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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AWSD reactive flow model for PBX 9404

An Arrhenius–Wescott–Stewart–Davis (AWSD) reactive flow model for high explosive PBX 9404 is developed. We specifically calibrate an AWSD model for PBX 9404 by fitting equations of state for reactants and detonation products to the results of thermochemical calculations and to experimental data from multiple sources. The calibrated equations of state are then coupled with an Arrhenius rate law based on shock temperature that describes the reaction progress during PBX 9404 detonation. The parameter values in the rate law are calibrated to experimental gas-gun data and diameter effect results. The results of the calibrated AWSD model are in strong agreement with available experimental data for PBX 9404. A similar level of agreement between predicted and experimental results is observed when the calibrated model is validated on data that were not used in the model parameterization procedure. Our results illustrate that the AWSD model is capable of accurately describing the many important properties and observables in the reactive burn of PBX 9404. Because of the historical significance of PBX 9404 in high explosives research and its current use in aging studies, this work provides an important model of a legacy material, which can be used to make comparisons to new high explosive formulations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Study of the agreement between binary neutron star ejecta models derived from numerical relativity simulations

Neutron star mergers have recently become a tool to study extreme gravity, nucleosynthesis, and the chemical composition of the Universe. To date, there has been one joint gravitational and electromagnetic observation of a binary neutron star merger, GW170817, as well as a solely gravitational observation, GW190425. In order to accurately identify and interpret electromagnetic signals of neutron star mergers, better models of the matter outflows generated by these mergers are required. We compare a series of ejecta models to see where they provide strong constraints on the amount of ejected mass expected from a system, and where systematic uncertainties in current models prevent us from reliably extracting information from observed events. We also examine 2396 neutron star equations of state compatible with GW170817 to see whether a given ejecta mass could be reasonably produced with a neutron star of said equation of state, and whether different ejecta models provide consistent predictions. We find that the difference between models is often comparable to or larger than the error generally assumed for these models, implying better constraints on the models are needed. In conclusion, we also note that the extrapolation of outflow models outside of their calibration window, while commonly needed to analyze gravitational wave events, is extremely unreliable and occasionally leads to completely unphysical results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Shock Hugoniot of Forged and Additively Manufactured 304L Stainless Steel

The purpose of this research was to measure the equation of state for additively manufactured (AM) and forged 304L stainless steel using a novel experimental technique. An understanding of the dynamic behavior of AM metals is integral to their timely adoption into various applications. The Hugoniot of the AM 304L was compared to that of the forged 304L at particle velocities where the material retains a two-wave structure. This comparison enabled us to determine the sensitivity of the equation of state to microstructure as varied due to processing. Our results showed that there was a measurable difference in the measured shock velocity between the AM and forged 304L. The shock wave velocities for the AM 304L were found to be ~3% slower than those for the forged 304L at similar particle velocities. To understand these differences, properties such as densities, sound speeds, and texture were measured and compared between the forged and AM materials. Our results showed that no measurable difference was found in these properties. Additionally, it is possible that differing elastic wave amplitudes may influence shock velocity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hydrogen and Silicon Effects on Hexagonal Close Packed Fe Alloys at High Pressures: Implications for the Composition of Earth's Inner Core

Hexagonal close-packed (hcp) structured Fe-Ni alloy is believed to be the dominant phase in the Earth's inner core. This phase is expected to contain 4%–5% light elements, such as Si and H. While the effects of individual light element candidates on the equation of state (EoS) of the hcp Fe metal have been studied, their combined effects remain largely unexplored. Here, in this study, we report the equations of state for two hcp-structured Fe-Si-H alloys, namely Fe 0.83 Si 0.17 H 0.07 and Fe 0.83 Si 0.17 H 0.46 , using synchrotron X-ray diffraction measurements up to 125 GPa at 300 K. These alloys were synthesized by cold compression of Fe-9wt%Si in either pure H 2 or Ar-H 2 mixture medium in diamond-anvil cells. The volume increase caused by a H atom in hcp Fe-Si-H alloys is approximately eight times greater than that by a Si atom. We used the improved data set to develop a composition-dependent EoS that covers a wide range of compositions. Our calculated density and bulk sound velocity of hcp Fe-Si-H alloys suggest a large trade-off between Si and H contents in fitting the seismic properties of the inner core. Combining our new EoS with geophysical and geochemical constraints, we propose 1.6–3 wt% Si and 0.15–0.6 wt% H in the Earth's inner core.

