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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Potential defect structure effects in the volatility separation of sub-picogram quantities of fission and activation products from an irradiated UO2 matrix

Here, the use of fluorination as a rapid separation technique for quantification of trace-mass, short-lived isotopes is illustrated. Single crystal 238 UO 2 was exposed to a 14 MeV neutron source to produce mixed fission and activation products. Selective removal of trace volatile fluorides from non-volatile ones produced two results of interest. A decrease in background produced better detection and quantification of select analytes across the gamma spectrum. Second, at the very low burnup condition described, the volatility behaviors of common isotopes were altered relative to their well-established behaviors in higher burnup metal and metal oxide fuels.

Fission and activation product separations↗
NASA NTRS1972

Resolution of defects by microwave holography.

Basic techniques for microwave holography are considered, giving attention to ways of approaching the problem, swept frequency depth resolution, optical processing of swept frequency data, B-scans with optical processing, and the side-looking radar principle. Aspects of image formation with Vander Lugt filters are discussed together with holograms for Vander Lugt filter imaging. It is shown that a single basic scanning operation with microwaves can produce records for optical processing to provide any of the common readouts used in flaw detection.

Cribbs, R. W.↗
DOE OSTI2022

Reduced photothermal heating in diamonds enriched with H3 point defects

Solid-state laser refrigeration of semiconductors remains an outstanding experimental challenge. In this work, we show that, following excitation with a laser wavelength of 532 nm, bulk diamond crystals doped with H3 centers both emit efficient up-conversion (anti-Stokes) photoluminescence and also show significantly reduced photothermal heating relative to crystals doped with nitrogen–vacancy (NV) centers. The H3 center in diamond is a highly photostable defect that avoids bleaching at high laser irradiances of 10–70 MW/cm 2 and has been shown to exhibit laser action, tunable over the visible band of 500–600 nm. Here, the observed reduction of photothermal heating arises due to a decrease in the concentration of absorbing point defects, including NV-centers. These results encourage future exploration of techniques for H3 enrichment in diamonds under high-pressure, high-temperature conditions for the simultaneous anti-Stokes fluorescence cooling and radiation balanced lasing in semiconductor materials. Reducing photothermal heating in diamond through the formation of H3 centers also opens up new possibilities in quantum sensing via optically detected magnetic resonance spectroscopy at ambient conditions.

42 ENGINEERING↗
NASA NTRS1999

Development of Optical Diagnostic Techniques for Microgravity Materials Processing

Materials processing including crystal growth, either under a gravity environment on ground or a microgravity environment in space, involves complicated phenomena of fluid motions in gas or liquid phases as well as interaction of various species. To obtain important physical insight, it is very necessary to provide gross-field optical diagnostics for monitoring various physical properties. Materials processing inhibits easy access by ordinary instruments and thus characterizing gross-field physical properties is very challenging. Typical properties of importance can be fluid velocity, temperature, and species concentration for fluids, and surface topology and defects for solids. Observing surface grow rate during crystal growth is also important. Material microstructures, i.e., integrity of crystal structures, is strongly influenced by the existence of thermally-induced flow as well as local nucleation of particles during solidification, which may act in many detrimental ways. In both ground-based and microgravity experiments, the nature of product property changes resulting from three-dimensional fluid or particle motions need be characterized. Gross-field diagnostics is thus required to identify their effects on product defects and process deficiencies. The quantitative visualization techniques can also be used for validation of numerical modeling. For optical nonintrusive gross-field diagnostic techniques, two approaches were developed as summer projects. One optical approach allows us to provide information of species concentration and temperature for monitoring in real time. The other approach, that is, the concept which is formulated for detection of surface topography measurement can provide unprecedented spatial resolution during crystal growth.

