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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 OSTI2024

Determining the tilt of the Raman laser beam using an optical method for atom gravimeters

The tilt of a Raman laser beam is a major systematic error in precision gravity measurement using atom interferometry. The conventional approach to evaluating this tilt error involves modulating the direction of the Raman laser beam and conducting time-consuming gravity measurements to identify the error minimum. In this work, we demonstrate a method to expediently determine the tilt of the Raman laser beam by transforming the tilt angle measurement into characterization of parallelism, which integrates the optical method of aligning the laser direction, commonly used in freely falling corner-cube gravimeters, into an atom gravimeter. A position-sensing detector (PSD) is utilized to quantitatively characterize the parallelism between the test beam and the reference beam, thus measuring the tilt precisely and rapidly. After carefully positioning the PSD and calibrating the relationship between the distance measured by the PSD and the tilt angle measured by the tiltmeter, we achieved a statistical uncertainty of less than 30 µrad in the tilt measurement. Furthermore, we compared the results obtained through this optical method with those from the conventional tilt modulation method for gravity measurement. The comparison validates that our optical method can achieve tilt determination with an accuracy level of better than 200 µrad, corresponding to a systematic error of 20 µGal in g measurement. This work has practical implications for real-world applications of atom gravimeters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Understanding detachment of the W7-X island divertor

The fundamental behavior of the W7-X island divertor under detached conditions, which has been theoretically predicted with the EMC3-Eirene code, is re-examined here under the experimental conditions achieved so far and compared with the first experimental results. Both simulations and experiments cover a range of divertor configurations and plasma parameters, and show the following common trends: (1) with rising impurity radiation, the target heat load decreases 'uniformly' over the entire target surface in the sense that both the peak and average heat loads can drop by an order of magnitude. Impurity radiation (mainly from intrinsic carbon) occurs primarily at the plasma edge and the resulting negative impact on the stored energy is less than 10%. (2) When the total radiation exceeds a critical level, the target particle flux (the recycling flux Γrecy) begins to fall and can drop by a factor of 3–5 at high radiation levels without an obvious indication of significant volume recombination. (3) While Γ recy decreases, the divertor neutral pressure continues to build up and reaches a maximum, at which point Γ recy has declined significantly. (4) During detachment, the electron temperature at the last closed flux surface falls in a way that is not quantitatively understandable from parallel classical heat conduction processes. This paper presents a physical explanation of the numerical/experimental results described above. Furthermore, using the EMC3-Eirene code as a diagnostic tool, we are able, apparently for the first time, to provide a full quantitative analysis of each transport channel in the island divertor, aiming to clarify how the island divertor plasma self-regulates to maintain particle, energy, and momentum balance under detached conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

TH-CD-209-07: Preliminary Experimental Comparison of Spot- and Continuous Line Scanning with Or Without Rescanning for Gated Proton Therapy

Purpose: We aim to compare the performance of discrete spot- or continuous line scanning combined with rescanning in mitigating residual organ motion during gated proton therapy treatments. Methods: The Quasar respiratory phantom was used to move a 2D scintillation detector on a linear trajectory with sinusoidal motion pattern (sin{sup 4}), 20 mm peak-to-peak amplitude and 5 sec period. Its motion was monitored using a customized solution based on optical tracking technology. We compared spot and line scanning plans for a monoenergetic 150 MeV circular field, 50.4 mm radius at isocenter. Transverse dose distributions at 13 cm depth in PMMA (15.47 mm water equivalent) were measured to compare three options for motion mitigation: rescanning (10× factor), gating and their combination. The gating window was centered in the trajectory plateau to simulate end-exhale gated treatment in presence of 2 mm and 4 mm residual motion, parallel or perpendicular to the primary scanning direction. Results: When the target moves perpendicular to the primary scanning direction, large dose deviations are measured (γ3%/3mm=47%) without mitigation techniques. Beam gating combined with rescanning restores target coverage (γ3%/3mm=91%). For parallel target motion, observed dose distortions in the non-compensated irradiation are smaller (γ3%/3mm=77%). Beam gating alone recovers the 100% gamma pass-rate at 3%/3mm. Continuous line scanning reduces delivery time by up to 60% with respect to discrete spot scanning in presence of motion mitigation, and improves homogeneity when rescanning is applied (up to 20%, perpendicular motion, 4 mm residual motion). Conclusion: The direction of motion has a large impact on the target dose coverage. Nevertheless, even in the worst case scenario, gating combined with rescanning could mitigate the impact of motion on dose deposition. Moreover, continuous line rescanning improves the robustness against residual motion in the gating window. This study has received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreement n.290605 (PSI-FELLOW/COFUND) and ‘Giuliana and Giorgio Stefanini Foundation’.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Distributed Training and Optimization of Neural Networks

