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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Constraints on the finite volume two-nucleon spectrum at 𝑚𝜋 ≈806 MeV

The low-energy, finite-volume spectrum of the two-nucleon system at a quark mass corresponding to a pion mass of 𝑚𝜋≈806 MeV is studied with lattice quantum chromodynamics (LQCD) using variational methods. The interpolating-operator sets used in [Variational study of two-nucleon systems with lattice QCD, Phys. Rev. D 107, 094508 (2023).] are extended by including a complete basis of local hexaquark operators, as well as plane-wave dibaryon operators built from products of both positive- and negative-parity nucleon operators. Results are presented for the isosinglet and isotriplet two-nucleon channels. In both channels, noticeably weaker variational bounds on the lowest few energy eigenvalues are obtained from operator sets which contain only hexaquark operators or operators constructed from the product of two negative-parity nucleons, while other operator sets produce low-energy variational bounds which are consistent within statistical uncertainties. The consequences of these studies for the LQCD understanding of the two-nucleon spectrum are investigated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Vorticity-induced flow-focusing leads to bubble entrainment in an inkjet printhead: Synchrotron x-ray and volume-of-fluid visualizations

The oscillatory flows present in an inkjet printhead can lead to strong deformations of the air-liquid interface at the nozzle exit. Such deformations may lead to an inward directed air jet with bubble pinch-off and the subsequent entrainment of an air bubble, which is highly detrimental to the stability of inkjet printing. Understanding the mechanisms of bubble entrainment is therefore crucial to improving print stability. Here, in the present work, we use ultrafast x-ray phase-contrast imaging and direct numerical simulations based on the volume-of-fluid method to study the mechanisms underlying the bubble entrainment in a piezoacoustic printhead. We first demonstrate good agreement between experiments and numerics. We then show the different classes of bubble pinch-off obtained in experiments, and that those were also captured numerically. The numerical results are then used to show that the baroclinic torque, which is generated at the gas-liquid interface due to the misalignment of density and pressure gradients, results in a flow-focusing effect that drives the formation of the air jet from which a bubble can pinch off.

42 ENGINEERING↗
DOE OSTI2021

Eigenstate Entanglement: Crossover from the Ground State to Volume Laws

For the typical quantum many-body systems that obey the eigenstate thermalization hypothesis (ETH), we argue that the entanglement entropy of (almost) all energy eigenstates is described by a single crossover function. The ETH implies that the crossover functions can be deduced from subsystem entropies of thermal ensembles and have universal properties. These functions capture the full crossover from the ground-state entanglement regime at low energies and small subsystem size (area or log-area law) to the extensive volume-law regime at high energies or large subsystem size. For critical one-dimensional systems, a universal scaling function follows from conformal field theory and can be adapted for nonlinear dispersions. We use it to also deduce the crossover scaling function for Fermi liquids in d > 1 dimensions. Here, the analytical results are complemented by numerics for large noninteracting systems of fermions in d ≤ 3 dimensions and have also been confirmed for bosonic systems and nonintegrable spin chains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Prospects for Light Dark Matter Searches at Large-Volume Neutrino Detectors

We propose a new approach to search for light dark matter (DM), with keV–GeV mass, via inelastic nucleus scattering at large-volume neutrino detectors such as Borexino, DUNE, Super-K, Hyper-K, and JUNO. The approach uses inelastic nuclear scattering of cosmic-ray boosted DM, enabling a low-background search for DM in these experiments. Large neutrino detectors, with higher thresholds than dark matter detectors, can be used, since the nuclear deexcitation lines are O ( 10 ) MeV . Using a hadrophilic dark-gauge-boson-portal model as a benchmark, we show that the nuclear inelastic channels generally provide better sensitivity than the elastic scattering for a large region of light DM parameter space. Published by the American Physical Society 2024

Dutta, Bhaskar↗
DOE OSTI2024

Inverse Volume Scaling of Finite-Size Error in Periodic Coupled Cluster Theory

Coupled cluster theory is one of the most popular post-Hartree-Fock methods for molecular quantum chemistry. The finite-size error of the correlation energy in periodic coupled cluster calculations for three-dimensional insulating systems has been observed to satisfy the inverse volume scaling, even in the absence of any correction schemes. This is surprising, as simpler theories that utilize only a subset of the coupled cluster diagrams exhibit much slower decay of the finite-size error, which scales inversely with the length of the system. In this study, we review the current understanding of finite-size error in quantum chemistry methods for periodic systems. We introduce new tools that elucidate the mechanisms behind this phenomenon in the context of coupled cluster doubles calculations. This reconciles some seemingly paradoxical statements related to finite-size scaling. Our findings also show that singularity subtraction can be a powerful method to effectively reduce finite-size errors in practical quantum chemistry calculations for periodic systems. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Signs of nonmonotonic finite-volume corrections to 𝑔 𝐴

