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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Single-Use Destructive Assay for Uranium Hexafluoride Sampling

Sampling uranium hexafluoride (UF6) for the determination of enrichments by destructive analysis (DA) is a critical component in the International Atomic Energy Agency’s layered safeguards approach for uranium processing facilities. Typically, gram-quantity UF6 samples are collected during inspections and stored under tag-and-seal until transportation to an off-site analytical laboratory. The shipping times can be long, and evolving restrictions on radioactive/corrosive materials shipments may increasingly limit the IAEA’s ability to transport UF6 samples easily. Pacific Northwest National Laboratory has developed a low-cost UF6 sampling technology called Single-Use Destructive Assay (SUDA) that addresses these challenges, as well as provides DA sample geometries that can be tailored for different analytical methods, including potential on-site analyses. The SUDA samplers, along with a unique holder, are designed for direct attachment to existing taps at uranium processing facilities, allowing gaseous UF6 to come into direct contact with a zeolite film. The SUDA technology features the ability to capture uranium in a more easily shipped and handled form as the solid, more stable, and relatively less hazardous hydrated uranyl fluoride (UO2F2•nH2O), which is formed through the controlled hydrolysis of UF6. We have recently simulated uranium collection under enrichment plant sampling conditions to further improve our understanding of SUDA sampling. Presented here is our recent work on measuring the relationship between sampling conditions and uranium collection, which includes control of the uranium-mass-to-zeolite ratio and assessing variable UF6 gas and sampling parameters that can affect collection using the SUDA sampler.

Pope, Timothy R.↗
DOE OSTI2023

Quantification of spatial and seasonal trends in the atmosphere and construction of statistical models for infrasonic propagation

SUMMARY Infrasonic waves are influenced by variations in the density, pressure and temperature as well as the ambient winds. Modelling infrasonic propagation can be challenging due to the dynamic nature of the atmosphere as well as the sparseness of measurements which result in variability and notable uncertainty. A framework is presented to quantify spatial and seasonal trends in atmospheric structure via analysis of the effective sound speed profile and identification of temporal trends in the middle atmospheric waveguide produced by the circumpolar vortex winds. Seasonal definitions identifying typical atmospheric structures during the summer, winter and spring/fall transition periods are identified using atmospheric data from 2010 through 2020. Seasonal trend analysis is conducted for a number of locations across the contiguous United States to quantify spatial variations in atmospheric structure that impact infrasonic propagation. For each season and location, empirical orthogonal function analysis is used to reduce the historical archive of atmospheric data into a smaller representative set that can be analysed using numerical tools more efficiently. Infrasonic ray tracing and finite-frequency modal propagation analyses are applied to construct propagation path geometry and transmission loss statistics which are useful in localization and yield estimation for infrasonic sources, respectively. An example application is detailed in which transmission loss statistics are combined with an explosive source model and noise statistics to quantify the capability of a network to detect nearby sources.

58 GEOSCIENCES↗
DOE OSTI2020

Tunable mechanical behavior of graphene nanoribbon-metal composites fabricated through an electrocharge-assisted process

This work investigates the role of a carbon nanophase on the local mechanical behavior of nanocarbon metal matrix composites (NCMCs) produced through an electrocharge-assisted process. Nanoindentation experiments on single crystal Al, Al 1350 parent alloys, and Al 1350 NCMCs revealed variable mechanical properties, caused by an interplay between microstructure and graphitic reinforcements. TEM and AFM studies also reveal nanoscale structural changes based on the incorporation of a carbon nanophase. In order to decouple the effects of the aforementioned mechanical behaviors, molecular dynamics nanoindentation simulations were performed on the (111) surface of Al and Al NCMC samples containing semi-infinite graphene nanoribbons to examine the evolution of plasticity over time. Findings indicate that the arrangement of a finite graphene nanophase within a host matrix can alter plasticity mechanisms and therefore yield strength in near-surface mechanical behavior with little effect on elastic properties. Here, this understanding enables further study into tunable bulk properties of Al-based NCMCs while isolating microstructural effects and reinforcement effects of the carbon phase. Such an understanding will lead to application-specific material geometries ranging from highperforming vehicle structures to next-generation electrical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Climate reconstructions for the Last Glacial Maximum from a simple cirque glacier in Fiordland, New Zealand

