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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Unraveling the convoluted and dynamic interphasial mechanisms on Li metal anode

Accurate understanding of the chemistry of solid-electrolyte interphase (SEI) is key to developing new electrolytes for high-energy batteries using lithium metal (Li-0) anodes(1). SEI is generally believed to be formed by the reactions between Li-0 and electrolyte(2,3). However, our new study shows this is not the whole story. Through synchrotron-based X-ray diffraction and pair distribution function analysis, we reveal a much more convoluted formation mechanism of SEI, which receives considerable contributions from electrolyte, cathode, moisture and native surface species on Li-0, with highly dynamic nature during cycling. Using isotope labelling, we traced the origin of LiH to electrolyte solvent, moisture and a new source: the native surface species (LiOH) on pristine Li-0. When lithium accessibility is very limited as in the case of anode-free cells, LiOH develops into plate-shaped large crystals during cycling. Alternatively, when the lithium source is abundant, as in the case of Li||NMC811 cells, LiOH reacts with Li-0 to form LiH and Li2O. While the desired anion-derived LiF-rich SEI is typically found in the concentrated electrolytes or their derivatives, we found it can also be formed in low-concentration electrolyte via the crosstalk effect, emphasizing the importance of formation cycle protocol and opening up opportunities for low-cost electrolyte development.

Polzin, Bryant J.↗
DOE OSTI2022

Training calibration-based counterfactual explainers for deep learning models in medical image analysis

The rapid adoption of artificial intelligence methods in healthcare is coupled with the critical need for techniques to rigorously introspect models and thereby ensure that they behave reliably. This has led to the design of explainable AI techniques that uncover the relationships between discernible data signatures and model predictions. In this context, counterfactual explanations that synthesize small, interpretable changes to a given query while producing desired changes in model predictions have become popular. This under-constrained, inverse problem is vulnerable to introducing irrelevant feature manipulations, particularly when the model’s predictions are not well-calibrated. Hence, in this paper, we propose the TraCE (training calibration-based explainers) technique, which utilizes a novel uncertainty-based interval calibration strategy for reliably synthesizing counterfactuals. Given the wide-spread adoption of machine-learned solutions in radiology, our study focuses on deep models used for identifying anomalies in chest X-ray images. Using rigorous empirical studies, we demonstrate the superiority of TraCE explanations over several state-of-the-art baseline approaches, in terms of several widely adopted evaluation metrics. Our findings show that TraCE can be used to obtain a holistic understanding of deep models by enabling progressive exploration of decision boundaries, to detect shortcuts, and to infer relationships between patient attributes and disease severity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Complexity-calibrated benchmarks for machine learning reveal when prediction algorithms succeed and mislead

Abstract Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a “next-generation” reservoir computer was introduced in which the memory trace involves only a finite number of previous symbols. We explore the inherent limitations of finite-past memory traces in this intriguing proposal. A lower bound from Fano’s inequality shows that, on highly non-Markovian processes generated by large probabilistic state machines, next-generation reservoir computers with reasonably long memory traces have an error probability that is at least $$\sim 60\%$$ ∼ 60 % higher than the minimal attainable error probability in predicting the next observation. More generally, it appears that popular recurrent neural networks fall far short of optimally predicting such complex processes. These results highlight the need for a new generation of optimized recurrent neural network architectures. Alongside this finding, we present concentration-of-measure results for randomly-generated but complex processes. One conclusion is that large probabilistic state machines—specifically, large $$\epsilon$$ ϵ -machines—are key to generating challenging and structurally-unbiased stimuli for ground-truthing recurrent neural network architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An approach to separating Pu, U, and Ti from high-purity graphite for isotopic analysis by MC-ICP-MS

Information about elemental and isotopic systematics of ultra-trace level actinides (e.g. U and Pu) and main group elements (e.g. Ti) present within nuclear grade graphite is vital to the nuclear community for improved reactor operation and security. In support of this, extensive effort has been placed on improving analysis methods (i.e., inductively coupled plasma-mass spectrometry). However, significantly less effort has been devoted to the optimization of chemical separation methods. Within the separation community, commercially available Eichrom™ resins are often employed, as their elution characteristics for various elements have been well studied, but the direct optimization of actinides and trace metal separations from a single sample have not been widely investigated. Here, methods using various Eichrom pre-packed cartridges were explored to achieve separation of ultra-trace levels of U, Pu, and Ti from a variety of graphite samples. Once the validity of the combined separation scheme was established using certified reference materials, the method was applied to historic, unirradiated and irradiated, graphite samples. For all samples investigated, precise isotope ratio measurements for the titanium isotope systems were made.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

