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At least 379 records · Page 21

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NASA NTRS1999

Fundamental Studies of Solidification in Microgravity Using Real-Time X-Ray Microscopy

This research applies a state of the art X-ray Transmission Microscope, XTM, to image (with resolutions up to 3 micrometers) the solidification of metallic or semiconductor alloys in real-time. We have successfully imaged in real-time: interfacial morphologies, phase growth, coalescence, incorporation of phases into the growing interface, and the solute boundary layer in the liquid at the solid-liquid interface. We have also measured true local growth rates and can evaluate segregation structures in the solid; a form of in-situ metallography. During this study, the growth of secondary phase fibers and lamellae from eutectic and monotectic alloys have been imaged during solidification, in real-time, for the first time in bulk metal alloys. Current high resolution X-ray sources and high contrast X-ray detectors have advanced to allow systematic study of solidification dynamics and the resulting microstructure. We have employed a state-of-the-art sub-micron source with acceleration voltages of 10-100 kV to image solidification of metals. One useful strength of the XTM stems from the manner an image is formed. The radiographic image is a shadow formed by x-ray photons that are not absorbed as they pass through the specimen. Composition gradients within the specimen cause variations in absorption of the flux such that the final image represents a spatial integral of composition (or thickness). The ability to image these features in real-time enables more fundamental and detailed understanding of solidification dynamics than has previously been possible. Hence, application of this technique towards microgravity experiments will allow rigorous testing of critical solidification models.

Curreri, Peter A.↗

DOE OSTI2024

Quantitative Insight to Fission Gas Pores Distribution in Irradiated Annular U-10Zr Metallic Fuel Using Machine Learning

Metallic fuels, particularly U-10Zr and its performance in reactor irradiation conditions, have been thoroughly investigated and are a promising candidate for next-generation sodium-cooled fast spectrum nuclear reactors. Irradiation in reactors can lead to the formation of fission gas and increased pore formation which can significantly impact fuel performance. Due to the large number of pores and various phases formed in metallic fuel during irradiation, a quantitative description of fission gas pores as a function of irradiation conditions is not yet available, undermining the fidelity of fuel performance modeling to support fuel qualification. It has been difficult to clearly detect pore boundaries and distinguish matrix phases from fission gas pores using optical microscopy by using simple threshold methods working with low magnification images. The pre-trained deep learning model for fission gas pore detection was applied to ~10,260 high magnification scanning electron microscopy images. The model increased the accuracy of fission gas pore segmentation to obtain statistical features, which cannot be processed manually. A pre-trained decision tree model was used to classify pores as isolated or connected pores, providing new insight into the correlation between the movement of lanthanides, solid fission products, and the radial temperature gradient developed in fuel irradiation conditions. This paper emphasizes the potential that artificial intelligence-based machine learning models have to accelerate qualification and support nuclear fuel development.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Elemental segregation to lattice defects in the CrMnFeCoNi high-entropy alloy during high temperature exposures

The influence of small plastic pre-strains on the elevated-temperature stability and microstructure of the equiatomic CrMnFeCoNi FCC solid solution is investigated. Particular attention is given to whether any of the alloy elements segregate to individual dislocations. To that end, CrMnFeCoNi samples were first deformed in tension at room temperature to plastic strains of 0.2 and 2.3%, and subsequently annealed at 973 K for 800 hours. The pre-strains activated planar slip of 1/2<110>-type dislocations on {111}-type glide planes. Interactions of this planar slip with special Σ3 grain boundaries formed a large number of dislocation segments with a <110>-type crystallographic orientation suitable for a credible end-on analysis of dislocation cores in HR-STEM. The cores of the 1/2<110> dislocations pushed up against the investigated grain boundaries were found to be close to the compact configuration. Within the sensitivity of the Super-X EDS mapping, no concentration gradient was detected near dislocations that would indicate enrichment at dislocation cores of any of the elemental constituents of the alloy after the pre-deformation and annealing. However, a Cr-rich tetragonal sigma phase nucleated and grew at grain boundary triple junctions during this anneal, processes that were not accelerated by the enhanced dislocation density present after pre-strain. A clear chromium gradient was observed in the Cr-depleted zones near grain boundaries suggesting that Cr transport occurred by relatively slow diffusion from the bulk to the grain boundaries and then by relatively fast diffusion along the grain boundaries to the precipitates. Accompanying the Cr depletion near grain boundaries is a simultaneous Ni and Mn enrichment, which promotes formation of the L1 0 NiMn phase that is observed on the grain boundaries after prolonged annealing.