Cha, Soyoung Stephen↗
NASA NTRS2024

Presound: UAV Diagnostic System Enabled by Vibration-Based Machine Learning

A low-weight, inexpensive small unmanned aerial system (sUAS) that takes off, performs a mission, lands, and safely stows and recharges itself has myriad future applications ranging from agricultural imaging to last-mile package delivery. Likewise, Urban Air Mobility (UAM) systems will enable people to take air taxis from point to point in cities, rapidly moving commuters long distances without concern for road traffic and congestion. Fully electric aviation systems will be cleaner and quieter than ground transport. Cities could eliminate cars and buses, and convert roads to higher capacity bike and pedestrian throughways. Yet, for sUAS as well as UAM, system reliability and assurance is a limiting factor to deploying affordable autonomous flight systems. For this bright future of aviation to be realized, aircraft must be able to autonomously and accurately self-diagnose health issues both before takeoff and during flight. The GreenSight PreSound system is designed to identify defects on aircraft through intelligent analysis of vibration. It accomplishes this by measuring structural vibrations induced by the vehicle’s own propellers, and analyzing that data using a machine learning model that determines whether a defect is present. The PreSound system is designed to require no human oversight, and to operate across a wide array of vehicles through re-training of the model for each target aircraft. PreSound has been developed and seen limited early success using data collected from the GreenSight Dreamer sUAS, a 5lb quadrotor vehicle designed for aerial imaging applications. The final detection model, trained on data with props spinning at 50% throttle, achieves excellent performance with over 99% average accuracy in detecting blade damage using a single FFT vector input. It demonstrates the ability to generalize to new types of blade damage, correctly classifying a different type of blade damage with 98% accuracy. Full test pulses were classified with 100% accuracy, and in live testing, all sets of data during blade movement were classified accurately with over 95% confidence. When trained on in-flight data, the same model achieves an average accuracy of 85% in distinguishing between undamaged and blade-damaged states in flight. The authors believe that these accuracies show significant potential of this approach to expand unmanned flight safety, with significant potential benefits in accelerating Advanced Aerial Mobility (AAM) and UAM aviation applications.

UAS↗
DOE OSTI2021

Neutron diffraction study of magnetism in van der Waals layered MnBi 2n Te 3n+1

Two-dimensional van der Waals MnBi 2 n Te 3 n +1 ( n = 1, 2, 3, 4) compounds have been recently found to be intrinsic magnetic topological insulators rendering quantum anomalous Hall effect and diverse topological states. Here, we summarize and compare the crystal and magnetic structures of this family, and discuss the effects of chemical composition on their magnetism. We found that a considerable fraction of Bi occupies at the Mn sites in MnBi 2 n Te 3 n +1 ( n = 1, 2, 3, 4) while there is no detectable Mn at the non-magnetic atomic sites within the resolution of neutron diffraction experiments. The occupancy of Mn monotonically decreases with the increase of n . The polarized neutron diffraction on the representative MnBi 4 Te 7 reveals that its magnetization density is exclusively accumulated at the Mn site, in good agreement with the results from the unpolarized neutron diffraction. The defects of Bi at the Mn site naturally explain the continuously reduced saturated magnetic moments from n = 1 to n = 4. The experimentally estimated critical exponents of all the compounds generally suggest a three-dimensional character of magnetism. Our work provides material-specified structural parameters that may be useful for band structure calculations to understand the observed topological surface states and for designing quantum magnetic materials through chemical doping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Advanced Thermoluminescence Spectroscopy as a Research Tool for Semiconductor and Photonic Materials: A Review and Perspective

Thermoluminescence (TL) or thermally stimulated luminescence (TSL) spectroscopy is based on liberating charge carriers from traps in the bandgap by providing enough thermal energy to overcome the potential barrier of the traps. It provides a powerful tool to measure the positions of the localized states/traps in the bandgap. Despite that, its applications in semiconductors are very limited. Herein, the basics of TL spectroscopy and the recent advances in the technique with focus on cryogenic thermally stimulated photoemission spectroscopy (C‐TSPS) which extends TL measurements to cryogenic regime and allows the detection of very low concentrations of shallow and deep localized states is discussed. One goal herein is to introduce the reader to the use of TL and C‐TSPS in the characterization of semiconductors, explaining how it can be applied and demonstrating its advantages as a powerful tool for measuring shallow donor/acceptor ionization energies in semiconductors and as a method for characterizing compensating defects. The article also discusses interesting potential applications of C‐TSPS in new research areas such as corrosion and formation of oxide layers on metal surfaces.

36 MATERIALS SCIENCE↗
NASA NTRS1987

The acousto-ultrasonic approach

The nature and underlying rationale of the acousto-ultrasonic approach is reviewed, needed advanced signal analysis and evaluation methods suggested, and application potentials discussed. Acousto-ultrasonics is an NDE technique combining aspects of acoustic emission methodology with ultrasonic simulation of stress waves. This approach uses analysis of simulated stress waves for detecting and mapping variations of mechanical properties. Unlike most NDE, acousto-ultrasonics is less concerned with flaw detection than with the assessment of the collective effects of various flaws and material anomalies. Acousto-ultrasonics has been applied chiefly to laminated and filament-wound fiber reinforced composites. It has been used to assess the significant strength and toughness reducing effects that can be wrought by combinations of essentially minor flaws and diffuse flaw populations. Acousto-ultrasonics assesses integrated defect states and the resultant variations in properties such as tensile, shear, and flexural strengths and fracture resistance. Matrix cure state, porosity, fiber orientation, fiber volume fraction, fiber-matrix bonding, and interlaminar bond quality are underlying factors.

