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At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗

DOE OSTI2022

Spectral quadrature for the first principles study of crystal defects: Application to magnesium

In this work, we present an accurate and efficient finite-difference formulation and parallel implementation of Kohn-Sham Density (Operator) Functional Theory (DFT) for non periodic systems embedded in a bulk environment. Specifically, employing non-local pseudopotentials, local reformulation of electrostatics, and truncation of the spatial Kohn-Sham Hamiltonian, and the Linear Scaling Spectral Quadrature method to solve for the pointwise electronic fields in real-space and the non-local component of the atomic force, we develop a parallel finite difference framework suitable for distributed memory computing architectures to simulate non-periodic systems embedded in a bulk environment. Choosing examples from magnesium-aluminum alloys, we first demonstrate the convergence of energies and forces with respect to spectral quadrature polynomial order, and the width of the spatially truncated Hamiltonian. Next, we demonstrate the parallel scaling of our framework, and show that the computation time and memory scale linearly with respect to the number of atoms. Next, we use the developed framework to simulate isolated point defects and their interactions in magnesium-aluminum alloys. Our findings conclude that the binding energies of divacancies, Al solute-vacancy and two Al solute atoms are anisotropic and are dependent on cell size. Furthermore, the binding is favorable in all three cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Fatigue behavior of low-cost, non-spherical Ti-6Al-4V powder processed via laser powder bed fusion

Hydride-dehydride Ti-6Al-4V powder with particle size distribution of 75–175 μm were used to manufacture fatigue samples. Optimized processing parameters were used to maintain a relative density of >99.5% in the samples. Fatigue tests were carried out in R = σ min /σ max = -1 condition under stresses ranging from 150 to 500 MPa and the results were compared to samples that were additively manufactured using spherical powders. The fatigue lives were similar between the two types of powder; i.e., powder morphology has no effect on fatigue performance. However, the high surface roughness and martensitic microstructure resulting from the laser powder bed fusion process result in poor performance compared to samples machined from conventionally produced materials. In conclusion, crack initiation occurred consistently from surface defects because of high surface roughness of the additively manufactured parts.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Synthesis of Nano-Oxide Precipitates by Implantation of Ti, Y and O Ions in Fe-10%Cr: Towards an Understanding of Precipitation in Oxide Dispersion-Strengthened (ODS) Steels

The properties of oxide dispersion-strengthened steels are highly dependent on the nature and size distribution of their constituting nano-oxide precipitates. A fine control of the processes of synthesis would enable the optimization of pertinent properties for use in various energy systems. This control, however, requires knowledge of the precise mechanisms of nucleation and growth of the nanoprecipitates, which are still a matter of debate. In the present study, nano-oxide precipitates were produced via the implantation of Y, Ti, and O ions in two different sequential orders in an Fe-10%Cr matrix that was subsequently thermally annealed. The results show that the oxides that precipitate are not necessarily favoured thermodynamically, but rather result from complex kinetics aspects related to the interaction between the implanted elements and induced defects. When Y is implanted first, the formation of nanoprecipitates with characteristics similar to those in conventionally produced ODS steels, especially with a core/shell structure, is evidenced. In contrast, when implantation starts with Ti, the precipitation of yttria during subsequent high-temperature annealing is totally suppressed, and corundum Cr 2 O 3 precipitates instead. Moreover, the systematic involvement of {110} matrix planes in orientation relationships with the precipitates, independently of the precipitate nature, suggests matrix restriction effects on the early stages of precipitation.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Early self-organization of fission gas bubble superlattice formation in neutron-irradiated monolithic U-10Mo fuels

Self-organization of defect superlattices in far-from-equilibrium systems presents a promising way to mitigate swelling concerns in nuclear materials. The gas bubble superlattice (GBS) is a highly ordered, three-dimensional complex defect structure that can retain fission gasses in Uranium-Molybdenum (U-Mo) fuels. Transmission electron microscopy (TEM) investigation of monolithic U-10Mo fuel irradiated to 1.15 × 10 21 fissions/cm 3 and 1.30 × 10 21 fissions/cm 3 revealed that early-stage ordering preferentially occurs at the grain boundaries (GB) and that the critical bubble size for complete ordering is ~3 nm. Once formed at the GB, the GBS extends towards the grain interior; however, the spread in distance from the GB varies likely depending on the type and strength of the GB sink. TEM results also showed a possible correlation between the growth and evolution of the intragranular disordered bubbles and large dislocation networks. The fission product distribution in and outside of the GBS was also investigated confirming the presence of xenon in the GBS, as well as other fission products including cesium, barium, lanthanum, and cerium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1990

