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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Constraining the initial stages of ultrarelativistic nuclear collisions

It is frequently supposed that quark-gluon plasma created in heavy-ion collisions undergoes free streaming at early times. Here, we examine this issue based on the assumption that a universal attractor dominates the dynamics already at the earliest stages, which offers a way to connect the initial state with the start of the hydrodynamic expansion in an approximate but conceptually transparent fashion. We demonstrate that the centrality dependence of the measured particle multiplicities can be used to quantitatively constrain the pressure anisotropy and find that it strongly depends on the model of the initial energy deposition. As an illustration, we compare three initial state models and show that they predict rather different early-time values of the pressure anisotropy. This suggests that while assuming free streaming prior to hydrodynamization may be compatible with some initial state models, in general, features of the prehydrodynamic flow need to be matched with the model of the initial state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Examining metastatic behavior within 3D bioprinted vasculature for the validation of a 3D computational flow model

Understanding the dynamics of circulating tumor cell (CTC) behavior within the vasculature has remained an elusive goal in cancer biology. To elucidate the contribution of hydrodynamics in determining sites of CTC vascular colonization, the physical forces affecting these cells must be evaluated in a highly controlled manner. To this end, we have bioprinted endothelialized vascular beds and perfused these constructs with metastatic mammary gland cells under physiological flow rates. By pairing these in vitro devices with an advanced computational flow model, we found that the bioprinted analog was readily capable of evaluating the accuracy and integrated complexity of a computational flow model, while also highlighting the discrete contribution of hydrodynamics in vascular colonization. This intersection of these two technologies, bioprinting and computational simulation, is a key demonstration in the establishment of an experimentation pipeline for the understanding of complex biophysical events.

42 ENGINEERING↗
DOE OSTI2024

Sensitivity of Simulations of Double-detonation Type Ia Supernovae to Integration Methodology

Abstract We study the coupling of hydrodynamics and reactions in simulations of the double-detonation model for Type Ia supernovae. When assessing the convergence of simulations, the focus is usually on spatial resolution; however, the method of coupling the physics together as well as the tolerances used in integrating a reaction network also play an important role. In this paper, we explore how the choices made in both coupling and integrating the reaction portion of a simulation (operator/Strang splitting versus the simplified spectral deferred corrections method we introduced previously) influences the accuracy, efficiency, and nucleosynthesis of simulations of double detonations. We find no need to limit reaction rates or reduce the simulation time step to the reaction timescale. The entire simulation methodology used here is GPU-accelerated and made freely available as part of the Castro simulation code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Automated Detection of Instability-Inducing Channel Geometry Transitions in Saint-Venant Simulation of Large-Scale River Networks

A new sweep-search algorithm (SSA) is developed and tested to identify the channel geometry transitions responsible for numerical convergence failure in a Saint-Venant equation (SVE) simulation of a large-scale open-channel network. Numerical instabilities are known to occur at “sharp” transitions in discrete geometry, but the identification of problem locations has been a matter of modeler’s art and a roadblock to implementing large-scale SVE simulations. The new method implements techniques from graph theory applied to a steady-state 1D shallow-water equation solver to recursively examine the numerical stability of each flowpath through the channel network. The SSA is validated with a short river reach and tested by the simulation of ten complete river systems of the Texas–Gulf Coast region by using the extreme hydrological conditions recorded during hurricane Harvey. The SSA successfully identified the problematic channel sections in all tested river systems. Subsequent modification of the problem sections allowed stable solution by an unsteady SVE numerical solver. The new SSA approach permits automated and consistent identification of problem channel geometry in large open-channel network data sets, which is necessary to effectively apply the fully dynamic Saint-Venant equations to large-scale river networks or for city-wide stormwater networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Systematic Local Simulations of Fast Neutrino Flavor Conversions with Scattering Effects

We investigate the dynamics of fast neutrino flavor conversions (FFCs) in the one-dimensional (1D) and zero-dimensional (0D) models, in which spatial advection is considered and ignored, respectively. In this study, we employ snapshots obtained by our self-consistent, realistic Boltzmann-neutrino-radiation-hydrodynamics simulations. We show that the FFC growth rate is considerably larger in the 1D model than in the 0D model, as expected from the previous linear analysis results. We find that the momentum space dimension does not significantly influence the neutrino transition probability in 1D models. On the other hand, in the 0D model without collisions, the FFC depends on the momentum space, and the azimuthal angle dependence breaks the periodicity of the FFC. Our study demonstrates that collisional instability can lead to further flavor conversions on a long timescale in 1D models after the asymptotic state of FFC has been reached. Such an effect should be taken into consideration when the fast and collisional flavor instabilities coexist.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Three-dimensional signatures of self-similarity in a high-energy-density plasma shear-driven mixing layer