We study finite-volume (FV) corrections to determinations of 𝑔 𝐴 via lattice quantum chromodynamics (QCD) using analytic results and numerical analysis. We observe that 𝑆⁢𝑈⁡(2) heavy Baryon chiral perturbation theory does not provide an unambiguous prediction for the sign of the FV correction, which is not surprising when one also considers large-𝑁 𝑐 constraints on the axial couplings. We further show that nonmonotonic FV corrections are naturally allowed when one considers either including explicit Δ-resonance degrees of freedom or one works to higher orders in the chiral expansion. We investigate the potential impact of these FV corrections with a precision study of 𝑔 𝐴 using models of FV corrections that are monotonic and nonmonotonic. Using lattice QCD data that is approximately at the 1% level of precision, we do not see significant evidence of nonmonotonic corrections. Looking forward to the next phase of lattice QCD calculations, we estimate that calculations that are between the 0.1% and 1% level of precision may be sensitive to these FV artifacts. Finally, we present an update of the CalLat prediction of 𝑔 𝐴 in the isospin limit with subpercent precision, 𝑔$^{QCD}_{𝐴}$ = 1.2674⁢(96).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Pressure-induced irreversible volume collapse in a high-entropy alloy

At ambient conditions, the high-entropy alloy superconductor R⁢e 0.6⁢ (NbTiZrHf) 0.4 exhibits exceptional mechanical properties among high-entropy alloys, with its hexagonal phase achieving nanoindentation hardness of 18.5 GPa. We report on a unique pressure-induced structural transformation from a hexagonal phase to a body-centered cubic (BCC) phase, revealed by synchrotron x-ray diffraction measurements up to 70 GPa. This first-order transition, accompanied by a 6.1% volume collapse, occurs at 44 GPa and results in a BCC structure with random site occupancy by the five constituent elements, which is remarkably retained upon decompression to ambient conditions. The transformation proceeds via a martensiticlike, diffusionless mechanism without elemental segregation, enabled by pressure-induced electronic redistribution and atomic-scale disorder. These findings demonstrate a rare case of metastable phase retention in a chemically complex alloy and offer new insights into structure-stability relationships under pressure.

Alloys↗
DOE OSTI2020

A partial-volume correction for quantitative spectral x-ray radiography

The technique of spectral radiography has been shown to accurately discriminate a materials elemental composition by using known x-ray physics. This is achieved with a state-of-the-art pixelated spectrometer and a high-fidelity physical model. Similar to other radiographs, the system suffers from partial volume attenuation where the sample projection onto a pixel is only a fraction of the pixel area, leaving the rest unattenuated. This study updates the physical model to account for fractional area which presents new challenges to the existing algorithm. We present how this update is made and explore approaches to stabilize the algorithm through parameter scaling, constrained optimization, and hyperparameter selection.

Gillis, Wesley C.↗
DOE OSTI2022

Design and Characterization of an Optically Segmented Single Volume Scatter Camera Module

Here, the optically segmented single volume scatter camera (OS-SVSC) aims to image neutron sources for nuclear nonproliferation applications using the kinematic reconstruction of elastic double-scatter events. We report on the design, construction, and calibration of one module of a new prototype. The module includes 16 EJ-204 organic plastic scintillating bars individually wrapped in Teflon tape, each measuring 0.5cx0.5cmx20cm . The scintillator array is coupled to two custom silicon photomultiplier (SiPM) boards consisting of a 2x8 array of SensL J-Series-60035 SiPMs, which are read out by a custom 16 channel DRS4 based digitizer board. The electrical crosstalk between SiPMs within the electronics chain is measured as 0.76%±0.11% among all 16 channels. We report the detector response of one module including interaction position, time, and energy, using two different optical coupling materials: EJ-560 silicone rubber optical coupling pads and EJ-550 optical coupling grease. We present results in terms of the overall mean and standard deviation of the z -position reconstruction and interaction time resolutions for all 16 bars in the module. We observed the 1σz -position resolution for gamma interactions in the 0.3–0.4 MeVee range to be 2.24 cm ± 1.10 cm and 1.45 cm ± 0.19 cm for silicone optical coupling pad and optical grease, respectively. The observed 1σ interaction time resolution is 265 ps ± 29 ps and 235 ps ± 10 ps for silicone optical coupling pad and optical grease, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Make the Fastest Faster: Importance Mask Synthesis for Interactive Volume Visualization using Reconstruction Neural Networks

