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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗
DOE OSTI2022

Metabolism of Scenedesmus obliquus cultivated with raw plant substrates

The potential benefits of adding raw, non-food, lignocellulosic plant material as a carbon source for mixotrophic growth of microalgae have previously been demonstrated. This approach has advantages over using traditional carbon sources like glucose or acetate due to wide-spread plant biomass availability and substrate recalcitrance to bacterial contamination. Here, we report the overall growth characteristics and explore the metabolic patterns of Scenedesmus obliquus cultured in the presence raw plant substrate. An initial screen of plant substrate candidates showed an increase in specific growth rate and biomass accumulation when S. obliquus was cultured in the presence of switchgrass or yard waste compared to media alone. We observed a near doubling of microalgal dry weight when S. obliquus was grown with 0.2% ( w/v ) switchgrass under ambient CO 2 . Scanning electron microscopy (SEM) of corn stem after S. obliquus cultivation exhibited substantial phloem degradation. Transcriptomic analyses of S. obliquus during mid- and late-log phase growth revealed a dynamic metabolic landscape within many KEGG pathways. Notably, differential expression was observed for several potential glycosyl hydrolases. We also investigated the influence of switchgrass on the growth of S. obliquus at 50 L volume in mini raceway ponds to determine the scalability of this approach.

Schambach, Jenna Y.↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
NASA NTRS1977

A factory concept for processing and manufacturing with lunar material

A conceptual design for an orbital factory sized to process 1.5 million metric tons per year of raw lunar fines into 0.3 million metric tons of manufacturing materials is presented. A conservative approach involving application of present earth-based technology leads to a design devoid of new inventions. Earth based counterparts to the factory machinery were used to generate subsystem masses and lumped parameters for volume and mass estimates. The results are considered to be conservative since technologies more advanced than those assumed are presently available in many areas. Some attributes of potential space processing technologies applied to material refinement and component manufacture are discussed.

Driggers, G. W.↗
DOE OSTI2021

Hybrid Machine Learning for Scanning Near-Field Optical Spectroscopy

The underlying physics behind an experimental observation often lacks a simple analytical description. This is especially the case for scanning probe microscopy techniques, where the interaction between the probe and the sample is nontrivial. Realistic modeling to include the details of the probe is always exponentially more difficult than its "spherical cow" counterparts. On the other hand, a well-trained artificial neural network based on real data can grasp the hidden correlation between the signal and sample properties. In this work, we show that, via a combination of model calculation and experimental data acquisition, a physics-infused hybrid neural network can predict the tip-sample interaction in the widely used scattering-type scanning near-field optical microscope. This hybrid network provides a long-sought solution for accurate extraction of material properties from tip-specific raw data. The methodology can be extended to other scanning probe microscopy techniques as well as other data-oriented physical problems in general.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Bridging the Gap between the X-ray Absorption Spectroscopy and the Computational Catalysis Communities in Heterogeneous Catalysis: A Perspective on the Current and Future Research Directions

X-ray absorption spectroscopy (XAS) [extended X-ray absorption fine structure (EXAFS) and X-ray absorption near-edge structure (XANES)] is a key technique within the heterogeneous catalysis community to probe the structure and properties of the active site(s) for a diverse range of catalytic materials. Furthermore, the interpretation of the raw experimental data to derive an atomistic picture of the catalyst requires modeling and analysis; the EXAFS data are compared to a model, and a goodness of fit parameter is used to judge the best fit. This EXAFS modeling can often be nontrivial and time-consuming; overcoming or improving these limitations remains a central challenge for the community. Considering these limitations, this Perspective highlights how recent developments in analysis software, increased availability of reliable computational models, and application of data science tools can be used to improve the speed, accuracy, and reliability of EXAFS interpretation. In particular, we emphasize the advantages of combining theory and EXAFS as a unified technique that should be treated as a standard (when applicable) to identify catalytic sites and not two separate complementary methods. Building on the recent trends in the computational catalysis community, we also present a community-driven approach to adopt FAIR Guiding Principles for the collection, analysis, dissemination, and storage of XAS data. Written with both the experimental and theory audience in mind, we provide a unified roadmap to foster collaborations between the two communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
NASA NTRS2026

Impact Testing of 410 Stainless Steel for Material Impact Model Development

A project is underway to develop a consistent set of material properties, impact test data, and failure analysis for a variety of metallic aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the Federal Aviation Administration William J. Hughes Technical Center. Particular features of this set of data are that all material property and impact test data are obtained using traceable material, the test methods and procedures are extensively documented, and all the raw data are available. Four parallel efforts are currently underway: measurement of material deformation and failure response over a wide range of strain rates and temperatures, failure analysis of material property specimens and impact test articles, development of improved numerical modeling techniques for deformation and failure, and impact testing of flat panels and substructures for model validation. This report describes impact testing performed on 410 stainless steel sheet and plate samples of different thicknesses with two different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

410 Stainless Steel↗
NASA NTRS2013

Impact Testing of Aluminum 2024 and Titanium 6Al-4V for Material Model Development

