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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fourier method for 3-dimensional data fusion of X-ray Computed Tomography and ultrasound

X-ray Computed Tomography (CT) is essential for nondestructive inspection of many manufactured components but is susceptible to various forms of artifacts and noise. In particular, multi-detector row cone-beam CT systems can suffer from so called “cone-beam” artifacts and partial volume effects, particularly on planar edges at the periphery of the field of view in the cone angle dimension. Uni-directional ultrasonic testing methods generally have extremely accurate in-plane depth resolution but poorer lateral resolution due to physical and geometric constraints. This paper presents a novel technique called Computed Tomographic Fusion (CT-F) which uses three-dimensional Fourier filtering to combine x-ray cone-beam CT reconstructions and ultrasound data in the frequency space. The result is a single image with improved accuracy and quality. CT-F mitigates artifacts while allowing for rapid, accurate characterization of large three-dimensional CT volumes. Finally, using simulations and experiments, we demonstrate artifact reduction and edge contrast improvement in volumetric reconstructions.

42 ENGINEERING↗
DOE OSTI2023

In-pixel AI for lossy data compression at source for X-ray detectors

Integrating neural networks for data compression directly in the Read-Out Integrated Circuits (ROICs), i.e. the pixelated front-end, would result in a significant reduction in off-chip data transfer, overcoming the I/O bottleneck. Our ROIC test chip (AI-In-Pixel-65) is designed in a 65 nm Low Power CMOS process for the readout of pixelated X-ray detectors. Each pixel consists of an analog front-end for signal processing and a 10b analog-to-digital converter operating at 100KSPS. Here, we compare two non-reconfigurable techniques, Principal Component Analysis (PCA) and an AutoEncoder (AE) as lossy data compression engines implemented within the pixelated area. The PCA algorithm achieves 50$×$ compression, adds one clock cycle latency, and results in a 21% increase in the pixel area. The AE achieves 70$×$ compression, adds 30 clock cycle latency, and results in a similar area increase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1986

Delamination growth in composite materials

The Double Cantilever Beam (DCB) and the End Notched Flexure (ENF) specimens are employed to characterize MODE I and MODE II interlaminar fracture resistance of graphite/epoxy (CYCOM 982) and graphite/PEEK (APC2) composites. Sizing of test specimen geometries to achieve crack growth in the linear elastic regime is presented. Data reduction schemes based upon beam theory are derived for the ENF specimen and include the effects of shear deformation and friction between crack surfaces on compliance, C, and strain energy release rate, G sub II. Finite element (FE) analyses of the ENF geometry including the contact problem with friction are presented to assess the accuracy of beam theory expressions for C and G sub II. Virtual crack closure techniques verify that the ENF specimen is a pure Mode II test. Beam theory expressions are shown to be conservative by 20 to 40 percent for typical unidirectional test specimen geometries. A FE parametric study investigating the influence of delamination length and depth, span, thickness and material properties on G sub II is presented. Mode I and II interlaminar fracture test results are presented. Important experimental parameters are isolated, such as precracking techniques, rate effects, and nonlinear load-deflection response. It is found that subcritical crack growth and inelastic materials behavior, responsible for the observed nonlinearities, are highly rate-dependent phenomena with high rates generally leading to linear elastic response.

Gillespie, J. W., Jr.↗
NASA NTRS1985

Results of wind simulations in the mesosphere using precision C-band radars and the inflatable falling sphere technique

The inflatable sphere technique represents a relatively inexpensive approach for obtaining density and wind data between 30 and 90 km. The procedure in its current form is adequate for operational rocket network type application. However, detailed information is lost because of oversmoothing. The present study had the objective to determine whether more detailed wind profiles could be obtained using the inflatable falling sphere and Hirobin. Hirobin is the name for the sphere reduction program used at NASA Wallops Island, VA. In connection with the aim of the study, information had to be obtained regarding the precision of the radar used to track the sphere. For this purpose, data from three C-band radars, each with a different tracking precision, were simulated. On the basis of the results of the investigation, it is concluded that, given a radar with a known precision and a perfectly performing sphere, the Hirobin filters can be adjusted to provide small-scale wind information to about 70 km.

