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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 433 records · Page 24

Tetrahedral Trees: A Family of Hierarchical Spatial Indexes for Tetrahedral Meshes

In this work, we address the problem of performing efficient spatial and topological queries on large tetrahedral meshes with arbitrary topology and complex boundaries. Such meshes arise in several application domains, such as 3D Geographic Information Systems (GISs), scientific visualization, and finite element analysis. To this aim, we propose Tetrahedral trees, a family of spatial indexes based on a nested space subdivision (an octree or a kD-tree) and defined by several different subdivision criteria. We provide efficient algorithms for spatial and topological queries on Tetrahedral trees and compare to state-of-the-art approaches. Our results indicate that Tetrahedral trees are an improvement over R*-trees for querying tetrahedral meshes; they are more compact, faster in many queries, and stable at variations of construction thresholds. They also support spatial queries on more general domains than topological data structures, which explicitly encode adjacency information for efficient navigation but have difficulties with domains with a non-trivial geometric or topological shape.

97 MATHEMATICS AND COMPUTING↗

Changes in Aerosols, Meteorology, and Radiation in the Southeastern U.S. Warming Hole Region during 2000 to 2019

Abstract Surface air temperatures in the southeastern United States that did not change from the climatological mean from 1900 to 2000 have increased since the year 2000. Analyzed herein are factors modulating the surface air temperatures in the region for a 20-yr period (2000–19) using space- and surface-based observations, and output from a reanalysis model. The 20-yr period is segregated into two decades, 2000–09 and 2010–19, corresponding to different tropospheric chemical regimes. Changes in seasonal and decadal averages are examined. The later decade experienced higher average surface air temperatures with significant warming during summer and fall seasons. Decadal and seasonal averages of cloud properties, column water vapor, rain rates, and top-of-atmosphere outgoing longwave radiation did not exhibit statistically significant differences between the two decades. The region experienced strong warm and moist advection during the winter months and very weak advection during the summer months. The later decade exhibited higher low-level moisture advection during the winter months than the earlier decade with insignificant changes in the temperature advection between the two decades. The later decade had significantly lower aerosol dry and liquid water mass during all seasons, along with lower aerosol optical depth, higher single scattering albedo, and lower top-of-the-atmosphere outgoing shortwave radiation during cloud-free conditions in the summer season. Collectively, these results suggest that changes in the aerosol direct radiative forcing are responsible for warming during summer months that experience weak advection and highlight seasonal differences in the temperature controlling mechanisms in the region.

54 ENVIRONMENTAL SCIENCES↗

Zinc oxide (ZnO) hybrid metasurfaces exhibiting broadly tunable topological properties

Extreme light confinement observed in periodic photonic structures, such as the vortex singularities in momentum (k) space, has been associated with their topological nature. Consequently, by exploiting and tuning their topological properties, optical metasurfaces have been demonstrated as an attractive platform for active photonics. However, given the fact that most active media under external excitations can only provide limited refractive index change, the potential advancements offered by the topological character of active metasurfaces have remained mostly unexplored. Zinc oxide (ZnO), which has recently exhibited optically-induced extraordinarily large permittivity modulations at visible and near-infrared frequencies, is an excellent active material for dynamic metasurfaces exhibiting strong tuning. This work demonstrates that a hybrid metasurface consisting of an array of ZnO nanodisks on a silver backplane displays broadly tunable topological properties. In particular, by performing k-space scattering simulations using measured pump-fluence-dependent material properties of ZnO, we study in detail the light reflection from the hybrid metasurface. Our results validate that the large k-space topology tuning of the metasurface can result in enormously strong polarization manipulation of near-infrared light in the vicinity of the topological features. The observed polarization switching effect is highly sensitive to the polarization and wavelength of an incident wave, owing to the symmetry and dispersion characteristics of the proposed system. Our study indicates that leveraging a combination of the extraordinary material properties and the k-space topology, hybrid metasurfaces based on ZnO may open new avenues for creating all-optical switchable metadevices.

36 MATERIALS SCIENCE↗

Recent progress in laser wire-based H- beam diagnostics at the SNS linac

Laser wire has been used for nonintrusive profile and emittance measurements of operational hydrogen ion (H-) beam at the SNS linac. In this talk, we will describe the following recent developments in the laser wire system. 1) An upgraded light source and laser transport line which enables novel measurement capabilities including longitudinal profile measurement and high-energy proton beam extraction over potentially an entire macropulse. 2) A dual-detector emittance measurement scheme that boosted the dynamic range by an order of magnitude. 3) Design and implementation laser-wire-based nonintrusive longitudinal phase space measurement system.

Liu, Yun↗

Penetration Bounds For Azimuthal Slot On Infinite Cylinder With Finite Length Backing Cylindrical Cavity

We examine coupling into azimuthal slots on an infinite cylinder with a infinite length interior cavity operating both at the fundamental cavity modal frequencies, with small slots and a resonant slot, as well as higher frequencies. The coupling model considers both radiation on an infinite cylindrical exterior as well as a half space approximation. Bounding calculations based on maximum slot power reception and interior power balance are also discussed in detail and compared with the prior calculations. For higher frequencies limitations on matching are imposed by restricting the loads ability to shift the slot operation to the nearest slot resonance; this is done in combination with maximizing the power reception as a function of angle of incidence. Finally, slot power mismatch based on limited cavity load quality factor is considered below the first slot resonance.

