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At least 1,657 records · Page 92

Measurements and Computations of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction specifically for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This paper will present and discuss the results of a recent experiment with the juncture-flow model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of that test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model pitch angle. Laser Doppler velocimetry (LDV) measurements were made at three model pitch angles (0 deg: fully attached, 1 deg: incipient separation, and 5 deg: separated flow) and for each one, mean-flow and Reynolds-stress data was obtained on the fuselage and at several streamwise locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and included model and tunnel wall static pressures, tunnel wall and ceiling boundary-layer rake data, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. Comparisons between the experimental data and Reynolds averaged Navier-Stokes CFD results will also be presented and discussed.

Juncture Flow↗

Measurements and Computational Analysis of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow Experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This report presents and discusses the results of a recent experiment with the Juncture Flow Model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of the test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model angle of incidence. Laser Doppler velocimetry (LDV) measurements were made at three model angles of incidence (0° : fully attached, 1° : incipient separation, and 5° : separated flow) and for each angle, mean-flow and Reynolds-stress data were obtained on the fuselage and at several locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and include model and tunnel wall static pressures, tunnel wall boundary-layer profiles, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. A companion set of Reynolds-averaged Navier-Stokes (RANS) CFD simulations were also performed and those results were used to support the discussion of the experimental test results.

Juncture Flow↗

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Λ polarization from vortex rings as the medium response for jet thermalization

We performed a systematic study on the formation of vorticity rings as the process for jet thermalization in the medium created in high-energy nuclear collisions. In this work, we expanded our previous analysis to a more realistic framework by considering noncentral events and fluctuations in the initial condition. We simulate the formation and evolution of the flow vortex structure in a relativistic viscous hydrodynamic model and study the sensitivity of the proposed “ring observable” (ℛ$^{𝑡}_{Λ}$) that can be measured experimentally through the polarization of Λ hyperons. We show that this observable is robust with respect to fluctuating initial conditions to capture the jet-induced vortex flow signal and further study its dependence on different model parameters, such as the jet's velocity, position, the fluid's shear viscosity, and the collision centrality. The proposed observable is associated with the formation of vorticity in a quark-gluon plasma, showing that the measurement of particle polarization can be a powerful tool to probe different properties of jet-medium interactions and to understand better the polarization induced by the transverse and longitudinal expansions of the medium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗

A two dimensional analysis of sheet resistance and contact resistance effects in solar cells

A computer model is developed to study the two-dimensional nature of the sheet resistance and contact resistance effects in solar cells. A major result is the demonstration that the distributed nature of the semiconductor sheet resistance causes the terminal dark I-V characteristics to exhibit an exp(qV/2kT) type dependence even when the one-dimensional characteristics of the cell exhibit an exp(qV/kT) type voltage dependence. The analytical model which is developed provides an easy method for estimating the sheet resistance of a solar cell from the terminal I-V data.

Fang, C. R.↗

On the Origin and Evolution of Stellar Chromospheres, Coronae and Winds

The final report discusses work completed on proposals to construct state-of-the-art, theoretical, two-component, chromospheric models for single stars of different spectral types and different evolutionary status. We suggested to use these models to predict the level of the "basal flux", the observed range of variation of chromospheric activity for a given spectral type, and the decrease of this activity with stellar age. In addition, for red giants and supergiants, we also proposed to construct self-consistent, purely theoretical, chromosphere-wind models, and investigate the origin of "dividing lines" in the H-R diagram. In the report, we list the following six specific goals for the first and second year of the proposed research and then describe the completed work: (1) To calculate the acoustic and magnetic wave energy fluxes for stars located in different regions of the H-R diagram; (2) To investigate the transfer of this non-radiative energy through stellar photospheres and to estimate the amount of energy that reaches the chromosphere; (3) To identify major sources of radiative losses in stellar chromospheres and calculate the amount of emitted energy; (4) To use (1) through (3) to construct purely theoretical, two-component, chromospheric models based on the local energy balance. The models will be constructed for stars of different spectral types and different evolutionary status; (5) To explain theoretically the "basal flux", the location of stellar temperature minima and the observed range of chromospheric activity for stars of the same spectral type; and (6) To construct self-consistent, time-dependent stellar wind models based on the momentum deposition by finite amplitude Alfven waves.

