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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The underappreciated role of anthropogenic sources in atmospheric soluble iron flux to the Southern Ocean

The atmospheric deposition of soluble (bioaccessible) iron enhances ocean primary productivity and subsequent atmospheric CO 2 sequestration in iron-limited ocean basins, especially the Southern Ocean. While anthropogenic sources have been recently suggested to be important in some northern hemisphere oceans, the role in the Southern Ocean remains ambiguous. By comparing multiple model simulations with the new aircraft observations for anthropogenic iron, we show that anthropogenic soluble iron deposition flux to the Southern Ocean could be underestimated by more than a factor of ten in previous modeling estimates. Our improved estimate for the anthropogenic iron budget enhances its contribution on the soluble iron deposition in the Southern Ocean from about 10% to 60%, implying a dominant role of anthropogenic sources. We predict that anthropogenic soluble iron deposition in the Southern Ocean is reduced substantially (30-90%) by the year 2100, and plays a major role in the future evolution of atmospheric soluble iron inputs to the Southern Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Deep Koopman operators for causal discovery

Causal discovery aims to identify cause-effect mechanisms for better scientific understanding, explainable decision-making, and more accurate modeling. Standard statistical frameworks, such as Granger causality, lack the ability to quantify causal relationships in nonlinear dynamics due to the presence of complex feedback mechanisms, timescale mixing, and nonstationarity. Thus, applying these methods to study causal dynamics in real-world systems, such as the Earth, is a major challenge. Addressing this shortcoming, we leverage deep learning and a Koopman operator-theoretic formalism to present a class of causal discovery algorithms. Kausal uses deep Koopman operator methods to approximate nonlinear dynamics in a linearized vector space in which traditional causal inference methods such as Granger causality can be more easily applied. Our idealized experiments demonstrate Kausal’s superior ability in discovering and characterizing causal signals compared to existing deep learning and non-deep learning state-of-the-art approaches. Finally, the successful identification of major El Niño and La Niña events in observations showcases Kausal’s skill to handle real-world applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling hydrodynamics, magnetic fields, and synthetic radiographs for high-energy-density plasma flows in shock-shear targets

Three-dimensional FLASH radiation-magnetohydrodynamics (radiation-MHD) modeling is carried out to study the hydrodynamics and magnetic fields in the shock-shear derived platform. Here, simulations indicate that fields of tens of Tesla can be generated via the Biermann battery effect due to vortices and mix in the counterpropagating shock-induced shear layer. Synthetic proton radiography simulations using MPRAD and synthetic X-ray image simulations using SPECT3D are carried out to predict the observable features in the diagnostics. Quantifying the effects of magnetic fields in inertial confinement fusion and high-energy-density plasmas represents frontier research that has far-reaching implications in basic and applied sciences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Code-to-code comparison and validation of the radiation-hydrodynamics capabilities of the FLASH code using a laboratory astrophysical jet

The potential for laser-produced plasmas to yield fundamental insights into high energy density physics (HEDP) and deliver other useful applications can sometimes be frustrated by uncertainties in modeling the properties and behavior of these plasmas using radiation-hydrodynamics codes. In an effort to overcome this and to corroborate the accuracy of the HEDP capabilities in the publicly available FLASH radiation-hydrodynamics code, we present detailed code-to-code comparisons between FLASH and the HYDRA code developed at Lawrence Livermore National Laboratory using previously published HYDRA simulations from Grava et al. [Phys. Rev. E 78, 016403 (2008)]. That study describes a laser experiment that produced a jet-like feature that the authors compare to astrophysical jets. Importantly, the Grava et al. [Phys. Rev. E 78, 016403 (2008)] experiment included detailed x-ray interferometric measurements of electron number densities and a time-integrated measurement of the soft x-ray spectrum. Despite markedly different methods for treating the computational mesh, and different equations of state and opacity models, the FLASH results resemble the results from HYDRA and, most importantly, the experimental measurements of electron density. Having validated the FLASH code in this way, we use the code to further investigate and understand the formation of the jet seen in the Grava et al. [Phys. Rev. E 78, 016403 (2008)] experiment and discuss its relation to the Wan et al. [Phys. Rev. E 55, 6293 (1997)] experiment at the NOVA laser.