Deep learning models are yielding increasingly better performances thanks to multiple factors. To be successful, model may have large number of parameters or complex architectures and be trained on large dataset. This leads to large requirements on computing resource and turn around time, even more so when hyperparameter optimization is done (e.g. search over model architectures). While this is a challenge that goes beyond particle physics, we review the various ways to do the necessary computations in parallel, and put it in the context of high-energy physics.

Vlimant, Jean-Roch↗
DOE OSTI2019

Electronic Structure Engine

INQ is an engine for electronic structure calculations. INQ is implemented as a C++ library of components designed to build a parallel, portable code for electronic structure calculations, including ground state and excited states. INQ is based on density functional theory (DFT). It can calculate ground state properties in DFT, and also excited states using time-dependent DFT (TDDFT) in real-time and linear-response. It implements different approximations for the exchange and correlation part: semi-local functionals like LDAs, GGAs and metaGGAs, and hybrid functionals that are implemented through the ACE approach for fast execution.

ANDRADE-VALENCIA, XAVIERI↗
DOE OSTI2023

Seismic Response Processing Module

The seismic response processing module is a Java based library that provides support for removing instrument response signals from seismic recordings. The response module provides support for EvalResp, PZF, PAZ, FAP, PAZFIR, PAZFAP, FIRFAP, and CSS response types and parallel processing support for transfer operations. Additionally, the response module uses the JSR-363 units of measurement specification to allow for transfer to and from a wide range of units types to represent the time-series.

Dodge, Douglas↗
DOE OSTI2024

xesn: Echo state networks powered by Xarray and Dask

Xesn is a Python package that allows scientists to easily design Echo State Networks (ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture introduced by Jaeger (2001) that are part of a class of techniques termed Reservoir Computing. One defining characteristic of these techniques is that all internal weights are determined by a handful of global, scalar parameters, thereby avoiding problems during backpropagation and reducing training time significantly. Because this architecture is conceptually simple, many scientists implement ESNs from scratch, leading to questions about computational performance. Xesn offers a straightforward, standard implementation of ESNs that operates efficiently on CPU and GPU hardware. The package leverages optimization tools to automate the parameter selection process, so that scientists can reduce the time finding a good architecture and focus on using ESNs for their domain application. Importantly, the package flexibly handles forecasting tasks for out-of-core, multi-dimensional datasets, eliminating the need to write parallel programming code. Xesn was initially developed to handle the problem of forecasting weather dynamics, and so it integrates naturally with Python packages that have become familiar to weather and climate scientists such as Xarray (Hoyer & Hamman, 2017). However, the software is ultimately general enough to be utilized in other domains where ESNs have been useful, such as in signal processing (Jaeger & Haas, 2004).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Paracousti User Guide

Paracousti is a parallelized acoustic wave propagation simulation package developed at Sandia National Laboratories. It solves the linearized coupled set of acousto-dynamic partial differential equations using finite-difference approximations that are second order accurate in time and fourth order accurate in space. Paracousti simulates sound wave propagation within realistic 3-D earth, static atmosphere and hydroacoustic models, including 3-D variations in medium densities and acoustic sound speeds and topography or bathymetry. It can also incorporate attenuative media such as would be expected from physical mechanisms such as molecular dissipation. This report explains the usage of the Paracousti algorithm.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Comparative Evaluation of U.S. Brand and Generic Intravenous Sodium Ferric Gluconate Complex in Sucrose Injection: In Vitro Cellular Uptake

Iron deficiency anemia is a common clinical consequence for people who suffer from chronic kidney disease, especially those requiring dialysis. Intravenous (IV) iron therapy is a widely accepted safe and efficacious treatment for iron deficiency anemia. Numerous IV iron drugs have been approved by U.S. Food and Drug Administration (FDA), including a single generic product, sodium ferric gluconate complex in sucrose. In this study, we compared the cellular iron uptake profiles of the brand (Ferrlecit®) and generic sodium ferric gluconate (SFG) products. We used a colorimetric assay to examine the amount of iron uptake by three human macrophage cell lines. This is the first published study to provide a parallel evaluation of the cellular uptake of a brand and a generic IV iron drug in a mononuclear phagocyte system. The results showed no difference in iron uptake across all cell lines, tested doses, and time points. The matching iron uptake profiles of Ferrlecit® and its generic product support the FDA’s present position detailed in the draft guidance on development of SFG complex products that bioequivalence can be based on qualitative (Q1) and quantitative (Q2) formulation sameness, similar physiochemical characterization, and pharmacokinetic bioequivalence studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

