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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Drift turbulence, particle transport, and anomalous dissipation at the reconnecting magnetopause

Here, using fully kinetic 3D simulations, the reconnection dynamics of asymmetric current sheets are examined at the Earth's magnetopause. The plasma parameters are selected to model MMS magnetopause diffusion region crossings with guide fields of 0.1, 0.4, and 1 of the reconnecting magnetosheath field. In each case, strong drift-wave fluctuations are observed in the lower-hybrid frequency range at the steep density gradient across the magnetospheric separatrix. These fluctuations give rise to cross-field electron particle transport. In addition, this turbulent mixing leads to significantly enhanced electron parallel heating in comparison to 2D simulations. We study three different methods of quantifying the anomalous dissipation produced by the drift fluctuations, based on spatial averaging, temporal averaging, and temporal averaging followed by integrating along magnetic field lines. A comparison of different methods reveals complications in identifying and measuring the anomalous dissipation. Nevertheless, the anomalous dissipation from short wavelength drift fluctuations appears weak for each case, and the reconnection rates observed in 3D are nearly the same as in 2D models. Finally, the 3D simulations feature a number of interesting new features that are consistent with recent MMS observations, including cold beams of magnetosheath electrons that penetrate into the hotter magnetospheric inflow, the related observation of decreasing temperature in regions of increasing total density, and an effective turbulent diffusion coefficient that agrees with predictions from quasi-linear theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Distributed Control of Inverter-Interfaced Microgrids Based on Consensus Algorithm with Improved Transient Performance

Conventional control solutions of the inverter-interfaced microgrids are usually designed based on models with fully decoupled subsystems. The negligence of the strong coupling due to power lines impedance leads to large transient line currents, which might trigger false protection. Besides, the droop-based control methods unnecessarily introduce system frequency and voltage deviations. To overcome these issues, a novel distributed control scheme is proposed for the inverter-interfaced microgrids in this study. The objective of the primary control is to regulate the bus voltages and frequency while suppressing the transient line currents. The objective of secondary control is to maintain fair load sharing. Both primary control and secondary control are distributed and subsystems or control agents only require measurements from local and neighboring subsystems. The detailed control problem formulation, control design and stability analysis are presented in the paper. Finally, the effectiveness of the proposed control solution is evaluated through extensive simulations based on both simplified and detailed models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Synchrotron radiation-based far-infrared spectroscopic ellipsometer with full Mueller-matrix capability

We developed far-IR spectroscopic ellipsometer at the U4IR beamline of the National Synchrotron Light Source in Brookhaven National Laboratory. This ellipsometer is able to measure both, rotating analyzer and full-Mueller matrix spectra using rotating retarders, and wire-grid linear polarizers. We utilize exceptional brightness of synchrotron radiation in the broad spectral range between about 20 and 4000 cm{sup -1}. Fourier-transform infrared (FT-IR) spectrometer is used for multi-wavelength data acquisition. The sample stage has temperature variation between 4.2 and 450 K, wide range of {theta}-2{theta} angular rotation, {chi} tilt angle adjustment, and X-Y-Z translation. A LabVIEW-based software controls the motors, sample temperature, and FT-IR spectrometer and also allows to run fully automated experiments with pre-programmed measurement schedules. Data analysis is based on Berreman's 4 Multiplication-Sign 4 propagation matrix formalism to calculate the Mueller matrix parameters of anisotropic samples with magnetic permeability {mu}{ne} 1. A nonlinear regression of the rotating analyzer ellipsometry and/or Mueller matrix (MM) spectra, which are usually acquired at variable angles of incidence and sample crystallographic orientations, allows extraction of dielectric constant and magnetic permeability tensors for bulk and thin-film samples. Applications of this ellipsometer setup for multiferroic and ferrimagnetic materials with {mu}{ne} 1 are illustrated with experimental results and simulations for TbMnO{sub 3} and Dy{sub 3}Fe{sub 5}O{sub 12} single crystals. We demonstrate how magnetic and electric dipoles, such as magnons and phonons, can be distinguished from a single MM measurement without adducing any modeling arguments. The parameters of magnetoelectric components of electromagnon excitations are determined using MM spectra of TbMnO{sub 3}.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Understanding and Modulating Metalloenzymes with Unnatural Amino Acids, Non-Native Metal Ions, and Non-Native Metallocofactors

