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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Episodic jet power extracted from a spinning black hole surrounded by a neutrino-dominated accretion flow in gamma-ray bursts

It was suggested that the relativistic jets in gamma-ray bursts (GRBs) are powered via the Blandford-Znajek (BZ) mechanism or the annihilation of neutrinos and anti-neutrinos from a neutrino cooling-dominated accretion flow (NDAF). The advection and diffusion of the large-scale magnetic field of an NDAF is calculated, and the external magnetic field is found to be dragged inward efficiently by the accretion flow for a typical magnetic Prandtl number P{sub m}=η/ν∼1. The maximal BZ jet power can be ∼10{sup 53}-10{sup 54} erg s{sup –1} for an extreme Kerr black hole, if an external magnetic field with 10{sup 14} Gauss is advected by the NDAF. This is roughly consistent with the field strength of the disk formed after a tidal disrupted magnetar. The accretion flow near the black hole horizon is arrested by the magnetic field if the accretion rate is below than a critical value for a given external field. The arrested accretion flow fails to drag the field inward and the field strength decays, and then the accretion re-starts, which leads to oscillating accretion. The typical timescale of such episodic accretion is of an order of one second. This can qualitatively explain the observed oscillation in the soft extended emission of short-type GRBs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Biased tracers of two fluids in the Lagrangian picture

We explore Lagrangian perturbation theory (LPT) for biased tracers in the presence of two fluids, focusing on the case of cold dark matter (CDM) and baryons. The presence of two fluids induces corrections to the Lagrangian bias expansion and tracer advection, both of which we formulate as expansions in the three linear modes of the Lagrangian equations of motion. We compute the linear-order two-fluid corrections in the Zeldovich approximation, finding that modifications to the bias expansion and tracer advection both enter as percent-level corrections over a large range of wavenumbers at low redshift and draw parallels with the Eulerian formalism. We then discuss nonlinear corrections in the two-fluid picture, and calculate contributions from the relative velocity effect ($\propto$ v$_r^2$) at one loop order. Finally, we conduct an exploratory Fisher analysis to assess the impact of two-fluid corrections on baryon acoustic oscillations (BAO) measurements, finding that while modest values of the relative bias parameters can introduce systematic biases in the measured BAO scale of up to 0.5 $σ$, fitting for these effects as additional parameters increases the error bar by less than 30% across a wide range of bias values.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Recommendations on setup in simulating atmospheric gravity waves under conventionally neutral boundary layer conditions

Wind farm-induced atmospheric gravity waves have been the subject of recent research as they can impact wind farm performance. Pressure variations associated with gravity waves can contribute to the global blockage effect and wind farm wake recovery. Therefore, accurate numerical simulation of flow fields, where wind-farm-induced gravity waves may be produced, is important. Three main considerations in such simulations are the overall domain size, the use of Rayleigh damping near domain boundaries to dampen gravity waves, and advection damping at the inlet to prevent spurious oscillations. Often these considerations are treated ad hoc rather than systematically. This work aims to test and extend the systematic modelling of internal gravity waves proposed in a preliminary investigation to modelling of both internal and trapped gravity waves. The preliminary study identifies the length scales to set the domain and damping layer sizes and the time scale to configure the Rayleigh damping coefficient but under linearly stratified conditions. Large eddy simulations of flow through a wind farm canopy are performed under conventionally neutral boundary layer (CNBL) conditions to test the validity of proposed setups for CNBL conditions. Background atmospheric parameters, such as Froude number (Fr), inversion height (H i ), and inversion layer Froude number (Fr i ) control most of the atmospheric gravity wave characteristics. We validated for CBNL conditions that the effective wavelengths of the internal gravity waves are the correct length scale to configure the domain size and damping layer thickness. Likewise, the optimum damping coefficient to dampen the internal gravity waves relates to the free atmosphere's buoyancy frequency or buoyant perturbations' time scale. We infer that the damping coefficient in the inversion layer may relate to the inversion buoyancy frequency to effectively dampen the trapped gravity waves. Moreover, the advection damping length is linked to the horizontal wavelength of the trapped gravity waves in the inversion layer to prevent spurious waves at the inlet by retaining wave energy accumulation.

