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At least 1,315 records · Page 73

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Quantifying and modeling of stress-driven short-circuits in lithium-ion batteries in electrified vehicles

Despite the huge expansion of electric vehicle sales in the market, customers are discouraged by the possible catastrophic consequences brought by the safety issues of lithium-ion batteries, such as internal short circuits, especially in crash scenarios. Herein, we reveal the quantitative relationship between the deformations of the battery and the internal short circuit. By in situ and ex situ observations and post mortem characterization of the component materials, we quantify the stress-driven internal short circuit and failure behavior of the component material. With the aid of a validated numerical computational model as well as the in situ characterization of the global-field temperature, we successfully identify the minor and major short circuits of the cells upon various mechanical abusive loadings. Finally, we establish the internal short circuit criteria for typical formats of batteries. Furthermore, this discovery also provides a fundamental understanding of both internal and external stress-driven short circuits in a much broader context.

25 ENERGY STORAGE↗

NASA NTRS2009

An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

Arnold, Steven M.↗

DOE OSTI2023

Characterization of wind turbine flow through nacelle-mounted lidars: a review

This article provides a comprehensive review of the most recent advances in the planning, execution, and analysis of inflow and wake measurements from nacelle-mounted wind Doppler lidars. Lidars installed on top of wind turbines provide a holistic view of the inflow and wake characteristics required to characterize and optimize wind turbine performance, carry out model validation and calibration, and aid in real-time control. The need to balance the enhanced capabilities and limitations of lidars compared to traditional anemometers inspired a broad variety of approaches for scan design and wind reconstruction, which we discuss in this review. We give particular emphasis to identifying common guidelines and gaps in the available literature with the aim of providing an exhaustive picture of the state-of-the-art techniques for reconstructing wind plant flow using nacelle-mounted lidars.

17 WIND ENERGY↗

NASA NTRS2003

Characterization of Polyimide Foams for Ultra-Lightweight Space Structures

Ultra-lightweight materials have played a significant role in nearly every area of human activity ranging from magnetic tapes and artificial organs to atmospheric balloons and space inflatables. The application range of ultra-lightweight materials in past decades has expanded dramatically due to their unsurpassed efficiency in terms of low weight and high compliance properties. A new generation of ultra-lightweight materials involving advanced polymeric materials, such as TEEK (TM) polyimide foams, is beginning to emerge to produce novel performance from ultra-lightweight systems for space applications. As a result, they require that special conditions be fulfilled to ensure adequate structural performance, shape retention, and thermal stability. It is therefore important and essential to develop methodologies for predicting the complex properties of ultra-lightweight foams. To support NASA programs such as the Reusable Launch Vehicle (RLV), Clark Atlanta University, along with SORDAL, Inc., has initiated projects for commercial process development of polyimide foams for the proposed cryogenic tank integrated structure (see figure 1). Fabrication and characterization of high temperature, advanced aerospace-grade polyimide foams and filled foam sandwich composites for specified lifetimes in NASA space applications, as well as quantifying the lifetime of components, are immensely attractive goals. In order to improve the development, durability, safety, and life cycle performance of ultra-lightweight polymeric foams, test methods for the properties are constant concerns in terms of timeliness, reliability, and cost. A major challenge is to identify the mechanisms of failures (i.e., core failure, interfacial debonding, and crack development) that are reflected in the measured properties. The long-term goal of the this research is to develop the tools and capabilities necessary to successfully engineer ultra-lightweight polymeric foams. The desire is to reduce density at the material and structural levels, while at the same time maintaining or increasing mechanical and other properties.

