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At least 127 records · Page 7

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗

The Statistical Mechanics of Ideal MHD Turbulence

Turbulence is a universal, nonlinear phenomenon found in all energetic fluid and plasma motion. In particular. understanding magneto hydrodynamic (MHD) turbulence and incorporating its effects in the computation and prediction of the flow of ionized gases in space, for example, are great challenges that must be met if such computations and predictions are to be meaningful. Although a general solution to the "problem of turbulence" does not exist in closed form, numerical integrations allow us to explore the phase space of solutions for both ideal and dissipative flows. For homogeneous, incompressible turbulence, Fourier methods are appropriate, and phase space is defined by the Fourier coefficients of the physical fields. In the case of ideal MHD flows, a fairly robust statistical mechanics has been developed, in which the symmetry and ergodic properties of phase space is understood. A discussion of these properties will illuminate our principal discovery: Coherent structure and randomness co-exist in ideal MHD turbulence. For dissipative flows, as opposed to ideal flows, progress beyond the dimensional analysis of Kolmogorov has been difficult. Here, some possible future directions that draw on the ideal results will also be discussed. Our conclusion will be that while ideal turbulence is now well understood, real turbulence still presents great challenges.

Shebalin, John V.↗

Thermonuclear 28 P(p, γ ) 29 S reaction rate and astrophysical implication in ONe nova explosion

An accurate 28 P(p, γ) 29 S reaction rate is crucial to defining the nucleosynthesis products of explosive hydrogen burning in ONe novae. Using the recently released nuclear mass of 29 S, together with a shell model and a direct capture calculation, we reanalyzed the 28 P(p, γ) 29 S thermonuclear reaction rate and its astrophysical implication. We focus on improving the astrophysical rate for 28 P(p, γ) 29 S based on the newest nuclear mass data. Our goal is to explore the impact of the new rate and associated uncertainties on the nova nucleosynthesis. We evaluated this reaction rate via the sum of the isolated resonance contribution instead of the previously used Hauser-Feshbach statistical model. The corresponding rate uncertainty at different energies was derived using a Monte Carlo method. Nova nucleosynthesis is computed with the 1D hydrodynamic code SHIVA. The contribution from the capture on the first excited state at 105.64 keV in 28 P is taken into account for the first time. We find that the capture rate on the first excited state in 28 P is up to more than 12 times larger than the ground-state capture rate in the temperature region of 2.5 × 10 7 K to 4 × 10 8 K, resulting in the total 28 P(p, γ) 29 S reaction rate being enhanced by a factor of up to 1.4 at ~1 × 10 9 K. In addition, the rate uncertainty has been quantified for the first time. It is found that the new rate is smaller than the previous statistical model rates, but it still agrees with them within uncertainties for nova temperatures. The statistical model appears to be roughly valid for the rate estimation of this reaction in the nova nucleosynthesis scenario. Using the 1D hydrodynamic code SHIVA, we performed the nucleosynthesis calculations in a nova explosion to investigate the impact of the new rates of 28 P(p, γ) 29 S. Our calculations show that the nova abundance pattern is only marginally affected if we use our new rates with respect to the same simulations but statistical model rates. Finally, the isotopes whose abundance is most influenced by the present 28 P(p, γ) 29 S uncertainty are 28 Si, 33,34 S, 35,37 Cl, and 36 Ar, with relative abundance changes at the level of only 3% to 4%.

Astronomy & Astrophysics↗

Simulating the filamentation of smoothed laser beams with three-dimensional nonlinear dynamics

In a plasma, the ponderomotive force of an inhomogeneous electromagnetic field expels plasma from regions of high intensity. When a laser propagates through a plasma, this force creates density wells that subsequently modify the index of refraction. The beam refracts and focuses into these wells and may filament. In extreme cases, the laser beam will spray due to increasing angular divergence of the beam. The threshold for ponderomotive self-focusing is well established for isolated laser hotspots or speckles. Here, we define a practical threshold for characterizing the filamentation of thousands of speckles that are found in the focal plane of high-power laser beams spatially smoothed with random phase plates as used at high energy and power laser facilities studying inertial confinement fusion. This threshold is tested against three-dimensional simulations of speckled laser light propagating through plasma. Four metrics are applied to assess filamentation: the fraction of power above five times the average intensity, an effective f-number, the mean-squared perpendicular wavenumber, and the fraction of rarefied density with deviation from the initial density exceeding | δn/ n| = 0.1. The speckled beams studied are generated by random phase plates, both with and without additional polarization smoothing, in a parameter regime of relevance to indirect drive experiments. While filamentation has been discussed extensively in the literature, we believe this to be the first published simulation study with three-dimensional nonlinear hydrodynamics that addresses the onset threshold of ponderomotive filamentation and establishes the lengths and time scales necessary to reach a statistical steady state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MODELING THE Ly α FOREST IN COLLISIONLESS SIMULATIONS

