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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5

Modeling of Chemical Slurry Rheology in DWPF Sludge Batch (SB) 10 Simulants

The Defense Waste Processing Facility (DWPF) treats high-activity radionuclides from sludge through a process called vitrification. This process converts radioactive liquid waste currently stored in tank farms into a solid glass form that is suitable for long-term storage and disposal. Due to the complexities involved in vitrifying this waste within each operation of the Chemical Processing Cell (CPC), waste rheology is studied to characterize the fluid-mechanical properties as it passes through the CPC and into the Melter. To better understand the waste and validate flow behavior, slurry rheology of simulants that represents the waste was studied at various acid stoichiometry percentages and solids concentrations to determine the simulant’s yield stress and viscosity. This research work has been supported by the DOE-FIU Science & Technology Workforce Development Initiative, an innovative program developed by the U.S. Department of Energy’s Office of Environmental Management (DOE-EM) and Florida International University’s Applied Research Center (FIU-ARC). During the spring of 2022, a DOE Fellow intern, Brendon Cintas, spent 10 weeks doing a summer internship at Savannah River National Laboratory (SRS) under the supervision and guidance of Dan Lambert, Chemical Flowsheet Development. The intern’s project was initiated on June 6, 2022, and continued through August 11, 2022 with the objective of assisting scientists at SRNL’s Rheology and Grout Laboratory at Aiken Country Technology Lab (ACTL) better understand the sludge composition on the rheology of a simulant slurry using a HAAKE RheoStress 6000 rheometer and extrapolate the results to the real-waste data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Generative Physics-Informed Neural Network Solving Multi-Scale and Multi-Phase Plasma Chemical Flow Field

Low-temperature plasmas (LTPs) are non-equilibrium systems with near-room-temperature gas and highly energetic electrons. This makes them ideal for delicate applications in biomedicine and semiconductor manufacturing, enabling processes like wound healing, sterilization, etching, and plasma-enhanced chemical vapor deposition without thermal damage. However, LTPs involve complex chemistries, with hundreds of species and thousands of reactions, complicating their diagnosis, prediction, and control. Conventional diagnostics, such as Fourier-transform infrared spectroscopy (FTIR), laser-induced fluorescence (LIF), and optical emission spectroscopy (OES), offer limited species detection, while mass spectrometry (MS) struggles with low-sensitivity species. Additionally, LTP simulations face multi-scale challenges, as macroscopic fluid dynamics and microscopic particle collisions operate on vastly different timescales. To address these issues, we developed an artificial intelligence (AI) based diagnostic system: a generative physics-informed neural network (PINN-Gen) that can predict spatially resolved species concentrations and temperatures in LTPs by integrating experimental data from planar LIF with microscopic plasma chemical kinetics and macroscopic fluid mechanics, including plasma-liquid interactions at the interface between two phases. PINN-Gen solves no equations but checks the errors of physical laws by substituting the output from neural network, and the comparison with the experimental results. Thus, it naturally avoids the multi-scale difficulty of numerical simulations and predicts the results of conventionally unsolvable multi-scale and multi-phase problems. The real-time prediction will be robust due to the physical information used in the training of such a neural network, and only very limited input of condition required due to its generative feature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Beam Shaping and Oscillation for Metals Additive Manufacturing

Additive Manufacturing (AM) is pivotal for next-generation industrial manufacturing but is hampered by process control challenges leading to unwanted defects and sub-optimal material properties. Our research builds on prior work that utilized beam oscillation techniques to mitigate these issues (Wu et al., 2023). We focus on investigating the influence of beam oscillation frequency on melt pool dynamics, utilizing in-situ synchrotron material characterization from the ESRF (Chen et al., 2026). Preliminary findings indicated that beam oscillation results in unique fluid flow patterns and enhanced melting stability. These findings suggested the possibility of optimized AM process control, including minimized defects and tailored thermal histories. We proposed further research to explore the effects of beam oscillation frequencies comprehensively, using the in-situ characterization capabilities at the ESRF. The goal was to quantify this relationship, offering a pathway to more precise AM process control and optimization. Our research is expected to offer new scientific insights into the fluid mechanics and thermal behaviour in AM, contributing to its broader applicability and commercial viability.

36 MATERIALS SCIENCE↗

Thermal field reconstruction and compressive sensing using proper orthogonal decomposition

Model order reduction allows critical information about sensor placement and experiment design to be distilled from raw fluid mechanics simulation data. In many cases, sensed information in conjunction with reduced order models can also be used to regenerate full field variables. In this paper, a proper orthogonal decomposition (POD) inferencing method is extended to the modeling and compressive sensing of temperature, a scalar field variable. The method is applied to a simulated, critically stable, incompressible flow over a heated cylinder (Re = 1000) with Prandtl number varying between 0.001 and 50. The model is trained on pressure and temperature data from simulations. Field reconstructions are then generated using data from selected sensors and the POD model. Finally, the reconstruction error is evaluated across all Prandtl numbers for different numbers of retained modes and sensors. The predicted trend of increasing reconstruction accuracy with decreasing Prandtl number is confirmed and a Prandtl number/sensor count error matrix is presented.