42 ENGINEERING↗

Application of a Null-Space Monte Carlo Flow Model Set to the Composite Analysis Base Case Fate and Transport Modeling

The Plateau-to-River (P2R) Model is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by Central Plateau Cleanup Company (CPCCo) at the Hanford Site in Washington State. Figure 1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the composite analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3 documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Real-Time, Simultaneous Soil Water Content and Meteorological Data Measurement to Support TRACER over Harris County, Texas (Field Campaign Report: Part I)

The main purpose of this project was to provide ground-truth and satellite-based soil water content data in the Houston, Texas, area to support the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s 2022 field campaign, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This involved installing four soil monitoring stations at different locations in the Houston area, two of which were part of the ARM facility and two were ancillary. The two stations associated directly with ARM were installed alongside other facilities managed and maintained by the TRACER research team during the intensive operational period (IOP), one located at the La Porte, Texas airport and the other near Guy, Texas. Data from these stations were assimilated with similar data collected by the Harris County Flood Control District (HCFCD) to improve the spatial coverage of the real-time monitoring network. The ground-truth data were compared to the satellite-based (National Aeronautics and Space Administration [NASA]’s Soil Moisture Active Passive [SMAP] mission) data in the TRACER area of interest, and analyzed further to nowcast gridded data over the Houston area. The nowcasted, gridded data product was made available to TRACER researchers for use in climate and land-atmosphere interaction modeling that can help understand formation and persistence of convective storms in dense urban areas, and predict possible environmental events such as floods.

54 ENVIRONMENTAL SCIENCES↗

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗

Real-Time, Simultaneous Soil Water Content and Meteorological Data Measurement to Support TRACER over Harris County, Texas Field Campaign Report: Part II

The main purpose of this project was to provide ground-truth and satellite-based soil water content data in the Houston, Texas, area to support the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s 2022 field campaign, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This involved installing four soil monitoring stations at different locations in the Houston area, two of which were part of the ARM facility and two were ancillary. The two stations associated directly with ARM were installed alongside other facilities managed and maintained by the TRACER research team during the intensive operational period (IOP), one located at the La Porte, Texas airport and the other located near Guy, Texas. Data from these stations were assimilated with similar data collected by the Harris County Flood Control District (HCFCD) to improve the spatial coverage of the real-time monitoring network. The ground-truth data were compared to the satellite-based (National Aeronautics and Space Administration [NASA]’s Soil Moisture Active Passive [SMAP] mission) data in the TRACER area of interest, and analyzed further to nowcast gridded data over the Houston area. The nowcasted, gridded data product was made available to TRACER researchers for use in climate and land-atmosphere interaction modeling that can help understand formation and persistence of convective storms in dense urban areas, and predict possible environmental events such as floods.

54 ENVIRONMENTAL SCIENCES↗

Particle configurations in the $NN\bar K$ system

Three-body AAB model for the $NN\bar K$(s NN = 0) kaonic cluster is considered based on the configuration space Faddeev equations. Within a single channel approach, the difference between masses of nucleons and kaons and the charge independence breaking of nucleon-nucleon interaction are taken into consideration. We definite the particle configurations in the system according to the particle masses and pair potentials. There are two sets of the particle configurations, ppK¯, npK¯ 0 and nnK¯ 0 , npK¯, charged and neutral. The three-body calculations are performed by applying NN and NK¯ phenomenological isospin-dependent potentials. The mass and energy spectra related to the particle configurations are presented. We evaluate the mass and energy uncertainties for the NNK¯ model. As a result, an analogy to NNN model for the 3 H and 3 He nuclei is proposed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A Phase-Field Model for In-Space Manufacturing of Binary Alloys

The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface.

36 MATERIALS SCIENCE↗

Galaxy Clusters Selected via the Sunyaev–Zel’dovich Effect in the SPTpol 100-square-degree Survey

In this work, we present a catalog of galaxy cluster candidates detected in 100 square degrees surveyed with the SPTpol receiver on the South Pole Telescope. The catalog contains 89 candidates detected with a signal-to-noise ratio greater than 4.6. The candidates are selected using the Sunyaev–Zel'dovich effect at 95 and 150 GHz. Using both space- and ground-based optical and infrared telescopes, we have confirmed 81 candidates as galaxy clusters. We use these follow-up images and archival images to estimate photometric redshifts for 66 galaxy clusters and spectroscopic observations to obtain redshifts for 13 systems. An additional two galaxy clusters are confirmed using the overdensity of near-infrared galaxies only and are presented without redshifts. We find that 15 candidates (18% of the total sample) are at redshift z ≥ 1.0, with a maximum confirmed redshift of ${z}_{\max }=1.38\pm 0.10$. We expect this catalog to contain every galaxy cluster with ${M}_{500c}\gt 2.6\times {10}^{14}{M}_{\odot }{{h}}_{70}^{-1}$ and z > 0.25 in the survey area. The mass threshold is approximately constant above z = 0.25, and the complete catalog has a median mass of approximately ${M}_{500c}=2.7\times {10}^{14}{M}_{\odot }{{h}}_{70}^{-1}$. Compared to previous SPT works, the increased depth of the millimeter-wave data (11.2 and 6.5 μK-arcmin at 95 and 150 GHz, respectively) makes it possible to find more galaxy clusters at high redshift and lower mass.

