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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Example of exponentially enhanced magnetic reconnection driven by a spatially bounded and laminar ideal flow

In laboratory and natural plasmas of practical interest, the spatial scale Δ d at which magnetic field lines lose distinguishability differs enormously from the scale a of magnetic reconnection across the field lines. In the solar corona, plasma resistivity gives a/Δ d ~ 10 12 , which is the magnetic Reynold number R m . The traditional resolution of the paradox of disparate scales is for the current density j associated with the reconnecting field Brec to be concentrated by a factor of Rm by the ideal evolution, so j ~ B rec /µ 0 Δ d . A second resolution is for the ideal evolution to increase the ratio of the maximum to minimum separation between pairs of arbitrarily chosen magnetic field lines, Δ max /Δ min , when calculated at various points in time. Reconnection becomes inevitable where Δ max /Δ min ~ R m . A simple model of the solar corona will be used for a numerical illustration that the natural rate of increase in time is linear for the current density but exponential for Δ max /Δ min . Reconnection occurs on a time scale and with a current density enhanced by only ln(a/Δ d ) from the ideal evolution time and from the current density B rec /µ 0 a. In both resolutions, once a sufficiently wide region, Δ r , has undergone reconnection, the magnetic field loses static force balance and evolves on an Alfv´enic time scale. The Alfv´enic evolution is intrinsically ideal but expands the region in which Δ max /Δ min is large.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Measured Potential Profile in a Quantum Anomalous Hall System Suggests Bulk-Dominated Current Flow

Ideally, quantum anomalous Hall systems should display zero longitudinal resistance. Yet in experimental quantum anomalous Hall systems elevated temperature can make the longitudinal resistance finite, indicating dissipative flow of electrons. Here, we show that the measured potentials at multiple locations within a device at elevated temperature are well-described by solution of Laplace's equation, assuming spatially-uniform conductivity, suggesting non-equilibrium current flows through the two-dimensional bulk. Extrapolation suggests that at even lower temperatures current may still flow primarily through the bulk rather than, as had been assumed, through edge modes. In conclusion, an argument for bulk current flow previously applied to quantum Hall systems supports this picture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

The appearance, motion, and disappearance of three-dimensional magnetic null points

While theoretical models and simulations of magnetic reconnection often assume symmetry such that the magnetic null point when present is co-located with a flow stagnation point, the introduction of asymmetry typically leads to non-ideal flows across the null point. To understand this behavior, we present exact expressions for the motion of three-dimensional linear null points. The most general expression shows that linear null points move in the direction along which the magnetic field and its time derivative are antiparallel. Null point motion in resistive magnetohydrodynamics results from advection by the bulk plasma flow and resistive diffusion of the magnetic field, which allows non-ideal flows across topological boundaries. Null point motion is described intrinsically by parameters evaluated locally; however, global dynamics help set the local conditions at the null point. During a bifurcation of a degenerate null point into a null-null pair or the reverse, the instantaneous velocity of separation or convergence of the null-null pair will typically be infinite along the null space of the Jacobian matrix of the magnetic field, but with finite components in the directions orthogonal to the null space. Not all bifurcating null-null pairs are connected by a separator. Furthermore, except under special circumstances, there will not exist a straight line separator connecting a bifurcating null-null pair. The motion of separators cannot be described using solely local parameters because the identification of a particular field line as a separator may change as a result of non-ideal behavior elsewhere along the field line.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Experiments with nonneutral plasmas

Selected experiments with nonneutral plasmas are discussed. These include the laser cooling of a pure ion plasma to a crystalline state, a measurement of the Salpeter enhancement factor for fusion in a strongly correlated plasma and the measurement of thermally excited plasma waves. Also, discussed are experiments that demonstrate Landau damping, trapping and plasma wave echoes in the 2D ExB drift flow of a pure electron plasma, which is isomorphic to the 2D ideal flow (incompressible and inviscid flow) of a neutral fluid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

An Assessment of the Error Due to Computing Waste Isolation Pilot Plant Porosity Using the Porosity Response Surface Approach