Mountain glacier records offer important constraints on the timing and magnitude of climate variability during the last glacial cycle. Existing moraine chronologies from the central Southern Alps indicate maximum ice extent was achieved during marine isotope stages 3–4, followed by repeated advances of similar, but gradually declining extent during marine isotope stage 2, until onset of the glacial termination. Questions remain over the precise role of climate in driving these changes, as most existing moraine chronologies come from large, complex former valley glacier systems, where non-climatic influences such as changing bed topography and proglacial lake formation may have influenced glacier length changes. In this work, we address this problem via a new cosmogenic 10Be chronology and equilibrium line altitude reconstruction from a cirque glacier situated in Fiordland, New Zealand. Our chronology shows moraine deposition at 32 ± 11 ka, 18.7 ± 0.2 ka, 18.1 ± 0.1 ka, and c. 17.2 ± 0.3 ka. The simple geometry of the former glacier supports the role of climate in driving a net decline of regional ice volume during marine isotope stages 3–2. Close spacing and good preservation of the 19–17 ka moraines permits 2D glacier reconstruction which suggests the equilibrium line altitude remained depressed by c.1130 m (equivalent to 5.8 ± 0.6 °C colder than present) during this interval. Onset of warming after 17.2 ± 0.2 ka is consistent with climate proxy evidence for a sustained southward shift in the southern westerly winds, which may have promoted deglaciation via shifting ocean currents and promoting increases in atmospheric carbon dioxide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mixed Element Microparticle Characterization by Electron Probe Microanalysis

Abstract Microparticle compositional characterization for nuclear forensics has traditionally been achieved by “gold-standard” destructive analytical techniques such as large geometry-secondary ion mass spectrometry and fission track-thermal ionization mass spectrometry, but long processing times and total sample consumption eliminate the option of subsequent analysis by other methods. Electron probe microanalysis has long been widely employed for rapid, nondestructive, micrometer-scale compositional measurements and imaging in fields such as material science and geology and may therefore need to be reevaluated as an alternative tool for microparticle analysis for the nuclear forensics community. This study presents the use of electron probe microanalysis for imaging and quantitative characterization of homogeneous microparticles utilizing a calibration curve based on high-precision quadrupole-inductively coupled plasma-mass spectrometry analyses. Samples of opportunity synthesized at Savannah River National Laboratory, nickel-doped cerium oxide microparticles, were selected as analogs for plutonium-doped uranium oxide microparticles. Positive detection and accurate quantification of variable amounts of nickel dopant down to trace levels (10s of parts per million) suggest applicability of this technique to other mixed element systems (e.g., actinides). Quantitative single-particle characterization via electron probe microanalyzer may thus provide a high fidelity, nondestructive complement to techniques currently in use.

Riche, Alexis T. (ORCID:0009000121978126)↗
DOE OSTI2020

Symbol alphabets from plabic graphs

Symbol alphabets of n-particle amplitudes in N = 4 super-Yang-Mills theory are known to contain certain cluster variables of Gr(4, n) as well as certain algebraic functions of cluster variables. In this paper we suggest an algorithm for computing these symbol alphabets from plabic graphs by solving matrix equations of the form C ∙ Z = 0 to associate functions on Gr(m, n) to parameterizations of certain cells of Gr(k, n) indexed by plabic graphs. For m = 4 and n = 8 we show that this association precisely reproduces the 18 algebraic symbol letters of the two-loop NMHV eight-particle amplitude from four plabic graphs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mudstone Baffles and Barriers in Lower Cretaceous Strata at a Proposed CO 2 Storage Hub in Kemper County, Mississippi, United States

The Cretaceous and Tertiary deposits in Mississippi, Alabama, and the adjacent continental shelf constitute a widespread succession of sandstone, mudstone, and carbonate that has proven to be an important target for geologic CO 2 storage in the onshore Gulf of Mexico basin. Integrated analysis of stratigraphy, sedimentology, and reservoir properties based on cores and geophysical well logs indicates that the Paluxy Formation and Washita- Fredericksburg interval present gigatonne-class storage opportunities. The distribution, geometry, and composition of the area is a direct reflection of the original depositional environments, and understanding these factors is essential for understanding the geologic storage potential of the Paluxy Formation and Washita-Fredericksburg interval at the Kemper County energy facility in Mississippi. Geologic characterization of the Mississippi Embayment at the energy facility focused primarily on characterizing the confinement potential of the storage complex. Integration of core analyses and geophysical well logs has yielded a high-resolution stratigraphic analysis of storage reservoirs, baffles, barriers, and seals. Scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS), and quantitative X-ray diffraction (XRD) was used to characterize microfabric, pore types, and mineralogy within mudstone of the east-central Mississippi Embayment at the Kemper County energy facility. Mudstone beds in the Paluxy Formation and Washita-Fredericksburg interval have variable thickness and continuity. High water saturation in the Cretaceous mudstone units influences swelling smectite clay and mudrock permeability based on pulse decay analysis is 1–96 nD. These low permeability values indicate that the mudstone units are effective baffles, barriers, and confining intervals that make significant migration of injected CO 2 out of the storage complex unlikely. The numerous baffles and barriers within the target reservoir intervals, moreover, favor the retention of multiple CO 2 in plumes within the abundant stacked sandstone bodies.

