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At least 145 records · Page 8

Challenge Problem 1: Preliminary Results of the Direct Numerical Simulation of Transient Flows

This report presents the first direct numerical simulations (DNS) of transient mixed convection in an idealized downcomer-like channel (Challenge Problem 1, Phase II). Using the GPU-accelerated NekRS solver, we modeled a sudden decay in driving pressure, mimicking loss-of-flow events, and tracked the resulting evolution of Reynolds number, boundary-layer structure, turbulence statistics, and heat-transfer metrics. Key findings include the systematic thickening and eventual asymmetry of velocity and thermal boundary layers under buoyant deceleration; minimal “memory” lag in Reynolds shear stress and TKE profiles when sampled at matching Re, yet clear shifts of peak locations toward the cooled wall; overshoots in transient eddy-viscosity and eddy-diffusivity (and corresponding sub-unity turbulent Prandtl numbers) on the cooled side; and a pronounced transient Nusselt-number enhancement driven by wall-temperature inertia and residual eddy mixing. These effects combined to offer a temporary cooling margin above steady-state predictions during reactor LOF transients. Future work will extend this work to a more complex “Case II” geometry (90° turn + lower plenum) and generate multi-Re/Pr datasets for data-driven turbulence closures.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Low-Energy Backgrounds in Solid-State Phonon and Charge Detectors

Solid-state phonon and charge detectors probe the scattering of weakly interacting particles, such as dark matter and neutrinos, through their low recoil thresholds. Recent advancements have pushed sensitivity to eV-scale energy depositions, uncovering previously unseen low-energy excess backgrounds. While some arise from known processes such as thermal radiation, luminescence, and stress, others remain unexplained. This review examines these backgrounds, their possible origins, and parallels to low-energy effects in solids, an understanding of which is essential for interpreting particle interactions at and below the eV scale.

coherent neutrino–nucleus scattering

Optimizing Deep Geothermal Drilling for Energy Sustainability in the Appalachian Basin

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings.

Environmental Sciences & Ecology

Design of a shipping fixture for a compact cryomodule hermetic assembly

Two conduction-cooled 915 MHz superconducting radio frequency hermetic assemblies must be safely transported from the Jefferson Lab in Newport News, VA to General Atomics in San Diego, CA for perfor-mance testing in a custom horizontal test cryostat. One hermetic assembly consists of a 2-cell 915 MHz cavity, a coaxial fundamental power coupler, and the warm-to-cold transition beam tubes. The second hermetic assembly consists of a 2-cell 915 MHz cavity only. The assemblies will be transported on a flatbed air-ride trailer over the approximate 4000 km distance. Design requirements included adequate attenuation of 4g vertical axis, 5g beamline axis, and 1.5g lateral axis shock events. The isolation system was designed using helical wire-rope isolators with modal and transient finite element analysis performed in Ansys. Results show shock attenuation of a 10 ms half-sine pulse input to < 1g in the vertical axis, < 1.5g in the beam-line axis, and < 0.5g in the lateral axis for both assem-blies at the specified design loads and all structural stresses are kept below the material yield limits. Addi-tionally, the natural frequencies of both isolation sys-tems adequately attenuate the fundamental modes of the critical structures.

Accelerator Physics

Freestream turbulence effects on unsteady wind turbine loads and wakes: An IDDES study

We investigate numerically the effects of freestream turbulence on the unsteady aerodynamics and wakes of the National Renewable Energy Laboratory Phase VI wind turbine rotor for increasing wind speed. Turbulence is modeled using the Improved Delayed Detached-Eddy Simulation (IDDES) method. As a first step, a detailed mesh resolution study is conducted with the decaying freestream turbulence model at turbulence intensity of 0.5%. Our blade-resolved IDDES simulations show that grid-independent average torque and thrust results can be achieved with relatively coarse meshes, whereas dramatically higher mesh resolution is required for grid-independent results for power spectral densities of thrust force, especially in the deep-stall regime. Comparing the loads with the Shear-Stress Transport model demonstrates the superiority of IDDES in predicting massively separated flows. The aerodynamic performance and wake predictions with the decaying freestream turbulence model are compared with the synthetic freestream turbulence model. Both models predict nearly the same loads, spectral energy content, and wake characteristics. The properties of both the near- and far-wake regions are then examined. Furthermore, we show that separated boundary layers accelerate turbulent mixing and entrainment of the external flow, which results in faster wake recovery. The effect of increasing turbulence intensity to 6% is investigated using the synthetic freestream turbulence model. In contrast with the fully attached boundary layer, higher freestream turbulence in deep stall does not significantly affect the loads and vortex-shedding characteristics. However, the turbulent mixing in the wake is enhanced, which further hastens the recovery of the self-similar velocity profile. In general, increasing the wind speed at high turbulence intensity shifts the recovery farther upstream and increases the wake width.