Meador, Michael↗

DOE OSTI2021

Deep learning approaches to semantic segmentation of fatigue cracking within cyclically loaded nickel superalloy

Improvements to synchrotron-based micro-computed tomography scanning capabilities have gifted researchers the ability to characterize 4D material thermomechanical responses more thoroughly than ever before. These advancements, however, have brought about new challenges in analyzing the resulting deluge of data. We report on a nickel-based superalloy specimen imaged 26 times in-situ during cyclic loading at Argonne National Laboratory Advanced Photon Source beamline 1ID, in order to monitor crack growth within the microstructure. Therefore, several deep learning approaches which utilize convolutional neural networks are implemented to segment crack features from reconstructed tomography scans. U-Net architecture implementations are found to be especially effective, achieving IoU = 0.995 +/- 0.004 and Matthews correlation coefficient scores of Φ = 0.826 +/- 0.085. These advancements broaden possibilities for scientists seeking to automate segmentation analyses of similar large datasets.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Heterogeneous M-N-C Catalysts for Aerobic Oxidation Reactions: Lessons from Oxygen Reduction Electrocatalysts

Nonprecious metal heterogeneous catalysts composed of first-row transition metals incorporated into nitrogen-doped carbon matrices (M-N-Cs) have been studied for decades as leading alternatives to Pt for the electrocatalytic O 2 reduction reaction (ORR). More recently, similar M-N-C catalysts have been shown to catalyze the aerobic oxidation of organic molecules. Here, this Focus Review highlights mechanistic similarities and distinctions between these two reaction classes and then surveys the aerobic oxidation reactions catalyzed by M-N-Cs. As the active-site structures and kinetic properties of M-N-C aerobic oxidation catalysts have not been extensively studied, the array of tools and methods used to characterize ORR catalysts are presented with the goal of supporting further advances in the field of aerobic oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Transcription factor binding divergence drives transcriptional and phenotypic variation in maize

Regulatory elements are essential components of plant genomes that have shaped the domestication and improvement of modern crops. However, their identity, function and diversity remain poorly characterized, limiting our ability to harness their full power for agricultural advances using induced or natural variation. Here, in this study, we mapped transcription factor (TF) binding for 200 TFs from 30 families in two distinct maize inbred lines historically used in maize breeding. TF binding comparison revealed widespread differences between inbreds, driven largely by structural variation, that correlated with gene expression changes and explained complex quantitative trait loci such as Vgt1, an important determinant of flowering time, and DICE, an herbivore resistance enhancer. CRISPR–Cas9 editing of TF binding regions validated the function and structure of regulatory regions at various loci controlling plant architecture and biotic resistance. Our maize TF binding catalogue identifies functional regulatory regions and enables collective and comparative analysis, highlighting its value for agricultural improvement.

Galli, Mary [Rutgers Univ., Piscataway, NJ (United↗

DOE OSTI2020

SUGAR: An improved empirical model of Type Ia supernovae based on spectral features

Type Ia supernovae (SNe Ia) are widely used to measure the expansion of the Universe. Improving distance measurements of SNe Ia is one technique to better constrain the acceleration of expansion and determine its physical nature. This document develops a new SNe Ia spectral energy distribution (SED) model, called the SUpernova Generator And Reconstructor (SUGAR), which improves the spectral description of SNe Ia, and consequently could improve the distance measurements. This model was constructed from SNe Ia spectral properties and spectrophotometric data from the Nearby Supernova Factory collaboration. In a first step, a principal component analysis-like method was used on spectral features measured at maximum light, which allowed us to extract the intrinsic properties of SNe Ia. Next, the intrinsic properties were used to extract the average extinction curve. Third, an interpolation using Gaussian processes facilitated using data taken at different epochs during the lifetime of an SN Ia and then projecting the data on a fixed time grid. Finally, the three steps were combined to build the SED model as a function of time and wavelength. This is the SUGAR model. Results. The main advancement in SUGAR is the addition of two additional parameters to characterize SNe Ia variability. The first is tied to the properties of SNe Ia ejecta velocity and the second correlates with their calcium lines. The addition of these parameters, as well as the high quality of the Nearby Supernova Factory data, makes SUGAR an accurate and efficient model for describing the spectra of normal SNe Ia as they brighten and fade. The performance of this model makes it an excellent SED model for experiments like the Zwicky Transient Facility, the Large Synoptic Survey Telescope, or the Wide Field Infrared Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Archive of AGR-5/6/7 Particle Radiographs for Identification of Particles with Defective IPyC