Metalloproteins set the gold standard for performing important functions, including catalyzing demanding reactions under mild conditions. Designing artificial metalloenzymes (ArMs) to catalyze abiological reactions has been a major endeavor for many years, but most ArM activities are far below those of native enzymes, making them unsuitable for most pratical applications. A critical step to advance the field is to fundamentally understand what it takes to not only confer but also fine-tune ArM activities so they match those of native enzymes. Indeed, only once we can freely modulate ArM activity to rival (or surpass!) natural enzymes can the potential of ArMs be fully realized. A key to unlocking ArM potential is the observation that one metal primary coordination sphere can display a range of functions and levels of activity, leading to the realization that secondary coordination sphere (SCS) interactions are critically important. However, SCS interactions are numerous, long-range, and weak, making them very difficult to reproduce in ArMs. Furthermore, natural enzymes are tied to a small set of biologically available functional moieties from canonical amino acids and physiologically available metal ions and metallocofactors, severely limiting the chemical space available to probe and tune ArMs. We summarize the use of unnatural amino acids (UAAs) and non-native metal ions and metallocofactors by our group and our collaborators to probe and modulate ArM functions. We incorporated isostructural UAAs in a type 1 copper (T1Cu) protein azurin to provide conclusive evidence that axial ligand hydrophobicity is a major determinant of T1Cu redunction potential (E°'). Closely related work from other groups are also discussed. We also probed the role of protein backbone interactions that cannot be altered by standard mutagenesis by replacing the peptide bond with an ester linkage. We used insight gained from these studies to tune the E°' of azurin across the entire physiological range, the broadest range ever achieved in a single metalloprotein. Introducing UAA analogues of Tyr into ArM models of heme-copper oxidase (HCO) revealed a linear relationship between pK a , E°', and activity. We also substituted non-native hemes and non-native metal ions for their native equivalents in these models to resolve several issues that were intractable in native HCOs and the closely related nitric oxide reductases, such as their roles in modulating substrate affinity, electron transfer rate, and activity. We incorporated abiological cofactors such as ferrocene and Mn(salen) into azurin and myoglobin, respectively, to stabilize these inorganic and organometallic compounds in water, confer abiological functions, tune their E°' and activity through SCS interactions, and show that the approach to metallocofactor anchoring and orientation can tune enantioselectivity and alter function. Replacing Cu in azurin with non-native Fe or Ni can impart novel activities, such as superoxide reduction and C–C bond formation. While progress was made, we have identified only a small fraction of the interactions that can be generally applied to ArMs to fine-tune their functions. Because SCS interactions are subtle and heavily interconnected, it has been difficult to characterize their effects quantitatively. It is vital to develop spectroscopic and computational techniques to detect and quantify their effects in both resting states and catalytic intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Development and Benchmarking of a Hybrid PIC Code For Dense Plasmas and Fast Ignition (Final Report)

