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At least 523 records · Page 29

Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data

In this work, we propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision which generates individual segmentation masks for every object of interest that is recognized in an image. Using an out-of-the-box implementation of Mask R-CNN, instance segmentation is applied to images of metal powder particles produced through gas atomization. Leveraging transfer learning allows for the analysis to be conducted with a very small training set of labeled images. As well as providing another method for measuring the particle size distribution, we demonstrate the first direct measurements of the satellite content in powder samples. After analyzing the results for the labeled data dataset, the trained model was used to generate measurements for a much larger set of unlabeled images. The resulting particle size measurements showed reasonable agreement with laser scattering measurements. The satellite measurements were self-consistent and showed good agreement with the expected trends for different samples. Finally, we present a small case study showing how instance segmentation can be used to measure spheroidite content in the UltraHigh Carbon Steel DataBase, demonstrating the flexibility of the technique.

36 MATERIALS SCIENCE↗

Nanoarray-Based Monolithic Adsorbers for SO 2 Removal

Nanoarray-based monolithic catalysts have been developed for various applications, including CO oxidation, hydrocarbon combustion, lean NO x trapping, and low-pressure CO 2 hydrogenation. In this work, SO 2 adsorption properties have been explored and evaluated on the cordierite honeycomb monoliths grown with zinc oxide nanoarray (ZnO), zinc oxide nanoarray washcoated by BaCO 3 nanoparticles (ZnO/BaCO 3 ), and manganese oxide nanowire array with cryptomelane structure (MnO x ) at a temperature range from 50 to 425 °C. All samples show temperature-dependent SO 2 adsorption behaviors. The adsorption results reveal the performance order: MnO x > ZnO/BaCO 3 > ZnO, with ~ 90% SO 2 adsorbed in MnO x at 425 °C. Washcoated BaCO 3 contributes to the improvement of SO 2 adsorption in ZnO nanoarray, and the best performance displayed in MnO x may be attributed to their high specific surface area. After regeneration, nanoarrays all exhibit good thermal stability during test-regeneration cycles. No additional phase is formed in regenerated ZnO nanoarrays (ZnO-R), while BaCO 3 is converted to BaSO 4 in the regenerated ZnO/BaCO 3 nanoarrays (ZnO/BaCO 3 -R), and the sulfur species (possibly MnSO 4 ) and Mn 2 O 3 are found in regenerated MnO x nanoarrays (MnO x -R). It is noted that a small amount of sulfur species (possibly MnSO 4 ) may promote the SO 2 adsorption of MnO x -R at a lower temperature, while the formed Mn 2 O 3 contributes to the deactivation of MnO x -R.

36 MATERIALS SCIENCE↗

Velocity Extraction Using Complete Time-Domain Waveform Data and Audio Machine Learning

We developed a new machine learning-based tool for extracting information from interferometry measurements: MIDWAZE (Modular Interferometry Direct Waveform AnalyZEr). This paper showcases MIDWAZE’s ability to extract an object’s velocity information from Photonic Doppler Velocimetry (PDV) data at near-human accuracy with little to no human intervention. MIDWAZE can extract velocities roughly 350 times as fast as a human analyst "rushing" to complete their extractions, with similar extraction accuracy. MIDWAZE’s most outstanding feature is that it operates directly in waveform/temporal space, freeing analysis from certain limitations imposed by traditional spectrogram-based approaches and opening the way to "phase aware" PDV analysis. MIDWAZE also has limited ability to discriminate between different solid objects, which we develop as a first step towards automated discrimination of different kinds of objects such as ejecta clouds.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Monte Carlo simulations of Cu/Ni–Si–Mn co-precipitation in duplex stainless steels

First-Passage Kinetic Monte Carlo (FPKMC) simulations of species migration in duplex stainless steels were performed in order to establish relationships between alloy content, segregation behavior, and the formation of Ni-Si-Mn rich particles in cast duplex stainless steels during thermal aging. The Ni-Si-Mn-rich second phase forms after extended aging at reactor operating temperatures and degrades alloy properties. Simulations of Ni-Si-Mn cluster formation were validated through comparison with experimental results obtained through Atom Probe Tomography (APT) on similar alloy compositions, identifying several trends. First, Cu promotes the formation of Ni-Si-Mn clusters, but only when Ni or Mn prefer segregation to the surface of Cu particles; without the segregation of these species, the critical composition for the clusters to form was not achieved. Second, the width of precipitate-denuded zones near ?/d interfaces increases with decreasing Cu content. This finding was in strong agreement with APT results, further validating our model. Finally, our model predicts that Ni-Si-Mn cluster formation will be the most extensive when the Si:Mn ratio is approximately 1:1 and the least extensive when one of these key elements is less concentrated (Mn = 0.5 at.% or Si = 0.5 at.%). The implications of these results on how to improve alloy properties are discussed.