Musielak, Z. E.↗

Acoustic Tomography of the Atmosphere: A Large-Eddy Simulation Sensitivity Study

Accurate measurement of atmospheric turbulent fluctuations is critical for understanding environmental dynamics and improving models in applications such as wind energy. Advanced remote sensing technologies are essential for capturing instantaneous velocity and temperature fluctuations. Acoustic tomography (AT) offers a promising approach that utilizes sound travel times between an array of transducers to reconstruct turbulence fields. This study presents a systematic evaluation of the time-dependent stochastic inversion (TDSI) algorithm for AT using synthetic travel-time measurements derived from large-eddy simulation (LES) fields under both neutral and convective atmospheric boundary-layer conditions. Unlike prior work that relied on field observations or idealized fields, the LES framework provides a ground-truth atmospheric state, enabling quantitative assessment of TDSI retrieval reliability, sensitivity to travel-time measurement noise, and dependence on covariance model parameters and temporal data integration. A detailed sensitivity analysis was conducted to determine the best-fit model parameters, identify the tolerance thresholds for parameter mismatch, and establish a maximum spatial resolution. The TDSI algorithm successfully reconstructed large-scale velocity and temperature fluctuations with root mean square errors ( RMSE s) below 0.35 m/s and 0.12 K, respectively. Spectral analysis established a maximum spatial resolution of approximately 1.4 m, and reconstructions remained robust for travel-time measurement uncertainties up to 0.002 s. These findings provide critical insights into the operational limits of TDSI and inform future applications of AT for atmospheric turbulence characterization and system design.

17 WIND ENERGY↗

Evolution of attached and detached slabs and their associated mantle dynamics

Over the two years of the NASA grant, this project has produced a significant amount of research results related to the plate subduction process and the surface crustal deformation at convergent boundaries (i.e., above subduction zones). While some research objectives are completely accomplished, other research tasks remain active and continue to be investigated at present. A steady state analytic thermal model for subducting slabs was used to examine the torques acting on a descending slab. It is found that gravitational torque vanishes when a slab is dipping either vertically or horizontally, unlike previous studies indicating that the magnitude of gravitational torque decreases as dip angle increases. Subsequently, a new time-dependent, analytic thermal model for a subducting slab was developed. The new model enables us to study transient phenomena associated with plate subduction analytically. On the basis of this model, the nature of slab dip angles was evaluated. Slab dip angles are found to be transient features. As they penetrate into the mantle and increase their lengths, the associated gravitational torque also increases resulting in a downward pulling of the slab to the steeper dip angle. This is especially true once a slab penetrates the olivine-spinel phase boundary at about 400 km depth. However, if the phase transformation does not follow the equilibrium condition, the gravitational torque may have a different behavior. This problem was investigated. Except for fast descending slabs, non-equilibrium phase transformation can only slow down the transient increase of slab dip angles discussed earlier. Its effect is not sufficiently strong to reverse the downward pulling for most of the slabs. However, when slabs subducting at 10 cm/yr or faster, a sufficient amount of metastable olivine can exist beneath 400 km. Because of its low density compared with the surrounding spinel, an upward buoyancy is produced resulting in an upward bending of the slab and possibly an upward rotation of the slab such that smaller dip angles are formed. Seismic studies of the Japanese Slab seem to support this interpretation. The development of oroclinal geometries at convergent boundaries was also examined to study plate obduction which is an important ingredient to the initiation of plate subduction. Although the study suggests that surface features are better modeled by block models, the large scale deformation can be adequately studied by viscous models. Such a model is now under development to complete our original objective to study the initiation of plate subduction. Finally, a three-dimensional, finite element, spherical convective model is developed to study dynamic plate subductions. The model development is now complete and it is being tested to ensure its proper operation. The model is able to generate convection results with a viscosity contrast of about 100. Our research continues to push the viscosity contrast to a level that is appropriate for a subducting slab.

Hsui, Albert T.↗

Electronic effects in radiation-induced collision cascades in nickel

The accurate treatment of electronic effects in multi-million-atom simulations of radiation-induced collision cascades is crucial for reliable predictions of primary radiation damage. In this work, we explore the fidelity of a recently developed two-temperature molecular dynamics model implementing an electron density-dependent coupling of electronic and atomic subsystems for cascade simulations in nickel. We show that the parameter-free model realistically captures the instantaneous energy losses during all stages of the highly nonequilibrium cascade process. Our simulations predict two distinct coupling regimes, corresponding to the rapid energy losses through electronic stopping in the early stages of the cascade and to the slow equilibration through the electron-phonon coupling mechanism in the later stages, without the use of separate models or coupling terms. The intermediate stage of the cascade dynamics displays a complex energy transfer between the subsystems, which cannot be interpreted by comparison to either electronic stopping or electron-phonon coupling theories. We therefore compare the predicted atomic mixing, which is sensitive to the energy losses during the intermediate cascade stage, with experimental ion beam mixing measurements. We find good agreement with the experiments, validating the coupling model for the intermediate stage of the cascade. Predictions of final defect numbers and cluster sizes are found in line with the results from conventional electronic stopping-based methods, while significantly reducing the theoretical uncertainty in the outcomes of conventional models stemming from arbitrary choices of thresholds for different coupling terms. Our results represent a notable improvement in cascade damage predictions in nickel, providing validation of the electron density-dependent coupling model for radiation damage simulations in general. The results lead us to propose an interpretation of the electronic energy losses in the intermediate regime of velocities, where we find an effectively nonlinear dissipation.