PLASMA EFFECTS ON EXTRAGALACTIC ULTRAHIGH-ENERGY COSMIC-RAY HADRON BEAMS IN COSMIC VOIDS. II. KINETIC INSTABILITY OF PARALLEL ELECTROSTATIC WAVES

The linear instability of an ultrarelativistic hadron beam in the unmagnetized intergalactic medium (IGM) is investigated with respect to the excitation of parallel electrostatic and electromagnetic fluctuations. This analysis is important for the propagation of extragalactic ultrarelativistic cosmic rays from their distant sources to Earth. As opposed to the previous paper, we calculate the minimum instability growth time for Lorentz-distributed cosmic rays which traverse the hot IGM. The growth times are orders of magnitude higher than the cosmic-ray propagation time in the IGM. Since the backreaction of the generated plasma fluctuations (plateauing) lasts longer than the propagation time, the cosmic-ray hadron beam can propagate to the Earth without losing a significant amount of energy to electrostatic turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Parallel Particle Advection Bake-Off for Scientific Visualization Workloads

There are multiple algorithms for parallelizing particle advection for scientific visualization workloads. While many previous studies have contributed to the understanding of individual algorithms, our study aims to provide a holistic understanding of how algorithms perform relative to each other on various workloads. To accomplish this, we consider four popular parallelization algorithms and run a “bake-off” study (i.e., an empirical study) to identify the best matches for each. The study includes 216 tests, going to a concurrency of up to 8192 cores and considering data sets as large as 34 billion cells with 300 million particles. Overall, our study informs three important research questions: (1) which parallelization algorithms perform best for a given workload?, (2) why?, and (3) what are the unsolved problems in parallel particle advection? In terms of findings, we find that the seeding box is the most important factor in choosing the best algorithm, and also that there is a significant opportunity for improvement in execution time, scalability, and efficiency.

Pugmire, Dave↗
DOE OSTI2015

Parallel transmit excitation at 1.5 T based on the minimization of a driving function for device heating

Purpose: To provide a rapid method to reduce the radiofrequency (RF) E-field coupling and consequent heating in long conductors in an interventional MRI (iMRI) setup. Methods: A driving function for device heating (W) was defined as the integration of the E-field along the direction of the wire and calculated through a quasistatic approximation. Based on this function, the phases of four independently controlled transmit channels were dynamically changed in a 1.5 T MRI scanner. During the different excitation configurations, the RF induced heating in a nitinol wire immersed in a saline phantom was measured by fiber-optic temperature sensing. Additionally, a minimization of W as a function of phase and amplitude values of the different channels and constrained by the homogeneity of the RF excitation field (B{sub 1}) over a region of interest was proposed and its results tested on the benchtop. To analyze the validity of the proposed method, using a model of the array and phantom setup tested in the scanner, RF fields and SAR maps were calculated through finite-difference time-domain (FDTD) simulations. In addition to phantom experiments, RF induced heating of an active guidewire inserted in a swine was also evaluated. Results: In the phantom experiment, heating at the tip of the device was reduced by 92% when replacing the body coil by an optimized parallel transmit excitation with same nominal flip angle. In the benchtop, up to 90% heating reduction was measured when implementing the constrained minimization algorithm with the additional degree of freedom given by independent amplitude control. The computation of the optimum phase and amplitude values was executed in just 12 s using a standard CPU. The results of the FDTD simulations showed similar trend of the local SAR at the tip of the wire and measured temperature as well as to a quadratic function of W, confirming the validity of the quasistatic approach for the presented problem at 64 MHz. Imaging and heating reduction of the guidewire were successfully performed in vivo with the proposed hardware and phase control. Conclusions: Phantom and in vivo data demonstrated that additional degrees of freedom in a parallel transmission system can be used to control RF induced heating in long conductors. A novel constrained optimization approach to reduce device heating was also presented that can be run in just few seconds and therefore could be added to an iMRI protocol to improve RF safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Bifurcation-like transition of divertor conditions induced by X-point radiation in KSTAR L-mode plasmas *