17 WIND ENERGY

Scalar flux transport models for self-similar turbulent mixing

A common approach to closing turbulent species flux in multicomponent Reynolds-averaged Navier-Stokes models is to use the standard gradient diffusion approximation. While such an approach has been shown to work well when applied to many canonical turbulent mixing configurations, a gradient diffusion approach is fundamentally limited in its ability to capture complex phenomena such as countergradient transport. For this reason, complicated mixing applications may benefit by treating the turbulent diffusivity with a model transport equation in a manner analogous to second-moment momentum closure in Reynolds-stress transport models. Here, the present work explores the development and application of two different scalar flux transport (SFT) models. Self-similarity constraints are derived for these models, and they are evaluated against gradient-diffusion-based models in several one- and two-dimensional problems of turbulent mixing. It is found that the new SFT models out-perform gradient diffusion models in problems involving rapid acceleration reversal and in problems involving anisotropic transport of materials. In addition, it is found that even a hybrid-SFT approach, in which an SFT equation is utilized along with a gradient diffusion closure, provides some measure of improvement over models that transport the mass flux rather than the scalar flux.

Reynolds-averaged Navier Stokes

Design and Optimization of a Hybrid Design for Quantum Transduction

This study presents the mechanical design and analysis of a quantum electro-optical transducer engineered to operate at millikelvin temperatures within a dilution refrigerator. The transducer enables bidirectional microwave-optical frequency conversion through a hybrid architecture that integrates a superconducting radiofrequency (SRF) cavity with an electro-optic optical cavity. Among several design options investigated, the configuration offering the best thermal and mechanical performance was selected, yielding a robust solution with reduced sensitivity to fabrication tolerances, improved heat dissipation, as well as alignment precision. The design ensures uniform temperature distribution, enabling higher laser pump powers and, thus, increased conversion efficiency, while maintaining mechanical stresses safely below the material yield strength. Electromagnetic simulations further validate the design, demonstrating enhanced coupling between the optical and microwave modes, as well as a broader tuning range achieved with smaller tuner displacements.

quantum computing

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE

Revealing structure and shaping priorities in plant and fungal cell wall architecture via solid-state NMR

Plant and fungal cell walls are essential for growth, adaptation, and survival, with their intricate architectures dictating both resistance to stress and susceptibility to antifungal or biomass-degrading strategies. Understanding how these walls are built, remodeled, and function at the molecular level is therefore central to both clinical and biotechnological applications. Solid-state nuclear magnetic resonance (ssNMR) has emerged as a uniquely powerful tool for this purpose, as it reveals the structure, dynamics, and interactions of intact biopolymers without disrupting their native organization. Using this approach, recent studies have shown how structural polymorphism, polymer-polymer interactions, and species-specific remodeling govern mechanical integrity, drug resistance, and stress adaptation. Applications highlighted here include lignin-carbohydrate packing during plant stem maturation, fungal wall reorganization under treatment by wall-targeting antifungals such as echinocandin and nikkomycin, and the functional diversity of glucans, chitins, and mannans. Together, these insights uncover conserved principles of polymer assembly across kingdoms while informing new opportunities for antifungal development and biomass utilization. Ongoing advances in sensitivity and resolution are expected to broaden the reach of ssNMR and further accelerate its role in linking structural heterogeneity to biosynthetic complexity and biological function.