Radiation processes play an important role in the study of both fast ignition and other inertial confinement schemes, such as plasma jet driven magneto-inertial fusion, both in their effect on energy balance, and in generating diagnostic signals. In the latter case, warm and hot dense matter may be produced by the convergence of a plasma shell formed by the merging of an assembly of high Mach number plasma jets. This innovative approach has the potential advantage of creating matter of high energy densities in voluminous amount compared with high power lasers or particle beams. An important application of this technology is as a plasma liner for the flux compression of magnetized plasma to create ultra-high magnetic fields and burning plasmas. HyperV Technologies Corp. has been developing plasma jet accelerator technology in both coaxial and linear railgun geometries to produce plasma jets of sufficient mass, density, and velocity to create such imploding plasma liners. An enabling tool for the development of this technology is the ability to model the plasma dynamics, not only in the accelerators themselves, but also in the resulting magnetized target plasma and within the merging/interacting plasma jets during transport to the target. Welch pioneered numerical modeling of such plasmas (including for fast ignition) using the LSP simulation code. Lsp is an electromagnetic, parallelized, plasma simulation code under development since 1995. It has a number of innovative features making it uniquely suitable for modeling high energy density plasmas including a hybrid fluid model for electrons that allows electrons in dense plasmas to be modeled with a kinetic or fluid treatment as appropriate. In addition to in-house use at Voss Scientific, several groups carrying out research in Fast Ignition (LLNL, SNL, UCSD, AWE (UK), and Imperial College (UK)) also use LSP. A collaborative team consisting of HyperV Technologies Corp., Voss Scientific LLC, FAR-TECH, Inc., Prism Computational Sciences, Inc. and Advanced Energy Systems Inc. joined efforts to develop new physics and numerical models for LSP in several key areas to enhance the ability of LSP to model high energy density plasmas (HEDP). This final report details those efforts. Areas addressed in this research effort include: adding radiation transport to LSP, first in 2D and then fully 3D, extending the EMHD model to 3D, implementing more advanced radiation and electrode plasma boundary conditions, and installing more efficient implicit numerical algorithms to speed complex 2-D and 3-D computations. The new capabilities allow modeling of the dominant processes in high energy density plasmas, and further assist the development and optimization of plasma jet accelerators, with particular attention to MHD instabilities and plasma/wall interaction (based on physical models for ion drag friction and ablation/erosion of the electrodes). In the first funding cycle we implemented a solver for the radiation diffusion equation. To solve this equation in 2-D, we used finite-differencing and applied the parallelized sparse-matrix solvers in the PETSc library (Argonne National Laboratory) to the resulting system of equations. A database of the necessary coefficients for materials of interest was assembled using the PROPACEOS and ATBASE codes from Prism. The model was benchmarked against Prism's 1-D radiation hydrodynamics code HELIOS, and against experimental data obtained from HyperV's separately funded plasma jet accelerator development program. Work in the second funding cycle focused on extending the radiation diffusion model to full 3-D, continued development of the EMHD model, optimizing the direct-implicit model to speed up calculations, add in multiply ionized atoms, and improved the way boundary conditions are handled in LSP. These new LSP capabilities were then used, along with analytic calculations and Mach2 runs, to investigate plasma jet merging, plasma detachment and transport, restrike and advanced jet accelerator design. In addition, a strong linkage to diagnostic measurements was made by modeling plasma jet experiments on PLX to support benchmarking of the code. A large number of upgrades and improvements advancing hybrid PIC algorithms were implemented in LSP during the second funding cycle. These include development of fully 3D radiation transport algorithms, new boundary conditions for plasma-electrode interactions, and a charge conserving equation of state that permits multiply ionized high-Z ions. The final funding cycle focused on 1) mitigating the effects of a slow-growing grid instability which is most pronounced in plasma jet frame expansion problems using the two-fluid Eulerian remap algorithm, 2) extension of the Eulerian Smoothing Algorithm to allow EOS/Radiation modeling, 3) simulations of collisionless shocks formed by jet merging, 4) simulations of merging jets using high-Z gases, 5) generation of PROPACEOS EOS/Opacity databases, 6) simulations of plasma jet transport experiments, 7) simulations of plasma jet penetration through transverse magnetic fields, and 8) GPU PIC code development. The tools developed during this project are applicable not only to the study of plasma jets, but also to a wide variety of HEDP plasmas of interest to DOE, including plasmas created in short-pulse laser experiments performed to study fast ignition concepts for inertial confinement fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