A hydrodynamic shear mixing layer experiment at the National Ignition Facility had previously demonstrated Eulerian scaling of integrated, late-time quantities, including turbulent kinetic energy. In this manuscript, the experiment is repeated with new materials. In this work, using the new dataset, we demonstrate that Euler-number scalings hold not just for late time, but dynamically throughout the experiment, for measurements in all three spatial dimensions. Incorporating the dynamic scaling leads to an enhanced calculation that the heavier of the two scaled experiments has approached three generations of mergers of its primary instability's structures and a consistent observation of such a merger in action in the lighter of the two scaled experiments. Furthermore, the improved scrutiny of the time evolution of instability structures leads to sharper estimates of turbulent kinetic energy, including a demonstration of different behaviors correlating with surface roughness (quantitatively consistent with transitions between laminar and turbulent initial states), as predicted by a Reynolds-averaged turbulent model, which evidently correctly handles the differing shock-roughness interactions to drive its internal state of the model into different regimes. Altogether, a picture arises of the analytical improvements in treating these variations (of times, densities, and roughnesses) as a unified whole and of multiple ways by which deviations from the scaling could indicate an onset of non-hydrodynamic behavior. Such deviations were not expected for these experiments (which models correctly indicated would remain hydrodynamic) but could be introduced by, for example, imposing external fields or increasing drive energy to test conditions relevant to inertial confinement fusion or other high-energy-density experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The development of thermodynamically consistent and physics-informed equation-of-state model through machine learning

Ab initio molecular dynamics (AIMD) simulations have become an important tool used in the construction of equations of state (EOS) tables for warm dense matter. Due to computational costs, only a limited number of system state conditions can be simulated, and the remaining EOS surface must be interpolated for use in radiation-hydrodynamic simulations of experiments. In this work, we develop a thermodynamically consistent EOS model that utilizes a physics-informed machine learning approach to implicitly learn the underlying Helmholtz free-energy from AIMD generated energies and pressures. The model, referred to as PIML-EOS, was trained and tested on warm dense polystyrene producing a fit within a 1% relative error for both energy and pressure and is shown to satisfy both the Maxwell and Gibbs–Duhem relations. In addition, we provide a path toward obtaining thermodynamic quantities, such as the total entropy and chemical potential (containing both ionic and electronic contributions), which are not available from current AIMD simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Graph Neural Networks for Surrogate Modeling of Offshore Floating Platforms

Floating offshore wind turbines (FOWTs) present an significant opportunity to increase renewable energy generation. However, significant challenges remain before FOWTs can be widely commercialized and deployed. In particular, hydrodynamic loading on the platforms can stress the overall structure, damage the mooring systems, and impact power generation. Studying these loads is difficult and often relies on computationally expensive models or experiments. In this work, we explore the use of graph neural networks (GNNs) to construct flexible, data-driven surrogates for hydrodynamic loads on platforms. We leverage the natural graph-like structure of offshore wind platform designs to enable the GNN model to learn to approximate the loads for different wave conditions and structural designs. We demonstrate potential uses for the surrogate by performing parameter sweeps and ridge analysis on the trained model to identify the impacts of different wave and structural features on the loads.

floating offshore wind turbines↗
DOE OSTI2020

An accelerated approach to inline non-LTE modeling

A goal across many physics and engineering disciplines is to use radiation-hydrodynamics codes to accurately simulate systems that are expected to deviate from local thermodynamic equilibrium (LTE), such as laser-driven hohlraums, stellar coronae, and supernova ejecta. The computational expense of traditional non-LTE (NLTE) opacity calculations can dominate the cost of simulating these systems and render NLTE physics untenable in most cases. In this paper, we present a new parallel implementation for NLTE opacity calculations that employs advanced load balancing, vectorization, and memory management to significantly reduce the computational costs of these calculations. Using the radiation-hydrodynamics code xRAGE , we demonstrate this new implementation on three test problems and present order-of-magnitude speed improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A Gigaparsec-scale Hydrodynamic Volume Reconstructed with Deep Learning

The next generation of spectroscopic surveys will map the large-scale structure of the Universe at high redshifts (2 ≤ z ≤ 5) using millions of quasar spectra, enabling major advances in constraining both the standard cosmological model and its extensions. Robust cosmological analyses of these data sets require numerical simulations that both cover gigaparsec volumes and resolve features on ∼10 kpc scales and smaller. However, running such large-volume, high-resolution hydrodynamic simulations is computationally prohibitive. We present a generative deep learning model that enhances a low-resolution, gigaparsec-scale (960 h −1 Mpc) hydrodynamic simulation using a smaller (80 h −1 Mpc) high-resolution input hydrodynamic simulation as training data. The resulting enhanced simulation reproduces the line-of-sight power spectrum to within ∼10% and the three-dimensional power spectrum at the ∼20% level at intermediate to small scales (k ≲ 2 h Mpc −1 ). Our method shows strong promise for producing realistic simulations for cosmological analyses with current surveys such as the Dark Energy Spectroscopic Instrument and upcoming next-generation experiments, but further improvements are needed to accurately recover the large-scale modes. We publicly release the enhanced hydrodynamic simulation, along with a halo catalog from a companion N-body dark matter simulation to support the calibration of data analysis pipelines for these large-scale surveys.