As a part of fuel quality control characterization, 2D radiographs of large numbers of particles produced by the Advanced Gas Reactor Fuel Development and Qualification (AGR) Program’s AGR-5/6/7 irradiation were acquired. These radiographs were used for the identification of particles with excessive uranium dispersion from the kernel into the surrounding buffer layer caused by chlorine infiltration through a defective inner pyrolytic carbon (IPyC) layer during silicon carbide (SiC) deposition. Additional features of interest associated with fabrication anomalies were also catalogued. Raw radiography images, along with the noted defective IPyC defects found by analysis at Oak Ridge National Laboratory are reported herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Unveiling the Hidden Evolution of Crystal Defects and Disorder in Energy Materials

Control of point defects and disorder in functional thin films and 2D materials is critical to realizing their full potential in applications ranging from energy storage to advanced electronics. However, these phenomena are often poorly understood, difficult to characterize, and challenging to direct with precision. This presentation explores emerging multi-modal computer vision to decipher and predict order in materials across multiple length scales in the electron microscope, from the atomic to the nanoscale. By fusing data from diverse sources, these powerful models provide unprecedented insights into materials' lifecycles, enabling the control of defects and their associated properties at a fundamental level. This capability promises to transform materials design and accelerate the development of next-generation technologies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

Ultrahigh molecular weight aromatic siloxane polymers

The condensation of a diol with a silane in toluene yields a silphenylene-siloxane polymer. The reaction of stiochiometric amounts of the diol and silane produced products with molecular weights in the range 2.0 - 6.0 x 10 to the 5th power. The molecular weight of the product was greatly increased by a multistep technique. The methodology for synthesis of high molecular weight polymers using a two step procedure was refined. Polymers with weight average molecular weights in excess of 1.0 x 10 to the 6th power produced by this method. Two more reactive silanes, bis(pyrrolidinyl)dimethylsilane and bis(gamma butyrolactam)dimethylsilane, are compared with the dimethyleminodimethylsilane in ability to advance the molecular weight of the prepolymer. The polymers produced are characterized by intrinsic viscosity in tetrahydrofuran. Weight and number average molecular weights and polydispersity are determined by gel permeation chromatography.

Ludwick, L. M.↗

NASA NTRS1982

Integrated infrared detector arrays for low-background applications

Advanced infrared detector and detector array technology is being developed and characterized for future NASA space astronomy applications. Si:Bi charge-injection-device arrays have been obtained, and low-background sensitivities comparable to that of good discrete detectors have been measured. Intrinsic arrays are being assessed, and laboratory and telescope data have been collected on a monolithic InSb CCD array. For wavelengths longer than 30 microns, improved Ge:Ga detectors have been produced, and steps have been taken to prove the feasibility of an integrated extrinsic germanium array. Other integrated arrays and cryogenic components are also under investigation.

Mccreight, C. R.↗

NASA NTRS1981

Transonic Flow Past a Symmetrical Airfoil at High Angle of Attack

The results of an experimental investigation of shock-induced stall and leading-edge stall on a 64A010 airfoil section are presented. Advanced nonintrusive techniques - laser velocimetry and holographic interferometry - were used in characterizing the inviscid and viscous flow regions. The measurements include Mach contours of the inviscid now regions, and mean velocity, flow direction, and Reynolds shear stress profiles in the separated regions. The experimental observations of this study are relevant to efforts to improve surface-pressure prediction methods for airfoils at or near stall.

Johnson, D. A.↗

NASA NTRS2002

NASA Smart Surgical Probe Project

Information Technologies being developed by NASA to assist astronaut-physician in responding to medical emergencies during long space flights are being employed for the improvement of women's health in the form of "smart surgical probe". This technology, initially developed for neurosurgery applications, not only has enormous potential for the diagnosis and treatment of breast cancer, but broad applicability to a wide range of medical challenges. For the breast cancer application, the smart surgical probe is being designed to "see" a suspicious lump, determine by its features if it is cancerous, and ultimately predict how the disease may progress. A revolutionary early breast cancer detection tool based on this technology has been developed by a commercial company and is being tested in human clinical trials at the University of California at Davis, School of Medicine. The smart surgical probe technology makes use of adaptive intelligent software (hybrid neural networks/fuzzy logic algorithms) with the most advanced physiologic sensors to provide real-time in vivo tissue characterization for the detection, diagnosis and treatment of tumors, including determination of tumor microenvironment and evaluation of tumor margins. The software solutions and tools from these medical applications will lead to the development of better real-time minimally-invasive smart surgical probes for emergency medical care and treatment of astronauts on long space flights.