The updated ITPA global H-mode confinement database: description and analysis

The multi-machine ITPA Global H-mode Confinement Database has been upgraded with new data from JET with the ITER-like wall and ASDEX Upgrade with the full tungsten wall. This paper describes the new database and presents results of regression analysis to estimate the global energy confinement scaling in H-mode plasmas using a standard power law. Various subsets of the database are considered, focusing on type of wall and divertor materials, confinement regime (all H-modes, ELMy H or ELM-free) and ITER-like constraints. Apart from ordinary least squares, two other, robust regression techniques are applied, which take into account uncertainty on all variables. Regression on data from individual devices shows that, generally, the confinement dependence on density and the power degradation are weakest in the fully metallic devices. Using the multi-machine scalings, predictions are made of the confinement time in a standard ELMy H-mode scenario in ITER. The uncertainty on the scaling parameters is discussed with a view to practically useful error bars on the parameters and predictions. One of the derived scalings for ELMy H-modes on an ITER-like subset is studied in particular and compared to the IPB98(y,2) confinement scaling in engineering and dimensionless form. Transformation of this new scaling from engineering variables to dimensionless quantities is shown to result in large error bars on the dimensionless scaling. Regression analysis in the space of dimensionless variables is therefore proposed as an alternative, yielding acceptable estimates for the dimensionless scaling. The new scaling, which is dimensionally correct within the uncertainties, suggests that some dependencies of confinement in the multi- machine database can be reconciled with parameter scans in individual devices. This includes vanishingly small dependence of confinement on line-averaged density and normalized plasma pressure (β), as well as a noticeable, positive dependence on effective atomic mass and plasma triangularity. Extrapolation of this scaling to ITER yields a somewhat lower confinement time compared to the IPB98(y, 2) prediction, possibly related to the considerably weaker dependence on major radius in the new scaling (slightly above linear). Further studies are needed to compare more flexible regression models with the power law used here. In addition, data from more devices concerning possible ‘hidden variables’ could help to determine their influence on confinement, while adding data in sparsely populated areas of the parameter space may contribute to further disentangling some of the global confinement dependencies in tokamak plasmas.

Database↗
DOE OSTI2022

Hvac: Removing I/O Bottleneck for Large-Scale Deep Learning Applications

Scientific communities are increasingly adopting deep learning (DL) models in their applications to accelerate scientific discovery processes. However, with rapid growth in the computing capabilities of HPC supercomputers, large-scale DL applications have to spend a significant portion of training time performing I/O to a parallel storage system. Previous research works have investigated optimization techniques such as prefetching and caching. Unfortunately, there exist non-trivial challenges to adopting the existing solutions on HPC supercomputers for large-scale DL training applications, which include non-performance and/or failures at extreme scale, lack of portability and generality in design, complex deployment methodology, and being limited to a specific application or dataset. To address these challenges, we propose High-Velocity AI Cache (HVAC), a distributed read-cache layer that targets and fully exploits the node-local storage or near node-local storage technology. HVAC seamlessly accelerates read I/O by aggregating node-local or near node-local storage, avoiding metadata lookups and file locking while preserving portability in the application code. We deploy and evaluate HVAC on 1,024 nodes (with over 6000 NVIDIA V100 GPUS) of the Summit supercomputer. In particular, we evaluate the scalability, efficiency, accuracy, and load distribution of HVAC compared to GPFS and XFS-on-NVMe. With four different DL applications, we observe an average 25 % performance improvement atop GPFS and 9% drop against XFS-on-NVMe, which scale linearly and are considered the performance upper bound. We envision HVAC as an important caching library for upcoming HPC supercomputers such as Frontier.