Abstract Density ramps with ion grad B drift directed into lower single null KSTAR L-mode plasmas are associated with a simultaneous and abrupt reduction of the divertor particle flux on both low- and high-field-side targets when the mid-plane line averaged electron density reaches a given level. Target embedded Langmuir probe signals show a clear ‘cliff edge’ behavior similar to that observed in the divertor target electron temperature in DIII-D H-mode plasmas (Eldon et al 2017 Nucl. Fusion 57 066039; McLean et al 2015 J. Nucl. Mater. 463 533–6). The collapse of the particle flux is observed along the whole divertor target area (from private flux region to the far scrape-off layer (SOL)). The critical upstream density of this target flux cliff is invariant under fuel gas throughput modulation. The transition along the cliff occurs in tens of milliseconds. With the cliff, carbon impurities and deuterium neutrals transported through the X-point to the core produce a strong radiation spot near the X-point, seen on bolometric signals, and increase the upstream density. The experimental observations are consistent with time-dependent SOLPS-ITER simulations, which also demonstrate an abrupt transition of the target flux and upstream density with the increase in X-point radiation. The timescale of the cliff predicted by SOLPS-ITER is consistent with the experiment, although, it is influenced by gas throughput or time-dependent numerical methods. In the L-mode phase space of separatrix electron density and temperature, branches are divided based on target temperature, because the latter is strongly coupled to the radiation front and ionization front due to the monotonic characteristic of the parallel electron temperature distribution. Since the H-mode condition operates at a much higher upstream density and electron temperature in phase space, dissipation from sputtered carbon alone leads to the density limit before reaching the X-point radiation condition. This is therefore consistent with the fact that cliffs have never been observed in H-mode KSTAR experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Interpreting the nonlinear dielectric response of glass-formers in terms of the coupling model

Nonlinear dielectric measurements at high electric fields of glass-forming glycerol and propylene carbonate initially were carried out to elucidate the dynamic heterogeneous nature of the structural α-relaxation. Recently, the measurements were extended to sufficiently high frequencies to investigate the nonlinear dielectric response of faster processes including the so-called excess wing (EW), appearing as a second power law at high frequencies in the loss spectra of many glass formers without a resolved secondary relaxation. While a strong increase of dielectric constant and loss is found in the nonlinear dielectric response of the α-relaxation, there is a lack of significant change in the EW. A surprise to the experimentalists finding it, this difference in the nonlinear dielectric properties between the EW and the α-relaxation is explained in the framework of the coupling model by identifying the EW investigated with the nearly constant loss (NCL) of caged molecules, originating from the anharmonicity of the intermolecular potential. The NCL is terminated at longer times (lower frequencies) by the onset of the primitive relaxation, which is followed sequentially by relaxation processes involving increasing number of molecules until the terminal Kohlrausch α-relaxation is reached. These intermediate faster relaxations, combined to form the so-called Johari-Goldstein (JG) β-relaxation, are spatially and dynamically heterogeneous, and hence exhibit nonlinear dielectric effects, as found in glycerol and propylene carbonate, where the JG β-relaxation is not resolved and in D-sorbitol where it is resolved. Like the linear susceptibility, χ{sub 1}(f), the frequency dispersion of the third-order dielectric susceptibility, χ{sub 3}(f), was found to depend primarily on the α-relaxation time, and independent of temperature T and pressure P. I show this property of the frequency dispersions of χ{sub 1}(f) and χ{sub 3}(f) is the characteristic of the many-body relaxation dynamics of interacting systems which are governed solely by the intermolecular potential, and thermodynamic condition plays no role in this respect. Although linked to χ{sub 3}(f), dynamic heterogeneity is one of the parallel consequences of the many-body dynamics, and it should not be considered as the principal control parameter for the other dynamic properties of glassforming systems. Results same as χ{sub 3}(f) at elevated pressures had been obtained before by molecular dynamics simulations from the four-points correlation function and the intermediate scattering function. Naturally all properties obtained from the computer experiment, including dynamics heterogeneity, frequency dispersion, the relation between the α- and JG β-relaxation, and the breakdown of the Stokes-Einstein relation, are parallel consequences of the many-body relaxation dynamics governed by the intermolecular potential.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems

