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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

An Efficient Image Recovery Algorithm for Diffraction Tomography Systems

A diffraction tomography system has potential application in ultrasonic medical imaging area. It is capable of achieving imagery with the ultimate resolution of one quarter the wavelength by collecting ultrasonic backscattering data from a circular array of sensors and reconstructing the object reflectivity using a digital image recovery algorithm performed by a computer. One advantage of such a system is that is allows a relatively lower frequency wave to penetrate more deeply into the object and still achieve imagery with a reasonable resolution. An efficient image recovery algorithm for the diffraction tomography system was originally developed for processing a wide beam spaceborne SAR data...

Jin, Michael Y.↗
NASA NTRS2018

The Apollo Sample Suite: 50 Years of Solar System Insight

The Apollo program was undoubtable a crowning achievement in human history. In addition to the obvious cultural significance, scientific results from the Apollo program had a lasting impression on a range of scientific fields, none more so that the effect the samples had on the fields of geology and cosmochemistry. The six Apollo missions collected 382 kg of rock, regolith, and core samples from geologically diverse locations on the Moon. In the nearly 50 years since the first samples were returned, there have been over 3000 different requests for samples, each yielding insights into fields as disparate as biology, medicine, astronomy, engineering, material science, and of course geology. Early studies of the Apollo samples revealed primary insights into the origin and evolution of the Moon, and of the Earth-Moon system, but the results also had implications for bodies throughout the solar system, e.g., defining crater counting rates. Over the decades, continued study of the Apollo samples by new generations of scientists using new instruments have continued to yield significant new discoveries, including the presence of endogenous water in the Moon and the possible presence of a lunar cataclysm, that in turn has contributed to new models of solar system formation and evolution. The Apollo samples have often been used as a proxy for studying other bodies like Mercury or asteroids. The Apollo samples have also directly contributed to the interpretation of remotely sensed data sets, including their use as ground truth for both Clementine and Lunar Prospector global geochemical maps. Despite the Apollo samples being a static collection, recent efforts will ensure that investigators continue to have access to new samples. For example, there was a recent solicitation for study of previously unopened Apollo samples in vacuum-sealed containers, as well as new access to samples stored frozen or in a He atmosphere. Similarly, the use of X-ray computed tomography as part of the curation process is identifying new clasts within polymict breccias that are available for study. Finally, the MoonDB project is putting all previously published lunar geochemical analyses into a searchable database, which should facilitate new investigations.

Zeigler, Ryan↗
NASA NTRS2004

Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

Decker, Arthur J.↗
DOE OSTI2024

Non-averaged single-molecule tertiary structures reveal RNA self-folding through individual-particle cryo-electron tomography

Large-scale and continuous conformational changes in the RNA self-folding process present significant challenges for structural studies, often requiring trade-offs between resolution and observational scope. Here, we utilize individual-particle cryo-electron tomography (IPET) to examine the post-transcriptional self-folding process of designed RNA origami 6-helix bundle with a clasp helix (6HBC). By avoiding selection, classification, averaging, or chemical fixation and optimizing cryo-ET data acquisition parameters, we reconstruct 120 three-dimensional (3D) density maps from 120 individual particles at an electron dose of no more than 168 e - Å -2 , achieving averaged resolutions ranging from 23 to 35 Å, as estimated by Fourier shell correlation (FSC) at 0.5. Each map allows us to identify distinct RNA helices and determine a unique tertiary structure. Statistical analysis of these 120 structures confirms two reported conformations and reveals a range of kinetically trapped, intermediate, and highly compacted states, demonstrating a maturation folding landscape likely driven by helix-helix compaction interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Interface stability of ultrasonic additively manufactured Zircaloy-4 during hydrothermal corrosion

Simulated pressurized water reactor conditions (330 °C, 15.6 MPa, ~20 ppb oxygen) without irradiation were used to investigate the hydrothermal corrosion behavior of ultrasonic additively manufactured Zircaloy-4 up to 1000 h. X-ray computed tomography allowed for visualization of defects from processing and their progression after corrosion experiments. The specimens were found to have clear variability in the mass change data, compared to typical wrought Zircaloy-4 specimens. The variation in the mass change after exposure was attributed to weld defects connected to the specimen surface which allowed ingress of oxidant into the samples. Defects visualized by computed tomography were found via metallography and characterized. In conclusion, ultrasonic additively manufactured Zircaloy-4 was found to have comparable corrosion behavior as wrought Zircaloy-4 for specimens which did not have clear surface defects along weld interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗
DOE OSTI2023

Understanding the effects of fabrication process on BaZr 0.9 Y 0.1 O 3– δ grain-boundary chemistry using atom probe tomography

