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At least 271 records · Page 15

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DOE OSTI2025

HPC for Optimizing Process Parameters to Control Material Evolution in Seamless Induction Hardening of Wind Turbine Main Shaft Bearings

Work proposed in this project focused on understanding the effect of martensitic transformation in the steel on the potential for cracking during seamless induction hardening (SIH) as a function of process conditions to allow the process to optimally scale up. Large-scale, three-dimensional phase-field simulations of martensitic transformation were performed using MEUMAPPS-SS (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid State) code developed at Oak Ridge National Laboratory. The simulations were guided by location-specific thermal history generated by experimental measurements of time-temperature history generated at The Timken Company. The simulations were able to capture the morphological evolution of the martensite variants in an Fe-1.0C-1.5Cr steel based on the Nishiyama-Wasserman (NW) orientation relationship. The simulations were also able to quantify the stress-state at the interface between impinging martensite variants. The simulations indicated that the magnitude of the various stress and strain components were dependent on the sizes of the impinging plates with a reduction in these quantities with reduced plate size in agreement with experimental findings. The results obtained from the simulations will be used to guide the optimization of the alloy thermal conditions to eliminate quench cracking during SIH of bearing steels.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

HPC for optimizing process parameters to control material evolution in seamless induction hardening of wind turbine main shaft bearings

17 WIND ENERGY↗

DOE OSTI2026

Engineering Anti-Microbial Peptide Production in Fungi and Bioprocess Development (CRADA 502)

Crop Protection, specifically controlling agricultural diseases and pests, is essential for crop production at every agricultural scale. Biologics hold enormous potential in this equation to decrease use of more toxic pesticides. Currently, the widespread use of biologics in crop protection is severely hampered by the lack of available tools for their mass production. To ensure biologics are regulated under EPA Biopesticide regulations, the following must be true: The biopesticide is a naturally occurring substance or structurally similar and functionally identical to a naturally occurring substance with a history of exposure to humans and the environment demonstrating minimal toxicity. Since this pertains to the marketed product it is also essential that fermentation hosts have a history of exposure and safe use by humans This research focuses on developing a novel platform for the production and delivery of the cghSAMP peptide using the filamentous fungus Aspergillus niger. A. niger is a well-established industrial microorganism, widely recognized for its strong protein secretion capabilities, high-yield production of enzymes, and classification as a generally recognized as safe (GRAS) organism. By genetically modifying A. niger to express the cghSAMP peptide transgene, we aim to leverage the fungus's robust fermentation system to produce a high volume of the antimicrobial agent. This engineered system represents a potential breakthrough in sustainable disease management, offering an environmentally friendly method for localized application or large-scale production of a biopesticide designed to mitigate the effects of citrus greening disease. The main objectives of this project were: 1. Developing a high-yield and cost-efficient bioprocess to produce an AMP in a current ABF host or readily onboarded hosts. 2. Scale up the process in stirred tank reactors and produce at least 100 grams of AMP at 1- 5g/L

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Using defects as a ‘fossil record’ to help interpret complex processes during additive manufacturing: as applied to raster-scanned electron beam powder bed additively manufactured Ti–6Al–4V

Abstract Defects in parts produced by additive manufacturing, instead of simply being perceived as deleterious, can act as important sources of information associated with the complex physical processes that occur during materials deposition and subsequent thermal cycles. Indeed, they act as materials-state ‘fossil’ records of the dynamic AM process. The approach of using defects as epoch-like records of prior history has been developed while studying additively manufactured Ti–6Al–4V and has given new insights into processes that may otherwise remain either obscured or unquantified. Analogous to ‘epochs,’ the evolution of these defects often is characterized by physics that span across a temporal length scale. To demonstrate this approach, a broad range of analyses including optical and electron microscopy, X-ray computed tomography, energy-dispersive spectroscopy, and electron backscatter diffraction have been used to characterize a raster-scanned electron beam Ti–6Al–4V sample. These analysis techniques provide key characteristics of defects such as their morphology, location within the part, complex compositional fields interacting with the defects, and structures on the free surfaces of defects. Observed defects have been classified as banding, spherical porosity, and lack of fusion. Banding is directly related to preferential evaporation of Al, which has an influence on mechanical properties. Lack-of-fusion defects can be used to understand columnar grain growth, fluid flow of melt pools, humping, and spattering events. Graphical abstract