A comparison of single-cycle versus multiple-cycle proof testing strategies

An evaluation of single-cycle and multiple-cycle proof testing (MCPT) strategies for SSME components is described. Data for initial sizes and shapes of actual SSME hardware defects are analyzed statistically. Closed-form estimates of the J-integral for surface flaws are derived with a modified reference stress method. The results of load- and displacement-controlled stable crack growth tests on thin IN-718 plates with deep surface flaws are summarized. A J-resistance curve for the surface-cracked configuration is developed and compared with data from thick compact tension specimens. The potential for further crack growth during large unload/reload cycles is discussed, highlighting conflicting data in the literature. A simple model for ductile crack growth during MCPT based on the J-resistance curve is used to study the potential effects of key variables. The projected changes in the crack size distribution during MCPT depend on the interactions between several key parameters, including the number of proof cycles, the nature of the resistance curve, the initial crack size distribution, the component boundary conditions (load vs. displacement control), and the magnitude of the applied load or displacement. The relative advantages of single-cycle and multiple-cycle proof testing appear to be specific, therefore, to individual component geometry, material, and loading.

Hudak, S. J., Jr.↗

NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗

DOE OSTI2023

A deep learning model for automatic analysis of cavities in irradiated materials

Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.

36 MATERIALS SCIENCE↗

NASA NTRS2006

pH Sensitive Microcapsules for Delivery of Corrosion Inhibitors

A considerable number of corrosion problems can be solved by coatings. However, even the best protective coatings can fail by allowing the slow diffusion of oxygen and moisture to the metal surface. Corrosion accelerates when a coating delaminates. Often, the problems start when microscopic nicks or pits on the surface develop during manufacturing or through wear and tear. This problem can be solved by the incorporation of a self-healing function into the coating. Several new concepts are currently under development to incorporate this function into a coating. Conductive polymers, nanoparticles, and microcapsules are used to release corrosion-inhibiting ions at a defect site. The objective of this investigation is to develop a smart coating for the early detection and inhibition of corrosion. The dual function of this new smart coating system is performed by pH-triggered release microcapsules. The microcapsules can be used to deliver healing agents to terminate the corrosion process at its early stage or as corrosion indicators by releasing dyes at the localized corrosion sites. The dyes can be color dyes or fluorescent dyes, with or without pH sensitivity. Microcapsules were formed through the interfacial polymerization process. The average size of the microcapsules can be adjusted from 1 to 100 micron by adjusting the emulsion formula and the microcapsule forming conditions. A typical microcapsule size is around 10 microns with a narrow size distribution. The pH sensitivity of the microcapsule can also be controlled by adjusting the emulsion formula and the polymerization reaction time. Both corrosion indicator (pH indicator) and corrosion inhibitor containing microcapsules were formed and incorporated into paint systems. Test panels of selected steels and aluminum alloys were painted using these paints. Testing of compatibility between the microcapsule system and different paint systems are in progress. Initial experiments with the microcapsule containing paint show visible color changes at induced corrosion sites and improvement of corrosion protection. Further investigation of the performance of the coating using electrochemical techniques and long term exposure are currently underway.