One of the difficulties with developing and verifying accurate impact models is that parameters such as high strain rate material properties, failure modes, static properties, and impact test measurements are often obtained from a variety of different sources using different materials, with little control over consistency among the different sources. In addition there is often a lack of quantitative measurements in impact tests to which the models can be compared. To alleviate some of these problems, a project is underway to develop a consistent set of material property, impact test data and failure analysis for a variety of aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the FAA William J. Hughes Technical Center. Unique features of this set of data are that all material property data and impact test data are obtained using identical material, the test methods and procedures are extensively documented and all of the raw data is available. Four parallel efforts are currently underway: Measurement of material deformation and failure response over a wide range of strain rates and temperatures and failure analysis of material property specimens and impact test articles conducted by The Ohio State University; development of improved numerical modeling techniques for deformation and failure conducted by The George Washington University; impact testing of flat panels and substructures conducted by NASA Glenn Research Center. This report describes impact testing which has been done on aluminum (Al) 2024 and titanium (Ti) 6Al-4vanadium (V) sheet and plate samples of different thicknesses and with different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

Pereira, J. Michael↗
NASA NTRS1984

Materials properties data base computerization

Material property data plays a key role in the design of jet engine components. Consistency, accuracy and efficient use of material property data is of prime importance to the engineering community. The system conception, development, implementation, and future plans for computer software that captures the Material Properties Handbook into a scientific data base are described. The engineering community is given access to raw data and property curves, display of multiple curves for material evaluation and selection, direct access by design analysis computer programs, display of the material specification, and a historical repository for the material evolution. The impact of this activity includes significant productivity gains and cost reductions; all users have access to the same information nd provides consistent, rapid response to the needs of the engineering community. Future plans include incorporating the materials properties data base into a network environment to access information from other data bases and download information to engineering work stations.

Baur, R. G.↗
NASA NTRS1971

Fundamental ignition study for material fire safety improvement, part 2

The autoignition behavior of polymeric compositions in oxidizing media was investigated as well as the nature and relative concentration of the volatiles produced during oxidative decomposition culminating in combustion. The materials investigated were Teflon, Fluorel KF-2140 raw gum and its compounded versions Refset and Ladicote, 45B3 intumenscent paint, and Ames isocyanurate foam. The majority of the tests were conducted using a stagnation burner arrangement which provided a laminar gas flow and allowed the sample block and gas temperatures to be varied independently. The oxidizing atmospheres were essentially air and oxygen, although in the case of the Fluorel family of materials, due to partial blockage of the gas inlet system, some tests were performed unintentionally in enriched air (not oxygen). The 45B3 paint was not amenable to sampling in a dynamic system, due to its highly intumescent nature. Consequently, selected experiments were conducted using a sealed tube technique both in air and oxygen media.

Paciorek, K. L.↗
NASA NTRS2002

Laboratory Studies of Extraterrestrial Ices and PAHs: Making an Astrobiological Silk Purse Out of An Interstellar Sow's Ear

Tremendous strides have been made in our understanding of interstellar material over the past twenty years thanks to significant, parallel developments in observational astronomy and laboratory astrophysics. Today, the composition of dust in the ISM is reasonably well constrained to cold, micron-sized particles of various refractory materials. Shrouded within the protective confines of cold, opaque molecular clouds--the birthplace of stars and planets--these particles secrete mantles of mixed molecular lees whose major components are also well constrained. Finally, amidst the molecular inventory of these ice mantles are likely to be found polycyclic aromatic hydrocarbons (PAHs), whose telltale infrared signature I is now recognized throughout the Universe. However, of what significance is this scenario to the origin of life in our solar system--or any other? The major components of the icy materials observed in interstellar clouds and in our own solar system are uniformly quite simple. In addition, despite the fact that PAHs likely represent the single largest molecular reservoir of organic carbon in evolving planetary systems, they are not what would be considered "biogenic" molecules. Although interesting from a chemical and astrophysical standpoint, in the absence of a mechanism by which these materials can be transformed into more biochemically significant structures, they are of little Astrobiological significance. In this talk, we will begin with a brief review of the nature and abundance of the "raw" population of PAHs and PAH-related materials in the ISM. From there, we will move on to explore our laboratory simulations of the photochemical evolution of realistic mixed molecular ices under conditions which simulate those encountered in the ISM and in evolving planetary systems. Particular attention will be paid to the surprisingly complex array of organic species that are produced in these ices from such a deceptively simple inventory of starting materials. In addition, we will explore the chemistry of PAHs under these conditions and consider its potential for transforming that rich repository of pre-biotic organic "ore" into materials of greater importance to Astrobiology.