36 MATERIALS SCIENCE↗

DOE OSTI2023

A comparative study of solute trapping in Fe-(33–45 at%) Cu alloys manufactured by laser directed energy deposition

The high cooling rates in laser directed energy deposition (DED-LB) of alloys lead to substantial amounts of solute trapping as solute atoms cannot diffuse away from the solid/liquid interface before it advances. In some concentrated alloys, this results in supersaturated solid phases that form nanoscale hierarchical microstructures when the solute atoms precipitate out during reheating from subsequent laser passes. We choose the Iron-Copper (Fe-Cu) binary alloy as model system as it is chemically homogeneous in the liquid phase and has negligible solid solubility at room temperature. Two alloys with nominal compositions in atomic (at.) %, Fe67Cu33 and Fe55Cu45, were manufactured using DED-LB. Scanning transmission electron microscopy (STEM), energy dispersive spectroscopy (EDS) and wavelength dispersive spectroscopy (WDS) were used to characterize the nanostructures and heterogeneous chemical compositions. A non-equilibrium solute partitioning model was used to compute the supersaturated chemistries of the constituent phases and validated with experimentally measured compositions. The measured phase compositions of the two alloys were very similar, at roughly 12 at.% Cu and 4 at.% Fe in the α(bcc)-Fe and ε(fcc)-Cu phases respectively, despite having different processing parameters and mechanical behavior. This indicates that the total thermal history, that depends on both the processing parameters and laser scan pattern, plays a stronger role on the final microstructure evolution than just the initial quantity of trapped solute. In addition, we find that current non-equilibrium solute partitioning models applied on the continuum scale fall short of predicting accurate quantitative phase compositions in concentrated alloys, although the qualitative trends are captured correctly.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Deep abiotic weathering of pyrite

Pyrite is a ubiquitous iron sulfide mineral that is oxidized by trace oxygen. The mineral has been largely absent from global sediments since the rise in oxygen concentration in Earth’s early atmosphere. We analyzed weathering in shale, the most common rock exposed at Earth’s surface, with chemical and microscopic analysis. By looking across scales from 10 −9 to 10 2 meters, we determined the factors that control pyrite oxidation. Under the atmosphere today, pyrite oxidation is rate-limited by diffusion of oxygen to the grain surface and regulated by large-scale erosion and clast-scale fracturing. We determined that neither iron- nor sulfur-oxidizing microorganisms control global pyrite weathering fluxes despite their ability to catalyze the reaction. This multiscale picture emphasizes that fracturing and erosion are as important as atmospheric oxygen in limiting pyrite reactivity over Earth’s history.

58 GEOSCIENCES↗

DOE OSTI2020

Of Clouds and Craters: The History of U.S. Nuclear Weapons Testing

“Now!” With that word, the Atomic Age – and the era of nuclear weapons testing – dawned. The advent of World War II’s first irresistible weapon, which had been secretly tested in the New Mexico desert in July 1945, would help hasten the inevitable: complete victory for the Allies. Codenamed Trinity, the test was the first of over a thousand conducted by the United States between 1945 and 1992. Nuclear weapons would change future clashes as well. The looming Cold War, with roots stretching all the way back to 1917, was history’s first conflict between two, major nations armed with nuclear weapons. It is clear the existence of those weapons played an important role in maintaining a tenuous peace between the United States and the Soviet Union; it is also clear nuclear weapons testing played a prominent role in fueling both the arms race and the success of deterrence. Yet, the history of nuclear weapons testing is rarely remembered, even though nuclear tests have been performed in the very recent past. Of the estimated 2,000-plus nuclear tests ever performed, the U.S. is responsible for approximately half. This is the story of U.S. full-scale nuclear weapons testing.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2020

Titanium Niobium Oxide: From Discovery to Application in Fast-Charging Lithium-Ion Batteries