36 MATERIALS SCIENCE↗

DOE OSTI2023

CFD-based design optimization of ducted hydrokinetic turbines

Abstract Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines.

13 HYDRO ENERGY↗

DOE OSTI2024

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗

NASA NTRS2025

Direct Numerical Simulation of Flow Past a Gaussian Bump at a High Reynolds Number

We present the results from a direct numerical simulation of a spanwise-periodic turbulent flow past a Gaussian bump. The problem setup is designed to investigate the interaction of an incoming turbulent boundary layer with the strong favorable and adverse pressure gradients generated by the Gaussian bump as the flow passes over it at a Reynolds number of 340000 based on the bump height, or 4 million based on the bump length. The statistical results from the present simulation are compared against our earlier results at a Reynolds number of 2 million. An internal layer, which forms beneath the strongly accelerated boundary layer over the windward side of the bump, is found to generate its near-wall turbulence stress peaks in closer proximity of the wall in the higher Reynolds-number case. Furthermore, the logarithmic layer of the higher Reynolds-number boundary layer appears more resistant to changes induced by strong acceleration and surface curvature effects over the same region. Despite a nearly identical flow separation point in the two flows, the detached shear layer grows at a faster rate and subsequently reattaches at an earlier point in the higher Reynolds-number flow. The surface pressure and skin-friction distributions over the attached flow region compare well against the corresponding experimental data for both flows. However, some differences appear in the separated flow region, which are attributed to the three-dimensionality of the experimental model setup that is not included in the simulation owing to the spanwise periodic assumption. Comparisons with the stereoscopic particle image velocimetry measurements on the central plane of the experimental model over the windward side of the bump show reasonable overall agreement in the mean velocity components, but the turbulence stress components do not agree well at some streamwise locations. Comparisons over the leeward side of the bump show that the mean separated shear layer in the simulation is tilted significantly more toward the wall than the experimental shear layer on the central plane. This mismatch in the mean shear layer orientation is due to the experimental model three-dimensionality and tunnel end-wall effects, which are not modeled in the present spanwise-periodic simulation.

Favorable and Adverse Pressure Gradients↗

DOE OSTI2020

Steady detonation propagation in thin channels with strong confinement

We examine asymptotically the dynamics of two-dimensional, steady detonation wave propagation and failure for a strongly confined high explosive (HE), in which the width of the explosive is small relative to the reaction zone length. An energy balance equation is derived, which shows how the longitudinal acceleration of subsonic flow behind the detonation shock is influenced both by chemical reaction and by the effects of HE boundary streamline deflection, specifically via the induced rate of change of mass flux through the detonation wave. The latter serves to either counteract or reinforce the acceleration of longitudinal flow, depending on the sign of the gradient of the boundary streamline deflection at the detonation shock. The analysis is valid for general equations of state and chemical reaction rates in the HE. The asymptotically derived form of the energy equation represents an eigenvalue problem for the determination of the steady detonation propagation speed, solved via a shooting method. We explore specific results for ideal and stiffened equations of state, along with a pressure-dependent reaction rate for which changes in the pressure exponent and reaction order are also studied. We consider the influences of both straight and curved HE boundary streamline shapes. The asymptotic analysis reveals significant physical insights into how detonation propagation and failure are affected by strong confinement.

42 ENGINEERING↗

NASA NTRS1995

Magnetohydrodynamic simulations of outflows from accretion disks

Magnetohydrodynamic simulations have been made of the formation of outflows from a Keplerian disk threaded by a magnetic field. The disk is treated as a boundary condition, where matter is ejected with Keplerian azimuthal speed and poloidal speed less than the slow magnetosonic velocity, and where boundary conditions on the magnetic field correspond to a highly conducting disk. Initially, the space above the disk, the corona, is filled with high specific entropy plasma in thermal equilibrium in the gravitational potential of the central object. The initial magnetic field is poloidal and is represented by a superposition of monopoles located below the plane of the disk. The rotation of the disk twists the initial poloidal magnetic field, and this twist propagates into the corona pushing and collimating matter into jetlike outflow in a cylindrical region. Matter outflowing from the disk flows and accelerates in the z-direction owing to both the magnetic and pressure gradient forces. The flow accelerates through the slow magnetosonic and Alfven surfaces and at larger distances through the fast magnetosonic surface. The flow velocity of the jet is approximately parallel to the z-axis, and the collimation results from the pinching force of the toroidal magnetic field. For a nonrotating disk no collimation is observed.