Antifungal

FY25 Status Update on A709 Code Case Testing at ANL

This report provides an update on the status of the creep rupture testing on the precipitation-treated (PT) Alloy 709 samples fabricated from the first, the second and the third commercial heats, in support of the first, 100,000-hour Alloy 709 Code Case development under the American Society of Mechanical Engineers (ASME) Section III, Division 5 for high-temperature reactor construction. In Fiscal Year (FY) 25, no new tests were initiated, while 5 previously loaded tests were completed. This report presents an overview of the creep-rupture data gathered at Argonne National Laboratory (ANL) since FY21 that totaled 52 completed tests. Metallographic images showing crack morphologies in some representative samples ruptured in FY25 are also included. Key conclusions include: 1) the creep behavior of the three heats of Alloy 709 can be well described by the Larson-Miller relationship; 2) higher temperatures and larger stresses lead to shorter creep life and higher minimum creep rate; 3) Alloy 709 is overall very ductile under creep; 4) the crack morphologies near fracture surfaces are dependent on material’s grain size and test conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Heterogeneous doping via nanoscale coating impacts the mechanics of Li intrusion in brittle solid electrolytes

Lithium dendrite intrusion in solid-state batteries limits fast charging and causes short-circuiting, yet the underlying regulating mechanisms are not well-understood. Here, in this work, we discover that heterogeneous Ag + doping dramatically affects lithium intrusion into Li 6.6 La 3 Zr 1.6 Ta 0.4 O 12 (LLZO), a brittle solid electrolyte. Nanoscale Ag + doping is achieved by thermally annealing a 3-nm-thick metallic coating on LLZO, inducing Ag–Li ion exchange and Ag diffusion into grains and grain boundaries. Density functional theory calculations and experimental characterization show negligible impact on the electronic properties and surface wettability from Ag + incorporation. Mechanically, nanoindentation experiments show a fivefold increase in the mechanical force required to fracture the surface Ag + -doped LLZO, indicating substantial doping-induced surface toughening. Operando microprobe scanning electron microscopy experiments show that the Ag + -doped LLZO surface exhibits improved lithium plating at >250 mA cm −2 and an electroplating diameter that is expanded by over fourfold, even under an extreme indentation stress of 3 GPa. This demonstrates enhanced defect tolerance in LLZO, rather than electronic or adhesion effects. Our study reveals a chemo-mechanical mechanism via surface heterogeneous doping, complementing present bulk design rules to minimize mechanical failures in solid-state batteries.

36 MATERIALS SCIENCE

A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor

Abstract There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.

Kumar, Pankaj

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing

DESIGN ISSUES AND QUALIFICATION OF HYDROFORMED DOUBLE WALLED EXPANSION JOINTS IN VACUUM SERVICE

The Vacuum Auxiliary System for ITER is devoted to pumping out, venting, and purging the vacuum volumes of the tokamak. Over 5000 clients including the cryostat and vacuum vessel, at 8500 m3 and 1400 m3 respectively, are serviced by approximately 150 pumping stations through 6 km of pipework. The piping and functions provided to the clients include component operation, routing of potentially tritiated gases, and timely leak localization. Expansion joints are used to reduce loadings on pumps and piping stresses but also to qualify in-line components having low allowable design loads. The ITER project utilizes vacuum valves that are not designed to withstand typical piping system loadings and require detailed design and evaluation. Loading scenarios prescribed by governing system specifications must be considered. To maintain allowable design loads for components and to keep piping stresses below code requirements, double walled hydroformed expansion joints have been employed in the design. These are not standard items and require custom fabrication. Installation space constraints and adjacent pipe support attachment location availability at ITER limit standard expansion joint installation guidelines provided by the Expasion Joint Manufacturers Association (EJMA). Careful consideration must be given to the analysis model to ensure proper function and life expectancy of the component. These considerations include accurate accounting of thrust forces, thermal movements, seismic accelerations, equipment and building differential displacements. In addition to displacements, the process internal, external, and interspace pressures affect the qualification and selection of the double walled expansion joints. The calculation results shall confirm that deflections, forces, and moments are reasonable for the size and type required for the system’s demands as evaluated against the manufacturer’s design.