Cosmological hydrodynamic simulations can accurately predict the properties of the intergalactic medium (IGM), but only under the condition of retaining the high spatial resolution necessary to resolve density fluctuations in the IGM. This resolution constraint prohibits simulating large volumes, such as those probed by BOSS and future surveys, like DESI and 4MOST. To overcome this limitation, we present “Iteratively Matched Statistics” (IMS), a novel method to accurately model the Ly α forest with collisionless N -body simulations, where the relevant density fluctuations are unresolved. We use a small-box, high-resolution hydrodynamic simulation to obtain the probability distribution function (PDF) and the power spectrum of the real-space Ly α forest flux. These two statistics are iteratively mapped onto a pseudo-flux field of an N -body simulation, which we construct from the matter density. We demonstrate that our method can reproduce the PDF, line of sight and 3D power spectra of the Ly α forest with good accuracy (7%, 4%, and 7% respectively). We quantify the performance of the commonly used Gaussian smoothing technique and show that it has significantly lower accuracy (20%–80%), especially for N -body simulations with achievable mean inter-particle separations in large-volume simulations. In addition, we show that IMS produces reasonable and smooth spectra, making it a powerful tool for modeling the IGM in large cosmological volumes and for producing realistic “mock” skies for Ly α forest surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

ForestFlow: predicting the Lyman-α forest clustering from linear to nonlinear scales

On large scales, the Lyman-α forest provides insights into the expansion history of the Universe, while on small scales, it imposes strict constraints on the growth history, the nature of dark matter, and the sum of neutrino masses. This work introduces ForestFlow, a novel framework that bridges the gap between large- and small-scale analyses, which have traditionally relied on distinct modeling approaches. Using conditional normalizing flows, ForestFlow predicts the two Lyman-α linear biases (b δ and b η ) and six parameters describing small-scale deviations of the three-dimensional flux power spectrum (P 3D ) from linear theory as a function of cosmology and intergalactic medium physics. These are then combined with a Boltzmann solver to make consistent predictions, from arbitrarily large scales down to the nonlinear regime, for P 3D and any other statistics derived from it. Trained on a suite of 30 fixed-and-paired cosmological hydrodynamical simulations spanning redshifts from z = 2 to 4.5, ForestFlow achieves 3 and 1.5% precision in describing P 3D and the one-dimensional flux power spectrum (P 1D ) from linear scales to k = 5 Mpc −1 and k ∥ = 4 Mpc −1 , respectively. Thanks to its conditional parameterization, ForestFlow shows similar performance for ionization histories and two ΛCDM model extensions – massive neutrinos and curvature – even though none of these are included in the training set. This framework will enable full-scale cosmological analyses of Lyman-α forest measurements from the DESI survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Neutron Time-of-Flight Measurements of Charged-Particle Energy Loss in Inertial Confinement Fusion Plasmas

Neutron spectra from secondary 3 H(d,n)α reactions produced by an implosion of a deuterium-gas capsule at the National Ignition Facility have been measured with order-of-magnitude improvements in statistics and resolution over past experiments. Furthermore, these new data and their sensitivity to the energy loss of fast tritons emitted from thermal 2 H(d,p) 3 H reactions enable the first statistically significant investigation of charged-particle stopping via the emitted neutron spectrum. Radiation-hydrodynamic simulations, constrained to match a number of observables from the implosion, were used to predict the neutron spectra while employing two different energy loss models. This analysis represents the first test of stopping models under inertial confinement fusion conditions, covering plasma temperatures of k B T ≈ 1–4 keV and particle densities of n ≈ (12–2) × 10 24 cm –3 . Under these conditions, we find significant deviations of our data from a theory employing classical collisions whereas the theory including quantum diffraction agrees with our data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The influence of processor focus on speckle correlation statistics for a Shuttle imaging radar scene of Hurricane Josephine