Crystal defects↗

Data used in manuscript "Quantifying Subsurface Flow and Solute Transport in a Snowmelt-recharged Hillslope with Multiyear Water Balance", submitted to Water Resources Research on 5-26-2022

Data in this package were used to calculate subsurface flow and solute (specifically dissolved nitrogen) transport in the Pumphouse Lower Montane (PLM) hillslope. These data are included in separate CSV files associated with each figure presented in the manuscript. The files describe site locations and elevations, weather data (air temperatures and precipitation), modeled evapotranspiration, time dependent groundwater elevations, calculated annual subsurface flow, hydraulic conductivity values, time trends in subsurface flow within different zones, pore water concentrations of total dissolve nitrogen (TDN), rates of TDN transport, soil water matric potentials following snowmelt, soil water contents during drainage, and evapotranspiration calculated by soil water mass balance versus by CLM4 model.

54 ENVIRONMENTAL SCIENCES↗

Multiphysics modeling of printed surface acoustic wave thermometers

Surface acoustic wave (SAW) transducers are a class of sensors and actuators that operate on the fundamental principle of piezoelectricity. Aerosol jet printing and other additive manufacturing techniques have resulted in the low-cost fabrication of low-power and small-footprint SAW devices that are suitable for sensing in high-temperature and radioactive environments. In this work, we developed a series of temperature-dependent finite element models for a SAW transducer consisting of printed silver interdigitated transducers (IDTs) deposited onto piezoelectric lithium niobate. Modeling accuracy was evaluated experimentally from room temperature to 200 °C using an aerosol-jet-printed SAW thermometer. A time-domain study enabled visualization of the wave propagation and successfully guided the denoising of the scattering parameter measurement. Additionally, frequency-domain models using traditional modal analysis or the unique port boundary condition feature in COMSOL Multiphysics accurately predicted the temperature-driven natural frequency drift in the SAW thermometer. The finite element models developed in this study serve to facilitate the computer-aided design of future SAW transducers for applications in harsh environments.

47 OTHER INSTRUMENTATION↗

Getting Warmer: IceCube Nears Freeze Out

IceCube has recently detected a diffuse population of high-energy neutrinos arising from the Milky Way. We use this high-significance detection to place new limits on dark matter (DM) annihilation to neutrinos with two complementary approaches. The first method uses the background-subtracted Galactic longitude distribution of shower events to place a conservative bound on the DM annihilation cross section that does not rely on any assumed Galactic cosmic ray emission model; the resulting limits on the velocity-averaged annihilation cross section improve upon existing bounds by factors of a few. The second method uses the template-dependent neutrino energy spectra from the Inner Galaxy, inferred under different Galactic cosmic ray emission models. This complementary approach shows that the inferred Galactic neutrino intensities are already sensitive to DM contributions near the thermal-relic benchmark for a range of TeV-scale DM masses, though this comparison is more model-dependent. Our results demonstrate that measurements of diffuse Galactic neutrino emission can be used as a powerful probe of DM annihilation into neutrinos. Future observations with IceCube-Gen2 and KM3NeT will substantially extend this sensitivity, potentially allowing a decisive test of the thermal freeze-out mechanism with Galactic neutrino observations.

Mukhopadhyay, Mainak [Fermilab; Chicago U., KICP; ↗

Important role of stratospheric injection height for the distribution and radiative forcing of smoke aerosol from the 2019–2020 Australian wildfires