CaTS: Integration of Geant4 and Opticks

CaTS [6]is an advanced example that is part of Geant4 since version 11.0. It demonstrates the use of Opticks to offload the simulation of optical photons to GPUs. Opticks interfaces with the Geant4 toolkit to collect all the necessary information to generate and trace optical photons, re-implements the optical physics processes to be run on the GPU, and automatically translates the Geant4 geometry into a GPU appropriate format. To trace the photons, Opticks uses NVIDIA OptiX®. In this report, we describe CaTS and the integration of Opticks with Geant4. We demonstrate that the generation and tracing of optical photons represents an ideal application to be offloaded to GPUs, fully utilizing the high degree of available parallelism. In a typical liquid argon TPC simulation, a speedup of several hundred times is observed compared to an equivalent simulation using single threaded Geant4.

Wenzel, Hans↗
DOE OSTI2021

Gauge-invariant perturbation expansion in powers of electric charge for the density-of-states of a network model for charged-particle motion in a uniform background magnetic flux density

An explicitly gauge-invariant expansion in powers of e/$\hbar$ times the magnetic flux density is formally obtained for the density of states [as characterized by the trace of the resolvent $\hat{G}$ = (ω-$\hat{ℎ}$)-1] of a charged particle moving on a Hermitian quantum network that is embedded in a Euclidean background that supports a uniform magnetic flux density. The explicit expressions, given here up to third order in the flux density, are also valid for the “local trace” (the trace of $\hat{P}_i\hat{G}$ , where $\hat{P}_i$ is the projector on a network node) and do not appear to have been previously given.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Anomalous transport of multi-species edge plasma with the generalized Hasegawa–Wakatani model and the FLR effects

Anomalous transport of multi-species plasma is considered with the generalized Hasegawa–Wakatani model [A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024)] further extended to incorporate the Finite Larmor Radius (FLR) effects. By introducing the “associated” enstrophy, it is shown that with no FLR effects (where anomalous transport of all ion species is described as a transport of passive scalars in the turbulent fields of the electrostatic potential and electron density fluctuations) the fluctuating densities of ion species converge to the state where they are linearly proportional to electron density and vorticity fluctuations, which confirm previous numerical findings of [A. R. Knyazev and S. I. Krasheninnikov, Phys. Plasmas 31, 012502 (2024)]. However, in contrast to the “cold” ion approximation, with the FLR effects included, both the plasma turbulence and the dynamics of all ion species become interconnected. Therefore, for simplicity, the FLR effects in this work were considered only for a small “trace” impurity fraction. It is found that for light (neon) “trace” impurity, the FLR effects reduce both anomalous flux and density fluctuations. However, for heavy (tungsten) “trace” impurity, the FLR effects exhibit non-monotonic impact on anomalous transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Extraction of the muon signals recorded with the surface detector of the Pierre Auger Observatory using recurrent neural networks

The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from 1017eV up to more than 1020eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightforwardly separate the contributions of muons to the SD time traces from those of photons, electrons and positrons. In this paper, we present a method aimed at extracting the muon component of the time traces registered with each individual detector of the SD using Recurrent Neural Networks. We derive the performances of the method by training the neural network on simulations, in which the muon and the electromagnetic components of the traces are known. We conclude this work showing the performance of this method on experimental data of the Pierre Auger Observatory. We find that our predictions agree with the parameterizations obtained by the AGASA collaboration to describe the lateral distributions of the electromagnetic and muonic components of extensive air showers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Regional infrasonic observations from surface explosions – influence of atmospheric variations and realistic terrain