Khan, Awais↗
DOE OSTI2017

Analysis of operator splitting errors for near-limit flame simulations

High-fidelity simulations of ignition, extinction and oscillatory combustion processes are of practical interest in a broad range of combustion applications. Splitting schemes, widely employed in reactive flow simulations, could fail for stiff reaction–diffusion systems exhibiting near-limit flame phenomena. The present work first employs a model perfectly stirred reactor (PSR) problem with an Arrhenius reaction term and a linear mixing term to study the effects of splitting errors on the near-limit combustion phenomena. Analysis shows that the errors induced by decoupling of the fractional steps may result in unphysical extinction or ignition. The analysis is then extended to the prediction of ignition, extinction and oscillatory combustion in unsteady PSRs of various fuel/air mixtures with a 9-species detailed mechanism for hydrogen oxidation and an 88-species skeletal mechanism for n-heptane oxidation, together with a Jacobian-based analysis for the time scales. The tested schemes include the Strang splitting, the balanced splitting, and a newly developed semi-implicit midpoint method. Results show that the semi-implicit midpoint method can accurately reproduce the dynamics of the near-limit flame phenomena and it is second-order accurate over a wide range of time step size. For the extinction and ignition processes, both the balanced splitting and midpoint method can yield accurate predictions, whereas the Strang splitting can lead to significant shifts on the ignition/extinction processes or even unphysical results. With an enriched H radical source in the inflow stream, a delay of the ignition process and the deviation on the equilibrium temperature are observed for the Strang splitting. On the contrary, the midpoint method that solves reaction and diffusion together matches the fully implicit accurate solution. The balanced splitting predicts the temperature rise correctly but with an over-predicted peak. For the sustainable and decaying oscillatory combustion from cool flames, both the Strang splitting and the midpoint method can successfully capture the dynamic behavior, whereas the balanced splitting scheme results in significant errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2010

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Simon, Donald L.↗
NASA NTRS2015

Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult -- in both cost and schedule -- to enact. Indeed, the current capability-based paradigm that has emerged because of the constrained economic environment calls for the infusion of knowledge acquired during later design phases into earlier design phases, i.e. bring knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture as the need for more economically viable access to space solutions are needed in today's constrained economic environment. The problem of ascent trajectory optimization is not a new one. There are several programs that are widely used in industry that allows trajectory analysts to, based on detailed vehicle and insertion orbit parameters, determine the optimal ascent trajectory. Yet, little information is known about the launch vehicle early in the design phase - information that is required of many different disciplines in order to successfully optimize the ascent trajectory. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. Additionally, when these obstacles are coupled with The Program to Optimize Simulated Trajectories [1] (POST), an industry standard program to optimize ascent trajectories that is difficult to use, it requires expert trajectory analysts to effectively optimize a vehicle's ascent trajectory. As it has been pointed out, the paradigm of trajectory optimization is still a very manual one because using modern computational resources on POST is still a challenging problem. The nuances and difficulties involved in correctly utilizing, and therefore automating, the program presents a large problem. In order to address these issues, the authors will discuss a methodology that has been developed. The methodology is two-fold: first, a set of heuristics will be introduced and discussed that were captured while working with expert analysts to replicate the current state-of-the-art; secondly, leveraging the power of modern computing to evaluate multiple trajectories simultaneously, and therefore, enable the exploration of the trajectory's design space early during the pre-conceptual and conceptual phases of design. When this methodology is coupled with design of experiments in order to train surrogate models, the authors were able to visualize the trajectory design space, enabling parametric optimal ascent trajectory information to be introduced with other pre-conceptual and conceptual design tools. The potential impact of this methodology's success would be a fully automated POST evaluation suite for the purpose of conceptual and preliminary design trade studies. This will enable engineers to characterize the ascent trajectory's sensitivity to design changes in an arbitrary number of dimensions and for finding settings for trajectory specific variables, which result in optimal performance for a "dialed-in" launch vehicle design. The effort described in this paper was developed for the Advanced Concepts Office [2] at NASA Marshall Space Flight Center