17 WIND ENERGY↗
DOE OSTI2014

FERMI BUBBLES AND BUBBLE-LIKE EMISSION FROM THE GALACTIC PLANE

The diffuse gamma-ray sky revealed ''bubbles'' of emission above and below the Galactic plane, symmetric around the center of the Milky Way, with a height of 10 kpc in both directions. At present, there is no convincing explanation for the origin. To understand the role of the Galactic center, one has to study the bubble spectrum inside the disk, a region that has been excluded from previous analyses because of the large foreground. From a novel template fit, which allows a simultaneous determination of the signal and foreground in any direction, we find that bubble-like emission is not only found in the halo, but in the Galactic plane as well, with a width in latitude coinciding with the molecular clouds. The longitude distribution has a width corresponding to the Galactic bar with an additional contribution from the Scutum-Centaurus arm. The energy spectrum of the bubbles coincides with the predicted contribution from CRs trapped in sources (SCRs). Also, the energetics fits well. Hence, we conclude that the bubble-like emission has a hadronic origin that arises from SCRs, and the bubbles in the halo arise from hadronic interactions in advected gas. Evidence for advection is provided by the ROSAT X-rays of hot gas in the bubble region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The effects of magnetic fields and protostellar feedback on low-mass cluster formation

In this paper, we present a large suite of simulations of the formation of low-mass star clusters. Our simulations include an extensive set of physical processes – magnetohydrodynamics, radiative transfer, and protostellar outflows – and span a wide range of virial parameters and magnetic field strengths. Comparing the outcomes of our simulations to observations, we find that simulations remaining close to virial balance throughout their history produce star formation efficiencies and initial mass function (IMF) peaks that are stable in time and in reasonable agreement with observations. Our results indicate that small-scale dissipation effects near the protostellar surface provide a feedback loop for stabilizing the star formation efficiency. This is true regardless of whether the balance is maintained by input of energy from large-scale forcing or by strong magnetic fields that inhibit collapse. In contrast, simulations that leave virial balance and undergo runaway collapse form stars too efficiently and produce an IMF that becomes increasingly top heavy with time. In all cases, we find that the competition between magnetic flux advection towards the protostar and outward advection due to magnetic interchange instabilities, and the competition between turbulent amplification and reconnection close to newly formed protostars renders the local magnetic field structure insensitive to the strength of the large-scale field, ensuring that radiation is always more important than magnetic support in setting the fragmentation scale and thus the IMF peak mass. The statistics of multiple stellar systems are similarly insensitive to variations in the initial conditions and generally agree with observations within the range of statistical uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The non-linear onset of neutrino-driven convection in two- and three-dimensional core-collapse supernovae

Here, a toy model of the post-shock region of core-collapse supernovae is used to study the non-linear development of turbulent motions driven by convection in the presence of advection. Our numerical simulations indicate that buoyant perturbations of density are able to trigger self-sustained convection only when the instability is not linearly stabilized by advection. Large amplitude perturbations produced by strong shock oscillations or combustion inhomogeneities before the collapse of the progenitor are efficiently shredded through phase mixing and generate a turbulent cascade. Our model enables us to investigate several physical arguments that had been proposed to explain the impact of the dimensionality on the onset of explosions in global simulations of core-collapse supernovae. Three-dimensional (3D) simulations are found to lead to higher entropy values than two-dimensional (2D) ones. We attribute this to greater turbulent mixing and dissipation of the kinetic energy into heat in 3D. Finally, our results show that the increase of entropy is enhanced with finer numerical resolution and larger perturbation amplitude.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Closures for multicomponent reacting flows based on dispersion analysis