Li, Wenyan↗

DOE OSTI2022

Temporal and spatial laser intensification within nodular defects overcoated with multilayer dielectric mirrors over a wide range of defect geometries

The nodular defect shape and the laser incidence angle have a dramatic impact on the spatial distribution of light intensification within the nodule as well as how the laser light is drained from the defect. Nodular defect geometries unique to ion beam sputtering, ion-assisted deposition, and electron-beam (e-beam) deposition, respectively, are modeled in this parametric study over a wide range of nodular inclusion diameters and layer count for optical interference mirror coatings constructed with quarter-wave thicknesses and capped with a half wave of the low index material. It was found for hafnia ($n$=1.9) and silica ($n$=1.45) multilayer mirrors that the light intensification in nodular defects with a $C$ factor of 8, typical of e-beam deposited coatings deposited with a wide range of deposition angles, was maximized for a 24-layer design. For intermediate size inclusion diameters, increasing the layer count for normal incidence multilayer mirrors reduced the light intensification within the nodular defect. A second parametric study explored the impact of the nodule shape on the light intensification for a fixed number of layers. In this case, there is a strong temporal trend for the different nodule shapes. Narrow nodules tend to drain more laser energy through the bottom of the nodule into the substrate while wide nodules tend to drain more laser energy through the top of the nodule when irradiated at normal incidence. Further, at a 45° incidence angle, waveguiding is an additional method to drain laser energy from the nodular defect. Finally, laser light resonates within nodular defects longer than within the adjacent nondefective multilayer structure.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing

Powder spreading precedes creation of every new layer in powder bed additive manufacturing (AM). The powder spreading process can lead to powder layer defects such as porosity, poor surface roughness and particle segregation. Therefore, the creation of homogeneous layers is the first task for optimal part printing. Discrete element methods (DEM) powder spreading simulations are typically limited to a single layer and/or small number of particles. Therefore, results from such model configurations may not be generalized to multiple layer processes. In this study, a computationally efficient multi-layer powder spreading DEM simulation model is proposed. The model is calibrated experimentally using static Angle of Repose measurements. The adhesion model parameter, cohesive energy density is related to adhesive surface energy and strain energy release rate parameters. The model results show that interaction between particle and the powder spreading rake leads to noticeable variation in packing density, surface roughness, dynamic angle of repose (AOR), particle size distribution, and particle segregation. Finally, the powder model is experimentally validated using a recoater spreading rig to measure the dynamic AOR at spreading speeds consistent with recoating speeds and layer heights used in AM processes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

SiOC coatings on yttria stabilized zirconia microspheres using a fluidized bed coating process

In this study, defect-free SiOC coatings were prepared on yttria stabilized zirconia (YSZ) microspheres by a fluidized bed coating process. Effects of the rheological properties of the coating solution on the coating process were elucidated. An impact regime diagram was constructed, which demonstrated that the coating mechanisms were collision/impact. During the fluidized bed coating, longer spouted time resulted in wider dispersion, longer residence time, and more circulatory motion of particles; the fluid distributed more uniformly throughout the column, as demonstrated in our Multiphase Flow with Interface eXchange (MFiX) simulations. Two-step pyrolysis in Ar achieved complete coating layers, which were comprised of SiOC, SiO 2 , SiC, and graphite. The two stage mass loss during the pyrolysis corresponded to simultaneous reactions due to depolymerization and hydrocarbon loss from 400 to 600°C. Carbon cluster size in the pyrolyzed samples was calculated to be 25 ± 2 Å. In conclusion, this work provides a new method for producing SiOC coatings on micron spheres, with nuclear TRISO fuel particles as the application.

42 ENGINEERING↗

NASA NTRS2001

Effect of convection on osteoblastic cell growth and function in biodegradable polymer foam scaffolds

Culture of seeded osteoblastic cells in three-dimensional osteoconductive scaffolds in vitro is a promising approach to produce an osteoinductive material for repair of bone defects. However, culture of cells in scaffolds sufficiently large to bridge critical-sized defects is a challenge for tissue engineers. Diffusion may not be sufficient to supply nutrients into large scaffolds and consequently cells may grow preferentially at the periphery under static culture conditions. Three alternative culturing schemes that convect media were considered: a spinner flask, a rotary vessel, and a perfusion flow system. Poly(DL-lactic-co-glycolic acid) (PLGA) foam discs (12.7 mm diameter, 6.0 mm thick, 78.8% porous) were seeded with osteoblastic marrow stromal cells and cultured in the presence of dexamethasone and L-ascorbic acid for 7 and 14 days. Cell numbers per foam were found to be similar with all culturing schemes indicating that cell growth could not be enhanced by convection, but histological analysis indicated that the rotary vessel and flow system produced a more uniform distribution of cells throughout the foams. Alkaline phosphatase (ALP) activity per cell was higher with culture in the flow system and spinner flask after 7 days, while no differences in osteocalcin (OC) activity per cell were observed among culturing methods after 14 days in culture. Based on the higher ALP activity and better cell uniformity throughout the cultured foams, the flow system appears to be the superior culturing method, although equally important is the fact that in none of the tests did any of the alternative culturing techniques underperform the static controls. Thus, this study demonstrates that culturing techniques that utilize fluid flow, and in particular the flow perfusion system, improve the properties of the seeded cells over those maintained in static culture.