58 GEOSCIENCES↗
DOE OSTI2023

Effects of fragmentation on post-inflationary reheating

We consider the effects of fragmentation on the post-inflationary epoch of reheating. In simple single field models of inflation, an inflaton condensate undergoes an oscillatory phase once inflationary expansion ends. The equation of state of the condensate depends on the shape of the scalar potential, V(Φ), about its minimum. Assuming V(Φ) ~ Φ k , the equation of state parameter is given by w = P Φ /ρ Φ = (k - 2)/(k + 2). The evolution of condensate and the reheating process depend on k. For k ≥ 4, inflaton self-interactions may lead to the fragmentation of the condensate and alter the reheating process. Indeed, these self-interactions lead to the production of a massless gas of inflaton particles as w relaxes to 1/3. If reheating occurs before fragmentation, the effects of fragmentation are harmless. We find, however, that the effects of fragmentation depend sensitively to the specific reheating process. Reheating through the decays to fermions is largely excluded since perturbative couplings would imply that fragmentation occurs before reheating and in fact could prevent reheating from completion. Reheating through the decays to boson is relatively unaffected by fragmentation and reheating through scatterings results in a lower reheating temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

High-speed x-ray phase contrast imaging and digital image correlation analysis of microscale shock response of an additively manufactured energetic material simulant

The performance of energetic materials subjected to dynamic loading significantly depends on their micro- and meso-scale structural morphology. The geometric versatility offered by additive manufacturing opens new pathways to tailor the performance of these materials. Additively manufactured energetic materials (AMEMs) have a wide range of structural characteristics with a hierarchy of length scales and process-inherent heterogeneities, which are hitherto difficult to precisely control. It is important to understand how these features affect AMEMs’ response under dynamic/shock loading. Therefore, temporally and spatially resolved measurements of both macroscopic behavior and micro- and meso-level processes influencing macroscopic behavior are required. In this paper, we analyze the shock compression response of an AMEM simulant loaded under several impact conditions and orientations. Furthermore, x-ray phase contrast imaging (PCI) is used to track features across the observed shock front and determine the linear shock velocity vs particle velocity equation of state, as well as to quantify the interior deformation fields via digital image correlation (DIC) analyses. Photon Doppler velocimetry is simultaneously used to measure the particle velocities of the specimens, which are consistent with those obtained from x-ray PCI. The DIC analyses provide an assessment of the average strain fields inside the material, showing that the average axial strain depends on the loading intensity and reaches as high as 0.23 for impact velocities up to 1.5 km/s. The overall results demonstrate the utility of x-ray PCI for probing “in-material” equation of state and interior strains associated with dynamic shock compression behavior of the AMEM simulant.

3D printing↗
DOE OSTI2023

Observing the onset of pressure-driven K-shell delocalization

The gravitational pressure in many astrophysical objects exceeds one gigabar (one billion atmospheres), creating extreme conditions where the distance between nuclei approaches the size of the K shell. This close proximity modifies these tightly bound states and, above a certain pressure, drives them into a delocalized state. Both processes substantially affect the equation of state and radiation transport and, therefore, the structure and evolution of these objects. Still, our understanding of this transition is far from satisfactory and experimental data are sparse. Here, in this work, we report on experiments that create and diagnose matter at pressures exceeding three gigabars at the National Ignition Facility where 184 laser beams imploded a beryllium shell. Bright X-ray flashes enable precision radiography and X-ray Thomson scattering that reveal both the macroscopic conditions and the microscopic states. The data show clear signs of quantum-degenerate electrons in states reaching 30 times compression, and a temperature of around two million kelvins. At the most extreme conditions, we observe strongly reduced elastic scattering, which mainly originates from K-shell electrons. We attribute this reduction to the onset of delocalization of the remaining K-shell electron. With this interpretation, the ion charge inferred from the scattering data agrees well with ab initio simulations, but it is significantly higher than widely used analytical models predict.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Extreme compression of planetary gases: High-accuracy pressure-density measurements of hydrogen-helium mixtures above fourfold compression

Hydrogen (H 2 ) and helium (He), the most abundant elements in the universe, pose a unique challenge in measuring the equation of state of the mixture, owing to their differing physical properties. There remains a need for data with high enough precision to discriminate between existing equation of state (EOS) mix models in order to understand the internal structure of gas-giant planets. Here, we have measured the EOS of precompressed H 2 - He mixtures at conditions directly relevant to the planetary interiors using hypervelocity gas guns and Sandia’s Z machine with less than 10% uncertainty in density, enabling validation of mixture models. We precompressed 50:50 molar mixtures of H 2 -He to 0.1–0.2 GPa and directly measured particle velocity (in gas-gun experiments) and shock velocities (in Z-machine experiments). To complement the experimental efforts, we also computed the Hugoniots of precompressed H 2 -He mixtures using density-functional-theory-based molecular dynamics. Furthermore, we observe approximately 3- to 4.3-fold density compression at pressures up to 44 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

