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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 343 records · Page 19

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NASA NTRS1994

The N (II) 205 micron line in M82: The warm ionized medium

Detection of the 205 micrometer fine structure line of N II in the nearby starburst galaxy M82 is reported. The intensity wihin a 54 sec Full width at Half Maximum (FWHM) beam is (7.1 +/- 1.2) x 10(exp -19) W cm(exp -2). The ratio of the intensity of the recently detected 122 micrometer line to that of the 2.5 micrometer lines is = (4.2) (sup =1.6) (sub -1.2), significantly larger than the corresponding Galactic value of 1.6 +/- 0.3, reflecting higher electron densities within the central 850 pc of M82 in comparison to the Cosmic Background Explorer (COBE) Galactic average. The 2.5 micrometer line profile is consistent with other far-infrared fine-structure line profiles observed in M82. The observations are interpreted in the context of a two-component model of the ionized medium in M82. We find that a component of density as low as approximately 50 cm(exp -3) can comprise up to 70% of the total mass of warm ionized gas within the beam. The balance of the ionized mass is comprised of a component of density approximately greater than 100 cm(exp -3). A model is explored in which the dneser ionized medium constitute the boundaries of neutral surfaces which border the expanding hot plasma from the nuclear region.

Petuchowski, S. J.↗

NASA NTRS2022

A Model-Based Approach for Europa Lander Mission Concept Exploration

This study investigates the usage of a system model as a means to capture concept formulation for a potentialmission. Efforts are underway at JPL to explore thearchitectural and system concepts for a lander on Europa.Executing a mission on the surface of Europa poses uniquechallenges that will require the lander to operate with onboardautonomy that is more sophisticated than systems previouslyoperated by JPL. Current tasks to explore surface missionconcepts intend to identify concepts that enable a high degree ofonboard autonomy as well as identify the issues and technicallimitations that restrict autonomy. The Europa lander missionconcept team is developing a system model to support thisexploration.The results of this study highlight how executable systemmodeling and the associated engineering environment may beapplied to pre-project conceptual exploration. The applicationof system modeling has resulted in a central system model thatprecisely describes the concepts formulated by the EuropaLander Mission Concept Team. Documentation in the form ofdiagrams and narrative has been directly generated from thesystem model and accessible by team members in a webapplication. The executability of the system model enablesvarious analyses such as simulation of interactions betweencomponents and evaluating system behavior againstrequirements. Execution of the system model has produced statetimelines, plots of system variables, and simulation traces basedon input scenarios. The executable system model enables therapid and repeatable production of these artifacts.

Reeves, Glenn↗

DOE OSTI2023

Resolving dynamic mineral-organic interactions in the rhizosphere by combining in-situ microsensors with plant-soil reactive transport modeling

Associations between minerals and organic matter represent one of the most important carbon storage mechanisms in soils. Plant roots are major sources of soil carbon, and resolving the dynamics and dominance of microbial consumption versus mineral sorption of root-derived carbon is critical to understanding soil carbon storage. Here we integrate in-situ rhizosphere microsensor and plant physiological measurements with a 3-D plant-soil reactive transport model to explore the fate of dissolved organic carbon (DOC) in the rhizosphere, particularly its microbial consumption and interaction with Fe oxide minerals. Over several days, a microdialysis probe sampling pore water at the root-soil interface of growing Vicia faba roots in live soil, revealed clear diel patterns of DOC concentration. Daytime DOC spikes coincided with peaks in leaf-level photosynthesis rates and were accompanied by declining redox potential and dissolved oxygen as well as increasing pH in the rhizosphere. Incorporating microsensor data into our modeling framework showed that the measured rapid loss of DOC after each mid-day spike could not be explained by consumption via aerobic respiration, nor via anaerobic respiration dominated by Fe oxide reduction. Rather, in the model, a large fraction of rhizosphere DOC was rapidly immobilized each day by adsorption to Fe oxides. Further, modeled microbial Fe reduction (fueled by DOC) did not mobilize significant organic carbon from Fe oxides during the day. Instead, the model predicted equilibrium desorption of organic carbon from Fe oxides at night. This new mechanistic modeling framework, which couples aboveground plant physiological measurements with non-destructive high-resolution monitoring of rhizosphere processes, has great potential for exploring the dynamics and balance of the various microbial reactions and mineral interactions controlling carbon transformations and storage in soils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Investigating boosted decision trees as a guide for inertial confinement fusion design