03 NATURAL GAS↗
DOE OSTI2025

Remote sensing images, DEM, and point clouds associated with “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds”

This data package is associated with the publication “Accuracy evaluation of cost-effective 3D reconstruction approaches for hydrobiogeochemical processes in non-perennial stream riverbeds” published in Frontiers in Environmental Science, Environmental Informatics and Remote Sensing (Bao et al., 2026; doi: 10.3389/fenvs.2026.1725258). This data package includes the drone photos for a section of Umtanum Creek in Washington, Unted States. The photos were used to reconstruct the 3-dimensional (3D) digital elevation model (DEM) of the riverbed for the investigated stream section. The reconstruction results from four approaches are provided: (1) unoccupied aerial vehicle (UAV, colloquially known as drone) imagery-based Structure-from-Motion (SfM), (2) a machine learning-based 3D reconstruction model, Visual Geometry Grounded Deep Structure from Motion (VGGSfM), (3) Visual Geometry Grounded Transformer for long sequence of images (VGGT-Long), and (4) handheld smartphone LiDAR scanning. The ground truth measurements by tripod-mounted optical level kit and ground control points GPS locations for evaluating the accuracy of the four reconstruction approaches are also provided in this data package. A preliminary version of this data package was published in October 2025 at the time of manuscript submission. It was updated in March 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) 8 folders; (2) the detailed flight configuration html files; (3) field metadata; (4) a readme; (5) a data dictionary; and (6) file-level metadata. The folders “2024_10_18_d01” and “2024_10_18_d02” contain the original drone photos for the two drone flights (d01 and d02) on October 18, 2024. The reconstruction results from each of the approaches are in the folders called “ODM_SfM”, “VGGSfM”, “VGGTLong”, and “LiDAR”. The ground truth measurements are in the folder called “optical_level_kit”. Lastly, results comparing the different approaches are in the folder called “comparisons”. All files are .csv, .html, .jpg, .obj, .txt, and .npy. For information on using the .obj and .npy files, see the readme files within the same folder as the files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mesh refinement for anisotropic diffusion in magnetized plasmas

Highly accurate simulation of plasma transport is needed to drive the successful design and operation of magnetically confined fusion reactors. Unfortunately, the extreme anisotropy present in magnetized plasmas results in thin boundary layers that are expensive to resolve. Here, this work investigates how various mesh refinement strategies might reduce that expense to allow for more efficient simulation by comparing standard variable refinement approaches that use a field quantity to an adaptive approach that uses an error estimator. It is first verified that higher order discretization only realizes the proper rate of convergence once the mesh resolves the thin boundary layer, therefore motivating the focusing of refinement on the boundary layer. For three two-dimensional test cases that contain characteristic features of tokamak magnetic fields, an exponential refinement strategy based on the magnetic flux function, which is the standard refinement approach in the field, is compared to an adaptive strategy utilizing the established Zienwiekicz and Zhu error estimator. The adaptive mesh refinement strategy consistently achieves the same accuracy using orders of magnitude less degrees of freedom than either exponential or uniform refinement. This result makes the adaptive refinement strategy more efficient than the exponential refinement strategy while also being more generalizable to problems with complex magnetic geometries. Scaling laws are derived that quantify the improvement in cost of the adaptive refinement strategy over other refinement approaches in 2D and 3D.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Rapid prototyping of arbitrary 2D and 3D wireframe DNA origami

Wireframe DNA origami assemblies can now be programmed automatically from the top-down using simple wireframe target geometries, or meshes, in 2D and 3D, using either rigid, six-helix bundle (6HB) or more compliant, two-helix bundle (DX) edges. While these assemblies have numerous applications in nanoscale materials fabrication due to their nanoscale spatial addressability and high degree of customization, no easy-to-use graphical user interface software yet exists to deploy these algorithmic approaches within a single, standalone interface. Further, top-down sequence design of 3D DX-based objects previously enabled by DAEDALUS was limited to discrete edge lengths and uniform vertex angles, limiting the scope of objects that can be designed. Here, we introduce the open-source software package ATHENA with a graphical user interface that automatically renders single-stranded DNA scaffold routing and staple strand sequences for any target wireframe DNA origami using DX or 6HB edges, including irregular, asymmetric DX-based polyhedra with variable edge lengths and vertices demonstrated experimentally, which significantly expands the set of possible 3D DNA-based assemblies that can be designed. ATHENA also enables external editing of sequences using caDNAno, demonstrated using asymmetric nanoscale positioning of gold nanoparticles, as well as providing atomic-level models for molecular dynamics, coarse-grained dynamics with oxDNA, and other computational chemistry simulation approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