Cu co-precipitation, Atom probe tomography (APT), ↗

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗

Precipitation-site competition in duplex stainless steels: Cu clusters vs spinodal decomposition interfaces as nucleation sites during thermal aging

Competing microstructural evolution mechanisms can exist simultaneously when duplex stainless steels are operating for several decades in a high temperature service environment. Such competition between different microstructural evolution pathways can be difficult to ascertain using simple model alloy systems necessitating detailed structural and compositional analysis of phase transformation mechanisms in complex alloys Thus, in this study duplex stainless steels with complex but well understood chemistries were used to investigate the relative importance of different heterogeneous nucleation sites – specifically spinodal decomposition and Cu clustering – on precipitation of Ni-Si-Mn particles during long term thermal aging. Precipitation of Ni-Si-Mn particles in duplex stainless steels and ferritic steels during thermal aging and irradiation is known to have profound effect on mechanical properties. Using duplex stainless steels with custom modified compositions along with atom probe tomography characterization and first-passage kinetic Monte Carlo (FPKMC) simulations it is revealed that while the interface between Cr and Fe formed during spinodal decomposition can be a pathway for diffusion of Ni, Si, Mn, and Cu, it is not a site that encourages precipitation of Ni-Si-Mn rich particles. Instead, the presence of a higher concentration of Cu in these steels leads to formation of small Cu clusters with high energy interfaces that act as nucleation sites for Ni-Si-Mn particles because of its strong interaction particularly with Ni increasing the chemical driving force for precipitation. These results will help inform predictive models for the use of duplex stainless steels and other precipitation-hardened alloys for extended operation at high temperatures.

Duplex stainless steel, Thermal aging, Precipitati↗

In situ synchrotron investigation of degenerate graphite nodule evolution in ductile cast iron

Ductile cast irons (DCIs) are of increasing importance in the renewable energy and transportation sectors. The distribution and morphology of the graphite nodules, in particular the formation of degenerate features during solidification, dictate the mechanical performance of DCIs. In situ high-speed synchrotron X-ray tomography was used to capture the evolution of graphite nodules during solidification of DCI, including degenerate features and the effect of the carbon concentration field. The degeneration of nodules is observed to increase with re-melting cycles, which is attributed to Mg-loss. The dendritic primary austenite and carbon concentration gradients in the surrounding liquid phase were found to control nodule morphology by locally restricting and promoting growth. A coupled diffusion-mechanical model was developed, confirming the experimentally informed hypothesis that protrusions form through liquation cracking of the austenite shell and subsequent localised growth. In conclusion, these results provide valuable insights into the solidification kinetics of cast irons, supporting the design of advanced alloys.

36 MATERIALS SCIENCE↗

Origin, parameters, and underlying deformation mechanisms of propagating deformation bands in irradiated 316L stainless steel

Lüders-type propagating deformation bands were observed in specimens of irradiated 316L stainless steel samples removed from Spallation Neutron Source target vessels after service. Mechanical testing with digital image correlation (DIC) and in-situ tensile testing with scanning electron microscopy electron backscatter diffraction showed that the observed Lüders-type behavior was not related to the known transformation-induced plasticity or twinning-induced plasticity behavior. Instead, the phenomenon occurs at small local strain values before a significant amount of martensite or deformation twins appear in the microstructure. Microstructural analysis and in-situ mechanical test results suggest Lüders-type band formation and propagation were related to the appearance and evolution of defect-free channels—analogous to slip bands. A modified Swift equation with a Ludwigson-like component was offered to rationalize the phenomenon and model the strain-softening processes at small strain values. Finally, the results indicate complex microstructural processes and deformation mechanisms were active at small strain values and underline the benefits of advanced mechanical test approaches such as DIC.

36 MATERIALS SCIENCE↗

MX precipitate behavior in an irradiated advanced Fe-9Cr steel: Helium effects on phase stability

As part of an ongoing series aimed at optimizing Fe-9Cr reduced activation ferritic/martensitic (RAFM) alloys for fusion energy systems, this study explores MX precipitate behavior under dual-ion irradiations, specifically examining correlations between helium transmutation and irradiation-induced damage. Utilizing single and dual-beam ion irradiation, the research explores the combined effects of helium (10–25 appm He/dpa), temperature (400–600 °C), and damage levels (15–100 dpa) on the microstructural evolution of CNA9 steel, a variant of Castable Nanostructured Alloys (CNAs). The study demonstrates that helium co-implantation hinders radiation-enhanced coarsening of MX-TiC precipitates at 500 and 600 °C, maintaining MX-TiC precipitate stability at moderate damage levels (15 dpa) but failing to prevent complete precipitate dissolution at higher damage levels (≥50 dpa) when irradiated at 500 °C. Here, a generalized precipitate stability model suggests that helium-induced suppression of diffusion alters the balance between recoil resolution and back diffusion for MX-TiC precipitates, enhancing the current understanding of precipitate behavior under damage and transmutation simulated dual-ion irradiation conditions.