Visualizing a large-scale volumetric dataset with high resolution is challenging due to the substantial computational time and space complexity. Recent deep learning-based image inpainting methods significantly improve rendering latency by reconstructing a high-resolution image for visualization in constant time on GPU from a partially rendered image where only a portion of pixels go through the expensive rendering pipeline. However, existing solutions need to render every pixel of either a predefined regular sampling pattern or an irregular sample pattern predicted from a low-resolution image rendering. Both methods require a significant amount of expensive pixel-level rendering. In this work, we provide Importance Mask Learning (IML) and Synthesis (IMS) networks, which are the first attempts to directly synthesize important regions of the regular sampling pattern from the user’s view parameters, to further minimize the number of pixels to render by jointly considering the dataset, user behavior, and the downstream reconstruction neural network. Our solution is a unified framework to handle various types of inpainting methods through the proposed differentiable compaction/decompaction layers. Experiments show our method can further improve the overall rendering latency of state-of-the-art volume visualization methods using reconstruction neural network for free when rendering scientific volumetric datasets. Our method can also directly optimize the off-the-shelf pre-trained reconstruction neural networks without elongated retraining.

Large-scale data↗
DOE OSTI2024

Exploring Failure of Adhesively-Bonded Joints with Different Void Sizes at the Same Void Volume Fraction through A Micro-scale Numerical Modeling

This paper studied the effects of void sizes on the failure behavior of adhesively-bonded materials under global shear via micro-scale computational modeling. The numerical results indicate that large void sizes with increased distances between them at the same void volume fraction can alleviate the reduced joint strength of a weaker adherend-adhesive interface caused by interfacial voids. However, this is not the case for an adherend-adhesive interface with the interfacial tensile strength being sufficiently higher than the adhesive strength, showing the negligible effect on the joint strength due to various void sizes and the amount of interfacial voids. This preliminary investigation provides insightful information for scaling up the void size in the macro-scale computational modeling of joints, and enhances the understanding of the micro-mechanical adhesion in adherend-adhesive interfaces with different levels of bonding.

Qiao, Yao↗
DOE OSTI2020

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Volume of distribution at steady state (V D,ss ) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict V D,ss , accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human V D,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict V D,ss directly and to predict input parameters required for mechanistic and empirical V D,ss predictions. In addition, log D, fraction unbound in plasma (fup), and blood-to-plasma partition ratio (BPR) were measured on 254 compounds to estimate the impact of measured data on predictive performance of mechanistic models. Furthermore, the impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n = 189) on V D,ss predictions was also investigated. In predicting V D,ss directly from chemical structures, both mechanistic and empirical scaling using a combination of predicted rat and dog V D,ss demonstrated comparable performance (62%–71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 = 0.5, AAFE = 2.2) when built from a larger data set. Scaling to human from predicted V D,ss of either rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic V D,ss predictions significantly (81% within 3-fold, r 2 = 0.6, AAFE = 2.0). Adipocyte intracellular Kp showed good correlation to the V D,ss but was limited in estimating the compounds with low V D,ss .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Hybrid Finite-Volume, Discontinuous Galerkin Discretization for the Radiative Transport Equation

In this report we propose a hybrid spatial discretization for the radiative transport equation that combines a second-order discontinuous Galerkin (DG) method and a second-order finite-volume (FV) method. The strategy relies on a simple operator splitting that has been used previously to combine different angular discretizations. Unlike standard FV methods with upwind fluxes, the hybrid approach is able to accurately simulate problems in scattering dominated regimes. However, it requires less memory and yields a faster computational time than a uniform DG discretization. In addition, the underlying splitting allows naturally for hybridization in both space and angle. Numerical results are given to demonstrate the efficiency of the hybrid approach in the context of discrete ordinate angular discretizations and Cartesian spatial grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Probabilistic Scheme for Semilinear Nonlocal Diffusion Equations with Volume Constraints