Orban, Chris (ORCID:0000000312004538)↗
DOE OSTI2022

Insensitivity of a turbulent laser-plasma dynamo to initial conditions

It has recently been demonstrated experimentally that a turbulent plasma created by the collision of two inhomogeneous, asymmetric, weakly magnetized, laser-produced plasma jets can generate strong stochastic magnetic fields via the small-scale turbulent dynamo mechanism, provided the magnetic Reynolds number of the plasma is sufficiently large. In this paper, we compare such a plasma with one arising from two pre-magnetized plasma jets whose creation is identical save for the addition of a strong external magnetic field imposed by a pulsed magnetic field generator. We investigate the differences between the two turbulent systems using a Thomson-scattering diagnostic, x-ray self-emission imaging, and proton radiography. The Thomson-scattering spectra and x-ray images suggest that the external magnetic field has a limited effect on the plasma dynamics in the experiment. Although the external magnetic field induces collimation of the flows in the colliding plasma jets and although the initial strengths of the magnetic fields arising from the interaction between the colliding jets are significantly larger as a result of the external field, the energies and morphologies of the stochastic magnetic fields post-amplification are indistinguishable. We conclude that, for turbulent laser-plasmas with supercritical magnetic Reynolds numbers, the dynamo-amplified magnetic fields are determined by the turbulent dynamics rather than the seed fields or modest changes in the initial flow dynamics of the plasma, a finding consistent with theoretical expectations and simulations of turbulent dynamos.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Bootstrap estimation of the effect of instrument response function uncertainty on the reconstruction of fusion neutron sources

Neutron imagers are important diagnostics for the inertial confinement fusion implosions at the National Ignition Facility. They provide two- and three-dimensional reconstructions of the neutron source shape that are key indicators of the overall performance. To interpret the shape results properly, it is critical to estimate the uncertainty in those reconstructions. There are two main sources of uncertainties: limited neutron statistics, leading to random errors in the reconstructed images, and incomplete knowledge of the instrument response function (the pinhole-dependent point spread function). While the statistical errors dominate the uncertainty for lower yield deuterium-tritium (DT) shots, errors due to the instrument response function dominate the uncertainty for DT yields on the order of 10 16 neutrons or higher. In this work, a bootstrapping method estimates the uncertainty in a reconstructed image due to the incomplete knowledge of the instrument response function. The main reconstruction is created from the fixed collection of pinhole images that are best aligned with the neutron source. Additional reconstructions are then built using subsets of that collection of images. Variations in the shapes of these additional reconstructions originate solely from uncertainties in the instrument response function, allowing us to use them to provide an additional systematic uncertainty estimate.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

An assessment of spall failure modes in laser powder bed fusion fabricated stainless steel 316L with low-volume intentional porosity

Here, this paper reports on spall failure and damage modes in Laser Powder Bed Fusion fabricated Stainless Steel 316L (SS316L) with intentional levels of low-volume (1–5 vol. %) porosity and pore sizes of 200, 350, and 500 μm. The fabricated specimens were subjected to uniaxial-strain plate-impact loading at ~4.5 GPa, to initiate incipient spall failure. Analysis of velocimetry profiles measured using multi-probe photon-Doppler velocimetry coupled with post-mortem analysis of soft-recovered samples reveals local suppression of spall failure (termed as spall-dominated) as a function of porosity, as the failure mechanism transitions from spall-centered tensile stress dominated to a pore-centered microstructure-dominated damage mode involving void/crack nucleation and growth at pre-existing pores. The critical porosity level where the suppression of spall failure is first observed, as well as the spall location, is dependent on both the volume fraction and the size of the initially fabricated pores. In samples of 500 μm pore size, the suppression of spall failure is observed with as little as 1 vol. % porosity, while samples with smaller pores (200 μm) still experience spall-centered tensile stress dominated failure with higher levels (5 vol. %) of porosity. In the case of pore-centered microstructure-dominated failure, spall damage can occur but the spall plane is shifted toward the rear free surface, or more generally in areas further away from the region with pores. Highly heterogeneous deformation twinning, shear banding, grain rotation, and cracking are observed in the vicinity of pre-existing pores and expected spall failure sites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermonuclear performance variability near ignition at the National Ignition Facility

We describe our current understanding of the variability and degradation mechanisms observed through a series of five indirectly driven inertial fusion implosions fielded at the National Ignition Facility in the fall of 2021, four of which attempted to reproduce the first experiment to achieve Lawson's criterion for ignition with a thermonuclear yield of 1.35 MJ on August 8, 2021. A large number of absolutely calibrated (imaging, time-resolved, and spectrally resolved) x-ray and neutron diagnostics are fielded on the NIF along multiple lines of sight for each experiment. This allows for a reconstruction of the DT fuel and ablator mix injected into the hotspot around peak burn. We show that nuclear yield variations are well reproduced by numerical modeling when the measured low mode asymmetries and mix mass are included. Furthermore, these observed perturbations during burn are linked to small variations in laser delivery and capsule defects. Stringent specifications are then set to achieve robust ignition with the implosion design studied in this paper.