79 ASTRONOMY AND ASTROPHYSICS↗

Relativistic Alfvén Turbulence at Kinetic Scales

Abstract In a strongly magnetized, magnetically dominated relativistic plasma, Alfvénic turbulence can extend to scales much smaller than the particle inertial scales. It leads to an energy cascade somewhat analogous to inertial- or kinetic-Alfvén turbulent cascades existing in nonrelativistic space and astrophysical plasmas. Based on phenomenological modeling and particle-in-cell numerical simulations, we propose that the energy spectrum of such relativistic kinetic-scale Alfvénic turbulence is close to k −3 or slightly steeper than that due to intermittency corrections or Landau damping. We note the analogy of this spectrum with the Kraichnan spectrum corresponding to the enstrophy cascade in 2D incompressible fluid turbulence. Such turbulence strongly energizes particles in the direction parallel to the background magnetic field, leading to nearly one-dimensional particle momentum distributions. We find that these distributions have universal log-normal statistics.

79 ASTRONOMY AND ASTROPHYSICS↗

GAINN: The Galaxy Assembly and Interaction Neural Networks for High-redshift JWST Observations

We present the Galaxy Assembly and Interaction Neural Networks (Gainn), a series of artificial neural networks for predicting the redshift, stellar mass, halo mass, and mass-weighted age of simulated galaxies based on James Webb Space Telescope (JWST) photometry. Our goal is to determine the best neural network for predicting these variables at 11 < z < 15. The parameters of the optimal neural network can then be used to estimate these variables for real, observed galaxies. The inputs of the neural networks are JWST filter magnitudes of a subset of five broadband filters (F150W, F200W, F277W, F356W, and F444W) and two medium-band filters (F162M and F182M). We compare the performance of the neural networks using different combinations of these filters, as well as different activation functions and numbers of layers. The best neural network predicted redshift with a normalized rms error of $0.010^{+0.003}_{-0.001}$, stellar mass with rms = $0.089^{+0.044}_{-0.022}$, halo mass with a mean-squared error of $0.022^{+0.014}_{-0.008}$, and mass-weighted age with rms = $12.466^{+5.065}_{-2.408}$. We also test the performance of Gainn on real data from MACS0647JD, an object observed by JWST. Predictions from Gainn for the first projection of the object (JD1) have normalized bias $\langle$Δz$\rangle$ < 0.00228, which is significantly smaller than found with template-fitting methods. We find that the optimal filter combination is F277W, F356W, F162M, and F200W when considering both theoretical accuracy and observational resources from JWST.

97 MATHEMATICS AND COMPUTING↗

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗

Event-Based Anomaly Detection for Searches for New Physics

This paper discusses model-agnostic searches for new physics at the Large Hadron Collider using anomaly-detection techniques for the identification of event signatures that deviate from the Standard Model (SM). We investigate anomaly detection in the context of a machine-learning approach based on autoencoders. The analysis uses Monte Carlo simulations for the SM background and several selected exotic models. We also investigate the input space for the event-based anomaly detection and illustrate the shapes of invariant masses in the outlier region which will be used to perform searches for resonant phenomena beyond the SM. Challenges and conceptual limitations of this approach are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effects of interlayer spacing and applied pressure on the lanthanide transport in MoS 2 -based two-dimensional channels

Rare-earth elements (REEs) are critical to modern industry but difficult to separate due to their subtle and monotonic changes in physicochemical properties. MoS 2 -based two-dimensional (2D) materials offer novel opportunities for enhancing REE separation, exhibiting a distinct volcano-shaped transport performance distribution that peaks at Sm 3+ . However, the specific contributions of thermodynamic and kinetic factors to ion transport within 2D confinement remain unclear. In this study, we conducted a series of non-equilibrium all-atom molecular dynamics (MD) simulations to explore the effects of interlayer spacing and external pressure on the transport of lanthanide ions in Å-scale acetate functionalized 2D MoS 2 (MoS 2 -COOH) channels. We examined ion entry and permeation rates, water flux, dehydration, and binding modes. The simulation results reveal that the transport trends of lanthanide ions are jointly driven by the dehydration degree and the relative-binding strengths of ions to water and to the acetate within the 2D channels. Notably, the dehydration pattern of lanthanide ions during permeation is closely linked to kinetic factors. Overall, this study provides a detailed atomistic understanding of the mechanisms underlying lanthanide ion transport under confinement. These findings point to the significant potential for tuning confinement and chemical functionalization within Å-scale channels for more efficient REE separation.

2D channels↗