From disorganized data to emergent dynamic models: Questionnaires to partial differential equations

Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate the data-driven derivation of parameter dependent, evolutionary partial differential equation (PDE) models capable of generating the data. This tensor type of data is reminiscent of shuffled (multidimensional) puzzle tiles. The independent variables for the evolution equations (their “space” and “time”) as well as their effective parameters are all emergent , i.e. determined in a data-driven way from our disorganized observations of behavior in them. We use a diffusion map based questionnaire approach to build a smooth parametrization of our emergent space/time/parameter space for the data. This approach iteratively processes the data by successively observing them on the “space,” the “time” and the “parameter” axes of a tensor. Once the data become organized, we use machine learning (here, neural networks) to approximate the operators governing the evolution equations in this emergent space. Our illustrative examples are based (i) on a simple advection–diffusion model; (ii) on a previously developed vertex-plus-signaling model of Drosophila embryonic development; and (iii) on two complex dynamic network models (one neuronal and one coupled oscillator model) for which no obvious smooth embedding geometry is known a priori. This allows us to discuss features of the process like symmetry breaking, translational invariance, and autonomousness of the emergent PDE model, as well as its interpretability.

generative models↗
DOE OSTI2026

TCAD-Machine Learning Enabled TID Compact Model Development for Commercial SiC MOSFET

We propose a TCAD (Technology Computer Aided Design)-machine learning coupled approach that combines a TCAD tool (Charon), optimization/uncertainty quantification tool (Dakota), surrogate models, and Bayesian learning capabilities. The coupling approach is used for accurate modeling and calibration of total ionizing dose (TID) induced threshold voltage (V th ) shifts in Commercial-Off-The-Shelf (COTS) semiconductor devices and to develop physics-informed TID compact models. This versatile approach is applied to model the TID effect in an exemplar COTS 3.3 kV SiC power MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor). With the Charon-Dakota coupling, we can determine key device geometry and doping values based on device physics, which are difficult to obtain or not available for COTS devices but important for TCAD simulation; additionally, we can efficiently generate thousands of simulation results in a large parameter space, which makes it possible to develop data-driven surrogate models and perform Bayesian calibration. Utilizing the full tool-coupling approach, we achieve calibrated TCAD simulation models that accurately capture the average TID-induced V th shifts behavior with total doses and V th shifts saturation at high doses as observed in experimental data. More importantly, the calibrated TCAD simulations are obtained with determined TID model parameters (e.g., hole trap density and capture cross section) values that contain well quantified uncertainties. Furthermore, we can isolate and quantify the noises that are not captured by the TCAD models but exist in the measured data due to measurements and devices variabilities. Lastly, the calibrated surrogate models are used to develop physics-informed TID compact models. The method is generalizable to other devices and/or radiation conditions with few modifications and can provide well-determined uncertainties.

COTS↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2021

Design of Microwave Resonant Cavity Transducer. Development of sensor performance model of microwave cavity flow meter for advanced reactor high temperature fluids

High-temperature fluid reactors, such as molten salt cooled reactors (MSCR) and sodium fast reactors (SFR), are a promising advanced reactor option. Measurement of high-temperature fluid process variables, in particular the flow inside the pressure vessel, is a challenging task because of harsh environment, which includes high radiation, high temperature, and contact with highly corrosive coolant fluid. We are investigating a microwave cavity-based transducer for high-temperature fluid flow sensing. This sensor is a hollow metallic cylindrical cavity, which can be fabricated from stainless steel, and as such is expected to be resilient to radiation, high temperature and corrosive environment of MSCR and SFR. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. A cavity is characterized by its resonant frequencies. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. Feasibility of the flow sensor is evaluated with signal sensitivity using COMSOL computer simulations. A right cylinder geometry stainless steel cavity with dimeter of 0.8in was investigated. We choose membrane thickness of 10mil, so that corrosion anticipated to proceed at the rate of 1mil/year in liquid sodium would affect no more than 10% of the membrane. Using the properties of liquid sodium fluid, and stainless-steel material property values at 500oC, we calculate frequency shift for a range of values of fluid velocity from 0.5m/s to 2m/s. Results of computer simulations indicate measurable sensitivity to flow for this cavity design. Following these simulations, we have developed a preliminary design for fabrication of a transducer operating in microwave K-band for proof-of-principle tests.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Drag Coefficient Analysis of Arbitrary Fragment Geometry with Emphasis on Meshing Sensitivity Studies.