Divol, L. (ORCID:0000000269699898)↗
DOE OSTI2024

Numerical simulations of laser-driven experiments of ion acceleration in stochastic magnetic fields

We present numerical simulations used to interpret laser-driven plasma experiments at the GSI Helmholtz Centre for Heavy Ion Research. The mechanisms by which non-thermal particles are accelerated in astrophysical environments, e.g., the solar wind, supernova remnants, and gamma ray bursts, is a topic of intense study. When shocks are present, the primary acceleration mechanism is believed to be first-order Fermi, which accelerates particles as they cross a shock. Second-order Fermi acceleration can also contribute, utilizing magnetic mirrors for particle energization. Despite this mechanism being less efficient, the ubiquity of magnetized turbulence in the universe necessitates its consideration. Another acceleration mechanism is the lower-hybrid drift instability, arising from gradients of both density and magnetic field, which produce lower-hybrid waves with an electric field that energizes particles as they cross these waves. With the combination of high-powered laser systems and particle accelerators, it is possible to study the mechanisms behind cosmic-ray acceleration in the laboratory. In this work, we combine experimental results and high-fidelity three-dimensional simulations to estimate the efficiency of ion acceleration in a weakly magnetized interaction region. We validate the FLASH magneto-hydrodynamic code with experimental results and use OSIRIS particle-in-cell code to verify the initial formation of the interaction region, showing good agreement between codes and experimental results. We find that the plasma conditions in the experiment are conducive to the lower-hybrid drift instability, yielding an increase in energy ΔE of ~ 264 keV for 242 MeV calcium ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Enzyme-mediated depletion of serum L -Met abrogates prostate cancer growth via multiple mechanisms without evidence of systemic toxicity

Extensive studies in prostate cancer and other malignancies have revealed that L -methionine ( L -Met) and its metabolites play a critical role in tumorigenesis. Preclinical and clinical studies have demonstrated that systemic restriction of serum L -Met, either via partial dietary restriction or with bacterial L -Met–degrading enzymes exerts potent antitumor effects. However, administration of bacterial L -Met–degrading enzymes has not proven practical for human therapy because of problems with immunogenicity. As the human genome does not encode L -Met–degrading enzymes, we engineered the human cystathionine-γ-lyase (hMGL-4.0) to catalyze the selective degradation of L -Met. At therapeutically relevant dosing, hMGL-4.0 reduces serum L -Met levels to >75% for >72 h and significantly inhibits the growth of multiple prostate cancer allografts/xenografts without weight loss or toxicity. We demonstrate that in vitro, hMGL-4.0 causes tumor cell death, associated with increased reactive oxygen species, S-adenosyl-methionine depletion, global hypomethylation, induction of autophagy, and robust poly(ADP-ribose) polymerase (PARP) cleavage indicative of DNA damage and apoptosis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Radiative absorption enhancements by black carbon controlled by particle-to-particle heterogeneity in composition

Black carbon (BC) absorbs solar radiation, leading to a strong but uncertain warming effect on climate. A key challenge in modeling and quantifying BC’s radiative effect on climate is predicting enhancements in light absorption that result from internal mixing between BC and other aerosol components. Modeling and laboratory studies show that BC, when mixed with other aerosol components, absorbs more strongly than pure, uncoated BC; however, some ambient observations suggest more variable and weaker absorption enhancement. We show that the lower-than-expected enhancements in ambient measurements result from a combination of two factors. First, the often used spherical, concentric core-shell approximation generally overestimates the absorption by BC. Second, and more importantly, inadequate consideration of heterogeneity in particle-to-particle composition engenders substantial overestimation in absorption by the total particle population, with greater heterogeneity associated with larger model–measurement differences. We show that accounting for these two effects—variability in per-particle composition and deviations from the core-shell approximation—reconciles absorption enhancement predictions with laboratory and field observations and resolves the apparent discrepancy. Furthermore, our consistent model framework provides a path forward for improving predictions of BC’s radiative effect on climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Structure of a paramyxovirus polymerase complex reveals a unique methyltransferase-CTD conformation