Characterization↗

MX precipitate behavior in an irradiated advanced Fe-9Cr steel: Self-ion irradiation effects on phase stability

In an effort to optimize Fe-9Cr reduced activation ferritic/martensitic (RAFM) steels and to inform the design and operation of fusion reactors, this work represents the first in a series of cohesive studies dedicated to the evolution of MX-TiC precipitates under accelerated single and dual ion irradiations. This study investigates CNA9, a simplified Fe-9Cr RAFM steel featuring initial MX-TiC precipitate densities of (2.3±0.3)×10²¹ m⁻³. This material was subjected to single self-ion irradiation at damage levels ranging from 1 to 100 displacements per atom (dpa) over a temperature range of 300 to 600°C, with a nominal dose rate of 7×10⁻⁴ dpa/s. Irradiation-induced coarsening was observed, as evidenced by statistically significant increases in mean diameter sizes, at 15 dpa at both 500°C and 600°C, whereas no coarsening was noted at 300°C or 400°C. Further, complete dissolution of precipitates occurred at damage levels of 50 and 100 dpa across the two temperatures tested (300°C and 500°C) while no significant changes were observed at any doses below 15 dpa at 500°C. Experimentally parameterized recoil resolution modeling suggests that the observed radiation stability of MX-TiC precipitates is intricately linked to diffusional changes of solutes resulting from the co-evolution of microstructural features within the experiments. The findings align with current theoretical perspectives on radiation-induced precipitate stability in complex alloys.

36 MATERIALS SCIENCE↗

Hydrometeorological sensitivities of net ecosystem carbon dioxide and methane exchange of an Amazonian palm swamp peatland

Here, we report ecosystem-scale CO 2 and CH 4 flux observations for an Amazonian palm swamp peatland over a two-year period in relation to hydrometeorological forcings. Seasonal and short-term variations in hydrometeorological forcing had a strong effect on carbon dioxide and methane fluxes. High air temperature and vapor pressure deficit exerted an important limitation on photosynthesis during the dry season, while latent heat flux appeared to be insensitive to these climate drivers. Evidence from light-response analyses and flux partitioning support that photosynthetic activity was downregulated during dry conditions, while ecosystem respiration was either inhibited or enhanced depending on water table position. The cumulative net ecosystem carbon dioxide exchange indicated that the peatland was a significant carbon dioxide sink ranging from –465 (–279 to –651) g C m -2 y -1 in 2018 to –462 (–277 to –647) g C m -2 y -1 in 2019. The forest was a methane source of 22 (20 to 24) g C m -2 y -1 , similar in magnitude to other tropical peatlands and larger than boreal and arctic peatlands. Furthermore, the annual carbon budget of this Amazonian palm swamp peatland appears to be a major carbon sink under current hydrometeorological conditions, but evidence indicates that the sink strength is vulnerable to future climate change.

54 ENVIRONMENTAL SCIENCES↗

Effects of Cr/Zircaloy-4 coating qualities for enhanced accident tolerant fuel cladding

Cr-coated zirconium alloys represent a modern approach to enhance cladding safety during accident scenarios. Two high-power impulse magnetron sputtered Cr-coated Zry-4 systems were subjected to simulated loss-of-coolant accident conditions to investigate cladding performance. The first Cr-coating (4.8 µm thick) was deposited onto Zry-4 cladding and exhibited through-thickness cracking while the second Cr-coating (6.8 µm thick) was deposited with improved deposition parameters onto polished Zry-4 and exhibited no cracking. During burst testing, the coating with a higher density of defects failed to consistently reduce oxidation and exhibited similar burst behavior as Zry-4. In contrast, the second Cr-coating reduced ZrO 2 formation through formation of Cr 2 O 3 and displayed enhanced burst temperatures by ~80 °C compared to Zry-4. Utilizing an empirical relation for burst behavior of zirconium alloys, the 6.8 µm Cr/Zry-4 system displayed enhanced burst temperatures equivalent to an effective 0.464 mm increase in Zry-4 wall thickness, highlighting the value of continuous Cr coatings for accident scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling and Evaluation of Cyber-Attacks on Grid-Interactive Efficient Buildings