High Energy Density Physics of Inertial Confinement Fusion Ablator Materials

The historic December 5, 2022 experiment at Lawrence Livermore National Lab’s (LLNL) National Ignition Facility (NIF) reached fusion energy ignition for the first time. This is the most important scientific breakthrough of the 21st century paves the way to future clean inertial fusion energy (IFE). The diamond (high density carbon (HDC)) ablator material used in this experiment displays detrimental effects due to the development of hydrodynamic instabilities at the diamond/fuel interface under shock compression. New alternatives to diamond ablators are required to step up the energy yield in ICF experiments. The unique combination of mechanical strength (approaching that of diamond), the ability to accommodate high-Z dopants (in contrast to diamond), and the tunability of the properties (through synthesis material with varying sp 3 content) make amorphous carbon (a-C) a promising material for next-generation IFE ablative capsules. However, despite its critical importance to the IFE program, the behavior of a-C carbon at extreme temperatures and pressures remains largely unexplored. The primary goals of this project were to perform groundbreaking dynamic compression experiments and predictive simulations to uncover the fundamental high-energy-density physics of amorphous carbon. Our goals were (1) to uncover the metastability range of amorphous carbon and probe phase transitions to diamond or metastable supercooled liquid carbon; (2) to acquire high-quality equation of state (EOS) data and develop an experimentally validated EOS from machine-learning MD simulations of the complex states of carbon; and (3) to uncover the complex behavior of carbon liquid in both thermodynamically stable and metastable supercooled states by accessing large areas of carbon phase diagram with amorphous samples with variable sp 3 content. Our proposed experimental program included measurements of equation of state and diffraction measurements using the Omega EP laser at the Laboratory of Laser Energetics at the University of Rochester. The theoretical/simulation program involved the development of machine-learning models of the complex response of amorphous carbon under dynamic compression by performing molecular dynamics simulations at experimental time and length scales using leadership class DOE supercomputers. Simulations guided experiments to observe predicted phenomena and acquire critical experimental data in specific pressure-temperature domains to validate theoretical models. This research delivered fundamental properties of novel amorphous carbon IFE ablator material, including phase diagram and EOS. These results will aid in IFE target design and implosion experiments. A unique combination of predictive simulations and dynamic and static experiments provided a highly inspirational intellectual environment for graduate students and postdocs involved in this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Memory-efficient emulation of physical tabular data using quadtree decomposition

Computationally expensive functions are sometimes replaced in simulations with an emulator that approx-imates the true function (e.g., equations of state, wavelength-dependent opacity, or composition-dependent materials properties). For functions that have a constrained domain of interest, this can be done by discretizing the domain and performing a local interpolation on the tabulated function values of each local domain. For these so-called tabular data methods, the method of discretizing the domain and mapping the input space to each subdomain can drastically influence the memory and computational costs of the emulator. This is especially true for functions that vary drastically in different regions. We present a method for domain discretization and mapping that utilizes quadtrees, which results in significant reductions in the size of the emulator with minimal increases to computational costs or loss of global accuracy. We apply our method to the electron-positron Helmholtz free energy equation of state and show over an order of magnitude reduction in memory costs for reasonable levels of numerical accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Application of machine learning in the determination of impact parameter in the 132 Sn+ 124 Sn system

Here, 132 Sn + 124 Sn collisions at a beam energy of 270 MeV/nucleon were performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the nuclear equation of state. Reconstructing the impact parameter is one of the important tasks in the experiment as it relates to many observable. In this work, we employ three commonly used algorithms in machine learning, the artificial neural network (ANN), the convolutional neural network (CNN), and the light gradient boosting machine (LightGBM), to determine the impact parameter by analyzing either the charged particle spectra or several features simulated with events from the ultrarelativistic quantum molecular dynamics (UrQMD) model. To closely imitate experimental data and investigate the generalizability of the trained machine learning algorithms, incompressibility of nuclear equation of state and the in-medium nucleon-nucleon cross sections are varied in the UrQMD model to generate the training data. The mean absolute error Δb between the true and the predicted impact parameter is smaller than 0.45 fm if training and testing sets are sampled from the UrQMD model with the same parameter set. However, if training and testing sets are sampled with different parameter sets, Δb would increase to 0.8 fm. The generalizability of the trained machine learning algorithms suggests that these machine learning algorithms can be used reliably to reconstruct the impact parameter in experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Characterization of the inner edge of the neutron star crust