The Waste Isolation Pilot Plant Performance Assessment (WIPP PA) must predict the likelihood that radionuclides will escape into the biosphere via mechanisms that depend on geohydraulic flow. Ideally, one would predict the geohydraulic flow using coupled geohydraulic and geomechanical simulations, but such coupled simulations are not computationally tractable. Instead, Sandia has historically used a look-up table of porosities for a given fluid pressure and time, called the porosity response surface, but this approach can introduce porosity errors because it largely ignores the porosity’s dependence on the past fluid pressure history. This report discusses efforts to quantify these porosity errors for both the legacy and new porosity response surfaces. Six hundred different fluid pressure histories were fed through the legacy/new geomechanical model and the legacy/new porosity response surface to generate six hundred porosity error histories. The error associated with the legacy porosity surface was substantial, while the error associated with the new porosity surface was typically small, except when fluid pressures exceeded the lithostatic pressure at the repository. In response to the errors at high pressures, a preliminary study of the WIPP PA’s sensitivity to these porosity errors was conducted. The study found that reducing the porosity errors at high pressures negligibly affected predictions of radionuclide releases. Finally, an initial machine-learned model for porosity was developed. This ML model significantly reduced the porosity error at high pressures, but sizable errors remained, so more development is necessary before coupling an ML model to the geohydraulic model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Device Scale Modeling of Solvent Absorption using MFIX-TFM

Recent climate change is largely attributed to greenhouse gases (e.g., carbon dioxide, methane) and fossil fuels account for a large majority of global CO 2 emissions. That said, fossil fuels will continue to play a significant role in the generation of power for the foreseeable future. The extent to which CO 2 is emitted needs to be reduced, however, carbon capture and sequestration are also necessary actions to tackle climate change. Different approaches exist for CO 2 capture including both post-combustion and pre-combustion technologies, oxy-fuel combustion and/or chemical looping combustion. The focus of this effort is on post-combustion solvent-absorption technology. To apply CO 2 technologies at commercial scale, the availability and maturity and the potential for scalability of that technology need to be considered. Solvent absorption is a proven technology but not at the scale needed by typical power plant. The scale up and down and design of laboratory and commercial packed bed reactors depends heavily on the specific knowledge of two-phase pressure drop, liquid holdup, the wetting efficiency and mass transfer efficiency as a function of operating conditions. Simple scaling rules often fail to provide proper design. Conventional reactor design modeling approaches will generally characterize complex non-ideal flow and mixing patterns using simplified and/or mechanistic flow assumptions. While there are varying levels of complexity used within these approaches, none of these models resolve the local velocity fields. Consequently, they are unable to account for important design factors such as flow maldistribution and channeling from a fundamental perspective. Ideally design would be aided by development of predictive models based on truer representation of the physical and chemical processes that occur at different scales. Computational fluid dynamic (CFD) models are based on multidimensional flow equations with first principle foundations. CFD models can include a more accurate physical description of flow processes and be modified to include more complex behavior. Wetting performance and spatial liquid distribution inside the absorber are recognized as weak areas of knowledge requiring further investigation. CFD tools offer a possible method to investigating such topics and gaining a better understanding of their influence on reactor performance. This report focuses first on describing a hydrodynamic model for countercurrent gas-liquid flow through a packed column and then on the chemistry, heat and mass transfer specific to CO 2 absorption using monoethanolamine (MEA). The indicated model is implemented in MFIX, a CFD open source software package. The user defined functions needed to build this model are described in detail along with the keywords for the corresponding input file. A test case is outlined along with a few results. The example serves to briefly illustrate the developed CFD tool and its potential capability to investigate solvent absorption.

