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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Multiple element isotope probes, NanoSIMS, and the functional genomics of microbial carbon cycling in soils in response to chronic climatic change

In this project, we developed an innovative and groundbreaking technique, quantitative stable isotope probing, a technique that uses density separation of nucleic acids as a quantitative measurement technique. This work is substantial because it advances SIP beyond the qualitative technique that has dominate the field for years. The first methods paper was published in Applied and Environmental Microbiology (Hungate et al. 2015), and this paper describes the mathematical model underlying the quantitative interpretation. A second methods paper (Schwartz et al. 2015) provides a conceptual overview of the method and its application to research problems. A third methods paper was just published (Koch et al. 2018), in which we develop the quantitative model combining sequencing and isotope data to estimate actual rates of microbial growth and death in natural populations. This work has met much enthusiasm in scientific presentations around the world. It has met with equally enthusiastic resistance in the peerreview process, though our record of publication to date argues that people are accepting the merits of the approach. The skepticism and resistance are also potentially signs that this technique is pushing the field forward, albeit with some of the discomfort that accompanies extrapolation. Part of this is a cultural element in the field – the field of microbiology is not accustomed to the assumptions of ecosystem science. Research conducted in this project has pushed the philosophical perspective that major advances can occur when we advocate a sound merger between the traditions of strong inference in microbiology with those of grounded scaling in ecosystem science.

quantitative stable isotope probing↗
NASA NTRS1997

Advanced Modeling Techniques to Study Anthropogenic Influences on Atmospheric Chemical Budgets

This research work is a collaborative effort between research groups at MCNC and the University of North Carolina at Chapel Hill. The overall objective of this research is to improve the level of understanding of the processes that determine the budgets of chemically and radiatively active compounds in the atmosphere through development and application of advanced methods for calculating the chemical change in atmospheric models. The research performed during the second year of this project focused on four major aspects: (1) The continued development and refinement of multiscale modeling techniques to address the issue of the disparate scales of the physico-chemical processes that govern the fate of atmospheric pollutants; (2) Development and application of analysis methods utilizing process and mass balance techniques to increase the interpretive powers of atmospheric models and to aid in complementary analysis of model predictions and observations; (3) Development of meteorological and emission inputs for initial application of the chemistry/transport model over the north Atlantic region; and, (4) The continued development and implementation of a totally new adaptive chemistry representation that changes the details of what is represented as the underlying conditions change.

Mathur, Rohit↗
DOE OSTI2018

Search for additional heavy neutral Higgs and gauge bosons in the ditau final state produced in 36 fb –1 of pp collisions at $ \sqrt{s}=13 $ TeV with the ATLAS detector

Here, a search for heavy neutral Higgs bosons and Z' bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb –1 from proton-proton collisions at √s=13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to τ + τ – with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for Z' bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude tan β > 1.0 for m A = 0.25 TeV and tan β > 42 for m A = 1.5 TeV at the 95% confidence level. For the Sequential Standard Model, Z SSM ' with m Z ' < 2.42 TeV is excluded at 95% confidence level, while Z NU ' with m Z' < 2.25 TeV is excluded for the non-universal G(221) model that exhibits enhanced couplings to third-generation fermions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

Experimental dehydration of natural obsidian and estimation of DH2O at low water contents

Water diffusion experiments were carried out by dehydrating rhyolitic obsidian from Valles Caldera (New Mexico, USA) at 510-980 degrees C. The starting glass wafers contained approximately 0.114 wt% total water, lower than any glasses previously investigated for water diffusion. Weight loss due to dehydration was measured as a function of experiment duration, which permits determination of mean bulk water diffusivity, mean Dw. These diffusivities are in the range of 2.6 to 18 X 10(-14) m2/s and can be fit with the following Arrhenius equation: ln mean Dw (m2/s) = -(25.10 +/- 1.29) - (46,480 +/- 11,400) (J/mol) / RT, except for two replicate runs at 510 degrees C which give mean Dw values much lower than that defined by the above equation. When interpreted according to a model of water speciation in which molecular H2O is the diffusing species with concentration-independent diffusivity while OH units do not contribute to the transport but react to provide H2O, the data (except for the 510 degrees C data) are in agreement with extrapolation from previous results and hence extend the previous data base and provide a test of the applicability of the model to very low water contents. Mean bulk water diffusivities are about two orders of magnitude less than molecular H2O diffusivities because the fraction of molecular H2O out of total water is very small at 0.114 wt% total water and less. The 510 degrees C experimental results can be interpreted as due to slow kinetics of OH to H2O interconversion at low temperatures.