Grid-interactive efficient buildings (GEBs) are not only exposed to passive threats (e.g., physical faults) but also active threats such as cyber-attacks launched on the network-based control systems. The impact of cyber-attacks on GEB operation are not yet fully understood, especially as regards the performance of grid services. To quantify the consequences of cyber-attacks on GEBs, this paper proposes a modeling and simulation framework that includes different cyber-attack models and key performance indexes to quantify the performance of GEB operation under cyber-attacks. The framework is numerically demonstrated to model and evaluate cyber-attacks such as data intrusion attacks and Denial-of-Service attacks on a typical medium-sized office building that uses the BACnet/IP protocol for communication networks. Simulation results show that, while different types of attacks could compromise the building systems to different extents, attacks via the remote control of a chiller yield the most significant consequences on a building system’s operation, including both the building service and the grid service. It is also noted that a cyber-attack impacts the building systems during the attack period as well as the post-attack period, which suggests that both periods should be considered to fully evaluate the consequences of a cyber-attack.

Fu, Yanyang↗

Quantifying agricultural productive use of energy load in Sub-Saharan Africa and its impact on microgrid configurations and costs

The use of advanced energy technologies for agricultural purposes—such as irrigation, refrigeration, crop processing, and egg incubation—has the potential to increase crop yield, reduce vulnerability to changing precipitation patterns, increase shelf life, strengthen income and employment opportunities in rural areas, and reduce emissions by displacing fossil fuel-based technologies. These productive uses of energy (PUE) in remote areas could potentially be powered by microgrids that additionally serve otherwise unelectrified communities, most of which are located in rural Sub-Saharan Africa. Here, in this paper, we use high-resolution geospatial data to estimate the end-use electricity demand for a range of agricultural PUE across Sub-Saharan Africa, and we share these data in an open-access mapping tool. Next, we use REopt®, a techno-economic optimization model of energy systems, to determine the cost and system sizing implications of incorporating agricultural PUE into microgrid designs in Kenya and Zambia. We estimate the upper bound of agricultural PUE demand for irrigation, milling, shelling, refrigeration, and egg incubation across Sub-Saharan to be 16.8 TWh/yr. We find that incorporating local agricultural PUE into microgrid system designs increases the required system sizing while having minimal impact on the levelized cost of energy of these systems. Our analysis is the first to demonstrate the PUE potential in the agricultural sector at a 10x10-kilometer resolution across Sub-Saharan Africa and to show, at scale, how site-specific PUE can impact the cost and sizing of microgrids that are otherwise deployed to serve local household and community load.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analysis of power conversion technology options for a self-powered furnace

A self-powered furnace is defined as one that imports no electricity: a power cycle integrated into the furnace generates all the electrical power needed, and the heat rejected by the power cycle contributes to space heating. This paper presents criteria for selection of suitable power generation technology for such a furnace. A weighting system was presented to assign weight to each criterion based on its importance to the success of a self-powered furnace implementation. Power generation candidates were reviewed and scored based on the selection criteria. The top five candidates were analyzed to quantitatively compare the additional heat exchange requirements they impose on a baseline furnace. Air-cooled internal combustion engines and microturbine generators had negligible impact on the heat exchange requirement compared to a baseline furnace. Liquid-cooled internal combustion engines increased the heat exchange requirement by a factor of 1.5. Thermoelectric generators and thermophotovoltaic increased the heat exchange requirement by a factor of roughly 2.5. Organic Rankine cycle increased the heat exchange requirement by a factor of 5.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Parametric optimization of PCM-enhanced underground thermal energy storage for buildings in moderate cold climates

This study presents a novel underground thermal energy storage (UTES) system designed for space heating in buildings located in moderate cold climates. The proposed UTES features a borehole with a depth of 25 ft. (7.62 m) and a diameter of 3 ft. (0.91 m), containing two helical pipe loops-one for discharge fluid and another for recharge fluid-and a thermally enhanced phase change material (PCM) layer that provides high energy storage capacity. The system requires daily thermal recharging using a low-grade heat source for a few hours and delivers continuous heating at a nearly constant discharge rate without significant performance degradation over a 24-h period. This study demonstrates that the optimized UTES, when recharged with hot fluid at an inlet temperature of 40 degrees C for 6 h daily, can provide a continuous heat discharge rate of approximately 2.9 kW for 24 h or 3.4 kW if operated under a shorter discharge period of 15 h (17:00-08:00). With a round-trip efficiency of 72-97%, the proposed UTES offers an efficient and reliable solution for short- and long-duration thermal energy storage technology, making it a promising technology for cold climates.

15 GEOTHERMAL ENERGY↗

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Suicide is a leading cause of death worldwide, and non-fatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium. The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via mtCOJO, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders and other known risk factors. Results: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged. Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

60 APPLIED LIFE SCIENCES↗