Schmidlin, F. J.↗
NASA NTRS2019

Translating Phased Array Measurements of a Low-Noise Top-Mounted Propulsion Installation for a Supersonic Airliner

A novel translating-phased-array technique was applied during a model-scale validation test of low-noise propulsion concepts for supersonic transport aircraft. The test involved particle image velocimetry, far field and translating phased array acoustic measurements. This paper covers the translating phased array portion. Data were acquired for a series of nozzles with different chevron designs, both uninstalled and installed on a representative aircraft planform. The far field data confirmed the noise reduction potential of top-mounted installation, while the phased array results gave insights into how the reduction occurred and highlighted areas for improvement. This was the inaugural test for the new translating phased array, which measures source maps as seen by observers at different polar angles. Propagation effects through the free jet were documented for the different viewing angles. The source maps obtained were used to understand important aspects of the far field noise measurements.

Beamforming↗
DOE OSTI2023

Thermodynamics of Minerals Stable near Earth's Surface

Project “Thermodynamics of Minerals Stable Near the Earth’s Surface” uses specialized calorimetric techniques to obtain new thermochemical data for solid phases of interest in the Earth’s “critical zone”, the near surface regions of the planet most directly affecting and affected by human activity. Major activity was in three areas: manganese oxide materials, aluminum clusters which are precursors to aluminum oxyhydroxide precipitates, and zeolites. All these classes of minerals are potential carriers of heavy metals and radionuclides in the environment, both within their crystal structures and as adsorbed layers or colloids. Their thermodynamic stability, as well as the sequence of stability of competing phases, governs the aqueous solubility of contaminants (and nutrients) in soil, groundwater, and sediments. The thermodynamics of these phases is strongly affected by particle size and crystallinity, since they often occur as very fine particles which do not coarsen in the near-surface environment. Many of these materials exhibit extensive polymorphism, multicomponent solid solution, and variable hydration states. Thus, one must define and systematize important thermodynamic variables, since one cannot make measurements on each and every possible phase, particle size, and composition. A major finding of the work on manganese oxides was labile water-induced oxidation-reduction reactions. These will be studied further by a combination of thermodynamic and synchrotron-based spectroscopic methods, the latter in collaboration with Peggy O’Day at UC Merced. The adsorption of other species, including simple organics, on such redox-active surfaces will also be investigated by a combination of thermochemical and spectroscopic studies. Studies of the energetics of water adsorption on mineral surfaces will be expanded to emphasize the adsorption of CO2 and small organic molecules, relevant to soil, groundwater, and the subsurface environment. Gas adsorption calorimetry, immersion calorimetry, and solution calorimetry will be combined with appropriate analytical and spectroscopic techniques to obtain a comprehensive picture of the interactions and their energetics. The evolution of aqueous aluminum clusters to form aluminum oxyhydroxide precipitates will be studied in detail by a combination of calorimetric and structural methods applied to aqueous samples aged at room temperature. The energetics of new classes of clusters will be explored. The project addresses several common themes relevant to the broad mission of the Department of Energy. Thermochemical data for minerals stable near the Earth’s surface, though still incomplete, are essential for understanding both natural and anthropogenic processes that affect our very existence on this planet. Such data contribute to the fundamental underpinning for mitigation and management strategies for the extraction and use of energy. Fundamental thermodynamic and mechanistic understanding is required to model processes ranging from heavy metal pollution to nuclear waste disposal to climate change.

58 GEOSCIENCES↗
DOE OSTI2024

Efficient boundary-guided scanning for high-resolution X-ray ptychography

In the realm of X-ray ptychography experiments, a considerable amount of ptychography scans are typically performed within a field of view encompassing the target sample. While it is crucial to obtain overlapping scans in small increments over the region of interest for achieving high-resolution sample reconstruction, a significant number of these scans often redundantly measure the empty background within the wide field of view. To address this inefficiency, an innovative algorithm is proposed that introduces automatic guidance for data acquisition. The algorithm first directs the scan point to actively search for the object of interest within the field of view. Subsequently, it intelligently scans along the perimeter of the sample, strategically acquiring measurements exclusively within the boundary of the region of interest. By employing this approach, a reduction in the number of measurements required to obtain high-resolution reconstruction images is demonstrated, as compared with conventional raster scanning methods. Furthermore, the automatic guidance provided by the algorithm offers the added advantage of saving valuable time during the reconstruction process. Through practical implementation on real experiments, these findings showcase the efficacy of the proposed algorithm in enhancing the efficiency and accuracy of X-ray ptychography experiments. This novel approach holds immense potential for advancing sample analysis and imaging techniques in various scientific disciplines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗
DOE OSTI2025