Vary, Alex↗
NASA NTRS1988

The acousto-ultrasonic approach

The nature and underlying rationale of the acousto-ultrasonic approach is reviewed, needed advanced signal analysis and evaluation methods suggested, and application potentials discussed. Acousto-ultrasonics is an NDE technique combining aspects of acoustic emission methodology with ultrasonic simulation of stress waves. This approach uses analysis of simulated stress waves for detecting and mapping variations of mechanical properties. Unlike most NDE, acousto-ultrasonics is less concerned with flaw detection than with the assessment of the collective effects of various flaws and material anomalies. Acousto-ultrasonics has been applied chiefly to laminated and filament-wound fiber reinforced composites. It has been used to assess the significant strength and toughness reducing effects that can be wrought by combinations of essentially minor flaws and diffuse flaw populations. Acousto-ultrasonics assesses integrated defect states and the resultant variations in properties such as tensile, shear, and flexural strengths and fracture resistance. Matrix cure state, porosity, fiber orientation, fiber volume fraction, fiber-matrix bonding, and interlaminar bond quality are underlying factors.

Vary, Alex↗
DOE OSTI2022

Identifying Transient Candidates in the Dark Energy Survey Using Convolutional Neural Networks

The ability to discover new transient candidates via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine learning techniques such as Convolutional Neural Networks (CNNs) have shown remarkable success. In this work, we present the results of an automated transient candidate identification on images with CNNs for an extant data set from the Dark Energy Survey Supernova program, whose main focus was on using Type Ia supernovae for cosmology. By performing an architecture search of CNNs, we identify networks that efficiently select non-artifacts (e.g., supernovae, variable stars, AGN, etc.) from artifacts (image defects, mis-subtractions, etc.), achieving the efficiency of previous work performed with random Forests, without the need to expend any effort in feature identification. The CNNs also help us identify a subset of mislabeled images. Performing a relabeling of the images in this subset, the resulting classification with CNNs is significantly better than previous results, lowering the false positive rate by 27% at a fixed missed detection rate of 0.05.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Visualizing the atomic-scale origin of metallic behavior in Kondo insulators

A Kondo lattice is often electrically insulating at low temperatures. However, several recent experiments have detected signatures of bulk metallicity within this Kondo insulating phase. In this study, we visualized the real-space charge landscape within a Kondo lattice with atomic resolution using a scanning tunneling microscope. We discovered nanometer-scale puddles of metallic conduction electrons centered around uranium-site substitutions in the heavy-fermion compound uranium ruthenium silicide (URu 2 Si 2 ) and around samarium-site defects in the topological Kondo insulator samarium hexaboride (SmB 6 ). These defects disturbed the Kondo screening cloud, leaving behind a fingerprint of the metallic parent state. Our results suggest that the three-dimensional quantum oscillations measured in SmB 6 arise from Kondo-lattice defects, although we cannot exclude other explanations. Finally, our imaging technique could enable the development of atomic-scale charge sensors using heavy-fermion probes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Distributed fiber sensor and machine learning data analytics for pipeline protection against extrinsic intrusions and intrinsic corrosions

This paper presents an integrated technical framework to protect pipelines against both malicious intrusions and piping degradation using a distributed fiber sensing technology and artificial intelligence. A distributed acoustic sensing (DAS) system based on phase-sensitive optical time-domain reflectometry (φ-OTDR) was used to detect acoustic wave propagation and scattering along pipeline structures consisting of straight piping and sharp bend elbow. Signal to noise ratio of the DAS system was enhanced by femtosecond induced artificial Rayleigh scattering centers. Data harnessed by the DAS system were analyzed by neural network-based machine learning algorithms. The system identified with over 85% accuracy in various external impact events, and over 94% accuracy for defect identification through supervised learning and 71% accuracy through unsupervised learning.