Matulis, John↗

Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations

Neural operators such as the Fourier Neural Operator (FNO) have been shown to provide resolution-independent deep learning models that can learn mappings between function spaces. For example, an initial condition can be mapped to the solution of a partial differential equation (PDE) at a future time-step using a neural operator. Despite the popularity of neural operators, their use to predict solution functions over a domain given only data over the boundary (such as a spatially varying Dirichlet boundary condition) remains unexplored. In this paper, we refer to such problems as boundary-to-domain problems; they have a wide range of applications in areas such as fluid mechanics, solid mechanics, heat transfer etc. We present a novel FNO-based architecture, named Lifting Product FNO (or LP-FNO) which can map arbitrary boundary functions defined on the lower-dimensional boundary to a solution in the entire domain. Specifically, two FNOs defined on the lower-dimensional boundary are lifted into the higher dimensional domain using our proposed lifting product layer. We demonstrate the efficacy and resolution independence of the proposed LP-FNO for the 2D Poisson equation.

Kashi, Aditya↗

Shock tube experiments on the three-layer Richtmyer–Meshkov instability

Here, a vertical shock tube is used for experiments on the three-layer Richtmyer–Meshkov instability. Two closely spaced membrane-less interfaces are formed by the flow of two different sects of three gases: one with air above CO 2 above SF 6 and the other with helium above air above SF 6 . The lightest of the three gases enters the shock tube at the top of the driven section and flows downward. Conversely, the heaviest gas enters at the bottom of the shock tube and flows upward while the intermediate density gas enters at the middle through porous plates. All three gases are allowed to escape through holes at the layer location, leaving an approximately 30-mm layer of intermediate-density gas suspended between the lightest gas from above and the heaviest gas from below. A single-mode, two-dimensional initial perturbation is then imposed on the lower interface by oscillating the shock tube in the horizontal direction. The flow is visualized by seeding the intermediate gas with particles and illuminating it with a pulsed laser. Image sequences are then captured using high-speed video cameras. Perturbation amplitude measurements are made from the three-layer system and compared with measurements from 2, two-layer systems. It is observed that the presence of the upper, initially flat interface produces a decrease in growth of instability amplitude in the nonlinear phase over an equivalent single-interface configuration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Effect of pore fluid chemistry on the mechanical behavior of a divalent compacted bentonite, an experimental and constitutive study

Ongoing research in isolating high-level nuclear waste and spent fuel has highlighted compacted bentonite as a suitable material for engineered barrier systems in deep geological repositories due to its extraordinary swelling and retention properties. This research focuses on the chemo-mechanical behavior of compacted bentonite exposed to different pore fluids with different concentrations and loading conditions. The study involves swelling pressure and compressibility experiments along with mineralogy analysis employing X-ray diffraction (XRD) and Cation exchange. The tests were conducted on BCV (a Mg/Ca- bentonite) compacted at a dry density of 1.48 ± .02 Mg/m 3 . An advanced chemical-mechanical constitutive model for unsaturated highly expansive clays was adopted to simulate the material response and better understand its behavior. The model is able to account for the main phenomena at both macro and microstructural levels and the interactions between them. The model successfully replicated experimental observations. The XRD analyses support the macroscopic observation, indicating that salinity impacts crystalline swelling as demonstrated by the reduction of basal spacing from 19.27 Å to 15.68 Å when the osmotic suction increases from 0 MPa to 33 MPa. The results suggested that the osmotic pressure generated by the concentration in the pore fluids promotes a reduction in swelling pressures, swelling strains, and crystalline swelling of clay minerals. Also, it affects the pre-consolidation stress and the compressibility of the compacted samples. In conclusion, it was also observed that both solution type and solution concentration impact the clay swelling pressure.

Chemo-mechanical constitutive model↗

Modeling of shock-induced force on an isolated particle in water and air

The prediction of force on an isolated particle, while a shock is passing over it, is an important problem in many natural and industrial applications. Although the flow monotonically changes from the pre-shock to the post-shock state, the particle's force has been observed to behave nonmonotonically with a sharp peak when the shock is located halfway across the particle. This nonmonotonic behavior is due to the unsteady nature of the compression and rarefaction waves that radiate as the shock diffracts around the particle and, therefore, cannot be predicted by a quasi-steady model. An accurate force model must account for the unsteady nature of the flow and the sharp discontinues in the flow properties across the shock. In this work, we test four different inviscid models and observe that the compressible Maxey–Riley–Gatignol (C-MRG) model is the most accurate based on comparison with results from particle-resolved inviscid simulations at two different Mach numbers for both water and air as the medium. The C-MRG model is first demonstrated to predict the force on a stationary particle accurately and then extended to capture the force on a moving particle. Numerical complexities regarding the implementation of the C-MRG model are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Utah FORGE 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes - Workshop Presentation