Nuclear Astrophysics in the Storage Ring: Background Suppressed Simultaneous Measurement of (p,γ) and (p,n) Reactions

We report the application of the new elimination of Rutherford elastic scattering technique for the measurement of proton-induced reaction cross sections utilizing stored ions decelerated to astrophysical energies. This approach results in a background reduction factor of about 1 order of magnitude, enabling the first measurement of a (p, n) cross section in a storage ring. Here, the reaction channels 124 Xe⁢(p,n) and 124 Xe⁢(p,γ) have been studied just above the neutron threshold energy. The new data provide valuable constraints for Hauser-Feshbach theory and extrapolation of the (p,γ) cross section to lower energies. Most importantly, for nuclei of limited availability, the method represents a powerful improvement to efficiently study proton-induced reactions at energies within or close to the astrophysical Gamow window, bringing many reaction measurements within reach that were previously inaccessible in the laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

SVM-Based Parameter Identification for Composite ZIP and Electronic Load Modeling

This paper proposes a parameter identification technique for composite ZIP and electronic loads by leveraging the support vector machine (SVM) approach. Since the active power and the reactive power of electronic loads are piecewise functions of the voltage magnitude, the operating modes of electronic loads are determined by the voltage magnitude. To improve the accuracy of parameter identification, two filters (Hampel and Savitzky–Golay) are employed to preprocess measurements to reduce noise. The data after noise reduction serve as training data for the regression model that is solved by the SVM approach. Numerical results show that the SVM approach with filters can identify the parameters of the composite ZIP and electronic load model with high accuracy

Electronic load↗
DOE OSTI2021

The Building Adapter: Automatic Mapping of Commercial Buildings for Scalable Building Analytics

This project creates new solutions for the manual metadata mapping problem: the costly process of creating a match between a building’s sensor data streams and the inputs of a building analytics engine. This goal is achieved by creating and improving techniques for metadata inference: automatically constructing new contextual information for sensing and control points based on the sensor point names and the raw time series values. The objective is to enable vendors to apply building analytics to 90% of buildings with no manual mapping, and to 10% of buildings with a 90% reduction in manual mapping. These targets are set for all types of metadata required by current analytics engines, including type, location, equipment type, and other relationships. The outcome of this project is a suite of solutions to the manual mapping problem collectively called the Building Adapter that allows vendors to apply analytics engines to new buildings at a significantly reduced cost.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1988

CCD camera system for cometary research

The objective is to upgrade the NASA/GSFC 36 inch telescope instrumentation, primarily with a new charge coupled device (CCD) camera system, to permit an effective monitoring program of cometary activity by means of narrowband imaging and spectroscopic techniques. Researchers have twice taken delivery of the CCD camera system from Princeton Scientific Instruments and twice returned it within six weeks for repair. During the times they had the camera system in the lab, they measured the instrumental performance of the TEK 512 x 512 CCD chip (e.g., readout noise, dark current, etc) and developed the complete operational software for the camera system plus several useful observing and data reduction routines for use at the telescope. The CCD camera system is controlled by an IBM-AT computer. The peripheral equipment and software to permit the efficient transfer of large amounts of data to the LASP's computers (VAXs) and subsequent timely reductions are also in place. The Io torus (S II) emission was monitored with a Fabry-Perot scanning spectrometer, in conjunction with the International Jupiter Watch. The CCD camera system will be coupled to a narrowband interference filter imager and a long-slit spectrograph to provide regular and well-calibrated spatial and spectral observations of comets.

Oliversen, R. J.↗
DOE OSTI2021

A Multiplexed Hybrid Velocimeter

Optical velocimetry systems play a crucial role in studying the dynamic behavior of materials under extreme conditions. Two prominent systems used at the Nevada National Security Site are the velocity interferometer system for any reflector(VISAR) and the photon Doppler velocimeter (PDV) system. Their ability to accurately measure surface motion ranging from 0 to > 20km=s without interacting with material flow enables experimenters to construct thermodynamic equations of state for materials of interest. A number of modifications to VISAR and PDV have taken place over the past five decades, leading to improved performance, increased recording capacity, and a reduction in operational burden. Prior efforts to develop a hybrid velocimeter combining the advantages of both PDV and VISAR into a single diagnostic did not take into account progress in PDV technology or new optical components that had not been developed. This thesis describes the design and implementation of a multiplexed hybrid velocimeter (MHV) based on time-multiplexing techniques, an optical hybrid, and polarization-maintaining fiber and components. Data from experiments, compared with current velocity systems, serve to demonstrate the hybrid's performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Wave Detection and Tracking Within a Rotating Detonation Engine Through Object Detection