Lithium-ion batteries are essential for portable technology and are now poised to disrupt a century of combustion-based transportation. The electrification revolution could eliminate our reliance on fossil fuels and enable a clean energy future; advanced batteries would facilitate this transition. However, owing to the demanding performance, cost, and safety requirements, it is challenging to translate new materials from laboratory prototypes to industrial-scale products. This Perspective describes that journey for a new lithium-ion battery anode material, TiNb 2 O 7 (TNO). TNO is intended as an alternative to graphite or Li 4 Ti 5 O 12 with better rate and safety characteristics than the former and higher energy density than the latter. The high capacity of TNO stems from the multielectron redox of Nb 5+ to Nb 3+ , its operating voltage window well above the Li + /Li reduction potential prevents lithium dendrite formation, and its open crystal structure leads to high-power performance. Nevertheless, the creation of a practical TNO anode was nonlinear and nontrivial. Its history is built on 30 years of fundamental science that preceded its application as a battery anode, and its battery development included a nearly 30-year gap. The insights and lessons contained in this Perspective, many of them acquired firsthand, serve two purposes: (i) to unite the disparate studies of TiNb 2 O 7 into a coherent modern understanding relevant to its application as a battery material and (ii) to highlight briefly some of the challenges faced when scaling up a new material that affect TiNb 2 O 7 as well as new electrode candidates more generally.

25 ENERGY STORAGE↗

DOE OSTI2024

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗

DOE OSTI2022

Multi-physics modeling of grain growth during solidification in electron beam additive manufacturing of Inconel 718

While experimental work has shown promising results regarding control of additive manufacturing metal grain structure, the effects of processing parameters on the grain structure is difficult to understand and predict from experiment alone. To this end, a modeling framework is developed which sequentially couples a macro-scale, semi-analytic thermal model, and a meso-scale, cellular automata-based microstructure model. This framework is applied to electron beam additive manufacturing of Inconel 718 using a complex spot scan pattern. The model shows that, with the same scan pattern, variations in the spot time and electron-beam current produce thermal histories with significant spatial and temporal differences, which then produce complex solidification conditions from the interplay between molten pools in the same layer and subsequent layers, resulting in vastly different grain structures. Additionally, it is noted that the framework can significantly reduce the computational expenses for coupled thermal-metallurgical problems, and has the potential to be used for component level problems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Scalable probabilistic estimates of electric vehicle charging given observed driver behavior

To prepare for rapid growth in global electric vehicle adoption, grid and policy planners depend on detailed forecasts of future charging demand. In this paper we propose a novel holistic, scalable, probabilistic framework to produce large-scale estimates of electric vehicle charging load for long-term planning that capture real drivers’ charging patterns. Our framework captures the uncertainty and stochasticity in charging demand by taking a graphical modeling approach. It has three core elements: driver groups, charging segment choices, and charging session time and energy requirements. The framework uses hierarchical clustering to group drivers by their charging histories, capturing their heterogeneous behaviors and preferences across different segments or types of charging. The framework uses probabilistic mixture models for each driver group’s sessions to identify the unique charging behaviors observed within each segment. We illustrate its application with a large data set from California, profiling the charging patterns and unique driver clusters it identifies. Using the model knobs representing drivers’ battery capacities, behavior, and segment access we present scenarios for California’s charging demand in 2030 with 8 million passenger electric vehicles. Peak charging demand ranged from 3.3 to 8.7 GW across scenarios. Furthermore, each was calculated in under 45 s on a laptop computer.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Rates and delay times of type Ia supernovae in the Dark Energy Survey

We use a sample of 809 photometrically classified Type Ia supernovae (SNe Ia) discovered by the Dark Energy Survey (DES) along with 40 415 field galaxies to calculate the rate of SNe Ia per galaxy in the redshift range 0.2 < z < 0.6. We recover the known correlation between SN Ia rate and galaxy stellar mass across a broad range of scales 8.5 ≤ log (M*/M ⊙ ) ≤ 11.25. We find that the SN Ia rate increases with stellar mass as a power law with index 0.63 ± 0.02, which is consistent with the previous work. We use an empirical model of stellar mass assembly to estimate the average star formation histories (SFHs) of galaxies across the stellar mass range of our measurement. Combining the modelled SFHs with the SN Ia rates to estimate constraints on the SN Ia delay time distribution (DTD), we find that the data are fit well by a power-law DTD with slope index β = –1.13 ± 0.05 and normalization A = 2.11 ± 0.05 × 10 –13 SNe M ⊙ –1 yr –1 , which corresponds to an overall SN Ia production efficiency N Ia /M * = 0.9 $^{+4.0}_{–0.7}$ × 10 –3 SNe M$^{–1}_{⊙}$. Upon splitting the SN sample by properties of the light curves, we find a strong dependence on DTD slope with the SN decline rate, with slower-declining SNe exhibiting a steeper DTD slope. We interpret this as a result of a relationship between intrinsic luminosity and progenitor age, and explore the implications of the result in the context of SN Ia progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Evaluating turbulence models at high energy densities

