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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗
DOE OSTI2023

Fierro Version 2.x

FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three-dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.

Morgan, Nathaniel↗
DOE OSTI2023

Fierro

FIERRO is a parallel C++ code designed to simulate fluid mechanics, heat transfer, and solid mechanics in two- and three dimensional space. FIERRO is written to run on homogeneous (CPU) and heterogeneous (CPU+GPU) high performance computing machines. Fierro can aid a) modeling and design efforts that have historically relied on commercial implicit and explicit finite element codes, b) numerical methods research, c) manufacturing research, and d) computer science research. The code contains diverse numerical methods to solve the governing physics equations for both quasi-static and dynamic problems. Mathematical optimization solvers are coupled to the numerical methods to research topology and shape optimization that has application to additive manufacturing, and to create novel numerical approaches. Phase-field methods with micromechanical solvers are provided to simulate microstructure formation and evolution in manufacturing processes. The micromechanical solvers can also help research efforts create continuum-scale constitutive models for solids, as a function of the microstructure, in situ in a calculation or in a stand-alone manner. No physical data exists within the code.

Morgan, Nathaniel↗
DOE OSTI2020

A Bezier Curve Informed Melt Pool Geometry to Model Additive Manufacturing Microstructures Using SPPARKS

Additive manufacturing is a transformative technology with the potential to manufacture designs which traditional subtractive machining methods cannot. Additive manufacturing offers fast builds at near final desired geometry; however, material properties and variability from part to part remain a challenge for certification and qualification of metallic components. AM induced metallic microstructures are spatially heterogeneous and highly process dependent. Engineering properties such as strength and toughness are significantly affected by microstructure morphologies resulting from the manufacturing process Linking process parameters to microstructures and ultimately to the dynamic response of AM materials is critical to certifying and qualifying AM built parts and components and improving the performance of AM materials. The AM fabrication process is characterized by building parts layer by layer using a selective laser melt process guided by a computer. A laser selectively scans and melts metal according to a designated geometry. As the laser scans, metal melts, fuses, and solidifies forming the final geometry in a layerwise fashion. As the laser heat source moves away, the metal cools and solidifies forming metallic microstructures. This work describes a microstructure modeling application implemented in the SPPARKS kinetic Monte Carlo computational framework for simulating the resulting microstructures. The application uses Bzier curves and surfaces to model the melt pool surface and spatial temperature profile induced by moving the laser heat source; it simulates the melting and fusing of metal at the laser hot spot and microstructure formation and evolution when the laser moves away. The geometry of the melt pool is quite flexible and we explore effects of variances in model parameters on simulated microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Predictive multiphase evolution in Al-containing high-entropy alloys

The ability to predict and understand phases in high-entropy alloys (HEAs) is still being debated, and primarily true predictive capabilities derive from the known thermodynamics of materials. The present work demonstrates that prior work using high-throughput first-principles calculations may be further utilized to provide direct insight into the temperature- and composition-dependent phase evolution in HEAs, particularly Al-containing HEAs with a strengthening multiphase microstructure. Using a simple model with parameters derived from first-principles calculations, we reproduce the major features associated with Al-containing phases, demonstrating a generalizable approach for exploring potential phase evolution where little experimental data exists. Neutron scattering, in situ microscopy, and calorimetry measurements suggest that our high-throughput Monte Carlo technique captures both qualitative and quantitative features for both intermetallic phase formation and microstructure evolution at lower temperatures. This study provides a simple approach to guide HEA development, including ordered multi-phase HEAs, which may prove valuable for structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In situ measurement of damage evolution in shocked magnesium as a function of microstructure

Accurate modeling and prediction of damage induced by dynamic loading in materials have long proved to be a difficult task. Examination of postmortem recovered samples cannot capture the time-dependent evolution of void nucleation and growth, and attempts at analytical models are hindered by the necessity to make simplifying assumptions, because of the lack of high-resolution, in situ, time-resolved experimental data. We use absorption contrast imaging to directly image the time evolution of spall damage in metals at ~1.6-μm spatial resolution. We observe a dependence of void distribution and size on time and microstructure. The insights gained from these data can be used to validate and improve dynamic damage prediction models, which have the potential to lead to the design of superior damage-resistant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructurally driven self-sharpening mechanism in beaver incisor enamel facilitates their capacity to fell trees