More than 1 Tg smoke aerosol was emitted into the atmosphere by the exceptional 2019–2020 southeastern Australian wildfires. Triggered by the extreme fire heat, several deep pyroconvective events carried the smoke directly into the stratosphere. Once there, smoke aerosol remained airborne considerably longer than in lower atmospheric layers. The thick plumes traveled eastward, thereby being distributed across the high and mid-latitudes in the Southern Hemisphere, enhancing the atmospheric opacity. Due to the increased atmospheric lifetime of the smoke plume, its radiative effect increased compared to smoke that remains in lower altitudes. Global models describing aerosol-climate impacts lack adequate descriptions of the emission height of aerosols from intense wildfires. Here, we demonstrate, by a combination of aerosol-climate modeling and lidar observations, the importance of the representation of those high-altitude fire smoke layers for estimating the atmospheric energy budget. Through observation-based input into the simulations, the Australian wildfire emissions by pyroconvection are explicitly prescribed to the lower stratosphere in different scenarios. Based on our simulations, the 2019–2020 Australian fires caused a significant top-of-atmosphere (TOA) hemispheric instantaneous direct radiative forcing signal that reached a magnitude comparable to the radiative forcing induced by anthropogenic absorbing aerosol. Up to +0.50 W m -2 instantaneous direct radiative forcing was modeled at TOA, averaged for the Southern Hemisphere (+0.25 W m -2 globally) from January to March 2020 under all-sky conditions. At the surface, on the other hand, an instantaneous solar radiative forcing of up to -0.81 W m -2 was found for clear-sky conditions, with the respective estimates depending on the model configuration and subject to the model uncertainties in the smoke optical properties. Since extreme wildfires are expected to occur more frequently in the rapidly changing climate, our findings suggest that high-altitude wildfire plumes must be adequately considered in climate projections in order to obtain reasonable estimates of atmospheric energy budget changes.

54 ENVIRONMENTAL SCIENCES↗

Multiple switch-off slow shock solutions

A new electromagnetic quasi-neutral time-dependent implicit hybrid model for simulating the slow-mode switch-off shock is developed, in which the electrons are treated as a finite-mass adiabatic fluid (gamma sub e = 5/3), whose motion along the shock normal provides local charge neutrality. The model is used to examine the effects of various boundary conditions applied during shock formation. It is shown that, for each upstream condition, two distinctly different slow-shock structures can be obtained: a low-shock structure with a trailing magnetic wave (TMW) and a slow-shock structure without a TMW, depending strongly on the boundary conditions for the electric and magnetic fields at the physical piston which generates the shock. The results indicate that the slow-shock structure with a TMW is nonlinearly unstable with respect to changes in the upstream magnetic field, suggesting that the downstream structure of slow shocks need not be associated with a TMW.

Vu, H. X.↗

The Martian climate: Energy balance models with CO2/H2O atmospheres

Progress in the development of a multi-reservoir, time dependent energy balance climate model for Mars driven by prescribed insolation at the top of the atmosphere is reported. The first approximately half-year of the program was devoted to assembling and testing components of the full model. Specific accomplishments were made on a longwave radiation code, coupling seasonal solar input to a ground temperature simulation, and conceptualizing an approach to modeling the seasonal pressure waves that develop in the Martian atmosphere as a result of sublimation and condensation of CO2 in polar regions.

Hoffert, M. I.↗

Rate-Dependent Dynamic Cylindrical Cavity Expansion Equations for Conical- and Ogival-Nosed Projectiles

The dynamic cylindrical cavity expansion of rate-dependent materials was previously derived by Warren to examine the effects of strain-rate sensitivity on the radial stress acting on a perforating projectile. However, the equations presented were largely analytical and were not further applied to predict the ballistic performance of ductile target plates. The current work expands on Warren’s derivation to model the dynamics of conical and ogival geometries, and the rate-dependent model is compared to prior experimental results of 7.62-mm APM2 rounds impacting 6061-T6511 aluminum alloy plates. The results show that including rate effects improves the ballistic performance prediction, even for a marginally strain-rate sensitive material such as Al6061-T651. However, existing semi-empirical variations of the cavity expansion model can provide the same degree of accuracy if target material rate-sensitivity parameters are not readily available.

36 MATERIALS SCIENCE↗

IMF By-dependent plasma flow and Birkeland currents in the dayside magnetosphere. I - Dynamics Explorer observations

Plasma, magnetic-field, and dc electric-field observations from Dynamics Explorers 1 and 2 are used to investigate the morphology of solar-wind ion injection, Birkeland currents, and plasma convection in the morning sector for both positive and negative interplanetary magnetic field (IMF) By components. The results of the study are used to construct a By-dependent global convection model for southward IMF. A significant element of the model is the coexistence of three types of convection cells ('merging cells', 'viscous cells', and 'lobe cells'). This model can account for observations of a nearly stationary (in local time) convection 'throat', a sunward-antisunward convection reversal zone at the polar-cap boundary in both the morning and afternoon quadrants, the morphology of solar-wind ion injection and transport in the mid-altitude polar cusp, and the By-dependent dawn-dusk asymmetry of polar-cap electron fluxes.

Burch, J. L.↗