NASA Program Exobiology↗
NASA NTRS1990

Self-irradiated cooling condensations - The source of the optical line emission from cooling flows

The optical filaments seen at the centers of clusters of galaxies, which cannot be explained by standard photoionization or shock models, can be straightforwardly interpreted as self-irradiated cooling condensations. Fully developed (about 10,000 K) condensations embedded in thermally unstable 10 million K gas will be bathed in a powerful EUV/soft X-ray flux emanating from the surrounding condensing regions. The present models of the condensation/irradiation process give line ratios and luminosities similar to those observed. Because it is assumed that the condensations arise from linear perturbations, which grow significantly only when the local cooling time is less than the free-fall time, condensing regions of the type modeled here should arise only in cooling flows of central pressure less than about 1 billion ergs/cu cm and should extend only over the inner regions of the cluster.

Voit, G. Mark↗
DOE OSTI2021

A mechanistic understanding of oxygen isotopic changes in the Western United States at the Last Glacial Maximum

At the Last Glacial Maximum (LGM), records suggest drier conditions in the northwest United States and wetter conditions in the southwest United States relative to present-day as well as widespread changes in the isotopic composition of water. However, the mechanisms responsible for these changes remain ambiguous. Here, we explore differences in western United States hydroclimate between the LGM and preindustrial with a water isotope tracer enabled Earth System Model. We then use proxy forward models to compare simulated and recorded δ 18 O in speleothems. We find that the pattern of hydroclimate response in the western United States at the LGM relates to a combination of 1) increased frequency and southward shifted wintertime extratropical cyclones in the North Pacific, 2) greater rainout of moisture as it moves over the continent, and 3) reduced evaporation in the cooler LGM climate. The simulated lower δ 18 O of precipitation at the LGM relates predominantly to an increase in cool season moisture removal efficiency, with a secondary contribution from relatively more cool season precipitation. Both surface temperatures and North American ice sheets contribute to these hydroclimate changes at the LGM. Comparisons between δ 18 O from proxy forward models and speleothem records in the western United States show general agreement at the LGM, with increasing depletion moving towards the continental interior. Finally, this study highlights the similarities and differences between hydrologic and δ 18 O changes at the LGM and emphasizes the utility of model-proxy comparison for interpretation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Bayesian Hierarchical Air-Sea Interaction Modeling: Application to the Labrador Sea

The objectives are to: 1) Organize data from 26 MINIMET drifters in the Labrador Sea, including sensor calibration and error checking of ARGOS transmissions. 2) Produce wind direction, barometer, and sea surface temperature time series. In addition, provide data from historical file of 150 SHARP drifters in the Labrador Sea. 3) Work with data interpretation and data-modeling assimilation issues.

Niiler, Pearn P.↗
DOE OSTI2020

Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ 1 -regularization

We develop a new data-driven paradigm for efficient model reduction of a broad class of nonlinear dynamical systems. Our model reduction method directly enables the interpretation of key components of the dynamical system, unlike traditional projection-based model reduction methods that focus on reducing computational complexity more than interpretability. Our method is not application specific and is simple to implement on nonlinear dynamical systems arising from a variety of different fields. It requires minimal parameterization using a single parameter to trade-off between model complexity and estimation error. We use a data-driven paradigm to formulate model reduction as an efficient convex optimization problem that scales polynomially in the original size of the complex system, enabling systems with as many as thousands of components to be reduced in a matter of minutes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Predicting the dissolution kinetics of silicate glasses by topology-informed machine learning

Machine learning (ML) regression methods are promising tools to develop models predicting the properties of materials by learning from existing databases. However, although ML models are usually good at interpolating data, they often do not offer reliable extrapolations and can violate the laws of physics. Here, to address the limitations of traditional ML, we introduce a “topology-informed ML” paradigm—wherein some features of the network topology (rather than traditional descriptors) are used as fingerprint for ML models—and apply this method to predict the forward (stage I) dissolution rate of a series of silicate glasses. We demonstrate that relying on a topological description of the atomic network (i) increases the accuracy of the predictions, (ii) enhances the simplicity and interpretability of the predictive models, (iii) reduces the need for large training sets, and (iv) improves the ability of the models to extrapolate predictions far from their training sets. As such, topology-informed ML can overcome the limitations facing traditional ML (e.g., accuracy vs. simplicity tradeoff) and offers a promising route to predict the properties of materials in a robust fashion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dislocation loop evolution in Kr-irradiated ThO 2

Here, the early stage of microstructural evolution of ThO 2 , under krypton irradiation at 600, 800, and 1000°C, was investigated using in situ transmission electron microscopy (TEM). Dislocation loops grew faster, whereas their number density decreased with increasing irradiation temperature. Loop density was found to decrease with ion dose. Interstitial dislocation loops, including Frank loops with Burgers vector of $\textit{a}/3\langle111\rangle$ and perfect loops with Burgers vector of $\textit{a}/2\langle110\rangle$, were determined by traditional TEM and atomic resolution–scanning TEM techniques. Atomistic and mesoscale level modeling are performed to interpret experimental observations. The migration energy barriers of defects in ThO 2 were calculated using density-functional theory. The energetics of different dislocation loop types were studied using molecular dynamics simulations. Loop density and diameter were analyzed using a kinetic rate theory model that considers stoichiometric loop evolution. This analysis reveals that loop growth is governed by the mobility of cation interstitials, whereas loop nucleation is determined by the mobility of anion defects. Lastly, a rate theory model was used to extract the diffusion coefficients of thorium interstitials, oxygen interstitials, and vacancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Large historical growth in global terrestrial gross primary production