Hudgins, Douglas M.↗
DOE OSTI2022

Defect identification in simulated Bragg coherent diffraction imaging by automated AI

X-ray Bragg coherent diffraction imaging is a powerful technique for operando and in situ materials characterization and provides a unique means of quantifying the influence of one-dimensional (1D) and two-dimensional (2D) material defects on material response. However, obtaining full images from raw x-ray diffraction data is nontrivial and computationally intensive, precluding real-time experimental feedback. Here, we present a machine learning approach to identify the presence of crystalline line defects (edge and screw) in samples from the raw, 2D, coherent diffraction data without the need for image reconstruction through iterative phase retrieval. Further, we compare different approaches to designing neural networks for this application and demonstrate the potential of automated ML (autoML) approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2026

INL CRMO XRF Special Report No. 3: INL CRMO XRF Calibration Methods for the Analysis of Ceramics and Brick

This report details the analytical methods used by the Idaho National Laboratory Cultural Resource Management Office to characterize ceramic and brick artifacts using X-ray fluorescence spectrometry. More specifically, this report provides details on instrumentation, analysis times, and matrix-specific calibration protocols for ceramic materials. Calibration curves were developed to adjust raw instrumental output for 13 elements using a suite of reference standards made from historic brick borrowed from the Yale Peabody Museum. Calibration curves were validated by plotting predicted values against published reference values for the calibration set as well as a certified soil reference standard (SRM 2711a).

36 MATERIALS SCIENCE↗
NASA NTRS2009

Biologically Inspired Purification and Dispersion of SWCNTs

A biologically inspired method has been developed for (1) separating single-wall carbon nanotubes (SWCNTs) from other materials (principally, amorphous carbon and metal catalysts) in raw production batches and (2) dispersing the SWCNTs as individual particles (in contradistinction to ropes and bundles) in suspension, as required for a number of applications. Prior methods of purification and dispersal of SWCNTs involve, variously, harsh physical processes (e.g., sonication) or harsh chemical processes (e.g., acid reflux). These processes do not completely remove the undesired materials and do not disperse bundles and ropes into individual suspended SWCNTs. Moreover, these processes cut long SWCNTs into shorter pieces, yielding typical nanotube lengths between 150 and 250 nm. In contrast, the present method does not involve harsh physical or chemical processes. The method involves the use of biologically derived dispersal agents (BDDAs) in an aqueous solution that is mechanically homogenized (but not sonicated) and centrifuged. The dense solid material remaining after centrifugation is resuspended by vortexing in distilled water, yielding an aqueous suspension of individual, separated SWCNTs having lengths from about 10 to about 15 microns.

Feeback, Daniel L.↗
DOE OSTI2023

Measurement of the low-energy antitriton inelastic cross section

In this Letter, the first measurement of the inelastic cross section for antitriton–nucleus interactions is reported, covering the momentum range of 0.8 ≤ p < 2.4 GeV/c. The measurement is carried out using data recorded with the ALICE detector in pp and Pb–Pb collisions at a centre-of-mass energy per nucleon of 13 TeV and 5.02 TeV, respectively. The detector material serves as an absorber for antitriton nuclei. The raw yield of (anti)triton nuclei measured with the ALICE apparatus is compared to the results from detailed ALICE simulations based on the GEANT4 toolkit for the propagation of (anti)particles through matter, allowing one to quantify the inelastic interaction probability in the detector material. This analysis complements the measurement of the inelastic cross section of antinuclei up to A = 3 carried out by the ALICE Collaboration, and demonstrates the feasibility of the study of the isospin dependence of inelastic interaction cross section with the analysis techniques presented in this Letter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2020

Impact Testing of Inconel 718 for Material Impact Model Development

One of the difficulties with developing and verifying accurate impact models is that parameters such as high strain-rate material properties, failure modes, static properties, and impact test measurements are often obtained from a variety of different sources using different materials, with little control over consistency among the different sources. In addition, there is often a lack of quantitative measurements in impact tests to which the models can be compared. To alleviate some of these problems, a project is underway to develop a consistent set of material property, impact test data, and failure analysis for a variety of aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the Federal Aviation Administration (FAA) William J. Hughes Technical Center. Unique features of this set of data are that all material property and impact test data are obtained using traceable material, the test methods and procedures are extensively documented, and all of the raw data is available. Four parallel efforts are currently underway. The Ohio State University conducts both measurement of material deformation and failure response over a wide range of strain rates and temperatures and failure analysis of material property specimens and impact test articles. The George Mason University conducts the development of improved numerical modeling techniques for deformation and failure. Glenn conducts the impact testing of flat panels and substructures. This report describes impact testing performed on Inconel 718 sheet and plate samples of different thicknesses with different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

J Michael Pereira↗
NASA NTRS2008

Fabrication Capabilities Utilizing In Situ Materials

The National Aeronautics and Space Administration (NASA) has a Space Exploration Policy that lays out a plan that far exceeds the earlier Apollo goals where landing on the moon and taking those first historic steps fulfilled the mission. The policy states that we will set roots on the moon by establishing an outpost. This outpost will be used as a test bed for residing in more distant locales, such as Mars. In order to become self-sufficient, the occupants must have the capability to fabricate component parts in situ. Additionally, in situ materials must be used to minimize valuable mission upmass and to be as efficient as possible. In situ materials can be found from various sources such as raw lunar regolith whereby specific constituents can be extracted from the regolith (such as aluminum, titanium, or iron), and existing hardware already residing on the moon from past Apollo missions. The Electron Beam Melting (EBM) process lends itself well to fabricating parts, tools, and other necessary items using in situ materials and will be discussed further in this paper.

McLemore, Carole A.↗