The surface wave field produced by Hurricane Josephine was imaged by the L-band SAR aboard the Challenger on October 12, 1984. Exponential trends found in the two-dimensional autocorrelations of speckled image data support an equilibrium theory model of sea surface hydrodynamics. The notions of correlated specular reflection, surface coherence, optimal Doppler parameterization and spatial resolution are discussed within the context of a Poisson-Rayleigh statistical model of the SAR imaging process.

Tilley, David G.↗

Intrinsic alignments of galaxies in the MassiveBlack-II simulation: Analysis of two-point statistics

The intrinsic alignment of galaxies with the large-scale density field in an important astrophysical contaminant in upcoming weak lensing surveys. We present detailed measurements of the galaxy intrinsic alignments and associated ellipticity-direction (ED) and projected shape (w g ₊) correlation functions for galaxies in the cosmological hydrodynamic MassiveBlack-II (MB-II) simulation. We carefully assess the effects on galaxy shapes, misalignment of the stellar component with the dark matter shape and two-point statistics of iterative weighted (by mass and luminosity) definitions of the (reduced and unreduced) inertia tensor. We find that iterative procedures must be adopted for a reliable measurement of the reduced tensor but that luminosity versus mass weighting has only negligible effects. Both ED and w g ₊ correlations increase in amplitude with subhalo mass (in the range of 10¹⁰ – 6.0 X 10¹⁴h⁻¹ M ⊙ ), with a weak redshift dependence (from z = 1 to z = 0.06) at fixed mass. At z ~ 0.3, we predict a w g ₊ that is in reasonable agreement with SDSS LRG measurements and that decreases in amplitude by a factor of ~ 5–18 for galaxies in the LSST survey. We also compared the intrinsic alignment of centrals and satellites, with clear detection of satellite radial alignments within the host halos. Finally, we show that w g ₊ (using subhalos as tracers of density and w δ (using dark matter density) predictions from the simulations agree with that of non-linear alignment models (NLA) at scales where the 2-halo term dominates in the correlations (and tabulate associated NLA fitting parameters). The 1-halo term induces a scale dependent bias at small scales which is not modeled in the NLA model.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗

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↗

Influence of wave dispersion on vortex pairing in a jet

The geometry of large-scale structures in the turbulent mixing layer of a moderate Reynolds number jet is deduced from measurements of the fluctuating pressure in the hydrodynamic near field. The structures are rings of concentrated vorticity that distort with downstream distance until statistical axisymmetry disappears. The rings are spaced quasi-periodically and coalesce with each other, producing larger spacings. Statistical and flow-visualization techniques are applied to free and forced jets over a range of Reynolds numbers from 5000 to 50,000 to demonstrate that rings of a given spacing do not coalesce with each other until they are far enough downstream that the local mixing layer has attained some critical thickness which scales with the wavelength of the vortex pair. Wave dispersion is evaluated as a plausible mechanism for localizing the coalescences. The central feature of the model is the observation that a shear layer is dispersive to wavelengths much longer than its thickness and nondispersive to shorter waves.

Petersen, R. A.↗

Data-driven prediction of scaling and ignition of inertial confinement fusion experiments

Recent advances in inertial confinement fusion (ICF) at the National Ignition Facility (NIF), including ignition and energy gain, are enabled by a close coupling between experiments and high-fidelity simulations. Neither simulations nor experiments can fully constrain the behavior of ICF implosions on their own, meaning pre- and postshot simulation studies must incorporate experimental data to be reliable. Linking past data with simulations to make predictions for upcoming designs and quantifying the uncertainty in those predictions has been an ongoing challenge in ICF research. We have developed a data-driven approach to prediction and uncertainty quantification that combines large ensembles of simulations with Bayesian inference and deep learning. The approach builds a predictive model for the statistical distribution of key performance parameters, which is jointly informed by past experiments and physics simulations. The prediction distribution captures the impact of experimental uncertainty, expert priors, design changes, and shot-to-shot variations. We have used this new capability to predict a 10× increase in ignition probability between Hybrid-E shots driven with 2.05 MJ compared to 1.9 MJ, and validated our predictions against subsequent experiments. We describe our new Bayesian postshot and prediction capabilities, discuss their application to NIF ignition and validate the results, and finally investigate the impact of data sparsity on our prediction results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hydrodynamic analysis of laser-driven cylindrical implosions