Beavers ( Castor ) stand out among mammals for their unique capacity to fell trees using their large, ever-growing incisors. This routine consumption of resistant fodder induces prodigious wear in the lower incisors, despite this blunting effect the incisors maintain a remarkably sharp cutting edge. Notably, the enamel edges of their incisors show a highly complex two-part microstructure of which the biomechanical import is unknown. Here, using fracture analysis, nanoindentation, and wear testing on North American beaver ( C. canadensis ) incisors we test the microstructure's possible contribution to maintaining incisal sharpness. Although comparable in hardness, the inner enamel preferentially fails and readily wears at 2.5 times the rate of the outer enamel. The outer microstructure redirects all fractures in parallel, decreasing fracture coalescence. Conversely, the inner microstructure facilitates crack coalescence increasing the wear rate by isolating layers of enamel prisms that readily fragment. Together these two architectures form a microstructurally driven self-sharpening mechanism contained entirely within the thin enamel shell. Here, our results demonstrate that enamel microstructures exposed at the occlusal surface can markedly influence both enamel crest shape and surface texture in wearing dentitions. The methods introduced here open the door to exploring the biomechanical functionality and evolution of enamel microstructures throughout Mammalia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Understanding Fission Gas Bubble Distribution and Zirconium Redistribution in Neutron-irradiated U-Zr Metallic Fuel Using Machine Learning

U-10wt.% Zr (U-10Zr) based metallic fuel is the leading candidate for next-generation sodium cooled fast reactor in United States. Currently, Idaho National Laboratory (INL) has been the leading national laboratory for research, development, and demonstration (RD&D) on metallic fuel. Advanced post-irradiation characterization will help to understand fuel microstructure and property change during irradiation, benefiting fuel qualification for commercial application. Characterization capabilities ranging from sub-nanometer to micrometer, such as scanning electron microscopy (SEM), focused ion beam (FIB) sampling, transmission electron microscopy (TEM) characterization, and local thermal conductivity microscopy (TCM), have been utilized recently on irradiated U-10Zr fuel samples to gain a better understanding of nuclear fuel microstructure and property evolution inside a reactor. The FIB/SEM coupled with energy dispersive X-ray spectroscopy (EDS) can capture the essential information to achieve better understanding of fuel behaviors. Inside a nuclear reactor, the phase and microstructure of U-10Zr is constantly changing under neutron bombardment. For example, the gaseous fission product atoms have a limited solubility inside fuel matrix and tend to precipitate out in bubble form, which not only contribute to fuel thermal conductivity degradation but also provide a shortcut for movement of fission products, i.e. lanthanides. The resultant deposition of lanthanides at the cladding inner surface will potentially trigger a chemical reaction/interaction between nuclear fuel and cladding at reactor operational conditions, threatening fuel integrity and safety. FIB/SEM coupled with EDS can provide the fission bubble information as well as probe into phase separation or Zr redistribution, which is fundamental to predict the fuel performance. With high velocity image data generating method, such as FIB/SEM, an automatic way to extract the microstructural information quantitively can better serve the needs from post irradiation characterization. A trained machine learning model, named Decision Tree, is employed to generate a bubble classifier and to categorize bubbles into three categories: isolated bubble, connected without lanthanides, and connected with lanthanides bubbles[3]. This work presents a showcase of this approach on six regions of a fuel cross-section along the radial temperature gradient. We obtained distributions of bubble categories and porosity rates along the six regions. Moreover, a secondary phase U-Zr2 was determined and found on regions 5 and 6. The secondary phase fraction was increasing from 15.61% in region 5 to 34.79% in region 6 based on this approach . This quantitative data offers insights into the lanthanide migration and potentially thermal conductivity degradation. This information from machine learning will be fed into fuel design code for better prediction of fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Genetic programming for interpretable, data-driven continuum damage models.

The damage mechanisms that lead to failure in engineering alloys have been studied extensively, but converting this knowledge into constitutive models that are suitable for engineering-scale analysis remains a challenge. Evolution laws for continuum damage have been developed in the past and have proven effective but suffer from many non-physical assumptions that inhibit the overall accuracy of the model. Further, the assumptions inherent in these existing models prevent them from being applicable to a broad class of materials. At the same time, computational models of fine-scale damage mechanisms continue to advance making it tractable to generate large training data sets through computer simulation. Data-driven machine learning approaches can leverage these data sets to avoid making limiting assumptions, and instead produce models directly from the results of microstructural simulations and/or experiments. Many of these machine learning approaches are rapid and accurate, but they offer little to no insight into the underlying relationships among state variables being discovered. Conversely, genetic programming symbolic regression (GPSR) is a machine learning method that produces analytic expressions relating the state variables, allowing maximal insight and interpretability. To that end, we propose using GPSR as a data-driven method of obtaining microstructurally informed continuum damage models. Data is generated using microstructural simulations of damage evolution, parameterized over microstructural statistics (i.e., pore shape) and nominally applied deformations. Analytic expressions for damage evolution are obtained from the data using GPSR, and these expressions are then utilized within a continuum constitutive model. Overall, this approach is a promising method of automatically obtaining analytic relations describing constitutive phenomena in a material.