This work presents a probabilistic scheme for solving semilinear nonlocal diffusion equations with volume constraints and integrable kernels. The nonlocal model of interest is defined by a time-dependent semilinear partial integro-differential equation (PIDE), in which the integro-differential operator consists of both local convection-diffusion and nonlocal diffusion operators. Here, our numerical scheme is based on the direct approximation of the nonlinear Feynman–Kac formula that establishes a link between nonlinear PIDEs and stochastic differential equations. The exploitation of the Feynman–Kac representation avoids solving dense linear systems arising from nonlocal operators. Compared with existing stochastic approaches, our method can achieve first-order convergence after balancing the temporal and spatial discretization errors, which is a significant improvement of existing probabilistic/stochastic methods for nonlocal diffusion problems. Error analysis of our numerical scheme is established. The effectiveness of our approach is shown in two numerical examples. The first example considers a three-dimensional nonlocal diffusion equation to numerically verify the error analysis results. The second example presents a physics problem motivated by the study of heat transport in magnetically confined fusion plasmas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Two dimensional topology optimization of heat exchangers with the volume fraction method

We perform a comparison study of two topology optimizations methods applied to the design of a two fluids heat exchanger modeled with a coupled thermal-flow problem. The flow follows an isothermal and incompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion equation without internal generation and high Peclet number. To keep the two fluid phases separated, we solve two Stokes-Brinkman equations, where the Brinkman term models the other phase as a solid. These two velocity fields are then fed to the heat transfer equation. Our goal is to maximize the enthalpy at the cold outlet while constraining the pressure drop. We first solve the design modeling the solid and fluid phases with a volume fraction variable. A SIMP-like penalization in the Brinkman term drives the optimization to a discrete design. The cost and constraint function derivatives are calculated with the library pyadjoint and the optimization is performed by IPOPT. We present optimized designs in two dimensions and discuss the influence of the parameters.

Beck, VictorA.↗
DOE OSTI2026

3D Gaussian Splatting for Volume Compression

This codebase uses machine learning to train a collection of 3D Gaussian distributions to approximate scientific volume data. Because this collection uses less memory than the original dataset, it can be used as a compressed model of the original data for applications such as visualization.

Dyken, Landon↗
DOE OSTI2023

Design of an ultra-low mode volume piezo-optomechanical quantum transducer

Coherent transduction of quantum states from the microwave to the optical domain can play a key role in quantum networking and distributed quantum computing. We present the design of a piezo-optomechanical device formed in a hybrid lithium niobate on silicon platform, that is suitable for microwave-to-optical quantum transduction. Our design is based on acoustic hybridization of an ultra-low mode volume piezoacoustic cavity with an optomechanical crystal cavity. The strong piezoelectric nature of lithium niobate allows us to mediate transduction via an acoustic mode which only minimally interacts with the lithium niobate, and is predominantly silicon-like, with very low electrical and acoustic loss. We estimate that this transducer can realize an intrinsic conversion efficiency of up to 35% with <0.5 added noise quanta when resonantly coupled to a superconducting transmon qubit and operated in pulsed mode at 10 kHz repetition rate. The performance improvement gained in such hybrid lithium niobate-silicon transducers make them suitable for heralded entanglement of qubits between superconducting quantum processors connected by optical fiber links.

Chiappina, Piero↗
DOE OSTI2024

Cyclic Injection Leads to Larger and More Frequent Induced Earthquakes under Volume-Controlled Conditions

As carbon storage technologies advance globally, methods to understand and mitigate induced earthquakes become increasingly important. Although the physical processes that relate increased subsurface pore pressure changes to induced earthquakes have long been known, reliable methods to forecast and control induced seismic sequences remain elusive. Suggested reservoir engineering scenarios for mitigating induced earthquakes typically involve modulation of the injection rate. Some operators have implemented periodic shutdowns (i.e., effective cycling of injection rates) to allow reservoir pressures to equilibrate (e.g., Paradox Valley) or shut-in wells after the occurrence of an event of concern (e.g., Basel, Switzerland). Other proposed scenarios include altering injection rates, actively managing pressures through coproduction of fluids, and preinjection brine extraction. Here, in this work, we use 3D physics-based earthquake simulations to understand the effects of different injection scenarios on induced earthquake rates, maximum event magnitudes, and postinjection seismicity. For comparability, the modeled injection considers the same cumulative volume over the project’s operational life but varies the schedule and rates of fluid injected. Simulation results show that cyclic injection leads to more frequent and larger events than constant injection. Furthermore, with intermittent injection scenario, a significant number of events are shown to occur during pauses in injection, and the seismicity rate remains elevated for longer into the postinjection phase compared to the constant injection scenario.

58 GEOSCIENCES↗