NASA Discipline Cell Biology↗

DOE OSTI2023

Micro-beam bending of FCC bicrystals: A comparison between defect dynamics simulations and experiments

To understand the role of the grain boundary (GB) in plasticity at small scale, a concurrently coupled mesoscale plasticity model was developed to simulate micro-bending of bicrystalline micron-sized beams. By coupling dislocation dynamics (DD) with a finite element model (FEM), a novel defect dynamics model provides the means to investigate intricate interactions between dislocations and GBs under various loading conditions. Our simulations of micro-bending agree well with corresponding micro-bending experiments, and they show that mechanical response of bicrystals could have not only hardening but also softening depending on the characters of the GB. In addition, changing the location of the GB in the microbeams results in different mechanical responses; GBs located at the neutral plane show softening compared to single crystals, while inclined GBs located halfway along the length of the beam show little effect. In conclusion, simulation results could provide a clear picture on detailed dislocation-GB interactions, and quantitative resolved shear stress analysis supplemented by dislocation density distribution is used to analyze the mechanical response of bicrystalline samples.

36 MATERIALS SCIENCE↗

NASA NTRS2004

NASA Tech Briefs, November 2004

Topics include: Multifunction Imaging and Spectroscopic Instrument; Position-Finding Instrument Built Around a Magnetometer; Improved Measurement of Dispersion in an Optical Fiber; Probe for Sampling of Interstitial Fluid From Bone; Neuropsychological Testing of Astronauts; Method of Calibration for a Large Cathetometer System; Four-Channel PC/104 MIL-STD-1553 Circuit Board; Improved Method of Locating Defects in Wiring Insulation; Strobe Traffic Lights Warn of Approaching Emergency Vehicles; Improved Timing Scheme for Spaceborne Precipitation Radar; Concept for Multiple-Access Free-Space Laser Communications; Variable Shadow Screens for Imaging Optical Devices; Verifying Diagnostic Software; Initial Processing of Infrared Spectral Data; Activity-Centric Approach to Distributed Programming; Controlling Distributed Planning; New Material for Surface-Enhanced Raman Spectroscopy; Treated Carbon Nanofibers for Storing Energy in Aqueous KOH; Advanced Infant Car Seat Would Increase Highway Safety; Development of Biomorphic Flyers; Second-Generation Six-Limbed Experimental Robot; Miniature Linear Actuator for Small Spacecraft; Process for Making Single-Domain Magnetite Crystals; A New Process for Fabricating Random Silicon Nanotips; Resin-Transfer-Molding of a Tool Face; Improved Phase-Mask Fabrication of Fiber Bragg Gratings; Tool for Insertion of a Fiber-Optic Terminus in a Connector; Nanofluidic Size-Exclusion Chromatograph; Lightweight, Low-CTE Tubes Made From Biaxially Oriented LCPs; Using Redundancy To Reduce Errors in Magnetometer Readings; Compact Instrument for Measuring Profile of a Light Beam; Multilayer Dielectric Transmissive Optical Phase Modulator; Second-Generation Multi-Angle Imaging Spectroradiometer; Real-Time Adaptive Color Segmentation by Neural Networks; Research and Development in Optical Communications; Tests of Multibeam Scintillation Mitigation on Laser Uplinks; and Spaceborne Infrared Atmospheric Sounder.