Ustyugova, G. V.↗

DOE OSTI2024

Excellent performance of 650 MHz single-cell niobium cavity after electropolishing

Electropolishing process and cathodes have undergone modification and optimization for both low- and high-beta 650 MHz five-cell niobium cavities for PIP-II. Cavities treated with these modified electropolishing conditions exhibited smooth surfaces and good performance in baseline tests. Nonetheless, due to administrative constraints on project cavities, maximum gradient performance testing was not conducted. This paper presents a study conducted on a single-cell 650 MHz cavity utilizing the optimized electropolishing conditions, highlighting the maximum performance attained for this specific cavity. The cavity tested at 2 K in a vertical cryostat reached a superior accelerating field gradient of 53.3 MV/m at Q0 of 1.6x1010, which is the highest gradient attained for this type of large-sized cavities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Synchrotron Polarization Signatures of Surface Waves in Supermassive Black Hole Jets

Abstract Supermassive black holes in active galactic nuclei are known to launch relativistic jets, which are observed across the entire electromagnetic spectrum and thought to be efficient particle accelerators. Their primary radiation mechanism for radio emission is polarized synchrotron emission produced by a population of nonthermal electrons. In this Letter, we present a global general relativistic magnetohydrodynamical (GRMHD) simulation of a magnetically arrested disk (MAD). After the simulation reaches the MAD state, we show that waves are continuously launched from the vicinity of the black hole and propagate along the interface between the jet and the wind. At this interface, a steep gradient in velocity is present between the mildly relativistic wind and the highly relativistic jet. The interface is, therefore, a shear layer, and due to the shear, the waves generate roll-ups that alter the magnetic field configuration and the shear layer geometry. We then perform polarized radiation transfer calculations of our GRMHD simulation and find signatures of the waves in both total intensity and linear polarization, effectively lowering the fully resolved polarization fraction. The telltale polarization signatures of the waves could be observable by future very long baseline interferometric observations, e.g., the next-generation Event Horizon Telescope.

Astronomy & Astrophysics↗

DOE OSTI2024

Progress and Challenges in Traveling-Wave SRF cavity development at Fermilab

Traveling-wave (TW) technology can push the accelerator field gradient of niobium SRF cavity to 70MV/m or higher beyond the limit of 50~60MV/m in Standing-wave (SW) technology. The early stages of TW SRF cavity developments had been funded by several SBIR grants to Euclid Techlabs and completed in collaboration with Fermilab through a 1-cell prototype and a proof-of-principle 3-cell TW cavity. The TW resonance excitation in the 3-cell TW cavity at 2K was demonstrated through the low power RF test in early 2024. A high-power test of the 3-cell in TW mode being prepared. To advance a design and technology to fabricate a novel high gradient TW SRF cavity, FNAL proposed a half-meter TW RF design and R&Ds to realize that are in progress. Here we will report the recent progress in the 3-cell TW cavity and the challenges towards a half-meter scale TW cavity.

Furuta, F.↗

DOE OSTI2022

Fed-DeepONet: Stochastic Gradient-Based Federated Training of Deep Operator Networks

The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized strategy that requires transferring the training data to a centralized location. Such a strategy, however, limits our ability to secure data privacy or use high-performance distributed/parallel computing platforms. To alleviate such limitations, in this paper, we study the federated training of DeepONets for the first time. That is, we develop a framework, which we refer to as Fed-DeepONet, that allows multiple clients to train DeepONets collaboratively under the coordination of a centralized server. To achieve Fed-DeepONets, we propose an efficient stochastic gradient-based algorithm that enables the distributed optimization of the DeepONet parameters by averaging first-order estimates of the DeepONet loss gradient. Then, to accelerate the training convergence of Fed-DeepONets, we propose a moment-enhanced (i.e., adaptive) stochastic gradient-based strategy. Finally, we verify the performance of Fed-DeepONet by learning, for different configurations of the number of clients and fractions of available clients, (i) the solution operator of a gravity pendulum and (ii) the dynamic response of a parametric library of pendulums.