09 BIOMASS FUELS↗
DOE OSTI2015

Reynolds number scaling of the influence of boundary layers on the global behavior of laboratory quasi-Keplerian flows

Here, we present fluid velocity measurements in a modified Taylor-Couette device operated in the quasi-Keplerian regime, where it is observed that nearly ideal flows exhibit self-similarity under scaling of the Reynolds number. In contrast, nonideal flows show progressive departure from ideal Couette as the Reynolds number is increased. We present a model that describes the observed departures from ideal Couette rotation as a function of the fluxes of angular momentum across the boundaries, capturing the dependence on Reynolds number and boundary conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A high-order vertex-based central ENO finite-volume scheme for three-dimensional compressible flows

High-order discretization methods offer the potential to reduce the computational cost associated with modeling compressible flows. However, it is difficult to obtain accurate high-order discretizations of conservation laws that do not produce spurious oscillations near discontinuities, especially on multi-dimensional unstructured meshes. A novel, high-order, central essentially non-oscillatory (CENO) finite-volume method that does not have these difficulties is proposed for tetrahedral meshes. The proposed unstructured method is vertex-based, which differs from existing cell-based CENO formulations, and uses a hybrid reconstruction procedure that switches between two different solution representations. It applies a high-order k-exact reconstruction in smooth regions and a limited linear reconstruction when discontinuities are encountered. Both reconstructions use a single, central stencil for all variables, making the application of CENO to arbitrary unstructured meshes relatively straightforward. The new approach was applied to the conservation equations governing compressible flows and assessed in terms of accuracy and computational cost. For all problems considered, which included various function reconstructions and idealized flows, CENO demonstrated excellent reliability and robustness. Up to fifth-order accuracy was achieved in smooth regions and essentially non-oscillatory solutions were obtained near discontinuities. The high-order schemes were also more computationally efficient for high-accuracy solutions, i.e., they took less wall time than the lower-order schemes to achieve a desired level of error. In one particular case, it took a factor of 24 less wall-time to obtain a given level of error with the fourth-order CENO scheme than to obtain the same error with the second-order scheme.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Turbulence theories and statistical closure approaches

When discussing research in physics and in science more generally, it is common to ascribe equal importance to the three components of the scientific trinity: theoretical, experimental, and computational studies. This review will explore the future of modern turbulence theory by tracing its history, which began in earnest with Kolmogorov’s 1941 analysis of turbulence cascade and inertial range [A.N. Kolmogorov, Dokl. Akad. Nauk SSSR, 30, 299, (1941); 32, 19, (1941)]. The 80th Anniversary of Kolmogorov’s landmark study is a welcome opportunity to survey the achievements and evaluate the future of the theoretical approach of turbulence research. Over the years, turbulence theories have been critically important in laying the foundation of our understanding of the nature of turbulent flows. In particular, the Direct Interaction Approximation (DIA) [R.H. Kraichnan, J. Fluid Mech., 5, 497 (1959)] and its subsequent development, known as the statistical closure approach, can be identified as perhaps the most profound single advancement. The remarkable success of the statistical closure has furnished a platform to study such essential concepts as the energy transfer process and interacting scales, and the roles of the straining and sweeping motions. More recently, the quasi-Lagrangian formulation of V. L’vov & I. Procaccia and Kraichnan’s solvable passive scalar model provided powerful ways to explore another fundamental aspect of turbulent flows, the phenomena of intermittency, and the associated anomalous scaling exponents. In the meantime, the theory of fluid equilibria has been developed to describe the large-scale structures that can emerge from turbulent cascades of two-dimensional and geophysical flows at a later time. And yet, despite all these successes, analytical treatments suffer from mathematical complexities. As a result, the utility of theoretical approaches has been limited to relatively idealized flows. On the other hand, in recent decades, computational abilities and experimental facilities have reached an unprecedented scale. Looking beyond the horizon, the imminent deployment of exascale supercomputers will generate complete datasets of the entire flow field of key benchmark flows, allowing researchers to extract additional measurements concerning fully developed, complex turbulent flow fields far beyond those available from the statistical closure theories. Some other developments that could potentially influence the future course of turbulence theories include the advancement of machine learning, artificial intelligence, and data science; likely disruptions arising from the advent of quantum computation; and the increasingly prominent role of turbulence research in providing more accurate climate scientific data. Finally, turbulence theorists can leverage these developments by asking the right questions and developing advanced, sophisticated frameworks that will be able to predict and correlate vast amounts of data from the other two components of the trinity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