Buche, Michael Robert↗
NASA NTRS1987

Effect of undercooling on the microstructure of Ni-35 at. pct Mo (eutectic) and Ni-38 at. pct Mo (hypereutectic) alloys

Ni-35 at. pct Mo and Ni-38 at. pct Mo alloy specimens have been solidified from various levels of undercooling in the differential thermal analysis and the electromagnetic levitation units in a pyrex/vycor bed. The evolution of the microstructure in the solified specimens has been examined in terms of the degree of undercooling, the nature of the first phase to nucleate from the melt, and the specimen cooling rate. The melt has been observed to undercool more in the presence of intermetallic NiMo (beta) phase as compared to that in the presence of nickel-rich solid solution (gamma). The 'anomalous eutectic' type of microstructure has been shown to result from the initial formation of the dendritic skeleton of either of the two phases, its segmentation due to convection and ripening, and the subsequent nucleation of the other phase in the interdendritic liquid regions. The recalescence behavior has been examined as a function of undercooling and the nature of the phase nucleating first in the melt.

Tewari, S. N.↗
DOE OSTI2019

Microstructure and Mechanical Properties of Copper Billets Fabricated by the Repetitive Extrusion and Free Forging Process

In the present study, with the aim of obtaining a weakened texture, grain refinement and improved mechanical properties, copper billets were successfully fabricated using the severe plastic deformation method of repetitive extrusion and free forging (REFF) without using any additional tools or devices. The evolution of the microstructure, texture and mechanical behavior of the ultrafine grain copper billets over an increasing number of REEF cycles was also systematically studied. Our results show that the effective strain per REFF process was ε = 2.35. After two cycles of REFF process, the sum effective strain became ε = 4.7, leading to high efficiency of grain refinement. The grain size was refined from 50 to 0.8 μm; the yield strength was increased to 462 MPa, and we obtained a weakened texture in the pure copper billets. By increasing the number of cycles, the grain refinement ability was decreased, and the texture was thus strengthened further. Therefore, two cycles of REFF were a reasonable process for producing ultrafine-grained copper billets.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Crack Initiation Behavior of Cold-Worked Alloy 690 in Simulated PWR Primary Water - Role of Starting Microstructure, Applied Stress and Cold Work on Precursor Damage Evolution

Long-term stress corrosion crack (SCC) initiation behavior in Alloy 690 is being evaluated by constant load tensile testing in simulated pressurized water reactor primary water. Seven commercial Alloy 690 heats with different starting microstructures and cold-work levels are being tested at either 90% or 100% of the material yield stress. Previous studies have revealed grain boundary (GB) cavity formation after 7,110 to 9,220 hours of exposure in certain thermally treated (TT) Alloy 690 heats in highly cold-worked (CW) conditions, serving as precursors to intergranular cracks. This paper summarizes the new characterization results for the evolution of GB cavities in four Alloy 690TT heats in 21% and 31%CW conditions loaded at yield stress after 18,400 hours of exposure. Link-up of GB cavities has led to formation of long internal creep cracks, resulting in crack initiation detected by direct current potential drop in a highly CW Alloy 690TT heat with uniform, semi-continuous distribution of small GB carbides. In comparison, highly CW materials featuring larger and more widely spaced GB carbides did not show a significant increase in GB cavity density or size. Quantitative assessments were performed on GB cavity evolution in highly CW specimens for two Alloy 690TT heats demonstrating the strong dependence of GB cavity evolution on applied stress and starting GB microstructure.

Zhai, Ziqing↗
DOE OSTI2022

Friction stir welding and self-ion irradiation effects on microstructure and mechanical properties changes within oxide dispersion strengthened steel $\mathrm{MA956}$

We report the joining process for oxide dispersion strengthened (ODS) alloys remains a key challenge facing the nuclear community. The microstructure and mechanical properties were characterized in the base material and friction stir welded ODS MA956 irradiated with 5 MeV Fe 2+ ions from 400 to 500°C up to 25 dpa. Nanoindentation was performed to assess changes in hardness and yield stress, and the dispersed barrier hardening (DBH) model was applied to described results. A combination of scanning transmission electron microscopy (STEM) and atom probe tomography (APT) were used to assess evolution of the microstructure including dispersoids, network dislocations and dislocation loops, nanoclusters, and solid solution concentrations. Overall, softening was observed as a result of increased dose, which was exacerbated at 500°C. The formation and coarsening of new dispersoids was noted while nanoclusters tended to dissolve in the base material, and were not observed in the stir zone. Solute nanocluster evolution was identified as a primary driver of the changes in mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. Here, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Viscous Shear Banding in Cutting of Metals

Shear banding is a type of plastic flow instability with often adverse implications for cutting and deformation processing of metals. Here, we study the mechanics of plastic flow evolution within single shear bands in Ti- and Ni-based alloy systems. The local shear band displacement profiles are quantitatively mapped at high resolution using a special micromarker technique. The results show that shear bands, once nucleated, evolve by a universal viscous sliding mechanism that is independent of microstructural details. The evolution of local deformation around the band is accurately captured by a momentum diffusion equation based on a Bingham-type flow rule. The predicted band viscosity is very small, compared to those of liquid metals. A plausible explanation for this small viscosity and fluid-like behavior at the band, based on phonon drag, is presented.