Inertial confined fusion experiments at the National Ignition Facility have recently entered a new regime approaching ignition. Improved modeling and exploration of the experimental parameter space were essential to deepening our understanding of the mechanisms that degrade and amplify the neutron yield. The growing prevalence of machine learning in fusion studies opens a new avenue for investigation. Here in this paper, we have applied the Gradient-Boosted Decision Tree machine-learning architecture to further explore the parameter space and find correlations with the neutron yield, a key performance indicator. We find reasonable agreement between the measured and predicted yield, with a mean absolute percentage error on a randomly assigned test set of 35.5%. This model finds the characteristics of the laser pulse to be the most influential in prediction, as well as the hohlraum laser entrance hole diameter and an enhanced capsule fabrication technique. We used the trained model to scan over the design space of experiments from three different campaigns to evaluate the potential of this technique to provide design changes that could improve the resulting neutron yield. While these data-driven model cannot predict ignition without examples of ignited shots in the training set, it can be used to indicate that an unseen shot design will at least be in the upper range of previously observed neutron yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1991

Application of powder densification models to the consolidation processing of composites

Unidirectional fiber reinforced metal matrix composite tapes (containing a single layer of parallel fibers) can now be produced by plasma deposition. These tapes can be stacked and subjected to a thermomechanical treatment that results in a fully dense near net shape component. The mechanisms by which this consolidation step occurs are explored, and models to predict the effect of different thermomechanical conditions (during consolidation) upon the kinetics of densification are developed. The approach is based upon a methodology developed by Ashby and others for the simpler problem of HIP of spherical powders. The complex problem is devided into six, much simpler, subproblems, and then their predicted contributions are added to densification. The initial problem decomposition is to treat the two extreme geometries encountered (contact deformation occurring between foils and shrinkage of isolated, internal pores). Deformation of these two geometries is modelled for plastic, power law creep and diffusional flow. The results are reported in the form of a densification map.

Wadley, H. N. G.↗

DOE OSTI2022

Identification of a pharmacological approach to reduce ACE2 expression and development of an in vitro COVID-19 viral entry model

Because of rapid emergence and circulation of the SARS-CoV-2 variants, especially Omicron which shows increased transmissibility and resistant to antibodies, there is an urgent need to develop novel therapeutic drugs to treat COVID-19. In this study we developed an in vitro cellular model to explore the regulation of ACE2 expression and its correlation with ACE2-mediated viral entry. We examined ACE2 expression in a variety of human cell lines, some of which are commonly used to study SARS-CoV-2. Using the developed model, we identified a number of inhibitors which reduced ACE2 protein expression. The greatest reduction of ACE2 expression was observed when CK869, an inhibitor of the actin-related protein 2/3 (ARP2/3) complex, was combined with 5-(N-ethyl-N-isopropyl)-amiloride (EIPA), an inhibitor of sodium-hydrogen exchangers (NHEs), after treatment for 24 h. Using pseudotyped lentivirus expressing the SARS-CoV-2 full-length spike protein, we found that ACE2-dependent viral entry was inhibited in CK869 + EIPA-treated Calu-3 and MDA-MB-468 cells. This study provides an in vitro model that can be used for the screening of novel therapeutic candidates that may be warranted for further pre-clinical and clinical studies on COVID-19 countermeasures.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Using anion photoelectron spectroscopy of cluster models to gain insights into mechanisms of catalyst-mediated H 2 production from water