Proton-conducting oxides, such as BaZr 0.9 Y 0.1 O 3–δ (BZY10), are receiving significant scientific attention for application in a variety of electrochemical applications. It has been shown that the synthesis route has a significant effect on the ionic behavior of these materials, especially the grain boundaries (GB). In this study, laser-pulsed atom probe tomography (APT) is used to characterize the GB chemistry of BZY10 samples prepared by four different methods: (1) spark plasma sintering (SPS), (2) conventional sintering followed by high-temperature annealing (HT), (3) conventional sintering with NiO used as a sintering aid (SSR-Ni), and (4) solid-state reactive sintering of oxide precursor powders with NiO as a reactive sintering aid (SSRS-Ni). Oxygen depletion (corresponding to oxygen vacancy accumulation) was observed at every GB in this study, consistent with the positive space-charge GB region commonly assigned to these materials. In contrast to the consistent trends associated with oxygen depletion, cation constituents showed varying segregation/depletion behaviors. The samples that used NiO revealed Ni preferentially segregating to the GB. The most common impurities in BZY10 are Al, Fe, Mg, Si, and Sr, all of which generally accumulate at GBs. In order to quantify these chemical trends, the APT method was optimized for this material supplemented with understanding from density functional theory (DFT). Finally, this APT study reveals the complexity of BZY10 GB chemistry and shows that even adjacent GBs in the same material can sometimes show surprisingly different GB chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Three‐Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography

Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRINIDI (Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference)

This software is an open-source Python library that provides tools for processing hyperspectral neutron time-of-flight radiography data. This type of data allows material decomposed reconstructions to be generated with the use of material characteristic spectral responses and the algorithms provided in this code library. The software library will contain tools for pre-processing the neutron measurement data, estimating measurement system parameters, reconstructing material decomposed radiographs, and computing material decomposed computed tomography (CT). Furthermore, it will have capability to generate and process simulated neutron time-of-flight data with the goal of benchmarking and demonstrating the tools that are provided. The software will include thorough documentation and application examples.

Balke, Thilo↗
DOE OSTI2021

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Process-driven roadmap for depositing super duplex stainless steel via wire Arc additive manufacturing

Here, this study systematically investigates the effects of shielding gas, bead spacing, weld mode, and travel speed on the phase balance, porosity, and hardness of wire arc additively manufactured (WAAM) super duplex stainless steel (ER2594). Robotic WAAM was employed to fabricate multilayer walls under systematically varied process conditions, followed by phase transformation simulations, X-ray computed tomography (XCT), electron backscatter diffraction (EBSD), and microhardness evaluation. Thermodynamic simulations predicted rapid cooling of AM process can suppress the potential formation of deleterious precipitates which was later validated via cross-sectional microstructure analyses of printed samples. XCT revealed porosity levels below 0.2% for all deposits, with reduced travel speed significantly lowering defect volume. Microstructural analyses revealed the evolution of various austenite precipitates, including grain boundary austenite (GBA), Widmanstätten austenite (WA), and intergranular austenite (IGA), sequentially upon cooling of the ferrite phase. Among all process parameters, weld transfer mode exhibited the strongest influence on phase balance; pulsed mode promoted higher ferrite retention (~ 36%) compared to RapidX mode. No consistent relationship between stabilized phase fraction and captured microhardness was observed. This work provides critical insights for optimizing WAAM parameters to control phase balance and mechanical performance, which is essential for producing high-integrity super duplex stainless-steel components for nuclear and marine applications.

Grain orientation↗
DOE OSTI2022

Livermore tomography tools: Accurate, fast, and flexible software for tomographic science

Livermore Tomography Tools (LTT) is a customizable scientific software package that enables a broad range of research and development efforts into computed tomography (CT). Here, it was developed to process x-ray and neutron CT data accurately and rapidly from raw detector counts to reconstructed volumes with the flexibility to handle many special cases. LTT fulfills long-term CT software goals to provide quantitatively accurate results reported in physical units (e.g., mm -1 or cm -1 ) while exploiting all available computational advantages to maximize speed. Written in C/C++ with support for multiple CPUs and GPUs, LTT runs on many computing platforms (Linux/Unix, Windows, and Mac; laptops to supercomputers). As a result, LTT can:process data acquired from various custom-built and commercially available CT scanners, model and simulate x-ray and neutron interactions to encourage algorithm prototyping, and allow for rapid insertion of the latest algorithms.We describe LTT’s software architecture, user interfaces, and its 88 algorithms (as of this writing) for pre-processing, reconstruction, post-processing, and simulation that support many scanner geometries (parallel-, fan-, cone-beam, and custom). Several applications are presented that illustrate LTT’s accuracy, speed, and flexibility relative to other solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗
DOE OSTI2020