Kernel Ridge Regression (KRR) is a fundamental method in machine learning. Given an n-by-d data matrix as input, a traditional implementation requires Θ(n2) memory to form an n-by-n kernel matrix and Θ(n3) flops to compute the final model. These time and storage costs prohibit KRR from scaling up to large datasets. For example, even on a relatively small dataset (a 520k-by-90 input requiring 357 MB), KRR requires 2 TB memory just to store the kernel matrix. Additionally, the reason is that n usually is much larger than d for real-world applications. On the other hand, weak scaling becomes a problem: if we keep d and n/p fixed as p grows (p is # machines), the memory needed grows as Θ(p) per processor and the flops as Θ(p2) per processor. In the perfect weak scaling situation, both the memory needed and the flops grow as Θ(1) per processor (i.e. memory and flops are constant). The traditional Distributed KRR implementation (DKRR) only achieved 0.32% weak scaling efficiency from 96 to 1536 processors. In this work, we propose two new methods to address these problems: the Balanced KRR (BKRR) and K-means KRR (KKRR). These methods consider alternative ways to partition the input dataset into p different parts, generating p different models, and then selecting the best model among them. Compared to a conventional implementation, KKRR2 (optimized version of KKRR) improves the weak scaling efficiency from 0.32% to 38% and achieves a 591x speedup for getting the same accuracy by using the same data and the same hardware (1536 processors). BKRR2 (optimized version of BKRR) achieves a higher accuracy than the current fastest method using less training time for a variety of datasets. For the applications requiring only approximate solutions, BKRR2 improves the weak scaling efficiency to 92% and achieves 3505x speedup (theoretical speedup: 4096x).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

CSB-RNN: A Faster-Than-Realtime RNN Acceleration Framework with Compressed Structured Blocks

Recurrent Neural Networks (RNN) is widely applied to temporal sequence analysis, where real-time performance is usually in demand. However, RNN suffers a heavy computational workload as the model comes with a large weight matrix. To alleviate the pain, model compression (pruning) schemes have been proposed for RNN that pruning the redundant (near-zero) weight-values. On the one hand, the non-structured pruning methods achieve a considerable pruning rate while bringing the computational irregularity, which is un-friendly to parallel-hardware. On the other hand, the existing structured pruning methods consider the hardware parallelism; However, they suffer a poor pruning rate due to the restrict constraints on pruning structure. This paper presents CSB-RNN, an optimized full-stack RNN framework with the novel compressed structured block (CSB) technique. The CSB-pruned RNN model comes with both fine-granularity that benefits the pruning rate and regular structure that facilitates the hardware-parallelism. Further, we propose a novel hardware architecture for inferencing the CSB-pruned model. Different from conventional parallel hardware, this architecture solves the block-workload imbalance issue and achieves an over 95% hardware utilization. With the experiments on 10 RNN models in 5 application domains, the CSB-RNN realizes 7×-20× lossless compression and up to 50× acceptable lossy-compression, which is 2×-7× to the prior art. With the addition of the novel hardware, the compressed-RNN inference reaches a super real-time latency of 10-400µs with FPGA implementation.

Shi, Runbin↗
DOE OSTI2022

Symmetry-resolved CO desorption and oxidation dynamics on O/Ru(0001) probed at the C K-edge by ultrafast X-ray spectroscopy

In this work, we report on carbon monoxide desorption and oxidation induced by 400 nm femtosecond laser excitation on the O/Ru(0001) surface probed by time-resolved X-ray absorption spectroscopy (TR-XAS) at the carbon K-edge. The experiments were performed under constant background pressures of CO (6x10 -8 Torr) and O 2 (3x10 -8 Torr). Under these conditions, we detect two transient CO species with narrow 2π* peaks, suggesting little 2π* interaction with the surface. Based on polarization measurements, we find that these two species have opposing orientations: (1) CO favoring a more perpendicular orientation and (2) CO favoring a more parallel orientation with respect to the surface. We also directly detect gas-phase CO 2 using a mass spectrometer and observe weak signatures of bent adsorbed CO 2 at slightly higher X-ray energies than the 2π* region. These results are compared to previously reported TR-XAS results at the O K-edge where the CO background pressure was three times lower (2x10 -8 Torr) while maintaining the same O 2 pressure. At the lower CO pressure, in the CO 2π* region, we observed adsorbed CO and a distribution of OC-O bond lengths close to the CO oxidation transition state, with little indication of gas-like CO. The shift towards 'gas-like' CO species may be explained by the higher CO exposure, which blocks O adsorption, decreasing O coverage and increasing CO coverage. These effects decrease the CO desorption barrier through dipole-dipole interaction, while simultaneously increasing the CO oxidation barrier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