Clark, Forrest [ORNL] (ORCID:0009000678106843)

Oxidative stress is a shared characteristic of ME/CFS and Long COVID

Over 65 million individuals worldwide are estimated to have Long COVID (LC), a complex multisystemic condition marked by fatigue, post-exertional malaise, and other symptoms resembling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). With no clinically approved treatments or reliable diagnostic markers, there is an urgent need to define the molecular underpinnings of these conditions. By studying bioenergetic characteristics of peripheral blood lymphocytes in 25 healthy controls, 27 ME/CFS, and 20 LC donors, we find both ME/CFS and LC donors exhibit signs of elevated oxidative stress, especially in the memory subset. Using a combination of flow cytometry, RNA-seq, mass spectrometry, and systems chemistry analysis, we observed aberrations in reactive oxygen species (ROS) clearance pathways including elevated glutathione levels, decreases in mitochondrial superoxide dismutase protein levels, and glutathione peroxidase 4–mediated lipid oxidative damage. Strikingly, these redox pathways changes show sex-specific trends. While ME/CFS females exhibit higher total ROS and mitochondrial calcium levels, males have normal ROS levels, with pronounced mitochondrial lipid oxidative damage. In females, these higher ROS levels correlate with T cell hyperproliferation, consistent with the known role of elevated ROS in initiating proliferation. This hyperproliferation can be attenuated by metformin, suggesting this Food and Drug Administration (FDA)-approved drug as a possible treatment, as also suggested by a recent clinical study of LC patients. Moreover, these results suggest a shared mechanistic basis for the systemic phenotypes of ME/CFS and LC, which can be detected by quantitative blood cell measurements, and that effective, patient-tailored drugs might be discovered using standard lymphocyte stimulation assays.

ME/CFS

Strain-graded quantum dots with spectrally pure, stable and polarized emission

Structural deformation modifies the bandgap, exciton fine structure and phonon energy of semiconductors, providing an additional knob to control their optical properties. The impact can be exploited in colloidal semiconductor quantum dots (QDs), wherein structural stresses can be imposed in three dimensions while defect formation is suppressed by controlling surface growth kinetics. Yet, the control over the structural deformation of QDs free from optically active defects has not been reached. Here, we demonstrate strain-graded CdSe-ZnSe core-shell QDs with compositionally abrupt interface by the coherent pseudomorphic heteroepitaxy. Resulting QDs tolerate mutual elastic deformation of varying magnitudes at the interface with high structural fidelity, allowing for spectrally stable and pure emission of photons at accelerated rates with near unity luminescence efficiency. We capitalize on the asymmetric strain effect together with the quantum confinement effect to expand emission envelope of QDs spanning the entire visible region and exemplify their use in photonic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY

Alloy 625 Qualification Pathway for ASME Section III Division 5 Class A construction

The American Society of Mechanical Engineers Boiler and Pressure Vessel Code Section III Division 5 provides construction and inspection rules to ensure the safety of nuclear components operating at elevated temperatures, defined as those operating above 700°F (370°C) or 800°F (425°C), depending on the material type. At present, there are six materials approved for Class A (high safety significance) component construction under ASME BPVC Section III Division 5. Out of these six materials, five materials are steels or iron-based alloys and one material, Alloy 617, is a nickel alloy. Nickel alloys are stronger than steels; however, Alloy 617 consists of 10-15% cobalt, and activation is a concern under irradiation. Therefore, there is a need to qualify new nickel alloy with lower cobalt content. Alloy 625 is one candidate which has similar mechanical properties at elevated temperature compared to Alloy 617 and has a maximum of 1% cobalt. Although Alloy 625 material properties have been developed in the past to support allowable stress development under ASME Section II, new test results would be needed to qualify this material for elevated temperature component construction under ASME Section III Division 5. The purpose of this report is to describe a path towards developing a Nuclear Code Case to qualify Alloy 625 (UNS N06625; Grade 1 and Grade 2) for elevated temperature nuclear use in accordance with the ASME BPVC rules. This report reviews the existing database on Alloy 625, presents proposed test campaign, and discusses potential paths for accelerating the accelerated material qualification process.

36 - MATERIALS SCIENCE