This is a presentation on the Role of Fluid and Temperature in Fracture Mechanics and Coupled Thermo-Hydro-Mechanical-Chemical (THMC) Processes for Enhanced Geothermal Systems project by Purdue University, presented by Distinguished Professor of Physics & Astronomy, Laura J. Pyrak-Nolte. The project's objective was to develop and validate a macroscopic model that accounts for local deformation/frictional behavior, seismic/aseismic behavior, chemical reactions, and determine the adequacy of classic Coulomb failure vs. rate-and-state friction. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

Effects of external magnetic fields on the multi-mode Rayleigh–Taylor instability

The magneto-Rayleigh–Taylor instability (mRTI) is a key process in inertial confinement fusion and is thought to be widespread in the interstellar medium, where it can concentrate plasma into discrete structures. We present resistive MHD simulations of the nonlinear evolution of multi-mode mRTI in both two and three dimensions, examining the effects of uniform external magnetic fields oriented either parallel or perpendicular to the initial interface. In both 2D and 3D, weak parallel fields enhance mixing-zone growth, whereas stronger fields suppress it. For perpendicular fields, growth is initially inhibited but becomes enhanced at later times. These behaviors arise from magnetic tension, which modifies flow anisotropy, buoyancy, drag, and vortex dynamics. The interplay of these mechanisms governs the distinct ways in which magnetic fields influence mRTI evolution.

Flow instabilities↗

A mechanism for reduced compression in indirectly driven layered capsule implosions

High-yield implosions on the National Ignition Facility rely on maintaining low entropy in the deuterium–tritium fuel, quantified by its adiabat, in order to efficiently couple energy to the hot spot through high compression of the fuel layer. We present very-high-resolution xRAGE simulation results that study the impacts of interfacial mixing and the jetting of materials due to surface defects, defects on internal interfaces, voids, and engineering features on fuel layer compression. Defects and voids are typically neglected in implosion simulations due to their small size and three-dimensional geometry. Our results showed that supersonic jets of material arise through weak spots in the shell at peak implosion velocity that prevent uniform compression of the fuel layer even when they do not introduce contaminant into the hot spot. This occurs despite maintaining low fuel entropy, since the formation of the weak spots involves nonradial displacement of fuel mass. In contrast, simulations show that fuel–ablator mixing due to interfacial instabilities has a much smaller impact on compression. We show that defects on interior interfaces of plastic capsules decrease compression by 15% to 25% and interfacial mixing between the ablator and fuel decreases compression by less than 1% for implosions with plastic or high-density carbon (HDC) ablators. For low adiabat implosions, the impact of jetting seeded by the support tent can also decrease the compression by 25%. We demonstrate that the inclusion of interior defects in simulations can explain the inferred compression in two fielded plastic capsule implosions and that the inclusion of voids, for which available characterization has large uncertainties, in simulations of HDC capsule implosions has a qualitatively consistent impact. This mechanism offers a potential explanation for persistently overestimated fuel compression in design simulations of layered implosions on the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Utah FORGE 5-2557: Role of Fluid and Temperature in Fracture Mechanics and Couples THMC Processes for Enhanced Geothermal Systems - 2024 Annual Workshop Presentation

This is a presentation on the Role of Fluid and Temperature in Fracture Mechanics and Couples THMC Processes for Enhanced Geothermal Systems by Purdue University, presented by Laura Pyrak-Nolte. This video slide presentation describes the development and validation of a macroscopic model that can account for local deformation/friction behavior, seismic/aseismic behavior, chemical reactions, and determine the adequacy of classic Coulomb failure vs. rate-and-state friction. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13, 2024.

15 GEOTHERMAL ENERGY↗

Flow balancing devices, methods, and systems

The disclosed subject matter relates to extracorporeal blood processing or other processing of fluids. Volumetric fluid balance, a required element of many such processes, may be achieved with multiple pumps or other proportioning or balancing devices which are to some extent independent of each other. This need may arise in treatments that involve multiple fluids. Safe and secure mechanisms to ensure fluid balance in such systems are described.

Burbank, Jeffrey H.↗

Role of Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes for Enhanced Geothermal Systems

The ability to sustain high energy extraction efficiency from Enhanced Geothermal Systems (EGS) is affected by the ability to measure, characterize, and predict the effect of different perturbations that arise from fluid injection rates, fluid temperature, and shut-in conditions on existing and stimulated fracture systems throughout a subsurface reservoir’s lifecycle. The difficulty arises from limited knowledge of the interaction of fluid and temperature driven fractures with frictional interfaces that govern local deformation and frictional behavior in the surrounding rock. Thermo-poro-mechanical coupled processes tend to dominate this interaction and strongly affect the permeability and local stress distributions that impact efficiency and prevent optimal stimulation conditions over multi-decadal time frames.

Pyrak-Nolte, Laura [Purdue Univ., West Lafayette, ↗