The poorly known crustal equation of state plays a critical role in many observational phenomena associated with a neutron star. Here using semiclassical Monte Carlo simulations, we explore the possible configurations of the inner edge of the neutron star crust for a variety of baryon densities and proton fractions. Applying the Kirkwood-Buff theory to these two-component systems, we observe how the isothermal compressibility reaches a maximum when isolated nonsymmetric (or quasispherical) clusters are formed in an extremely dilute neutron gas. To determine the neutron fraction, we suggest a geometrical model based on the behavior of the proton-neutron pair correlation function. Accordingly, the equation of state of the inner crust is calculated, illustrating that the nuclear energy in β equilibrium follows a power-law behavior with baryon density. As a possible astrophysical outcome of this study, our results could help refine the mass-radius relation. Finally, our results pave the way towards further investigations of the impact of the proton-neutron pair correlation function on transport properties within the neutron star crust.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A compact x-ray diffraction system for dynamic compression experiments on pulsed-power generators

Pulsed-power generators can produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies using the magnetic loading technique. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength–strain rate dependence, structural phase transitions, and density of crystal defects, such as dislocations. Here, we present a cost-effective, compact, pulsed x-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically driven ramp compression of materials with a single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials’ community to investigate in situ dynamic phase transitions critical to equation of states. Finally, we present results using this new diagnostic to evaluate lattice compression in Zr and Al and to capture signatures of phase transitions in CdS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Polyimide dynamically compressed to decomposition pressures: Two-wave structures captured by velocimetry and modeling

We performed a series of six plate impact experiments on polyimide and modeled them using new reactant and products equations of state combined with an Arrhenius rate model. The first experiment was diagnosed with embedded electromagnetic velocity gauges through which we directly observed attenuation of the lead shock to an approximately constant state over a propagation distance of roughly 4 mm. Simulated gauge profiles were in excellent qualitative agreement with experiment and suggested a sluggish chemical reaction that did not proceed to completion. The remaining five experiments were conducted in a transmission geometry and diagnosed velocimetrically at the sample/window interface. All five of these yielded profiles with a sharp shock followed by a more gradual approach to maximum interface velocity that was “rounded” to varying degree. These profiles proved difficult to interpret unambiguously due to the convolution of the reactive wave upon first shock with reflection of the lead wave and reshock or release by the window. Comparison with thermochemical calculations strongly suggests that the point of maximum interface velocity corresponds to the equilibrium reshock or release locus. We discuss the implications of this point for the practice of impedance matching based on the reflected Hugoniot of reactive materials such as polymers. The reactant and thermochemical products equations of state are developmental SESAME tables 97710 and 97720, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dynamic experiments to study the α - ε phase transition in cerium

The ability to understand and predict the response of matter at extreme conditions requires knowledge of a material’s equation-of-state including the location of phase boundaries, transition kinetics, and the evolution of material strength. Cerium is a material with a complex phase diagram that continues to attract significant scientific interest. Recent dynamic experiments have provided information on the low-pressure γ–α phase transition, sound speed, and Hugoniot data for the higher-pressure α phase, as well as the incipient shock melt transition. Despite these efforts, there are still regions of the phase diagram that are largely unexplored dynamically, including the high-pressure region below the melt boundary. Along a room temperature isotherm, diamond anvil cell data report a transition to the ϵ phase between 13 and 17 GPa. At higher temperatures, similar diamond anvil cell data show significant disagreement regarding the existence, location, and slope of the ϵ-phase boundary. In this work, double-shock loading was used to access the α–ϵ region of the phase diagram to obtain equation-of-state information and to determine the location of the ϵ-phase boundary for shock loading.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

TOUGH3/EOS7MG (EOS7MG) v1.1

EOS7MG is a new TOUGH3 module for modeling water, brine, and multiple gas mixtures in the subsurface multiphase flow system. The module allows mixture of as more as three gas components selecting from a list of predefined gases (CH4, C2H6, C3H8, H2S, CO2, N2, NO2, H2, and AIR). EOS7MG was developed based on EOS7C and inherited the general modeling capabilities of the TOUGH3 platform. It uses cubic equation of states for gas density, viscosity, and enthalpy calculation. The module provides the selection options for Peng-Robinson, Redlich-Kwong, or Soave-Redlich-Kwong equations of state. The subsurface flow and transport of gas and aqueous phase mixtures over a wide range of pressures and temperatures is modeled with a multiphase Darcy's Law and an accurate chemical equilibrium approach as originally implemented in EOS7C is used for calculation of the solubilities of different mass components. EOS7MG was designed to allow flexible number of components based on the number of gases included in the model. The potential application of this module may include subsurface gas storage, energy storage, CCS, enhanced gas recovery, and more.

Zhang, Keni↗