The RESHOCK campaign at Lawrence Livermore National Laboratory has been working on increasing our understanding of the evolution of turbulent, unstable plasma interfaces which are applicable in various HED applications including ICF implosions. A common approach to model such interfaces involves the use of Renolds-Averaged-Navier-Stokes (RANS) models whose parameters have been constrained by theory and experiments. These parameter sets are not unique and the applicability of one set of tuned model parameters to systems with differing shock strengths or material densities has not been well tested. Our new NIF experiments, along with related studies of turbulent shear flows, provide data and model validation for plasma interfaces in the HED regime. Our experiments measure mixing-layer width at an unstable interface in the plasma regime and are specifically designed to challenge mix models of the Reynolds-Averaged-Navier-Stokes (RANS) type where turbulence is assumed to be fully developed, i.e. the flow exhibits a broad spectrum of length scales without memory of the initial condition.4 We utilize precise control of the initial interface conditions (densities on both sides of the interface, an initial rippled perturbation pattern consisting of equally weighted wavelengths between 10 and 20 microns, and initial material compositions) along with a repeatable drive history

36 MATERIALS SCIENCE↗

DOE OSTI2021

The Effect of Warm Dark Matter on Early Star Formation Histories of Massive Galaxies: Predictions from the CROC Simulations

Several massive (M * > 108 M ⊙ ), high-redshift (z = 8–10) galaxies have recently been discovered to contain stars with ages of several hundred million years, pushing the onset of star formation in these galaxies back to z ~ 15. The very existence of stars formed so early may serve as a test for cosmological models with suppressed small-scale power (and, hence, late formation of cosmic structure). We explore the ages of the oldest stars in numerical simulations from the Cosmic Reionization On Computers project with cold dark matter (CDM) and two warm dark matter (WDM) cosmologies with 3 and 6 keV particles. There are statistically significant differences of ~5 Myr between average stellar ages of massive galaxies in CDM and 3 keV WDM, while CDM and 6 keV WDM are statistically indistinguishable. Even this 5 Myr difference, however, is much less than current observational uncertainties on the stellar population properties of high-redshift galaxies. The age distributions of all galaxies in all cosmologies fail to produce a substantial Balmer break, although uncertainties in dust attenuation are a potentially significant factor. Finally, we assess the convergence of our simulation predictions and find that the systematic uncertainties on individual galaxy properties are comparable to the differences between cosmologies, suggesting these differences may not be numerically robust.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Radioarsenic: A promising theragnostic candidate for nuclear medicine

Molecular imaging is a non-invasive process that enable the visualization, characterization, and quantitation of biological processes at the molecular and cellular level. With the emergence of theragnostic agents to diagnose and treat disease for personalized medicine there is a growing need for matched pairs of isotopes. Matched pairs offer the unique opportunity to obtain patient specific information from SPECT or PET diagnostic studies to quantitate in vivo function or receptor density to inform and tailor therapeutic treatment. There are several isotopes of arsenic that have emissions suitable for either or both diagnostic imaging and radiotherapy. Their half-lives are long enough to pair them with peptides and antibodies which take longer to reach maximum uptake to facilitate improved patient pharmacokinetics and dosimetry then can be obtained with shorter lived radionuclides. Arsenic-72 even offers availability from a generator that can be shipped to remote sites and thus enhances availability. Arsenic has a long history as a diagnostic agent, but until recently has suffered from limited availability, lack of suitable chelators, and concerns about toxicity have inhibited its use in nuclear medicine. However, new production methods and novel chelators are coming online and the use of radioarsenic in the pico and nanomolar scale is well below the limits associated with toxicity. This manuscript will review the production routes, separation chemistry, radiolabeling techniques and in vitro/in vivo studies of three medically relevant isotopes of arsenic (arsenic-74, arsenic-72, and arsenic-77).