This work presents algebraic closure models associated with advective transport and nonlinear reactions in a Reynolds-averaged Navier-Stokes context for a system of species subject to binary reactions and transport by advection and diffusion. Expanding upon analysis originally developed for non-reactive transport in the context of Taylor dispersion of scalars, this work extends the modified gradient diffusion model explicated by Peters [N. Peters, Turbulent Combustion, Cambridge Monographs on Mechanics (Cambridge University Press, Cambridge, 2000)] and based on work by Corrsin [S. Corrsin, The reactant concentration spectrum in turbulent mixing with a first-order reaction, J. Fluid Mech. 11, 407 (1961)] beyond single-component transport phenomena and involving nonlinear reactions. The presented model forms, from this weakly nonlinear extension of the original dispersion theory, lead to an analytic expression for the eddy diffusivity matrix that explicitly captures the influence of the reaction kinetics on the closure operators. Furthermore, we demonstrate that the derived model form directly translates between flow topologies through a priori and a posteriori testing of a binary species system subject to homogeneous isotropic turbulence. Using two- and three-dimensional direct numerical simulations involving laminar and turbulent flows, it is shown that this framework improves prediction of mean quantities compared to previous results. Lastly, the presented model form, collapses to the earlier gradient diffusion and its modified version derived by Corrsin in the limits of nonreactive species and linear reactions, respectively.

42 ENGINEERING↗
DOE OSTI2022

Effective drift velocity from turbulent transport by vorticity

Here, we highlight the differing roles of vorticity and strain in the transport of coarse-grained scalars at length scales larger than ℓ by smaller scale (subscale) turbulence. We use the first term in a multiscale gradient expansion due to which exhibits excellent correlation with the exact subscale physics when the partitioning length ℓ is any scale smaller than that of the spectral peak. We show that unlike subscale strain, which acts as an anisotropic diffusion/antidiffusion tensor, subscale vorticity's contribution is solely a conservative advection of coarse-grained quantities by an eddy-induced nondivergent velocity, v * , that is proportional to the curl of vorticity. Therefore, material (Lagrangian) advection of coarse-grained quantities is accomplished not by the coarse-grained flow velocity, u¯ ℓ , but by the effective velocity, u¯ ℓ + v * , the physics of which may improve commonly used LES models.

42 ENGINEERING↗
DOE OSTI2013

Structure and Dynamics of Colliding Plasma Jets

Monoenergetic-proton radiographs of laser-generated, high-Mach-number plasma jets colliding at various angles shed light on the structures and dynamics of these collisions. The observations compare favorably with results from 2D hydrodynamic simulations of multistream plasma jets, and also with results from an analytic treatment of electron flow and magnetic field advection. In collisions of two noncollinear jets, the observed flow structure is similar to the analytic model’s prediction of a characteristic feature with a narrow structure pointing in one direction and a much thicker one pointing in the opposite direction. Spontaneous magnetic fields, largely azimuthal around the colliding jets and generated by the well-known ∇T e ×∇n e Biermann battery effect near the periphery of the laser spots, are demonstrated to be “frozen in” the plasma (due to high magnetic Reynolds number R M ~5×10⁴) and advected along the jet streamlines of the electron flow. These studies provide novel insight into the interactions and dynamics of colliding plasma jets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Structure of a magnetic flux annihilation layer formed by the collision of supersonic, magnetized plasma flows

We present experiments characterizing the detailed structure of a current layer, generated by the collision of two counter-streaming, supersonic and magnetized aluminum plasma flows. The anti parallel magnetic fields advected by the flows are found to be mutually annihilated inside the layer, giving rise to a bifurcated current structure—two narrow current sheets running along the outside surfaces of the layer. Measurements with Thomson scattering show a fast outflow of plasma along the layer and a high ion temperature (T i ~¯ZT e , with average ionization ¯Z=7). Lastly, analysis of the spatially resolved plasma parameters indicates that the advection and subsequent annihilation of the in-flowing magnetic flux determines the structure of the layer, while the ion heating could be due to the development of kinetic, current-driven instabilities.