Peng, Zhaoqiang↗
NASA NTRS2012

Development of Inspection for Friction Stir Welds for Rocket Fuel Tanks

During development of the Ares I weld processes nondestructive and destructive testing were used to identify and characterize defects that occurred. These defects were named and character noted. This catalogue of defects and characteristics was then used to develop inspection methods for Self Reacting Friction Stir Welds (SR ]FSW) and Conventional Friction Stir Welds (C ]FSW). Dye penetrant, eddy current, x ]radiography, single element ultrasonic, and phased array ultrasonic (PAUT) inspection procedures were developed to target the expected defects. Once the method procedure was developed a comparison was performed to allow for selection of the best inspection method. Tests of the effectiveness of the inspection were performed on purposely fabricated flawed specimens and electrodischarge machined notches. The initial test results prompted a revisit of the PAUT procedure and a redesign of the inspection. Subsequent testing showed that a multi ]angle PAUT inspection resulted in better detection capability. A discussion of the most effective orientations of the PAUT transducer will be presented. Also, the implementation of the inspection on production hardware will be presented. In some cases the weld tool is used as the transducer manipulator and in some cases a portable scanner is used

Russell, Samuel S.↗
NASA NTRS2000

Defect Characterization in a Thin Walled Composite RP-1 Tank: A Case Study

A full scale thin walled composite tank, designed and fabricated for the storage of pressurized RP- I rocket fuel, was fully inspected with digital infrared thermography (IR) during assembly and prior to proof testing. The tank featured a "pill capsule" design with the equatorial bondline being overwrapped on both the inner and outer surfaces. A composite skirt was bonded to the aft dome of the tank to serve as a structural support when the tank was stood on end in service. Numerous anomalies were detected and mapped prior to proof testing, some along bondlines and some scattered throughout the acreage. After the tank was intentionally burst, coupons were cut from the regions including thermographic anomalies. These coupons were again inspected thermographically to document the growth of any indications due to proof testing. Ultrasonic inspections (UT) were also performed on the coupons for comparison to thermography. Several coupons were dissected and micrographed. Relationships between IR and UT indications and the physical nature of the dissected material are presented.

Langsing, Matthew D.↗
DOE OSTI2020

Quality Control of Additively Manufactured Metallic Structures with Machine Learning of Thermography Images

Additive manufacturing (AM) of high-strength metals is currently based on the laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Quality control (QC) requires nondestructive evaluation of actual AM structures. Flash thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, the detection sensitivity of this method is limited by noise. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatial–temporal blind source separation and spatial–temporal sparse dictionary learning methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced by the LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, the ML methods with higher accuracy require a longer runtime. However, this runtime is sufficiently short to perform QC within a realistic time frame.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Topological phase transition to a hidden charge density wave liquid

Charge density waves (CDWs), electronic crystals that form within a host solid, have long been speculated to melt into a spatially textured electronic liquid. Though they have not been previously detected, liquid CDWs may nonetheless be fundamental to the phase diagrams of many correlated electron systems, including high temperature superconductors and quantum Hall states. In one of the most promising candidate materials capable of hosting a liquid CDW, 1T-TaS2, a structural phase transition impedes its observation. Here, by irradiating the material with a femtosecond light pulse, we circumvent the structural phase transition to reveal how topological defect dynamics govern the otherwise invisible CDW correlations. Upon photoexcitation, the CDW diffraction peaks broaden azimuthally, initially revealing a hexatic state. At higher temperatures, photoexcitation completely destroys translational and orientational order and only a ring of diffuse scattering is observed, a key signature of a liquid CDW. Our work provides compelling evidence for a defect-unbinding transition to a CDW liquid and presents a protocol for uncovering states that are hidden by other transitions in thermal equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

GPR Robotic Assisted Non-Destructive Evaluation of Concrete Structures - 20196

Reinforced concrete structures are always under exposure of internal or external deteriorations due to many factors such as environmental, nuclear radiation or even construction deficiencies. The use of nondestructive test is one of the reliable methods to inspect structural members. In this case, GPR has a good capability to detect inside deteriorations of concrete structures. However, in many cases it is hard to inspect structural members by hand due to safety issues or inaccessibility. Thus, an alternative way to reduce such risks is to employ robot to carry nondestructive equipment. In this research, twelve reinforced concrete RC beams (8 x 16 x 96, width, height and length) are cast in the lab. Three RC beams have no defect and nine others various defects such as corrosion, de-bonded bars, void, delamination and honeycombing. The one-point load is applied at the center of the RC beam. The loading level is carried out at three levels: 50%, 75% and 100% of maximum load and total load-displacement diagram are performed. The load is held at each level and the robotic GPR is used to scan the side of RC beams. Then, RADAN software is employed to find out any defects at different loading conditions and visualize the crack propagation. The RADAN results show that the pattern of crack propagation for corrosion and debonding are same. Also, the load-displacement results present that inside defect cause reduction of load-capacity of RC beam. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