This report characterizes Mach number effects in the hypersonic range from Mach 3 to Mach 7 for an arbitrary, computationally generated fragment. Force and moment coefficients in the x, y, z direction were successfully obtained and resulting trends were compared with theoretical expectations. Three orientations were tested in the form of unit vectors: [1,0,0], [0,1,0], and [0,0,1]; these represent the i, j, k principle axes. The final results ultimately showcased a trend very similar to that shown in previous literature — drag coefficients for a given orientation decreased with increasing Mach number by a very small amount in the hypersonic range. It was therefore concluded that the aerodynamic quantities used to obtain the fragment trajectory at low hypersonic Mach numbers (such as Mach 3) can be used to characterize the aerodynamic qualities at higher hypersonic Mach numbers (Mach 5, 7) with a reasonably small margin. A sensitivity study was also conducted which ultimately defined drag effects as a result of changing grid spacing and normal extrusion parameters for the unstructured tetrahedral mesh used in the simulation. Further work can be done in the form of experimental validation, specifically with regards to wind tunnels and ballistic range testing. Error can be reduced by testing more mesh variabilities and capturing a larger amount of fragment orientations. The results for force and moment characteristics dependent on meshing parameters and high Mach numbers are satisfactory and consistent with expected trends.

42 ENGINEERING↗
DOE OSTI2024

Measurement of flow coefficients in high-multiplicity 𝑝 + Au, 𝑑 + Au, and 3 He + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV

Flow coefficients (𝑣 2 and 𝑣 3 ) are measured in high-multiplicity 𝑝 + Au, 𝑑 + Au, and 3 He + Au collisions at a center-of-mass energy of $\sqrt{s_{NN}}$ = 200 GeV using the STAR detector. The measurements utilize two-particle correlations with a pseudorapidity requirement of |𝜂| < 0.9 and a pair gap of |Δ⁢𝜂| > 1.0. The primary focus is on analysis methods, particularly the subtraction of nonflow contributions. Four established nonflow subtraction methods are applied to determine 𝑣 𝑛 , validated using the HIJING event generator. 𝑣 𝑛 values are compared across the three collision systems at similar multiplicities; this comparison cancels the final-state effects and isolates the impact of initial geometry. While 𝑣 2 values show differences among these collision systems, 𝑣 3 values are largely similar, consistent with expectations of subnucleon fluctuations in the initial geometry. The ordering of 𝑣 𝑛 differs quantitatively from previous measurements using two-particle correlations with a larger rapidity gap, which, according to model calculations, can be partially attributed to the effects of longitudinal flow decorrelations. As a result, the prospects for future measurements to improve our understanding of flow decorrelation and subnucleonic fluctuations are also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Partons as unique ground states of quantum Hall parent Hamiltonians: The case of Fibonacci anyons

We present microscopic, multiple Landau level, (frustration-free and positive semi-definite) parent Hamiltonians whose ground states, realizing different quantum Hall fluids, are parton-like and whose excitations display either Abelian or non-Abelian braiding statistics. We prove ground state energy monotonicity theorems for systems with different particle numbers in multiple Landau levels, demonstrate S-duality in the case of toroidal geometry, and establish complete sets of zero modes of special Hamiltonians stabilizing parton-like states, specifically at filling factor \nu=2/3 ν = 2 / 3 . The emergent Entangled Pauli Principle (EPP), introduced in [Phys. Rev. B 98, 161118(R) (2018)] and which defines the “DNA” of the quantum Hall fluid, is behind the exact determination of the topological characteristics of the fluid, including charge and braiding statistics of excitations, and effective edge theory descriptions. When the closed-shell condition is satisfied, the densest (i.e., the highest density and lowest total angular momentum) zero-energy mode is a unique parton state. We conjecture that parton-like states generally span the subspace of many-body wave functions with the two-body M M -clustering property within any given number of Landau levels, that is, wave functions with M M th-order coincidence plane zeroes and both holomorphic and anti-holomorphic dependence on variables. General arguments are supplemented by rigorous considerations for the M=3 M = 3 case of fermions in four Landau levels. For this case, we establish that the zero mode counting can be done by enumerating certain patterns consistent with an underlying EPP. We apply the coherent state approach of [Phys. Rev. X 1, 021015 (2011)] to show that the elementary (localized) bulk excitations are Fibonacci anyons. This demonstrates that the DNA associated with fractional quantum Hall states encodes all universal properties. Specifically, for parton-like states, we establish a link with tensor network structures of finite bond dimension that emerge via root level entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