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2026

Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen, Coccidioides

A challenge in population ecology studies is identifying how to best group individuals into populations, especially when individual origin is unknown. Machine learning has improved upon traditional methods of identifying population structure and is more efficient at handling large, complex datasets. We demonstrate the applicability of a machine learning method to identify hierarchical population structure in an emerging pathogen, Coccidioides spp., the causative agent of Valley fever. We compared the network clusters to structure identified by traditional tools as a validation of the network performance. We used publicly available whole-genome data for 48 C. immitis and 102 C. posadasii, resulting in 168,211 genome-wide SNPs among the two species. The network analysis grouped samples into populations comparable to the literature for these species but also identified fine-scale geographic structure and travel-associated cases not reported thus far. Exploring different resolutions in the network made it easy to identify unique genotypes specific to California and possibly Nevada, as well as Phoenix- and Tucson-acquired infections in non-endemic areas, regardless of reported travel history. The present study provides a promising example of how a ML-based network analysis can improve our ability to understand pathogen ecology, group cases into populations and infer travel-associated infections.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The Relationship Between Dose Rate and Decay Heat for Spent Nuclear Fuel Casks

Decay heat and dose rate are two important limits used for determining the allowable contents of spent fuel (SNF) in dry storage systems and transportation packages. While the decay heat limit is used to maintain fuel cladding integrity and ensure retrievability, dose rates are used to demonstrate compliance with regulatory requirements on radiation protection. Because both dose rate and decay heat result from decay of radioisotopes in SNF, this study is an attempt to examine the relationship between dose rate and decay heat for a given cask design. Dose rates were evaluated for 198 cask configurations, that include various SNF system designs (e.g., storage, transfer, transport), SNF characteristics (e.g., fuel types, burnup, cooling time), and loading maps (e.g., uniform loading, zone loading), while a constant decay heat was maintained. The decay heat was calculated using US Nuclear Regulatory Commission (NRC) Regulatory Guide (RG) 3.54, Revision 2, and verified using ORIGEN sequence within SCALE code system. The ORIGEN outputs were used as source terms in the dose analysis using 198 different configurations. A computer script was developed to calculate the cooling time necessary to achieve a given decay heat for a given enrichment, assembly average burnup, assembly mass, and in-core history using a rootfinder algorithm. Initially the computer script was developed to provide cooling time and burnup calculations directly to the analysis of dose rates and decay heats, so a comparison between Used Nuclear Fuel-Storage Transportation and Disposal Analysis Resource Data System (UNF-ST&DARDS) results and RG3.54 data was made; results are included in the appendix to this document. However, an iterative approach was used to compute cooling time, and its accuracy did not depend on the results of the RG3.54r2 algorithm, although the algorithm was still used. The results of the evaluation presented herein clearly demonstrate that a given decay heat does not correspond to a unique dose rate for a variety of cask and package designs. There is no clear pattern to develop a correlation between decay heat and the source terms. Depending on burnup, enrichment, cask type, and loading pattern, dose rates varied for the exact same decay heat—in some cases by 400% for a given cask. For cases in which decay heat was held constant through selection of the appropriate cooling time, dose rates would decrease with increasing burnup, and in other cases, dose rates would increase. The large variation in dose rates for a constant decay heat indicates that casks loaded based on decay heat—that is allowing any burnup, cooling time, and enrichment combinations that yield the qualified decay heat limit(s) —cannot ensure that an Independent Spent Fuel Storage Installation or a spent fuel transportation package will meet the regulatory limits set forth by the respective regulations, i.e., 10 CFR 72 or 10 CFR 71.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

The FIREBIRD-II CubeSat Mission (Focused Investigations of Relativistic Electron Burst Intensity, Range, and Dynamics)

FIREBIRD-II is a National Science Foundation funded CubeSat mission designed to study the scale size and energy spectrum of relativistic electron microbursts. The mission consists of two identical 1.5 U CubeSats in a low earth polar orbit, each with two solid state detectors that differ only in the size of their geometric factors and fields of view. Having two spacecraft in close orbit allows the scale size of microbursts to be investigated through the intra-spacecraft separation when microbursts are observed simultaneously on each unit. Each detector returns high cadence (10 s of ms) measurements of the electron population from 200 keV to >1 MeV across six energy channels. The energy channels were selected to fill a gap in the observations of the Heavy Ion Large Telescope instrument on the Solar, Anomalous, and Magnetospheric Particle Explorer. FIREBIRD-II has been in orbit for 5 years and continues to return high quality data. After the first month in orbit, the spacecraft had separated beyond the expected scale size of microbursts, so the focus has shifted toward conjunctions with other magnetospheric missions. FIREBIRD-II has addressed all of its primary science objectives, and its long lifetime and focus on conjunctions has enabled additional science beyond the scope of the original mission. This paper presents a brief history of the FIREBIRD mission’s science goals, followed by a description of the instrument and spacecraft. The data products are then discussed along with some caveats necessary for proper use of the data.

47 OTHER INSTRUMENTATION↗