Source record↗

DOE OSTI2025

Influence of Process Parameter and Build Rate Variations on Defect Formation in Laser Powder Bed Fusion SS316L

Laser powder bed fusion (LPBF) is an additive manufacturing process that has gained interest for its material fabrication due to multiple advantages, such as the ability to print parts with small feature sizes, good mechanical properties, reduced material waste, etc. However, variations in the key process parameters in LPBF may result in the instantiation of porosity defects and variation in build rate. Particularly, volumetric energy density (VED) is a variable that encapsulates a number of those parameters and represents the amount of energy input from the laser source to the feedstock. VED has been traditionally used to inform the quality of the printed part but different values of VED are presented as optimal values for certain material systems. An optimal VED value can be maintained by changing the key process parameters so that various combinations yield a constant value. In this study, an optimal constant VED value is maintained while printing SS316L with variable key processing parameters. Porosity analysis is performed using optical microscopy, as well as X-ray computed tomography, to reveal the volume density and distribution of those pores. Two primary defect categories are identified, namely lack of fusion and porosity induced by balling defects. The findings indicate that, even at optimal VED, variations in process parameters can significantly influence defect type, underscoring the sensitivity of defect formation to the variation of these parameters. Furthermore, a minor change in the build rate, driven by adjustments in process parameters, was found to influence defect categories. These findings emphasize that fine tuning the process parameters and build rate is essential to minimize defects. Finally, fiducial marks have been identified as a source of unintentional porosity defects. These results enable the refinement of process parameters, ultimately optimizing LPBF to achieve enhanced material density and expedite the printing.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A method for mapping submicron-scale crystallographic order/disorder applied to human tooth enamel

Tooth enamel, the outermost layer of human teeth, is a complex, hierarchically structured biocomposite. The details of this structure are important in multiple human health contexts, from understanding the progression of dental caries (tooth decay) to understanding the process of amelogenesis and related developmental defects. Enamel is composed primarily of long, nanoscale crystallites of hydroxyapatite that are bundled by the thousands to form micron-scale rods. Studies with transmission electron microscopy show the relationships between small groups of crystallites and X-ray diffraction characterize averages over many rods, but the direct measurement of variations in local crystallographic structure across and between enamel rods has been missing. Here, we describe a synchrotron X-ray-based experimental approach and a novel analysis method developed to address this gap in knowledge. A ~500-nm-wide beam of monochromatic X-rays in conjunction with a sample section only 1 μm in thickness enables 2D diffraction patterns to be collected from small well-separated volumes within the enamel microstructure but still probes enough crystallites (~300 per pattern) to extract population-level statistics on crystallographic features like lattice parameter, crystallite size, and orientation distributions. Furthermore, the development of a quantitative metric to characterize relative order and disorder based on the azimuthal autocorrelation of diffracted intensity enables these crystallographic measurements to be correlated with their location within the enamel microstructure (e.g., between rod and interrod regions). These methods represent a step forward in the characterization of human enamel and will elucidate the variation of the crystallographic structure across and between enamel rods for the first time.

crystallographic order/disorder↗

DOE OSTI2022

3D analysis of TRISO fuel compacts via X-ray computed tomography

In this study, low-enriched uranium oxycarbide (LEUCO) and surrogate tristructural isotropic (TRISO)- coated-particle compacts with particle volumetric packing fractions of 25%, 40%, and 48% were imaged utilizing X-ray-computed tomography. Subsequent 3D image analysis identified and further quantified kernel size, sphericity, and observed porosity. In addition, the spatial distribution, coordination number, and kernel-nearest neighbors were analyzed and compared for the different packing fractions. Metrics such as observed porosity and sphericity enabled quantification and screening for abnormal kernels within TRISO compacts. Assessment of TRISO particle location confirmed and further quantified a non-uniform distribution of TRISO particles with the spatial distribution in the radial direction being roughly described as a dampened sinusoidal function. The amplitude and frequency of this non-uniform distribution increased with increasing packing fraction. Measured kernel-nearest neighbor distances indicated two regions along the radial surfaces of compacts where TRISO particles are more likely to be in intimate contact with one another. These regions were found: (1) at upper and lower faces of compacts (i.e., corners); (2) offset ~10% of a compact's length from the axial center near the exterior surface. Within these regions, small quantities of defective TRISO surrogate particles (48% packing fraction) and defective LEUCO TRISO particles (40% packing fraction) were found. No defective particles were found within 25% packing fraction LEUCO TRISO compacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