42 ENGINEERING↗
DOE OSTI2020

Torque and Angular-Momentum Transfer in Merging Rotating Bose-Einstein Condensates

When rotating classical fluid drops merge together, angular momentum can be advected from one to another due to the viscous shear flow at the drop interface. It remains elusive what the corresponding mechanism is in inviscid quantum fluids such as Bose-Einstein condensates (BECs). In this work, we report our theoretical study of an initially static BEC merging with a rotating BECin three-dimensional space along the rotational axis. We show that a solitonlike sheet, resembling a corkscrew, spontaneously emerges at the interface. Furthermore, rapid angular momentum transfer at a constant rate universally proportional to the initial angular-momentum density is observed. Strikingly, this transfer does not necessarily involve fluid advection or drifting of the quantized vortices. We reveal that the corkscrew structure can exert a torque that directly creates angular momentum in the static BEC and annihilates angular momentum in the rotating BEC. Uncovering this intriguing angular momentum transport mechanism may benefit our understanding of various coherent matter-wave systems, spanning from atomtronics on chips to dark matter BECs at cosmic scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Algorithms for propagating uncertainty across heterogeneous domains

We address an important research area in stochastic multi-scale modeling, namely the propagation of uncertainty across heterogeneous domains characterized by partially correlated processes with vastly different correlation lengths. This class of problems arise very often when computing stochastic PDEs and particle models with stochastic/stochastic domain interaction but also with stochastic/deterministic coupling. The domains may be fully embedded, adjacent or partially overlapping. The fundamental open question we address is the construction of proper transmission boundary conditions that preserve global statistical properties of the solution across different subdomains. Often, the codes that model different parts of the domains are black-box and hence a domain decomposition technique is required. No rigorous theory or even effective empirical algorithms have yet been developed for this purpose, although interfaces defined in terms of functionals of random fields (e.g., multi-point cumulants) can overcome the computationally prohibitive problem of preserving sample-path continuity across domains. The key idea of the different methods we propose relies on combining local reduced-order representations of random fields with multi-level domain decomposition. Specifically, we propose two new algorithms: The first one enforces the continuity of the conditional mean and variance of the solution across adjacent subdomains by using Schwarz iterations. The second algorithm is based on PDE-constrained multi-objective optimization, and it allows us to set more general interface conditions. The effectiveness of these new algorithms is demonstrated in numerical examples involving elliptic problems with random diffusion coefficients, stochastically advected scalar fields, and nonlinear advection-reaction problems with random reaction rates.

Cho, Heyrim↗
DOE OSTI2018

High-Order Multi-Material ALE Hydrodynamics

Here, we present a new approach for multi-material arbitrary Lagrangian--Eulerian (ALE) hydrodynamics simulations based on high-order finite elements posed on high-order curvilinear meshes. The method builds on and extends our previous work in the Lagrangian and remap phases of ALE, and depends critically on a functional perspective that enables subzonal physics and material modeling. Curvilinear mesh relaxation is based on node movement, which is determined through the solution of an elliptic equation. The remap phase is posed in terms of advecting state variables between two meshes over a fictitious time interval. The resulting advection equation is solved by a discontinuous Galerkin (DG) formulation, combined with a customized Flux Corrected Transport (FCT) type algorithm. Because conservative fields are remapped, additional synchronization steps are introduced to preserve bounds with respect to primal fields. These steps include modification of the low-order FCT solutions, definition of conservative FCT fluxes based on primal field bounds, and monotone transitions between primal and conservative fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators

We present an adaptive grid matrix-free operator approximation scheme based on a "product-convolution" interpolation of convolution operators. This scheme is appropriate for operators that are locally translation-invariant, even if these operators are high rank or full rank. Such operators arise in Schur complement methods for solving partial differential equations (PDEs), as Hessians in PDE-constrained optimization and inverse problems, as integral operators, as covariance operators, and as Dirichlet-to-Neumann maps. Constructing the approximation requires computing the impulse responses of the operator to point sources centered on nodes in an adaptively refined grid of sample points. A randomized a posteriori error estimator drives the adaptivity. Once constructed, the approximation can be efficiently applied to vectors using the fast Fourier transform. The approximation can be efficiently converted to hierarchical matrix (H-matrix) format, then inverted or factorized using scalable H-matrix arithmetic. The quality of the approximation degrades gracefully as fewer sample points are used, allowing cheap lower quality approximations to be used as preconditioners. Furthermore, this yields an automated method to construct preconditioners for locally translation-invariant Schur complements. We directly address issues related to boundaries and prove that our scheme eliminates boundary artifacts. We test the scheme on a spatially varying blurring kernel, on the nonlocal component of an interface Schur complement for the Poisson operator, and on the data misfit Hessian for an advection dominated advection-diffusion inverse problem. Numerical results show that the scheme outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Space-Time Block Preconditioning for Incompressible Flow