Characterization of PyC/SiC interfaces with FIB-SEM tomography

Tristructural-isotropic (TRISO) fuel is being considered for multiple reactor designs due to its exceptional performance. This work studies pyrocarbon (PyC) and silicon carbide (SiC) substrates that are near-representative of the inner pyrocarbon (IPyC) and SiC in TRISO fuel. Focused ion beam (FIB)-scanning electron microscopy (SEM) tomography was used to understand the influence of different processing routes on the PyC/SiC interface structure. Additionally, this work outlines a methodology for characterizing the IPyC/SiC interface when considering fission product accommodation and retention in TRISO fuel design. The high-fidelity images collected with FIB-SEM tomography can be used to achieve a more in-depth interpretation of microstructural parameters and pore-shape analysis that can inform simulations and processing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Grazing-incidence X-ray diffraction tomography for characterizing organic thin films

Characterization of thin films is of paramount importance for evaluating material processing outcomes/efficiency as well as establishing structure–property/performance relationships. This article introduces grazing-incidence diffraction tomography (GID tomography), a technique that combines grazing-incidence X-ray scattering and computed tomography to quantitatively determine the dimension and orientation of crystalline domains in thin films without restrictions on the beam coherence, substrate type or film thickness. This computational method extends the capability of synchrotron beamlines by utilizing standard X-ray scattering experiment setups.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Correlations Between Porosity, Spatter, and Process Metrics for Powder Bed Fusion Laser Beam Metallic Additive Manufacturing

Components fabricated using the powder bed fusion laser beam metallic (PBF-LB/M)additive manufacturing process are the result of a multitude of weld passes conducted sequentially. Qualifying components for aerospace applications requires a thorough understanding of the process-structure-properties relationships. Porosity defects are known to have a strong adverse effect on the mechanical properties of a component. In particular, porosity defects created by lack of fusion have high aspect ratio morphologies leading to stress concentrations that become crack initiation sites. In the present work, the occurrence of spatter induced lack of fusion porosity was studied using synchronized in-situ process monitoring, additive manufacturing model-based process metrics, and high-resolution X-ray computed tomography. The results show that lack of fusion porosity is statistically correlated with unremoved welding spatter ejecta of the PBF-LB/M process and process metrics related to the hatching strategy.

Qualification↗
DOE OSTI2020

High-performance molded composites using additively manufactured preforms with controlled fiber and pore morphology

Here, large-scale multimaterial preforms produced by additive manufacturing (AM) underwent compression molding (CM) to produce high-performance thermoplastic composites reinforced with short carbon fibers. AM and CM techniques were integrated to control the fiber orientation (microstructure) and to reduce void content for the improved mechanical performance of the composite. The new integrated manufacturing technique is termed “additive manufacturing-compression molding” (AM-CM). For the present study, the most common materials were used for large-scale printing, i.e., acrylonitrile butadiene styrene (ABS), carbon fiber (CF)–filled ABS (CF/ABS) and glass fiber (GF)–filled ABS (GF/ABS). Three different manufacturing processes; (a) AM (b) extrusion compression molding (ECM), and (c) AM-CM were used to prepare four different panel configurations: (1) neat ABS, (2) CF/ABS, (3) overmold (CF/ABS over neat ABS), and (4) sandwich (neat ABS between two CF/ABS layers). The mechanical properties (tensile and flexural strength and modulus, and Izod impact energy) of samples prepared via all three manufacturing processes were compared. X-ray microcomputer tomography was employed to evaluate the fiber orientation distribution and the volumetric porosity content. The preform maintained high fiber alignment (≈ 82% of fibers within the range of 0–20° in the deposition direction), and the volumetric porosity was reduced by 50% from 3.79% to 1.91% after compression. The alignment of long pores along the deposition direction was also observed. The mechanical properties are discussed with correlation to the fiber alignment and void content in the samples. CF/ABS samples prepared by AM-CM showed significant improvement of 11.15%, 35.27%, 28.6%, and 74.3% in the tensile strength, tensile modulus, flexural strength, and flexural modulus, respectively, when compared with samples prepared by ECM. Unique aspects of this study are the demonstration of large-scale multimaterial AM and the use of multimaterials as preforms to make high-performance composites.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dose and dose rate effects on the microstructural and mechanical stability of long-range ordered precipitates in Inconel 718

Nickel-based alloys offer exceptional mechanical properties and corrosion resistance for various applications in extreme environments such as high neutron flux, temperature, and stress. Precipitates, resulting from thermal treatments, increase the strength and creep resistance of these alloys. Here, heavy ion irradiation is shown to destabilize the γ' and γ" precipitates in Inconel 718 nickel-based alloy by disordering and dissolution processes. Transmission electron microscopy and atom probe tomography reveal that the disordering and dissolution rates of the precipitates are proportional to both irradiation dose and dose rate. Irradiation induced disordering occurs at a higher rate than the dissolution. From analyzing the hardening contributions, microscale mechanical results suggest radiation-induced disordering is responsible for the majority of the softening response at low dose. In addition, low dose radiation-induced disordering results in strain localization and is believed to be the primary cause for the drastic degradation of uniform elongation and toughness in irradiated Inconel 718.

36 MATERIALS SCIENCE↗