Convolutional neural networks↗
DOE OSTI2021

(U) Radiation Hydrodynamics in the Ristra Project’s Symphony code: Initial release

One of the recent focuses in the next-generation code (NGC/Ristra)project at LANL is to develop a cell-centered Lagrangian radiation-hydrodynamics code under FleCSI framework. The FleCSI frame-work provides a unified data and execution model in order to insulate production code development from the uncertainty of evolving runtimeand architectures. We have developed the code, Symphony, which in-corporates the hydrodynamics code, FleCSALE, and the radiation transport code, Puno.This memo is intended to describe the coupling of radiation and hydrodynamics within the Ristra Project’s code Symphony.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cross-code comparison of the impact of the fill tube on high yield implosions on the National Ignition Facility

Fill tubes are used to inject deuterium and tritium fuel into inertial confinement fusion capsules fielded on the National Ignition Facility. These fill tubes have been shown to have a detrimental effect on capsule performance, primarily by introducing a low-density pathway into the central fuel region that enables the jetting of ablation material into the hot spot. Due to the complexity of the highly nonlinear flow associated with the fill tube and the challenge of diagnosing the evolution of the fill tube jet late in the implosion experiments, the uncertainty in how this perturbation source evolves is great. In this work, we report on the results of a detailed code comparison performed to understand uncertainties in computational modeling of the impact of fill tubes on implosion performance. The study employed two radiation-hydrodynamics codes, HYDRA and xRAGE, which employ very different meshing strategies and hydrodynamics solvers, as well as two radiation transport methodologies, discrete ordinates and multi-group diffusion. Our results demonstrate generally good agreement between codes through most of the implosion although they indicate sensitivity to opacity averaging methods. Late in the implosion, differences arise in the distribution and amount of contaminant although these differences have a remarkably small impact on the amount of yield reduction due to the fill tube. While these results demonstrate sensitivity in fill tube modeling to algorithmic choices, the observed differences between codes are small relative to known sensitivities due to expected variations in the fill tube geometry. Finally, we have developed a methodology for performing multi-group diffusion simulations that show good agreement with the more accurate discrete ordinates method

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Molecular fluctuations inhibit intermittency in compressible turbulence

In the standard picture of fully developed turbulence, highly intermittent hydrodynamic fields are nonlinearly coupled across scales, where local energy cascades from large scales into dissipative vortices and large density gradients. Microscopically, however, constituent fluid molecules are in constant thermal (Brownian) motion, but the role of molecular fluctuations in large-scale turbulence is largely unknown, and with rare exceptions, it has historically been considered irrelevant at scales larger than the molecular mean free path. Recent theoretical and computational investigations have shown that molecular fluctuations can impact energy cascade at Kolmogorov length scales. Here, we show that molecular fluctuations not only modify energy spectrum at wavelengths larger than the Kolmogorov length in compressible turbulence, but also significantly inhibit spatio-temporal intermittency across the entire dissipation range. Using large-scale direct numerical simulations of computational fluctuating hydrodynamics, we demonstrate that the extreme intermittency characteristic of turbulence models is replaced by nearly Gaussian statistics in the dissipation range. These results demonstrate that the compressible Navier–Stokes equations should be augmented with molecular fluctuations to accurately predict turbulence statistics across the dissipation range. Our findings have significant consequences for turbulence modelling in applications such as astrophysics, reactive flows and hypersonic aerodynamics, where dissipation-range turbulence is approximated by closure models.

compressible turbulence↗
DOE OSTI2021

Biermann battery magnetic fields in ICF capsules: Total magnetic flux generation

This paper focuses on the process of magnetic flux generation in inertial confinement fusion implosions. Hot-spots are shown to be dominated by fields generated during stagnation when the temperature and density gradients are largest. A scaling of hot-spot magnetic flux is derived and compared with simulations, revealing that perturbations with both larger amplitudes and higher mode numbers generate more magnetic flux. Furthermore, the model allows for greater understanding of which target designs will be susceptible to magnetohydrodynamic effects. For example, the model can be used to ascertain the time when most magnetic flux is generated. If generation is weighted more toward early times, then more high-mode magnetic field loops will be present. A hot-spot with no high-mode perturbations at time of peak neutron production can still contain significant magnetic flux on those scales. By assuming that magnetic flux is deposited at the hot-spot edge by Nernst advection, the model can be used to post-process radiation-hydrodynamics data to estimate magnetic field strengths and magnetizations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Nonplanar effects in simulations of laser-driven ejecta microjet experiments