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including a large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modern chemical graph theory

Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures

Leite, Leonardo S. G.↗
NASA NTRS2007

New Evidence that CMEs are Self-Propelled Magnetic Bubbles

We briefly describe the "standard model" for the production of coronal mass ejections (CMEs), and our view of how it works. We then summarize pertinent recent results that we have found from SOHO observations of CMEs and the flares at the sources of these magnetic explosions. These results support our interpretation of the standard model: a CME is basically a self-propelled magnetic bubble, a low-beta plasmoitl, that (1) is built and unleashed by the tether-cutting reconnection that builds and heats the coronal flare arcade, (2) can explode from a flare site that is far from centered under the full-blown CME in the outer corona, and (3) drives itself out into the solar wind by pushing on the surrounding coronal magnetic field.

Moore, Ronald L.↗
DOE OSTI2025

Use of Rig Parameter Data in Bit Constraint Models for Improved Drilling Performance at The Geysers

Surface parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. However, these measurements are of reduced value without a standard to aid in evaluation and decision making. A method is demonstrated whereby drill bit constraint models are used to interpret drilling response parameters. Drill rig parameter data for well GDC-36 at the Geysers Geothermal Field Power were acquired by Geysers Power Company and drilling contractor Kenai Drilling using Pason US DataHub and evaluated. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) along with other model constraints in computational algorithms. The method is used to evaluate overall bit performance, monitor bit integrity, and detect the presence of drillstring vibrations and other conditions contributing to bit failure; comparisons are made to observations of bit wear and damage. The method will be applied in real-time to improve decision-making on subsequent wells and has applicability to development of advanced analytics on future geothermal wells using real-time electronic drilling recorder (EDR) data for improved performance and reduced drilling costs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

A model of Jupiter's sulfur nebula

A simple model of Jupiter's S II emission nebula is developed on the basis of a complete treatment of electron-impact excitation of sulfur ions. Forbidden line emission from S II ions excited by electron collisions in the Jovian nebula is analyzed, and existing observations are interpreted using a simple model of an S II nebula which is uniform in depth. The results show that the depth of the nebula is 300,000 to 600,000 km, the electron density is about 3160 per cu cm, the electron temperature is approximately 25,000 K, and the S II concentration is roughly 79 ions per cu cm. It is noted that these plasma conditions are quite different from those reported for the same region on the basis of Pioneer 10 data, indicating that the S II nebula is a sporadic event. Io is suggested as the source of the sulfur.

Brown, R. A.↗
DOE OSTI2019

Validation Metrics for Deterministic and Probabilistic Data

Computational modeling and simulation are paramount to modern science. Computational models often replace physical experiments that are prohibitively expensive, dangerous, or occur at extreme scales. Thus, it is critical that these models accurately represent and can be used as replacements for reality. This paper provides an analysis of metrics that may be used to determine the validity of a computational model. While some metrics have a direct physical meaning and a long history of use, others, especially those that compare probabilistic data, are more difficult to interpret. Furthermore, the process of model validation is often application-specific, making the procedure itself challenging and the results difficult to defend. We therefore provide guidance and recommendations as to which validation metric to use, as well as how to use and decipher the results. Furthermore an example is included that compares interpretations of various metrics and demonstrates the impact of model and experimental uncertainty on validation processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Modeling Dynamic Helium Release as a Tracer of Rock Deformation

Here, we use helium released during mechanical deformation of shales as a signal to explore the effects of deformation and failure on material transport properties. A dynamic dual-permeability model with evolving pore and fracture networks is used to simulate gases released from shale during deformation and failure. Changes in material properties required to reproduce experimentally observed gas signals are explored. We model two different experiments of 4He flow rate measured from shale undergoing mechanical deformation, a core parallel to bedding and a core perpendicular to bedding. We also found that the helium signal is sensitive to fracture development and evolution as well as changes in the matrix transport properties. We constrain the timing and effective fracture aperture, as well as the increase in matrix porosity and permeability. Increases in matrix permeability are required to explain gas flow prior to macroscopic failure, and the short-term gas flow postfailure. Increased matrix porosity is required to match the long-term, postfailure gas flow. This model provides the first quantitative interpretation of helium release as a result of mechanical deformation. The sensitivity of this model to changes in the fracture network, as well as to matrix properties during deformation, indicates that helium release can be used as a quantitative tool to evaluate the state of stress and strain in earth materials.

58 GEOSCIENCES↗