Moya, Christian↗

DOE OSTI2024

Progress and Challenges in Traveling-Wave SRF cavity development at Fermilab

Furuta, F.↗

DOE OSTI2023

Ultrafast Wavefront Shaping via Space-Time Refraction

A myriad of metasurfaces have been demonstrated that manipulate light by spatially structuring thin optical layers. Manipulation of the optical properties of such layers in both space and time can unlock new physical phenomena and enable new optical devices. Examples include photon acceleration and frequency conversion, which modifies Snell’s relation to a more general, nonreciprocal form. Here, we combine theory and experiment to realize wavefront shaping and frequency conversion on subpicosecond time-scales by inducing space-time refractive index gradients in epsilon-near-zero (ENZ) films with femtosecond light pulses. Furthermore, we experimentally tune wavefront steering by controlling the incident angle of the beams and the pump–probe delay without the need for nanostructure fabrication. As a demonstration of this approach, we leverage the ultrafast, high-bandwidth optical response of transparent oxides in their ENZ wavelength range to create large refractive index gradients and new types of nonreciprocal, ultrafast two-dimensional (2D) optics, including an ultrathin transient lens.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage

The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options, metal hydrides offer high volumetric storage density and operational safety, yet their application is limited by thermodynamic, kinetic, and compositional constraints. In this work, we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure, enthalpy, and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation, using the PADRE algorithm, on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size, while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore, clustering and cross-validation analyses highlight the limited generalizability of models across different material classes, though high accuracy is achieved when training and testing within a single hydride family (e.g., AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery, emphasizing the importance of dataset diversity and representation for robust property prediction.

augmentation↗

NASA NTRS2020

3D Propagation of Relativistic Solar Protons through Interplanetary Space

Context. Solar Energetic Particles (SEPs) with energy in the GeV range can propagate to Earth from their acceleration region near the Sun and produce Ground Level Enhancements (GLEs). The traditional approach to interpreting and modelling GLE observations assumes particle propagation only parallel to the magnetic field lines of interplanetary space, i.e. it is spatially 1D. Recent measurements by PAMELA have characterised SEP properties at 1 AU for the ~100 MeV-1 GeV range at high spectral resolution. Aims. We model the transport of GLE-energy solar protons using a 3D approach, to assess the effect of the Heliospheric Current Sheet (HCS) and drifts associated to the gradient and curvature of the Parker spiral. We derive 1 AU observables and compare the simulation results with data from PAMELA. Methods. We use a 3D test particle model including a HCS. Monoenergetic populations are studied first to obtain a qualitative picture of propagation patterns and numbers of crossings of the 1 AU sphere. Simulations for power law injection are used to derive intensity profiles and fluence spectra at 1 AU. A simulation for a specific event, GLE 71, is used to compare with PAMELA data. Results. Spatial patterns of 1 AU crossings and the average number of crossings are strongly influenced by 3D effects, with significant differences between periods of A+ and A- polarities. The decay time constant of 1 AU intensity profiles varies depending on the position of the observer and is not a simple function of the mean free path as in 1D models. Energy dependent leakage from the injection flux tube is particularly important for GLE energy particles, resulting in a rollover in the spectrum.

Solar energetic particles↗

DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴ speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously previously impossible with conventional tools while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗

NASA NTRS2020

3D propagation of relativistic solar protons through interplanetary space

Context.Solar energetic particles (SEPs) with energy in the GeV range can propagate to Earth from their acceleration region near the Sun and produce ground level enhancements (GLEs). The traditional approach to interpreting and modelling GLE observations assumes particle propagation which is only parallel to the magnetic field lines of interplanetary space, that is, spatially 1D propagation. Recent measurements by PAMELA have characterised SEP properties at 1 AU for the∼100 MeV–1 GeV range at high spectral resolution. Aims. We model the transport of GLE-energy solar protons using a 3D approach to assess the effect of the heliospheric current sheet(HCS) and drifts associated to the gradient and curvature of the Parker spiral. We derive 1 AU observables and compare the simulation results with data from PAMELA. Methods. We use a 3D test particle model including a HCS. Monoenergetic populations are studied first to obtain a qualitative picture of propagation patterns and numbers of crossings of the 1 AU sphere. Simulations for power law injection are used to derive intensity profiles and fluence spectra at 1 AU. A simulation for a specific event, GLE 71, is used for comparison purposes with PAMELA data. Results. Spatial patterns of 1 AU crossings and the average number of crossings per particle are strongly influenced by 3D effects, with significant differences between periods of A+ and A−polarities. The decay time constant of 1 AU intensity profiles varies depending on the position of the observer and it is not a simple function of the mean free path as in 1D models. Energy dependent leakage from the injection flux tube is particularly important for GLE energy particles, resulting in a rollover in the spectrum.

S. Dalla↗