Mah, Robert W.↗

NASA NTRS2004

Validation of Laser-Induced Fluorescent Photogrammetric Targets on Membrane Structures

The need for static and dynamic characterization of a new generation of inflatable space structures requires the advancement of classical metrology techniques. A new photogrammetric-based method for non-contact ranging and surface profiling has been developed at NASA Langley Research Center (LaRC) to support modal analyses and structural validation of this class of space structures. This full field measurement method, known as Laser-Induced Fluorescence (LIF) photogrammetry, has previously yielded promising experimental results. However, data indicating the achievable measurement precision had not been published. This paper provides experimental results that indicate the LIF-photogrammetry measurement precision for three different target types used on a reflective membrane structure. The target types were: (1) non-contact targets generated using LIF, (2) surface attached retro-reflective targets, and (3) surface attached diffuse targets. Results from both static and dynamic investigations are included.

Jones, Thomas W.↗

NASA NTRS1999

Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory

BACKGROUND: New methods of R-R interval variability based on fractal scaling and nonlinear dynamics ("chaos theory") may give new insights into heart rate dynamics. The aims of this study were to (1) systematically characterize and quantify the effects of aging from early childhood to advanced age on 24-hour heart rate dynamics in healthy subjects; (2) compare age-related changes in conventional time- and frequency-domain measures with changes in newly derived measures based on fractal scaling and complexity (chaos) theory; and (3) further test the hypothesis that there is loss of complexity and altered fractal scaling of heart rate dynamics with advanced age. METHODS AND RESULTS: The relationship between age and cardiac interbeat (R-R) interval dynamics from childhood to senescence was studied in 114 healthy subjects (age range, 1 to 82 years) by measurement of the slope, beta, of the power-law regression line (log power-log frequency) of R-R interval variability (10(-4) to 10(-2) Hz), approximate entropy (ApEn), short-term (alpha(1)) and intermediate-term (alpha(2)) fractal scaling exponents obtained by detrended fluctuation analysis, and traditional time- and frequency-domain measures from 24-hour ECG recordings. Compared with young adults (<40 years old, n=29), children (<15 years old, n=27) showed similar complexity (ApEn) and fractal correlation properties (alpha(1), alpha(2), beta) of R-R interval dynamics despite lower spectral and time-domain measures. Progressive loss of complexity (decreased ApEn, r=-0.69, P<0.001) and alterations of long-term fractal-like heart rate behavior (increased alpha(2), r=0.63, decreased beta, r=-0.60, P<0.001 for both) were observed thereafter from middle age (40 to 60 years, n=29) to old age (>60 years, n=29). CONCLUSIONS: Cardiac interbeat interval dynamics change markedly from childhood to old age in healthy subjects. Children show complexity and fractal correlation properties of R-R interval time series comparable to those of young adults, despite lower overall heart rate variability. Healthy aging is associated with R-R interval dynamics showing higher regularity and altered fractal scaling consistent with a loss of complex variability.

NASA Discipline Cardiopulmonary↗

NASA NTRS2005

Jupiter's Galilean Satellites

Jupiter's Galilean satellites Io, Europa, Ganymede and Callisto encompass some of the most bizarre environments known in the solar system, spanning that of Io, the most volcanically active and perhaps the most inhospitable body known, to Europa, currently the focus of a search for life in the solar system because of its subsurface ocean. One of the premier areas of scientific return in solar system research in the past 10 years, due in large part to the Galileo mission and observations by the Hubble Space Telescope, has been a remarkable increase in our knowledge about these satellites. Discoveries have been made of tenuous molecular oxygen atmospheres on Europa and Ganymede, a magnetic field and accompanying auroral emissions at the poles of Ganymede, and of ozone and sulfur dioxide embedded in the surfaces of Europa, Ganymede and Callisto. Io's unusual sulfur dioxide atmosphere, including its volcanic plumes and strong electrodynamic interaction with magnetospheric plasma, has finally been quantitatively characterized. This talk will present highlights from the recent discoveries and advances in our understanding of these fascinating objects.

McGrath, Melissa A.↗