Holt, James B.↗
DOE OSTI2021

Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures

Designing efficient and scalable sparse linear algebra kernels on modern multi-GPU based HPC systems is a daunting task due to significant irregular memory references and workload imbalance across the GPUs. This is particularly the case for \textit{Sparse Triangular Solver (SpTRSV)} which introduces additional two-dimensional computation dependencies among subsequent computation steps. Dependency information is exchanged and shared among GPUs, thus warrant for efficient memory allocation, data partitioning, and workload distribution as well as fine-grained communication and synchronization support. In this work, we demonstrate that directly adopting unified memory can adversely affect the performance of SpTRSV on multi-GPU architectures, despite linking via fast interconnect like NVLinks and NVSwitches. Alternatively, we employ the latest NVSHMEM technology based on Partitioned Global Address Space programming model to enable efficient fine-grained communication and drastic synchronization overhead reduction. Furthermore, to handle workload imbalance, we propose a malleable task-pool execution model which can further enhance the utilization of GPUs. By applying these techniques, our experiments on the NVIDIA multi-GPU supernode V100-DGX-1 and DGX-2 systems demonstrate that our design can achieve on average 3.53x (up to 9.86x) speedup on a DGX-1 system and 3.66x (up to 9.64x) speedup on a DGX-2 system with 4-GPUs over the Unified-Memory design. The comprehensive sensitivity and scalability studies also show that the proposed zero-copy SpTRSV is able to fully utilize the computing and communication resources of the multi-GPU system.

Xie, Chenhao↗
DOE OSTI2015

The angle-averaged squeezed limit of nonlinear matter N-point functions

Assuming Gaussian initial conditions, we show that in a certain, angle-averaged squeezed limit the N-point function of matter is related to the response of the matter power spectrum to a long-wavelength density perturbation, P{sup −1}d{sup nP}(k|δ{sub L})/dδ{sub L}{sup n}|{sub δ{sub L=0}}, with n=N−2. By performing N-body simulations with a homogeneous overdensity superimposed on a flat Friedmann-Robertson-Lemaȋtre-Walker (FRLW) universe using the separate universe approach, we obtain measurements of the nonlinear matter power spectrum response up to n=3, which is equivalent to measuring the fully nonlinear matter 3- to 5-point function in this squeezed limit. The sub-percent to few percent accuracy of those measurements is unprecedented. We then test the hypothesis that nonlinear N-point functions at a given time are a function of the linear power spectrum at that time, which is predicted in an Einstein-de Sitter (EdS) universe by standard perturbation theory (SPT) and its variants that are based on the ideal pressureless fluid equations. Specifically, we compare the responses computed from the separate universe simulations and simulations with a rescaled initial (linear) power spectrum amplitude. We find discrepancies of 10% at k≅ 0.2–0.5 h Mpc{sup −1} for 5- to 3-point functions at z=0. The discrepancy occurs at higher wavenumbers at z=2. Thus, theoretical predictions that are insensitive to the growth history, such as SPT and its variants assuming EdS, even when carried out to arbitrarily high order, are guaranteed to fail to describe matter N-point functions (N>2) around that scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Role of sheared E × B flow in self-organized, improved confinement states in magnetized plasmas

A great scientific success story of magnetic fusion research in the past several decades is the theoretical development and experimental testing of the process of turbulence decorrelation and stabilization by sheared E×B flow which shows that E×B shear effects are ubiquitous in magnetized plasmas. This concept of turbulence decorrelation and stabilization has the universality needed to explain the H-mode edge transport barriers seen in limiter and divertor tokamaks, stellarators, and mirror machines; the broader edge transport barrier seen in VHmode plasmas; and the core transport barriers formed in tokamaks. Similar effects are seen in linear devices. These examples of confinement improvement are of considerable physical interest; it is not often that a system self-organizes to reduce transport when an additional source of free energy is applied to it. The transport decrease associated with E×B velocity shear is also of great practical benefit to fusion research, since it contributed to substantially increased fusion yield in all DT magnetic fusion experiments conducted to date. The fundamental physics involved in transport reduction is the effect of E×B shear on the growth, radial extent, and phase correlation of turbulent eddies in the plasma. The same basic transport reduction process can be operational in various portions of the plasma because there are a number of ways to change the radial electric field Er. An important secondary theme in this area is the synergistic effect of E×B velocity shear and magnetic shear. Although the E×B velocity shear appears to have an effect on broader classes of microturbulence, magnetic shear can mitigate some potentially harmful effects of E×B velocity shear and facilitate turbulence stabilization. Our present understanding in this area is the result of a multi-decade, intertwined effort in theory, modeling and diagnostic development combined with continuing experimental investigations. These experiments have clearly demonstrated that increased E×B shear causes reductions in turbulence and transport. Finally, the experimental findings are generally consistent with the basic theoretical models although considerable work remains to be done before we have a fully predictive theory of transport in magnetized plasmas including E×B shear effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Low-Frequency Shear and Layer-Breathing Modes in Raman Scattering of Two-Dimensional Materials