We report that metal oxide cluster models of catalyst materials offer a powerful platform for probing the molecular-scale features and interactions that govern catalysis. This perspective gives an overview of studies implementing the combination of anion photoelectron (PE) spectroscopy and density functional theory calculations toward exploring cluster models of metal oxides and metal-oxide supported Pt that catalytically drive the hydrogen evolution reaction (HER) or the water–gas shift reaction. The utility in the combination of these experimental and computational techniques lies in our ability to unambiguously determine electronic and molecular structures, which can then connect to results of reactivity studies. In particular, we focus on the activity of oxygen vacancies modeled by suboxide clusters, the critical mechanistic step of forming proximal metal hydride and hydroxide groups as a prerequisite for H2 production, and the structural features that lead to trapped dihydroxide groups. The pronounced asymmetric oxidation found in heterometallic group 6 oxides and near-neighbor group 5/group 6 results in higher activity toward water, while group 7/group 6 oxides form very specific stoichiometries that suggest facile regeneration. Studies on the trans-periodic combination of cerium oxide and platinum as a model for ceria supported Pt atoms and nanoparticles reveal striking negative charge accumulation by Pt, which, combined with the ionic conductivity of ceria, suggests a mechanism for the exceptionally high activity of this system towards the water–gas shift reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Dwarf Galaxies at Cosmic Noon: New JWST Constraints on Satellite Models and Subhalo Tidal Evolution

The advent of JWST has revolutionized the study of faint satellite galaxies at z ≳ 1, enabling statistical constraints on galaxy evolution and the galaxy–halo connection in a previously unexplored mass and redshift regime. We compare satellite abundances at 1 < z < 3.5 from recent JWST observations with predictions from cosmological dark-matter-only zoom-in simulations. We identify and quantify several sources of biases that can impact theoretical satellite counts, finding that assumptions about subhalo tidal evolution introduce the largest uncertainty in predictions for the satellite mass function. Using a flexible galaxy disruption model, we explore a range of disruption scenarios, spanning hydrodynamically motivated and idealized prescriptions, to bracket plausible physical outcomes. We show that varying galaxy durability can change the predicted satellite mass functions by a factor of ∼3.5. The JWST data and our fiducial model are consistent within 1σ–2σ across the full redshift (1 < z < 3.5) and stellar mass (M⋆ > 10 7 M ⊙ ) range probed. We find evidence that subhalos are at least as long-lived as predicted by hydrodynamic simulations. Our framework will enable robust constraints on the tidal evolution of subhalos with future observations. This work presents the first direct comparison between cosmological models and observations of the high-redshift satellite population in this low-mass regime. These results showcase JWST’s emerging power to test structure formation in the first half of the Universe in a new domain and to constrain the physical processes driving the evolution of low-mass galaxies across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Biomass burning aerosol radiative effects in the Southeast Atlantic depend strongly on meteorological forcing method

Biomass burning aerosols (BBAs) from African fires may strongly impact Earth’s radiation budget in the southeast Atlantic (SEA), but the sign and magnitude of the overall radiative effect (RE) remain uncertain. Aerosol–climate models are needed to separately quantify direct, indirect, and semi-direct REs. Here, we evaluate improved simulations with the UK Met Office's Unified Model and explore REs resulting from various methods used to match observed meteorology (nudging or running forecasts reinitialized at different frequencies). REs are calculated as differences in radiative fluxes between simulations with and without smoke emissions and with and without aerosol absorption. All model setups agree on net warming for the SEA dominated by the direct effect. Simulated smoke, clouds, and the direct effect agree better with observations than previous studies using the same model, though biases in aerosol extinction and liquid water path remain. Changes in cloud droplet number concentration due to BBA self-lofting influence how cleanly we can separate cloud effects into semi-direct and indirect effects. Total RE, which remains unaffected, ranges from +3.0 to +7.9 W m −2 . The 4.9 W m −2 spread arises mainly from simulated semi-direct effects. Forecasts three days long or less probably do not allow time for plausible differences in boundary layer properties due to semi-direct effects to accumulate. Free running simulations with and without smoke accumulate differences in meteorology that are likely spurious “butterfly effects”. We recommend future research quantifying BBA REs over weeks to months to use meteorological forcing techniques that allow aerosol absorption to affect the boundary layer.