SUMMARY A pair of 1-ton, conventional surface explosions were conducted at the Nevada National Security Site in the fall of 2020 producing seismoacoustic signatures observable hundreds of kilometres from the source location. Regional infrasonic observations include tropospheric ducting at large distances to the south, a wide stratospheric waveguide with signals observed more than 700 km to the east, and anomalous arrivals in the stratospheric shadow zone. Notable differences in propagation between the events are identified despite the explosions being conducted just two days apart due to a sharp temporal shift in the tropospheric winds as well as structural changes in the stratospheric winds. Propagation simulations of the two events have been completed using a combination of ray tracing and parabolic equation (PE) methods. Simulations have been conducted to quantify the impact of the temporal variations in the atmosphere as well as the influence of terrain on propagation. Temporal variations in reflection locations are found to produce notable changes in downrange propagation due to spatially varying terrain features. Finite frequency effects modelled by the PE are found to predict ensonification not included in corresponding 2D ray tracing simulations. Notable variations in predicted signal amplitude are found due to focusing by along-path and cross-path terrain gradients; though, the later of these is only modelled using fully 3D ray tracing analysis.

58 GEOSCIENCES↗
DOE OSTI2020

Solar-metallicity gas in the extended halo of a galaxy at z ∼ 0.12

ABSTRACT We present the detection and analysis of a weak low-ionization absorber at z = 0.121 22 along the sightline of the blazar PG 1424+240, using spectroscopic data from both HST/COS and STIS. The absorber is a weak Mg ii analogue, with an incidence of weak C ii and Si ii, along with multicomponent C iv and O vi. The low ions are tracing a dense (nH ∼ 10−3 cm−3) parsec-scale cloud of solar or higher metallicity. The kinematically coincident higher ions are either from a more diffuse (nH ∼ 10−5–10−4 cm−3) photoionized phase of kiloparsec-scale dimensions or are tracing a warm (T ∼ 2 × 105 K) collisionally ionized transition temperature plasma layer. The absorber resides in a galaxy overdense region, with 18 luminous (>L*) galaxies within a projected radius of 5 Mpc and velocity of 750 km s−1. The multiphase properties, high metallicity, and proximity to a 1.4L* galaxy, at ρ ∼ 200 kpc and separation |Δv| = 11 km s−1, favour the possibility of the absorption tracing circumgalactic gas. The absorber serves as an example of weak Mg ii–O vi systems as a means to study multiphase high-velocity clouds in external galaxies.

Pradeep, Jayadev↗
DOE OSTI2024

Pion gravitational form factors in the QCD instanton vacuum. I

The pion form factors of the QCD energy-momentum tensor (EMT) are studied in the instanton liquid model (ILM) of the QCD vacuum. In this approach, the breaking of conformal symmetry is encoded in the form of stronger-than-Poisson fluctuations in the number of instantons. For the trace of the EMT, it is shown that the gluonic trace anomaly term contributes half the pion mass, with the other half coming from the quark-mass-dependent σ term. The Q 2 dependence of the form factors is governed by glueball and scalar meson exchanges. For the EMT, the spin-0 (trace) and spin-2 (traceless rank-2 tensor) form factors are computed at next-to-leading order in the instanton density using effective quark operators. Relations between the gluon and quark contributions to the EMT form factors are derived. The form factors are also expressed in terms of the pion light-front wave functions in the ILM. The results at the low resolution scale of the inverse instanton size are evolved to higher scales using the renormalization group equation. The ILM results compare well with those of recent lattice QCD calculations. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Signal Processing Based Method for Real-Time Anomaly Detection in High-Performance Computing

Performance anomalies can manifest as irregular execution times or abnormal execution events for many reasons, including network congestion and resource contention. Detecting such anomalies in real-time by analyzing the details of performance traces at scale is impractical due to the sheer volume of data High-Performance Computing (HPC) applications produce. In this paper, we propose formulating HPC performance anomaly detection as a signal-processing problem where anomalies can be treated as noise. We evaluate our proposed method in comparison with two other commonly used anomaly detection techniques of varying complexity based on their detection accuracy and scalability. Since real-time in-situ anomaly detection at a large scale requires lightweight methods that can handle a large volume of streaming data, we find that our proposed method provides the best trade-off. We then implement the proposed method in Chimbuko, the first online, distributed, and scalable workflow-level performance trace analysis framework. We compare our proposed signal-based anomaly detection algorithm with two other methods using a function of their accuracy, F1 score, and detection overhead. Our experiments demonstrate that our proposed approach achieves a 99% improvement for the benchmark datasets and a 93% improvement with Chimbuko traces.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Scalable Deep Learning-Based Microarchitecture Simulation on GPUs