Ever since the isolation of single-layer graphene in 2004, two-dimensional layered structures have been among the most extensively studied classes of materials. To date, the pool of two-dimensional materials (2DMs) continues to grow at an accelerated pace and already covers an extensive range of fascinating and technologically relevant properties. An array of experimental techniques have been developed and used to fully characterize and understand these properties. In particular, Raman spectroscopy has proven to be a key experimental technique, thanks to its capability to identify minute structural and electronic effects in nondestructive measurements. While high-frequency (HF) intralayer Raman modes have been extensively employed for 2DMs, recent experimental and theoretical progress has demonstrated that low-frequency (LF) interlayer Raman modes are more effective at determining layer numbers and stacking configurations, and provide a unique opportunity to study interlayer coupling. These advantages are due to 2DMs’ unique interlayer vibration patterns where each layer behaves as an almost rigidly moving object with restoring forces corresponding to weak interlayer interactions. Compared to HF Raman modes, the relatively small attention originally devoted to LF Raman modes is largely due to their weaker signal and their proximity to the strong Rayleigh line background, which previously made their detection challenging. Recent progress in Raman spectroscopy with technical and hardware upgrades now makes it possible to probe LF modes with a standard single-stage Raman system and has proven crucial to characterize and understand properties of 2DMs. Here, we present a comprehensive and forward-looking review on the current status of exploiting LF Raman modes of 2DMs from both experimental and theoretical perspectives, revealing the fundamental physics and technological significance of LF Raman modes in advancing the field of 2DMs. We review a broad array of materials, with varying thickness and stacking configurations, discuss the effect of in-plane anisotropy, and present a generalized linear chain model and interlayer bond polarizability model to rationalize the experimental findings. We also discuss the instrumental improvements of Raman spectroscopy to enhance and separate LF Raman signals from the Rayleigh line. Lastly, we highlight the opportunities and challenges ahead in this fast-developing field.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗
DOE OSTI2015

Magnetic Structure and Exchange Interactions in Quasi-One-Dimensional MnCl 2 (urea) 2

MnCl 2 (urea) 2 is a new linear chain coordination polymer that exhibits slightly counter-rotated Mn 2 Cl 2 rhomboids along the chain-axis. The material crystallizes in the noncentrosymmetric orthorhombic space group Iba2, with each Mn(II) ion equatorially surrounded by four Cl – that lead to bibridged ribbons. Additionally, urea ligands coordinate via O atoms in the axial positions. Hydrogen bonds of the Cl···H–N and O···H–N type link the chains into a quasi-3D network. Magnetic susceptibility data reveal a broad maximum at 9 K that is consistent with short-range magnetic order. Pulsed-field magnetization measurements conducted at 0.6 K show that a fully polarized magnetic state is achieved at B sat = 19.6 T with another field-induced phase transition occurring at 2.8 T. Zero-field neutron diffraction studies made on a powdered sample of MnCl 2 (urea) 2 reveal that long-range magnetic order occurs below T N = 3.2(1) K. Additional Bragg peaks due to antiferromagnetic (AFM) ordering can be indexed according to the Ib'a2' magnetic space group and propagation vector τ = [0, 0, 0]. Rietveld profile analysis of these data revealed a Néel-type collinear ordering of Mn(II) ions with an ordered magnetic moment of 4.06(6) μ B (5 μ B is expected for isotropic S = 5/2) oriented along the b-axis, i.e., perpendicular to the chain-axis that runs along the c-direction. Owing to the potential for spatial exchange anisotropy and the pitfalls in modeling bulk magnetic data, we analyzed inelastic neutron scattering data to retrieve the exchange constants: J c = 2.22 K (intrachain), J a = -0.10 K (interchain), and D = -0.14 K with J > 0 assigned to AFM coupling. Lastly, this J configuration is most unusual and contrasts the more commonly observed AFM interchain coupling of 1D chains.