Paramyxoviruses are enveloped, nonsegmented, negative-strand RNA viruses that cause a wide spectrum of human and animal diseases. The viral genome, packaged by the nucleoprotein (N), serves as a template for the polymerase complex, composed of the large protein (L) and the homo-tetrameric phosphoprotein (P). The ~250-kDa L possesses all enzymatic activities necessary for its function but requires P in vivo. Structural information is available for individual P domains from different paramyxoviruses, but how P interacts with L and how that affects the activity of L is largely unknown due to the lack of high-resolution structures of this complex in this viral family. In this study we determined the structure of the L–P complex from parainfluenza virus 5 (PIV5) at 4.3-Å resolution using cryoelectron microscopy, as well as the oligomerization domain (OD) of P at 1.4-Å resolution using X-ray crystallography. P-OD associates with the RNA-dependent RNA polymerase domain of L and protrudes away from it, while the X domain of one chain of P is bound near the L nucleotide entry site. The methyltransferase (MTase) domain and the C-terminal domain (CTD) of L adopt a unique conformation, positioning the MTase active site immediately above the poly-ribonucleotidyltransferase domain and near the likely exit site for the product RNA 5' end. Our study reveals a potential mechanism that mononegavirus polymerases may employ to switch between transcription and genome replication. This knowledge will assist in the design and development of antivirals against paramyxoviruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Time-resolved turbulent dynamo in a laser plasma

Understanding magnetic-field generation and amplification in turbulent plasma is essential to account for observations of magnetic fields in the universe. A theoretical framework attributing the origin and sustainment of these fields to the so-called fluctuation dynamo was recently validated by experiments on laser facilities in low-magnetic-Prandtl-number plasmas (Pm < 1). However, the same framework proposes that the fluctuation dynamo should operate differently when Pm ≳ 1, the regime relevant to many astrophysical environments such as the intracluster medium of galaxy clusters. This paper reports an experiment that creates a laboratory Pm ≳ 1 plasma dynamo. We provide a time-resolved characterization of the plasma’s evolution, measuring temperatures, densities, flow velocities, and magnetic fields, which allows us to explore various stages of the fluctuation dynamo’s operation on seed magnetic fields generated by the action of the Biermann-battery mechanism during the initial drive-laser target interaction. The magnetic energy in structures with characteristic scales close to the driving scale of the stochastic motions is found to increase by almost three orders of magnitude and saturate dynamically. It is shown that the initial growth of these fields occurs at a much greater rate than the turnover rate of the driving-scale stochastic motions. Here, our results point to the possibility that plasma turbulence produced by strong shear can generate fields more efficiently at the driving scale than anticipated by idealized magnetohydrodynamics (MHD) simulations of the nonhelical fluctuation dynamo; this finding could help explain the large-scale fields inferred from observations of astrophysical systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Implicit learning of convective organization explains precipitation stochasticity

Accurate prediction of precipitation intensity is crucial for both human and natural systems, especially in a warming climate more prone to extreme precipitation. Yet, climate models fail to accurately predict precipitation intensity, particularly extremes. One missing piece of information in traditional climate model parameterizations is subgrid-scale cloud structure and organization, which affects precipitation intensity and stochasticity at coarse resolution. Here, using global storm-resolving simulations and machine learning, we show that, by implicitly learning subgrid organization, we can accurately predict precipitation variability and stochasticity with a low-dimensional set of latent variables. Using a neural network to parameterize coarse-grained precipitation, we find that the overall behavior of precipitation is reasonably predictable using large-scale quantities only; however, the neural network cannot predict the variability of precipitation (R 2 ~ 0.45) and underestimates precipitation extremes. The performance is significantly improved when the network is informed by our organization metric, correctly predicting precipitation extremes and spatial variability (R 2 ~ 0.9). The organization metric is implicitly learned by training the algorithm on a high-resolution precipitable water field, encoding the degree of subgrid organization. The organization metric shows large hysteresis, emphasizing the role of memory created by subgrid-scale structures. We demonstrate that this organization metric can be predicted as a simple memory process from information available at the previous time steps. These findings stress the role of organization and memory in accurate prediction of precipitation intensity and extremes and the necessity of parameterizing subgrid-scale convective organization in climate models to better project future changes of water cycle and extremes.

54 ENVIRONMENTAL SCIENCES↗