization

Hybrid propulsion presents a promising alternative to conventional systems for in-space propulsion applications using In-Situ Propellant Production (ISPP). A hybrid propulsion test facility has been built at the NASA Jet Propulsion Laboratory (JPL) with the capability to evaluate ISPP oxidizers (gaseous mixtures of O2 and CO2) and modify fuel type and chamber geometry. This work is the result of a continuing effort at JPL to characterize the burn characteristics and performance of different propellant combinations and motor configurations in order to refine and support preliminary designs. Twelve tests using gaseous oxygen and two paraffin based fuels (Black Paraffin and SP1X) from the 2015 campaign are presented. Different reduction techniques are compared in an effort to determine the uncertainty associated with deriving a regression rate law and evaluating c* efficiency with the collected data.

Mechentel, F. S.↗

DOE OSTI2025

Identification of tau leptons using a convolutional neural network with domain adaptation

A tau lepton identification algorithm,DeepTau, based on convolutional neural network techniques, has been developed in the CMS experiment to discriminate reconstructed hadronic decays of tau leptons (τ h ) from quark or gluon jets and electrons and muons that are misreconstructed as τ h candidates. The latest version of this algorithm, v2.5, includes domain adaptation by backpropagation, a technique that reduces discrepancies between collision data and simulation in the region with the highest purity of genuine τh candidates. Additionally, a refined training workflow improves classification performance with respect to the previous version of the algorithm, with a reduction of 30–50% in the probability for quark and gluon jets to be misidentified as τ h candidates for given reconstruction and identification efficiencies. This paper presents the novel improvements introduced in theDeepTau algorithm and evaluates its performance in LHC proton-proton collision data at √(s) = 13 and 13.6 TeV collected in 2018 and 2022 with integrated luminosities of 60 and 35 fb -1 , respectively. Techniques to calibrate the performance of the τ h identification algorithm in simulation with respect to its measured performance in real data are presented, together with a subset of results among those measured for use in CMS physics analyses.

Large detector-systems performance↗

NASA NTRS1989

The reduction correction in North America

An inverse Poisson integral technique was used to determine a gravity field on the geoid which, when continued by analytic free space methods to the topographic surface, agrees with the observed field. The computation is performed in three stages, each stage refining the previous solution using data at progressively increasing resolution (1 x 1 deg, 5 x 5', 5/8 x 5/8') from a decreasing area of integration. Reduction corrections are computed at 5/8 x 5/8' granularity by differencing the geoidal and surface values, smoothed by low-pass filtering and sub-sampled at 5' intervals. The 1 x 1 deg averages of the reduction corrections thus obtained for 172 1 x 1 deg squares in western North America are discussed. The 1 x 1 deg mean reduction corrections are predominantly positive, varying from -3 to +15 mgal, with values in excess of 5 mgal for 26 squares. Their mean and rms values are +2.4 and 3.6 mgal respectively and they correlate well with the mean terrain corrections. The mean and rms contributions from the three stages of computation are: 1 x 1 deg stage +0.15 and 0.7 mgal; 5 x 5' stage + 1.0 and 1.6 mgal; and 5/8 x 5/8' stage +1.3 and 1.8 mgal. These results reflect a tendency for the contributions to become larger and more systematically positive as the wavelengths involved become shorter. The results are discussed in terms of two mechanisms; the first is a tendency for the absolute values of both positive and negative anomalies to become larger when continued downwards and, the second, a non-linear rectification, due to the correlation between gravity anomaly and topographic height, which results in the values continued to a level surface being systematically more positive than those on the topography.

Martzen, P. D.↗

NASA NTRS1985

Experimental techniques for three-axes load cells used at the National Full-Scale Aerodynamics Complex

The necessary information for an aerodynamic investigation requiring load cell force measurements at the National Full-Scale Aerodynamics Complex (NFAC) is provided. Included are details of the Ames 40x80 three component load cells; typical model/load cell installation geometries; transducer signal conditioning; a description of the Ames Standard Computations Wind Tunnel Data Reduction Program for Load Cells Forces and Moments (SCELLS), and the inputs required for SCELLS. The Outdoor Aerodynamic Facilities Complex (OARF), a facility within the NFAC where three axes load cells serve as the primary balance system, is used as an example for many of the techniques, but the information applies equally well to other static and wind tunnel facilities that make use of load cell balances.

Dudley, Michael R.↗

DOE OSTI2015

Practical uncertainty reduction and quantification in shock physics measurements

We report the development of a simple error analysis sampling method for identifying intersections and inflection points to reduce total uncertainty in experimental data. This technique was used to reduce uncertainties in sound speed measurements by 80% over conventional methods. Here, we focused on its impact on a previously published set of Mo sound speed data and possible implications for phase transition and geophysical studies. However, this technique's application can be extended to a wide range of experimental data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation

We present FPDetect, a low-overhead approach for detecting logical errors and soft errors affecting stencil computations without generating false positives. We develop an offline analysis that tightly estimates the number of floating-point bits preserved across stencil applications. This estimate rigorously bounds the values expected in the data space of the computation. Violations of this bound can be attributed with certainty to errors. FPDetect helps synthesize error detectors customized for user-specified levels of accuracy and coverage. FPDetect also enables overhead reduction techniques based on deploying these detectors coarsely in space and time. Experimental evaluations demonstrate the practicality of our approach.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

A least mean squares CUBIC algorithm for on-line differential of sampled analog signals

A digital computer algorithm is developed for on-line time differentiation of sampled analog voltage signals. The derivative is obtained by employing a least mean squares technique. The recursive algorithm results in a considerable reduction in computer time compared to a complete new solution of the normal equations each time a new data point is accepted. Implementation of the algorithm on a digital computer is discussed. Examples are simulated on a DEC PDP-8 computer.

Allum, J. H. J.↗

NASA NTRS1983

User's manual for three-dimensional analysis of propeller flow fields

A detailed operating manual is presented for the prop-fan computer code (in addition to supporting programs) recently developed by Kutler, Chaussee, Sorenson, and Pulliam while at the NASA'S Ames Research Center. This code solves the inviscid Euler equations using an implicit numerical procedure developed by Beam and Warming of Ames. A description of the underlying theory, numerical techniques, and boundary conditions with equations, formulas, and methods for the mesh generation program (MGP), three dimensional prop-fan flow field program (3DPFP), and data reduction program (DRP) is provided, together with complete operating instructions. In addition, a programmer's manual is also provided to assist the user interested in modifying the codes. Included in the programmer's manual for each program is a description of the input and output variables, flow charts, program listings, sample input and output data, and operating hints.

Chaussee, D. S.↗

NASA NTRS1999

Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and vegetation in the Land-Between-the Lakes (LBL) using Landsat-TM data. A Landsat-TM scene of the same day was obtained to relate ground measurements to the satellite data. A spectral library has been created for overstory species in LBL. Some of the methods, such as NPDF and IDFD techniques for spectral unmixing and reduction of effects of shadows in classifications- comparison of hyperspectral classification techniques, and spectral nonlinear and linear unmixing techniques, are being tested using the laboratory.

Cetin, Haluk↗