Cycle-accurate microarchitecture simulators are essential tools for designers to architect, estimate, optimize, and manufacture new processors that meet specific design expectations. However, conventional simulators based on discrete-event methods often require an exceedingly long time-to-solution for the simulation of applications and architectures at full complexity and scale. Given the excitement around wielding the machine learning (ML) hammer to tackle various architecture problems, there have been attempts to employ ML to perform architecture simulations, such as Ithemal and SimNet. However, the direct application of existing ML approaches to architecture simulation may be even slower due to overwhelming memory traffic and stringent sequential computation logic. This work proposes the first graphics processing unit (GPU)-based microarchitecture simulator that fully unleashes the potential of GPUs to accelerate state-of-the-art ML-based simulators. First, considering the application traces are loaded from central processing unit (CPU) to GPU for simulation, we introduce various designs to reduce the data movement cost between CPUs and GPUs. Second, we propose a parallel simulation paradigm that partitions the application trace into sub-traces to simulate them in parallel with rigorous error analysis and effective error correction mechanisms. Combined, this scalable GPU-based simulator outperforms by orders of magnitude the traditional CPU-based simulators and the state-of-the-art ML-based simulators, i.e., SimNet and Ithemal.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Coordinate-Based Seismic Interpolation in Irregular Land Survey: A Deep Internal Learning Approach

Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging. Preprocessing approaches, such as missing trace or shot interpolation, are typically employed to enhance seismic data in such cases. Recently, deep learning has been used to address the trace interpolation problem at the expense of large amounts of training data to adequately represent typical seismic events. Nonetheless, most research in this area has focused on trace reconstruction, with little attention having been devoted to shot interpolation. Furthermore, existing methods assume regularly spaced receivers/sources failing in approximating seismic data from real (irregular) surveys. This work presents a novel shot gather interpolation approach which uses a continuous coordinate-based representation of the acquired seismic wavefield parameterized by a neural network. The proposed unsupervised approach, which we call coordinate-based seismic interpolation (CoBSI), enables the prediction of specific seismic characteristics in irregular land surveys without using external data during neural network training. Importantly, experimental results on real and synthetic 3-D data validate the ability of the proposed method to estimate continuous smooth seismic events in the time-space and frequency-wavenumber domains, improving sparsity or low-rank-based interpolation methods.

58 GEOSCIENCES↗
DOE OSTI2020

Modifying Network Guided Vehicle for Repeatable EcoCAR ACC Energy Testing

The newest iteration of the Department of Energy (DOE) Advanced Vehicle Technology Competitions is the EcoCAR Mobility Challenge. In this paper, ANL and HORIBA MIRA collaborate to propose and pilot a test method that enables controlled, repeatable track-based energy consumption testing of semi-autonomous features. The testing was performed at MIRA’s proving ground facility in Nuneaton, UK, using their Network Guided Vehicle (NGV) connectivity and automation test platform. The NGV served as a repeatable lead vehicle following prescribed drive traces around two different track circuits while the host vehicle under test, a Honda Civic with full speed range Adaptive Cruise Control, followed behind. Over the course of a two day test, multiple iterations of certification and custom EPA drive traces were performed on track, demonstrating the viability of a two vehicle energy test. Results were analyzed to assess NGV lead vehicle performance in following the prescribed cycle using SAE J2951 standard calculations in an effort to quantify how repeatably and accurately the lead vehicle followed the trace. Host vehicle energy consumption was assessed using both vehicle CAN bus monitoring and an on-board fuel flow meter.

ACC↗
DOE OSTI2021

Clumped isotope thermometry of modern and fossil snail shells from the Himalayan-Tibetan Plateau: Implications for paleoclimate and paleoelevation reconstructions