Giuffrida, Eric [Carnegie Mellon University, Pitts↗

DOE OSTI2023

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

58 GEOSCIENCES↗

DOE OSTI2023

Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers

The Exa.TrkX project presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the Large Hadron Collider (LHC). Graphs describing particle interactions are formed by treating each detector hit as a node, with edges describing the relationships between hits. We utilise a multi-head attention message passing network which performs graph convolutions in order to label each node with a particle type.We present an updated variant of our GNN architecture, with several improvements. After testing the model on more realistic simulation with regions of unresponsive wires, the target was modified from edge classification to node classification in order to increase robustness. Removing edges as a classification target opens up a broader possibility space for edge-forming techniques; we explore the model’s performance across a variety of approaches, such as Delaunay triangulation, kNN, and radius-based methods. We also extend this model to the 3D context, sharing information between detector views. By using reconstructed 3D spacepoints to map detector hits from each wire plane, the model naively constructs 2D representations that are independent yet fully consistent.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1996

Heterogeneous Photocatalytic Oxidation of Atmospheric Trace Contaminants

Heterogeneous photocatalysis involves the use of a light-activated catalyst at room temperature in order to carry out a desired reaction. In the presence of molecular oxygen, illumination of the n-type semiconductor oxide titanium dioxide (TiO2) provides for production of highly active forms of oxygen, such as hydroxyl radicals, which are able to carry out the complete oxidative destruction of simple hydrocarbons such as methane, ethane, ethylene, propylene, and carbon monoxide. This broad oxidation potential, coupled with the ability with sufficient residence time to achieve complete oxidation of simple hydrocarbon contaminants to carbon dioxide and water, indicated that heterogeneous photocatalysis should be examined for its potential for purification of spacecraft air. If a successful catalyst and photoreactor could be demonstrated at the laboratory level, such results would allow consideration of photocatalysts as a partial or complete replacement of adsorption systems, thereby allowing for reduction in lift-off weight of a portion of the life support system for the spacecraft, or other related application such as a space station or a conventional commercial aircraft. The present research was undertaken to explore this potential through achievement of the following plan of work: (a) ascertain the intrinsic kinetics of conversion of pollutants of interest in spacecraft, (b) ascertain the expected lifetime of catalysts through examination of most likely routes of catalyst deactivation and regeneration, (c) model and explore experimentally the low pressure drop catalytic monolith, a commercial configuration for automotive exhaust control, and (d) examine the kinetics of multicomponent conversions. In the recent course of this work, we have also discovered how to increase catalyst activity via halide promotion which has allowed us to achieve approximately 100% conversion of an aromatic contaminant (toluene) in a very short residence time of 5-6 milliseconds.

Ollis, David F.↗

NASA NTRS1996

Heterogeneous Photocatalytic Oxidation of Atmospheric Trace Contaminants

Heterogeneous photocatalysis involves the use of a light-activated catalyst at room temperature in order to carry out a desired reaction. In the presence of molecular oxygen, illumination of the n-type semiconductor oxide titanium dioxide (TiO2) provides for production of highly active forms of oxygen, such as hydroxyl radicals, which are able to carry out the complete oxidative destruction of simple hydrocarbons such as methane, ethane, ethylene, propylene, and carbon monoxide. This broad oxidation potential, coupled with the ability with sufficient residence time to achieve complete oxidation of simple hydrocarbon contaminants to carbon dioxide and water, indicated that heterogeneous photocatalysis should be examined for its potential for purification of spacecraft air. If a successful catalyst and photoreactor could be demonstrated at the laboratory level, such results would allow consideration of photocatalysts as a partial or complete replacement of adsorption systems, thereby allowing for reduction in lift-off weight of a portion of the life support system for the spacecraft, or other related application such as a space station or a conventional commercial aircraft. The present research was undertaken to explore this potential through achievement of the following plan of work: (a) ascertain the intrinsic kinetics of conversion of pollutants of interest in spacecraft, (b) ascertain the expected lifetime of catalysts through examination of most likely routes of catalyst deactivation and regeneration (c) model and explore experimentally the low pressure drop catalytic monolith, a commercial configuration for automotive exhaust control (d) examine the kinetics of multicomponent conversions. In the recent course of this work, we have also discovered how to increase catalyst activity via halide promotion which has allowed us to achieve approximately 100% conversion of an aromatic contaminant (toluene) in a very short residence time of 5-6 milliseconds.