An Energy Principle for Ideal MHD Equilibria with Flows

In the standard ideal MHD energy principle for equilibria with no flows, the stability criterion, which is the defi niteness of the perturbed potential energy, is usually constructed from the linearized equation of motion. Equivalently while more straightforwardly, it can also be obtained from the second variation of the Hamiltonian calculated with proper constraints. For equilibria with flows, a stability criterion was proposed from the linearized equation of motion, but not explained as an energy principle1. In this paper, the second variation of the Hamiltonian is found to provide a stability criterion equivalent to, while more straightforward than, what was constructed from the linearized equation of motion. To calculate the variations of the Hamiltonian, a complete set of constraints on the dynamics of the perturbations is derived from the Euler-Poincare structure of the ideal MHD. In addition, a previous calculation of the second variation of the Hamiltonian was claimed to give a different stability criterion2, and in this paper we argue such a claim is incorrect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Modeling and simulation of transitional Rayleigh–Taylor flow with partially averaged Navier–Stokes equations

In this work, the partially averaged Navier–Stokes (PANS) equations are used to predict the variable-density Rayleigh–Taylor (RT) flow at Atwood number 0.5 and maximum Reynolds number 500. This is a prototypical problem of material mixing, featuring laminar, transitional, and turbulent flow, instabilities and coherent structures, density fluctuations, and production of turbulence kinetic energy by both shear and buoyancy mechanisms. These features pose numerous challenges to modeling and simulation, making the RT flow ideal to develop the validation space of the recently proposed PANS Besnard–Harlow–Rauenzahn-linear eddy viscosity model closure. The numerical simulations are conducted at different levels of physical resolution and test three approaches to set the parameters $f_\phi$ defining the range of physically resolved scales. The computations demonstrate the efficiency (accuracy vs cost) of the PANS model predicting the spatiotemporal development of the RT flow. Results comparable to large-eddy simulations and direct numerical simulations are obtained at significantly lower physical resolution without the limitations of the Reynolds-averaged Navier–Stokes equations in these transitional flows. The data also illustrate the importance of appropriate selection of the physical resolution and the resolved fraction of each dependent quantity $\phi$ of the turbulent closure, $f_\phi$. These two aspects determine the ability of the model to resolve the flow phenomena not amenable to modeling by the closure and, as such, the computations’ fidelity.

Navier Stokes equations↗
DOE OSTI2013

REEXAMINATION OF INDUCTION HEATING OF PRIMITIVE BODIES IN PROTOPLANETARY DISKS

We reexamine the unipolar induction mechanism for heating asteroids originally proposed in a classic series of papers by Sonett and collaborators. As originally conceived, induction heating is caused by the 'motional electric field' that appears in the frame of an asteroid immersed in a fully ionized, magnetized solar wind and drives currents through its interior. However, we point out that classical induction heating contains a subtle conceptual error, in consequence of which the electric field inside the asteroid was calculated incorrectly. The problem is that the motional electric field used by Sonett et al. is the electric field in the freely streaming plasma far from the asteroid; in fact, the motional field vanishes at the asteroid surface for realistic assumptions about the plasma density. In this paper we revisit and improve the induction heating scenario by (1) correcting the conceptual error by self-consistently calculating the electric field in and around the boundary layer at the asteroid-plasma interface; (2) considering weakly ionized plasmas consistent with current ideas about protoplanetary disks; and (3) considering more realistic scenarios that do not require a fully ionized, powerful T Tauri wind in the disk midplane. We present exemplary solutions for two highly idealized flows that show that the interior electric field can either vanish or be comparable to the fields predicted by classical induction depending on the flow geometry. We term the heating driven by these flows 'electrodynamic heating', calculate its upper limits, and compare them to heating produced by short-lived radionuclides.

79 ASTRONOMY AND ASTROPHYSICS↗