Parallel-in-time methods have become increasingly popular in the simulation of time-dependent numerical PDEs, allowing for the efficient use of additional message passing interface processes when spatial parallelism saturates. Most methods treat the solution and parallelism in space and time separately. In contrast, all-at-once methods solve the full space-time system directly, largely treating time as simply another spatial dimension. All-at-once methods offer a number of benefits over separate treatment of space and time, most notably significantly increased parallelism and faster time to solution (when applicable). However, the development of fast, scalable all-at-once methods has largely been limited to time-dependent (advection-)diffusion problems. This paper introduces the concept of space-time block preconditioning for the all-at-once solution of incompressible flow. By extending well-known concepts of spatial block preconditioning to the space-time setting, we develop a block preconditioner whose application requires the solution of a space-time (advection-)diffusion equation in the velocity block, coupled with a pressure Schur complement approximation consisting of independent spatial solves at each time-step, and a space-time matrix-vector multiplication. The new method is tested on four classical models in incompressible flow. Finally, the results indicate perfect scalability in refinement of spatial and temporal mesh spacing, perfect scalability in nonlinear Picard iteration count when applied to a nonlinear Navier--Stokes problem, and minimal overhead in terms of number of preconditioner applications compared with sequential time-stepping.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Parallel-in-Time Solution of Hyperbolic PDE Systems via Characteristic-Variable Block Preconditioning

We consider the parallel-in-time solution of both linear and nonlinear hyperbolic partial differential equation (PDE) systems in one spatial dimension. In the nonlinear setting, the discretized equations are solved with a preconditioned residual iteration based on a global linearization. The linear(ized) equation systems are approximately solved parallel-in-time using a block preconditioner applied in the characteristic variables of the underlying linear(ized) hyperbolic PDE. This change of variables is motivated by the observation that intervariable coupling between characteristic variables is weak, at least locally where spatio-temporal variations in the eigenvectors of the associated flux Jacobian are sufficiently small, while that between the original variables is not. For an ℓ-dimensional system of PDEs, applying the preconditioner consists of solving a sequence of ℓ scalar linear(ized)-advection-like problems, each associated with a different characteristic wave-speed in the underlying linear(ized) PDE. Furthermore, we approximately solve these linear advection problems using multigrid reduction-in-time (MGRIT); however, any other suitable parallel-in-time method could be used. Numerical examples are shown for the (linear) acoustics equations in heterogeneous media and for the (nonlinear) shallow water equations and Euler equations of gas dynamics with shocks and rarefactions. For many test problems, the solver converges in just a handful of iterations and with mesh-independent convergence rates.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Weak-Form Latent Space Dynamics Identification

This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI) algorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the data, then projects it onto test functions, and subsequently learns the local latent space models. Notably, WLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning techniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form ensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations. We demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples, including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid Burgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors consistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection simulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with LaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers' simulations compared to the corresponding full order model.

Choi, Youngsoo↗
DOE OSTI2024

Nonlinear manifold reduced order model

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations in which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space has a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated flow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a lowdimensional linear subspace poorly approximates the solution. To address cases such as these, we have developed a fast and accurate physics-informed neural network ROM, namely nonlinear manifold ROM (NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space dimension than the LS-ROMs. Our software takes advantage of the existing numerical methods that are used to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction technique in the context of the NM-ROM. Numerical results show that neural networks can learn a more efficient latent space representation on advection-dominated data from 1D and 2D Burgers' equations. A speedup of up to 2.6 for 1D Burgers' and a speedup of 11.7 for 2D Burgers' equations are achieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique.

Choi, Youngsoo↗