Carbonate clumped isotope thermometry has been applied to fossil mollusk shells from Tibet to reconstruct the paleoclimate and paleoelevation of the region. However, inferred paleoelevation and climatic conditions from this proxy are inconsistent with paleontological evidence. Here, we report new clumped isotope data from both modern and fossil (5–4 Ma) freshwater mollusk shells with the results of X-ray diffraction (XRD) analyses of fossil shells from the Himalayan-Tibetan Plateau. Although all of the fossil shells analyzed in this study appeared pristine based on visual inspection, XRD data reveal that more than half of these apparently “pristine” fossil shells contain trace amounts of calcite. Clumped isotope temperatures derived from the fossil shells display a large range of variation (>22 °C). Among the fossil shells analyzed, those containing traces of calcite have yielded temperatures that are on average ~10 °C lower than those with no detectable calcite from the same strata. These observations suggest that clumped isotope alteration can occur in aragonite shells in low-temperature environments and even in shells with no visible signs of alteration that contain only traces of calcite. The temperatures derived from fossil shells with no detectable calcite are on average 4 °C higher than those derived from modern shells, indicating that southwest Tibet was warmer 4–5 Ma than today. After accounting for temperature change due to global cooling, the difference in clumped isotope temperatures between pristine fossil shells and modern shells suggests that the paleoelevation of the southwestern Tibetan Plateau in the Pliocene was similar to its present-day elevation.

Geology↗
DOE OSTI2024

Compositional zoning of the Otowi Member of the Bandelier Tuff, Valles caldera, New Mexico, USA

The Otowi Member of the Bandelier Tuff erupted at ca. 1.60 Ma from the Valles caldera (New Mexico, USA). It consists of as much as 400 km 3 (dense rock equivalent) of strongly differentiated high-silica rhyolite and shows systematic upward variations in crystallinity, mineral chemistry, and trace element concentrations through its thickness, but the major element composition is almost constant and is near the low-pressure granite minimum. Incompatible trace elements in whole pumice fragments and glasses show well-correlated linear covariations. Upward zoning to lower abundances of incompatible trace elements is accompanied by development of overgrowths on quartz and alkali feldspar, although earlier-formed interiors of quartz and feldspar have near-constant compositions throughout the tuff, modified by cation diffusion in the case of feldspar. Melt inclusions in remnant quartz cores show diverse Pb isotope ratios, pointing to a wide range of distinct protoliths that contributed rhyolitic melt to the Otowi magma. Mineral thermometers suggest a modest temperature gradient through the melt body, perhaps of 40 °C, at the time of eruption. Chemical, textural, and mineralogical variations and volume-composition relations through the tuff are consistent with an origin for zoning by melting of a high-crystallinity cumulate layer beneath cognate supernatant liquid to produce denser, remobilized liquid of accumulative composition (i.e., the “modified mush model”). Melting may have occurred in several episodes. The latest of these episodes, probably thousands of years prior to eruption, introduced new rhyolitic liquid into the system and was associated with a thermal excursion, recorded in core compositions of pyroxene, during which much of the earlier crystal mass was dissolved. This left inherited cores and interiors of accumulated quartz and feldspar mantled with new growth having less-evolved compositions (higher Ti, Sr, and Ba). Changing solubility of zircon during cumulate melting produced a reversal of Zr concentrations. There is no clear petrologic evidence of a recharge eruption trigger; nonetheless, compositional zoning resulted mainly from repeated recharge-induced remobilization of quartz-feldspar cumulate. The Otowi system was built, evolved, and modified by several events over the course of a few hundred thousand years.

Wolff, J. A.↗
DOE OSTI2021

General approach to the Lagrangian ambiguity in f(R, T) gravity

Abstract The f ( R , T ) gravity is a theory whose gravitational action depends arbitrarily on the Ricci scalar, R , and the trace of the stress–energy tensor, T ; its field equations also depend on matter Lagrangian, $$\mathscr {L}_{m}$$ L m . In the modified theories of gravity where field equations depend on Lagrangian, there is no uniqueness on the Lagrangian definition and the dynamics of the gravitational and matter fields can be different depending on the choice performed. In this work , we have eliminated the $$\mathscr {L}_{m}$$ L m dependence from f ( R , T ) gravity field equations by generalizing the approach of Moraes in Ref. [1]. We also propose a general approach where we argue that the trace of the energy–momentum tensor must be considered an “unknown” variable of the field equations. The trace can only depend on fundamental constants and few inputs from the standard model. Our proposal resolves two limitations: first the energy–momentum tensor of the f ( R , T ) gravity is not the perfect fluid one; second, the Lagrangian is not well-defined. As a test of our approach we applied it to the study of the matter era in cosmology, and the theory can successfully describe a transition between a decelerated Universe to an accelerated one without the need for dark energy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