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

Planck 2018 results

We report on the implications for cosmic inflation of the 2018 release of the Planck cosmic microwave background (CMB) anisotropy measurements. The results are fully consistent with those reported using the data from the two previous Planck cosmological releases, but have smaller uncertainties thanks to improvements in the characterization of polarization at low and high multipoles. Planck temperature, polarization, and lensing data determine the spectral index of scalar perturbations to be n s = 0.9649 ± 0.0042 at 68% CL. We find no evidence for a scale dependence of n s , either as a running or as a running of the running. The Universe is found to be consistent with spatial flatness with a precision of 0.4% at 95% CL by combining Planck with a compilation of baryon acoustic oscillation data. The Planck 95% CL upper limit on the tensor-to-scalar ratio, r0.002 < 0.10, is further tightened by combining with the BICEP2/Keck Array BK15 data to obtain r 0.002 < 0.056. In the framework of standard single-field inflationary models with Einstein gravity, these results imply that: (a) the predictions of slow-roll models with a concave potential, V"(Φ) < 0, are increasingly favoured by the data; and (b) based on two different methods for reconstructing the inflaton potential, we find no evidence for dynamics beyond slow roll. Three different methods for the non-parametric reconstruction of the primordial power spectrum consistently confirm a pure power law in the range of comoving scales 0.005 Mpc -1 ≲ k ≲ 0.2 Mpc -1 . A complementary analysis also finds no evidence for theoretically motivated parameterized features in the Planck power spectra. For the case of oscillatory features that are logarithmic or linear in k, this result is further strengthened by a new combined analysis including the Planck bispectrum data. The new Planck polarization data provide a stringent test of the adiabaticity of the initial conditions for the cosmological fluctuations. In correlated, mixed adiabatic and isocurvature models, the non-adiabatic contribution to the observed CMB temperature variance is constrained to 1.3%, 1.7%, and 1.7% at 95% CL for cold dark matter, neutrino density, and neutrino velocity, respectively. Planck power spectra plus lensing set constraints on the amplitude of compensated cold dark matter-baryon isocurvature perturbations that are consistent with current complementary measurements. The polarization data also provide improved constraints on inflationary models that predict a small statistically anisotropic quadupolar modulation of the primordial fluctuations. However, the polarization data do not support physical models for a scale-dependent dipolar modulation. All these findings support the key predictions of the standard single-field inflationary models, which will be further tested by future cosmological observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Ion probe beam experiments and kinetic modeling in a dense plasma focus Z-pinch

The Z-pinch phase of a dense plasma focus (DPF) emits multiple-MeV ions in a ∼cm length. The mechanisms through which these physically simple devices generate such high energy beams in a relatively short distance are not fully understood. We are exploring the origins of these large gradients using measurements of an ion probe beam injected into a DPF during the pinch phase and the first kinetic simulations of a DPF Z-pinch. To probe the accelerating fields in our table top experiment, we inject a 4 MeV deuteron beam along the z-axis and then sample the beam energy distribution after it passes through the pinch region. Using this technique, we have directly measured for the first time the acceleration of an injected ion beam. Our particle-in-cell simulations have been benchmarked on both a kJ-scale DPF and a MJ-scale DPF. They have reproduced experimentally measured neutron yields as well as ion beams and EM oscillations which fluid simulations do not exhibit. Direct comparisons between the experiment and simulations enhance our understanding of these plasmas and provide predictive design capability for accelerator and neutron source applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