Ollis, David F.↗

NASA NTRS2019

Eddy Compensation Dampens Southern Ocean Sea Surface Temperature Response to Westerly Wind Trends

Anthropogenic influences have led to a strengthening and poleward shift of westerly winds over the Southern Ocean (SO), especially during austral summer. We use observations, an idealized eddy‐resolving ocean‐sea ice channel model, and a global coupled model to explore the SO response to a step‐change in westerly winds. Previous work hypothesized a two timescale response for sea surface temperature. Initially, Ekman transport cools the surface before sustained upwelling causes warming on decadal timescales. The fast response is robust across our models and the observations: we find Ekman‐driven cooling in the mixed layer, mixing‐driven warming below the mixed layer, and a small upwelling‐driven warming at the temperature inversion. The long‐term response is inaccessible from observations. Neither of our models shows a persistent upwelling anomaly, or long‐term, upwelling‐driven subsurface warming. Mesoscale eddies act to oppose the anomalous wind‐driven upwelling, through a process known as eddy compensation, thereby preventing long‐term warming.

Southern Annular Mode↗

DOE OSTI2022

Efficient emulation of relativistic heavy ion collisions with transfer learning

Measurements from the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) can be used to study the properties of quark-gluon plasma. Systematic constraints on these properties must combine measurements from different collision systems and methodically account for experimental and theoretical uncertainties. Such studies require a vast number of costly numerical simulations. While computationally inexpensive surrogate models (“emulators”) can be used to efficiently approximate the predictions of heavy ion simulations across a broad range of model parameters, training a reliable emulator remains a computationally expensive task. We use transfer learning to map the parameter dependencies of one model emulator onto another, leveraging similarities between different simulations of heavy ion collisions. By limiting the need for large numbers of simulations to only one of the emulators, this technique reduces the numerical cost of comprehensive uncertainty quantification when studying multiple collision systems and exploring different models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1986

Shock waves and shock tubes; Proceedings of the Fifteenth International Symposium, Berkeley, CA, July 28-August 2, 1985

A detailed survey is presented of shock tube experiments, theoretical developments, and applications being carried out worldwide. The discussions explore shock tube physics and the related chemical, physical and biological science and technology. Extensive attention is devoted to shock wave phenomena in dusty gases and other multiphase and heterogeneous systems, including chemically reactive mixtures. Consideration is given to techniques for measuring, visualizing and theoretically modeling flowfield, shock wave and rarefaction wave characteristics. Numerical modeling is explored in terms of the application of computational fluid dynamics techniques to describing flowfields in shock tubes. Shock interactions and propagation, in both solids, fluids, gases and mixed media are investigated, along with the behavior of shocks in condensed matter. Finally, chemical reactions that are initiated as the result of passage of a shock wave are discussed, together with methods of controlling the evolution of laminar separated flows at concave corners on advanced reentry vehicles.

Bershader, D.↗

NASA NTRS1997

Generalized Kinetic Description of Steady-State Collisionless Plasmas

We present a general solution to the collisionless Boltzmann (Vlasov) equation for a free-flowing plasma along a magnetic field line using Liouville's theorem, allowing for an arbitrary potential structure including non-monotonicities. The constraints of the existing collisionless kinetic transport models are explored, and the need for a more general approach to the problem of self- consistent potential energy calculations is described. Then a technique that handles an arbitrary potential energy distribution along the field line is presented and discussed. For precipitation of magnetospherically trapped hot plasma, this model yields moment calculations that vary by up to a factor of two for various potential energy structures with the same total potential drop. The differences are much greater for the high-latitude outflow scenario, giving order of magnitude variations depending on the shape of the potential energy distribution.

Khazanov, G. V.↗

NASA NTRS2014

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