As the operational time window of experimental rotating detonation engines (RDEs) is expanded and the technology matures toward integration within gas turbines, monitoring techniques must evolve to offer computationally efficient and highly time-resolved diagnostics. In this study, computer vision object detection methodology that seeks to reduce data processing time and calculate wave velocity within drastically reduced time intervals as compared to traditional high-frame-rate RDE images analysis techniques is proposed. The adapted you-only-look-once object detection network is trained to detect individual detonation waves within single down-axis RDE images. The wave location and rotational direction detected within a frame are tracked through a series of high-speed images to calculate the frame-to-frame wave velocity with the time-step resolution of $\mathrm{20 μs}$ across a series of frames. The analysis of the annotation box size and image linearization effects is presented, demonstrating the lowest frame-to-frame velocity total uncertainty of $\mathrm{±3.8\%}$ and the highest classification speed of 9.5 frames per second using linearized images. Linearized images “unwrap” the RDE annulus pixel region to a reduced image size. Here, this new method offers great reductions in data processing times and unsteady detonation behavior insight at intervals more comparable to the timescales of detonation wave interactions via the application of machine learning to experimental RDE data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Ensemble averaged structure–function relationship for nanocrystals: effective superparamagnetic Fe clusters with catalytically active Pt skin [Ensemble averaged structure-function relationship for composite nanocrystals: magnetic bcc Fe clusters with catalytically active fcc Pt skin]

Practical applications require the production and usage of metallic nanocrystals (NCs) in large ensembles. Besides, due to their cluster-bulk solid duality, metallic NCs exhibit a large degree of structural diversity. This poses the question as to what atomic-scale basis is to be used when the structure–function relationship for metallic NCs is to be quantified precisely. In this paper, we address the question by studying bi-functional Fe core-Pt skin type NCs optimized for practical applications. In particular, the cluster-like Fe core and skin-like Pt surface of the NCs exhibit superparamagnetic properties and a superb catalytic activity for the oxygen reduction reaction, respectively. We determine the atomic-scale structure of the NCs by non-traditional resonant high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Using the experimental structure data we explain the observed magnetic and catalytic behavior of the NCs in a quantitative manner. Lastly, we demonstrate that NC ensemble-averaged 3D positions of atoms obtained by advanced X-ray scattering techniques are a very proper basis for not only establishing but also quantifying the structure–function relationship for the increasingly complex metallic NCs explored for practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measuring the effectiveness of high-performance Co-Optima biofuels on suppressing soot formation at high temperature

Soot emissions in combustion are unwanted consequences of burning hydrocarbon fuels. The presence of soot during and following combustion processes is an indication of incomplete combustion and has several negative consequences including the emission of harmful particulates and increased operational costs. Efforts have been made to reduce soot production in combustion engines through utilizing oxygenated biofuels in lieu of traditional nonoxygenated feedstocks. The ongoing Co-Optimization of Fuels and Engines (Co-Optima) initiative from the US Department of Energy (DOE) is focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The Co-Optima program has identified a handful of biofuel compounds from a list of thousands of potential candidates. In this study, a shock tube was used to evaluate the performance of soot reduction of five high-performance biofuels downselected by the Co-Optima program. Current experiments were performed at test conditions between 1,700 and 2,100 K and 4 and 4.7 atm using shock tube and ultrafast, time-resolve laser absorption diagnostic techniques. The combination of shock heating and nonintrusive laser detection provides a state-of-the-art test platform for high-temperature soot formation under engine conditions. Soot reduction was found in ethanol, cyclopentanone, and methyl acetate; conversely, an α-diisobutylene and methyl furan produced more soot compared to the baseline over longer test times. For each biofuel, several reaction pathways that lead towards soot production were identified. The data collected in these experiments are valuable information for the future of renewable biofuel development and their applicability in engines.

09 BIOMASS FUELS↗
NASA NTRS1985

Mathematical analysis study for radar data processing and enhancement. Part 1: Radar data analysis

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altiude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This is in two parts. This is part 1, an analysis of radar data.

James, R.↗