Engineering↗
DOE OSTI2025

Bulk nanocrystalline Al–Mg–Y alloys with amorphous grain boundary complexions display high strength and compressive plasticity

Although nanocrystalline alloys regularly exhibit high strengths, their use in structural applications often face challenges due to sample size limitations, unstable microstructures, and the limited ability to plastically deform. The incorporation of amorphous grain boundary complexions has been proposed to address these issues, by simultaneously stabilizing nanocrystalline grain structures for scale-up processing and improving alloy toughness. In the present study, the mechanical behavior of bulk nanocrystalline Al–Mg–Y is examined with macroscale compression testing, probing a length scale that is relevant to real-world structural applications. Bulk samples were fabricated via a simple powder metallurgy approach, with different hot-pressing temperatures and durations employed for consolidation in order to investigate microstructural and property evolution. All of the specimens contained primary face-centered cubic Al and secondary Al 4 C 3 and Al 3 Y phases, with the Al 3 Y particles exhibiting two populations of small equiaxed and larger elongated particles. Appreciable plasticity was measured along with high ultimate stresses over 800 MPa due to the presence of amorphous grain boundary complexions. Microstructural characterization of fracture surfaces revealed that the area fraction of dimpled regions increased with longer hot-pressing time. Most importantly, the elongated Al 3 Y particles formed regular cellular patterns with increasing hot-pressing time, delaying shear localization and significantly enhancing plasticity. The hierarchy present in the microstructure of the Al–Mg–Y alloy, from amorphous grain boundary complexions to secondary phases, gives rise to excellent bulk mechanical properties, which are attractive for structural applications.

Bulk nanocrystalline alloy↗
DOE OSTI2018

Effect of annealing after strip casting on microstructure, precipitates and texture in non-oriented silicon steel produced by twin-roll strip casting

Highlights: • Non-oriented silicon steel with superior magnetic properties was produced by twin-roll strip casting. • The effect of annealing after strip casting on microstructure, precipitates and texture was investigated. • Role of precipitates in microstructure and texture evolution along the entire route was explored. • High magnetic induction and strong λ-fiber texture was obtained by optimizing strip annealing process. - Abstract: A 3.1 mm thick non-oriented Fe-1.0% Si steel as-cast strip was produced by twin-roll strip casting. Samples with/without strip annealing were cold rolled to 0.5 mm and then annealed. The development of microstructure, precipitate and texture was characterized along the entire processing route. It was found that annealing after strip casting had a minor influence on the average grain size and texture of the as-cast strip. A large number of particles precipitated and coarsened during the strip annealing process. Meanwhile, precipitates hindered dislocation slip and crystal rotation such that more significant in-grain shear bands were formed in cold rolled sheets. During recrystallization annealing process, the newly formed fine precipitates in directly cold-rolled sheets consumed stored strain energy and also hindered grain growth. But the initial precipitates in the annealed strip grew further and the effect of pinning of dislocations and grain boundary was lost. Therefore, annealed sheets with strip annealing process showed homogeneous equiaxed grains and the recrystallization texture was characterized by strong λ-fiber texture, which led to high permeability.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructural and phase changes in alpha uranium investigated via in-situ studies and molecular dynamics

A deeper knowledge of thermally induced microstructural and phase evolution in nuclear metallic fuel can be obtained using novel in-situ microscopic analyses. Such studies can provide information on the dynamics of phase transitions which is not possible with conventional postmortem characterization (post-irradiation examination). In this work, the behavior of alpha uranium (α-U) was investigated via in-situ heating tests in a transmission electron microscope. Here, the main objective is to understand the microstructural and phase changes, such as defect annihilation and ß phase formation and retention, observed in reactor in-pile transient studies at the Transient Reactor Test facility. Indeed, defect migration and rearrangement were observed within the α phase starting at 673 K; α→ß phase transition was observed between 773 K and 1,073 K during the heating ramp (which is in the temperature window reported for α→ß transition temperatures). Recrystallization and formation of nano grains was observed at high temperatures (over 1,073 K). Such recrystallization was possibly related to the formation of the γ phase. Finally, it was indeed observed that the ß phase (but not γ phase) was retained at room temperature upon rapid cooling. Molecular dynamics studies support these experimental results and shows that the γ phase of pure uranium cannot be retained at room temperature if not stabilized with the addition of an alloying element.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