Recent experiments of laser-driven ejecta microjets performed at OMEGA 60 reveal tortuous jets whereby the jets appear to deviate from their initial trajectory as they travel in vacuum. To understand these data, we perform two dimensional numerical simulations, considering different target thicknesses, pressures, and models of the drive conditions. In particular, modeling the finite laser spot size appears essential in reproducing qualitatively the non-planar shock observed in the experiment. Simulations capture jet deflection by accounting for a slight misalignment of the laser pointing with respect to the groove axis along with spatial variation of the laser pulse intensity. The principal physical mechanism appears to be that lateral momentum is imparted by release waves arising from the non-planar drive. The induced off-axis velocity is small in comparison to the jet axial velocity but integrates into a pronounced deflection over the course of the experiment. The analysis of jet axial and lateral mass distributions is found to be reproduced reasonably by the simulations. Simulated radiographs are in qualitative agreement with the experiments, though their differences point to potential shortcomings in modeling strictly three-dimensional experiments using two-dimensional hydrodynamic simulations. The simple analysis is able to explain part of the observed discrepancy in simulated vs experimental jet masses.

42 ENGINEERING↗
DOE OSTI2020

Heavy flavor quenching and flow: the roles of initial condition, pre-equilibrium evolution, and in-medium interaction

Within an advanced Langevin-hydrodynamics framework coupled to a hybrid fragmentation-coalescence hadronization model, we study heavy flavor quenching and flow in relativistic heavy-ion collisions. We investigate how the initial heavy quark spectrum, the in-medium energy loss and hadronization mechanisms of heavy quarks, the evolution profile of the pre-equilibrium stage, the medium flow, and the temperature dependence of heavy quark diffusion coefficients influence the suppression and elliptic flow of heavy mesons at the RHIC and the LHC. Our results show that the different modeling of initial conditions, pre-equilibrium evolution, and in-medium interactions can individually yield uncertainties of approximately 10-40% in D meson suppression and flow at a low transverse momentum. Furthermore, we also find that proper combinations of collisional versus radiative energy loss, coalescence versus fragmentation in hadronization, and the inclusion of medium flow are the most important factors for describing the suppression and elliptic flow of heavy mesons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Using baryonic charge balance functions to resolve questions about the baryo-chemistry of the quark gluon plasma

Baryon annihilations during the hadronic stage of heavy-ion collisions affects final-state baryon and antibaryon yields and final-state correlations of baryons and antibaryons. Understanding annihilation is important for addressing questions about the chemistry at the beginning of the hadronic stage and for interpreting charge-balance correlations involving baryons. Here, charge balance functions, using protons and antiprotons binned by relative momentum, rapidity, and azimuthal angle are shown to clarify the amount of annihilation in the hadronic stage. This enables a more accurate extraction of the baryo-chemistry at the beginning of the hadronic stage. Understanding annihilation is also crucial if charge balance correlations are to be used to infer the chemistry of the earliest stages of a heavy-ion collision. Furthermore, calculations are presented based on microscopic simulations of the hadronic stage coupled to a hydrodynamic description of the earlier stage, along with a detailed modeling of correlations of protons and antiprotons, known as charge-balance functions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Thermal energy transport in laser-driven high x-ray conversion efficiency metallic silver nanowire foams

Here, we report on record brightness from Ag x-ray emission obtained using a novel laser-produced plasma source. The reported K-shell conversion efficiency of nearly 1% with a radiant energy of ≈ 0.6 kJ/sr from Ag ions is the highest presently recorded and is about twofold greater than more conventional metal-lined cavity targets. He-like Ag ions are the dominant radiators at ≈ 22.7 keV, which contrast the x-ray sources from other pulse power facilities that produce K-shell x-rays from Auger processes in near-neutral ions driven by the nonthermal hot electrons produced in the Z-pinch implosion. The reported x-ray emission was produced from a 4-mm-diameter, 4-mm-long underdense silver nanowire target at 10⁢ mg/⁢cm 3 . The National Ignition Facility laser beams deposited ≈ 1000 kJ of 3ω light into the target with a ≈ 400 TW, 2.5 ns square pulse. Finally, we show via comparisons of data with radiation-hydrodynamics simulations that flux-limited classical thermal energy transport models are inadequate in correctly modeling the behavior of these non-local thermodynamic equilibrium plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