Three-dimensional hydrodynamic simulations are performed to study laser-driven cylindrical implosions in the context of experiments (F. Perez et al., Plasma Phys. Controlled Fusion 51, 124035 (2009)) carried out at the Rutherford Appleton Laboratory in the framework of the HiPER project. The analysis is carried out by using the 3D version of the hydrocode MULTI (R. Ramis et al., Comput. Phys. Commun. 49, 475-505 (1988)). The influence of the main laser parameters on implosion performance and symmetry is consistently studied and compared with the results of 2D analysis. Furthermore, the effects of uncertainties in laser irradiation (pointing, focusing, power balance, and time jitter) on implosion performance (average peak density and temperature) are studied by means of statistical analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding the fusion yield dependencies in OMEGA DT-layered implosion experiments using a physics-based statistical mapping model

Improving the performance of inertial confinement fusion implosions requires physics models that can accurately predict the response to changes in the experimental inputs. Good predictive capability has been demonstrated for the fusion yield using a statistical mapping of simulated outcomes to experimental data [Gopalaswamy et al., Nature 565(771), 581–586 (2019)]. In this paper, a physics-based statistical mapping approach is used to extract and quantify all the major sources of degradation of fusion yield for direct-drive implosions on the OMEGA laser. Here, the yield is found to be dependent on the age of the deuterium tritium fill, the ℓ = 1 asymmetry in the implosion core, the laser beam-to-target size ratio, and parameters related to the hydrodynamic stability. A controlled set of experiments were carried out where only the target fill age was varied while keeping all other parameters constant. The measurements were found to be in excellent agreement with the fill age dependency inferred using the mapping model. In addition, a new implosion design was created, guided by the statistical mapping model by optimizing the trade-offs between increased laser energy coupling at larger target size and the degradations caused by the laser beam-to-target size ratio and hydrodynamic instabilities. When experimentally performed, an increased fusion yield was demonstrated in targets with larger diameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimizing time integration for accurate recovery of shockwave interface location in radiography

We present simulations and experiments of time integrated radiographic imaging of a moving 1D shock wave front and a quantitative method for determining the statistical error in locating the shock front as a function of integration time and noise in the radiograph. We discuss the trade-off between increasing motion blur, which leads to decreased shock front location certainty, and increasing signal-to-noise, which leads to improved image quality with increasing integration time. We find an optimum integration time between a short integration time, where noise limits the error, and a long integration time, where motion blurring limits the error. This methodology can be used to tune experimental configurations to obtain the highest quality radiograph for a given experimental configuration.

Bremsstrahlung↗

THE EFFECT OF ANISOTROPIC CONDUCTION ON THE THERMAL INSTABILITY IN THE INTERSTELLAR MEDIUM

Thermal instability (TI) can strongly affect the structure and dynamics of the interstellar medium (ISM) in the Milky Way and other disk galaxies. Thermal conduction plays an important role in the TI by stabilizing small scales and limiting the size of the smallest condensates. In the magnetized ISM, however, heat is conducted anisotropically (primarily along magnetic field lines). We investigate the effects of anisotropic thermal conduction on the nonlinear regime of the TI by performing two-dimensional magnetohydrodynamic simulations. We present models with magnetic fields of different initial geometries and strengths, and compare them to hydrodynamic models with isotropic conduction. We find that anisotropic conduction does not significantly alter the overall density and temperature statistics in the saturated state of the TI. However, it can strongly affect the shapes and sizes of cold clouds formed by the TI. For example, for uniform initial fields long filaments of cold gas are produced that are reminiscent of some observed H I clouds. For initially tangled fields, such filaments are not produced. We also show that anisotropic conduction suppresses turbulence generated by evaporative flows from the surfaces of cold blobs, which may have implications for mechanisms for driving turbulence in the ISM.

79 ASTRONOMY AND ASTROPHYSICS↗