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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Probabilistic Prediction of Geomagnetic Storms and the K p index

Geomagnetic activity is often described using summary indices to summarize the likelihood of space weather impacts, as well as when parameterizing space weather models. The geomagnetic index K p in particular, is widely used for these purposes. Current state-of-the-art forecast models provide deterministic K p predictions using a variety of methods – including empirically-derived functions, physics-based models, and neural networks – but do not provide uncertainty estimates associated with the forecast. This paper provides a sample methodology to generate a 3-hour-ahead K p prediction with uncertainty bounds and from this provide a probabilistic geomagnetic storm forecast. Specifically, we have used a two-layered architecture to separately predict storm (K p ≥ 5 – ) and non-storm cases. As solar wind-driven models are limited in their ability to predict the onset of transient-driven activity we also introduce a model variant using solar X-ray flux to assess whether simple models including proxies for solar activity can improve the predictions of geomagnetic storm activity with lead times longer than the L1-to-Earth propagation time. By comparing the performance of these models we show that including operationally-available information about solar irradiance enhances the ability of predictive models to capture the onset of geomagnetic storms and that this can be achieved while also enabling probabilistic forecasts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Alkali Metal Control of Triplet-Mediated C–H Activation in Iron-Mediated Coupling of Dinitrogen and Benzene

Direct coupling of N 2 with abundant feedstocks like benzene to form N-containing organic compounds is a promising strategy for N 2 fixation pathways. The challenge of coupling N 2 activation and C–H bond oxidative addition was recently solved by introducing a reversible benzene C–H bond activation process mediated by a low-valent Fe(0) complex, which gave an organometallic product that could couple with partially reduced N 2 . Interestingly, the energetics of the C–H oxidative addition/reductive elimination step depends on the choice of alkali metal. However, the reason why the alkali metal influences the C–H bond activation remained elusive. In this work, we present a comprehensive study on this Fe(0)-mediated reversible C–H activation. Through density functional theory combined with high-level coupled cluster calculations, we discovered that the intermediate-spin triplet (S = 1) controls the energy of the transition state for C–H cleavage, while the high-spin quintet (S = 2) controls the position of the equilibrium. Na + drives the equilibrium toward oxidative addition due to an electrostatic effect, while K + and Rb + are dominated by a steric effect that favors the iron(0) species. The key role played by nonbonding interactions in the Fe-mediated C–H activation provides a conceptual model for alkali control over organometallic transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

FEOTS v0.0.0: a new offline code for the fast equilibration of tracers in the ocean

Abstract. In this paper we introduce a new software framework for the offline calculation of tracer transport in the ocean. The Fast Equilibration of Ocean Tracers Software (FEOTS) is an end-to-end set of tools to efficiently calculate tracer distributions on a global or regional sub-domain using transport operators diagnosed from a comprehensive ocean model. To the best of our knowledge, this is the first application of a transport matrix model to an eddying ocean state. While a Newton–Krylov-based equilibration capability is still under development and not presented here, we demonstrate in this paper the transient modeling capabilities of FEOTS in an application focused on the Argentine Basin, where intense eddy activity and the Zapiola Anticyclone lead to strong mixing of water masses. The demonstration illustrates progress in developing offline passive tracer simulation capabilities, while highlighting the challenges of the impulse response functions approach in capturing tracer transports by a non-linear advection scheme. Our future work will focus on improving the computational efficiency of the code to reduce time-to-solution, using different basis functions to better represent non-linear advection operators, applying FEOTS to a parent model with unstructured grids (Ocean Model for Prediction Across Scales, MPAS-Ocean), and fully implementing a Newton–Krylov steady-state solver.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A population data-driven workflow for COVID-19 modeling and learning

CityCOVID is a detailed agent-based model that represents the behaviors and social interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 million distinct places, including households, schools, workplaces, and hospitals, as determined by individual hourly activity schedules and dynamic behaviors such as isolating because of symptom onset. Disease progression dynamics incorporated within each agent track transitions between possible COVID-19 disease states, based on heterogeneous agent attributes, exposure through colocation, and effects of protective behaviors of individuals on viral transmissibility. Throughout the COVID-19 epidemic, CityCOVID model outputs have been provided to city, county, and state stakeholders in response to evolving decision-making priorities, while incorporating emerging information on SARS-CoV-2 epidemiology. Here we demonstrate our efforts in integrating our high-performance epidemiological simulation model with large-scale machine learning to develop a generalizable, flexible, and performant analytical platform for planning and crisis response.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Providing Satellite-Assisted Particulate Matter (SAPM) Estimates for the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group

The Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group is an international forum that promotes collaboration amongst researchers of these three atmospheric aerosol communities. MIRA currently consists of a collection of five interdisciplinary and independently funded Topic groups with focused goals and generally involve requests for additional scientific datasets. Participants of the MIRA Satellite-Assisted Particulate Matter (SAPM) Topic group study particulate matter with diameters smaller than 2.5 microns (PM2.5), because of its substantial role in air pollution and the resulting negative impacts on human health. SAPM seeks to provide intercomparisons of different methods and techniques for obtaining surface PM2.5 proxies using spaceborne passive and active remote sensors, aerosol models, and in situ observations. The ultimate motivation of SAPM is to provide greater PM2.5 coverage than in situ ground stations, which are limited in some areas of the contiguous United States and large regions throughout the globe. In this poster presentation, we provide an overview of the PM2.5 estimation techniques applied by current SAPM team members, as well as the strengths and limitations of each technique. These approaches include spaceborne lidar (Cloud-Aerosol Lidar with Orthogonal Polarization) only, combined spaceborne lidar (Cloud Aerosol Transport System) and a model (Goddard Earth Observing System), and using aerosol optical depth (AOD) from a spaceborne passive remote sensor (Moderate Resolution Imaging Spectroradiometer) to explore city trends in AOD and relate those to city trends in PM2.5. Also in this poster presentation, we highlight results of our SAPM study of India, a country characterized by high levels of PM2.5 concentrations. We show the temporal and spatial variability of PM2.5 over India derived using various approaches and validation with ground-based in situ PM2.5 observations. The SAPM Topic group actively seeks additional collaborators, including those working with in situ aerosol measurements, and is interested in aerosol datasets to improve and/or validate the PM2.5 estimates.

Travis D Toth↗
DOE OSTI2023

In-silico quantification of intersubject variability on aerosol deposition in the oral airway

The extrathoracic oral airway I s not only a major mechanical barrier for pharmaceutical aerosols to reach the lung but also a major source of variability in lung deposition. Using computational fluid dynamics, deposition of 1-30 µm particles was predicted in 11 CT-based models of the oral airways of adults (7 healthy subjects and 4 patients with chronic obstructive pulmonary disease). Simulations were performed for mouth breathing during both inspiration and expiration at two steady-state flow rates representative of resting/light activity (18 L/min) and of that typically used during aerosol inhalation from a dry powder inhaler (45 L/min). For each subject, oral deposition increased with increasing particle size and flow rate. When averaged over all subjects, there was no significant difference in oral deposition efficiency between inspiration and expiration, unlike subregional deposition that show significantly different patterns between the two breathing phases. Consistent with previous in-vitro inspiratory studies, our data showed a large intersubject variability in oral deposition. These results highlight the need for incorporating morphological variation of the upper airway in predictive models of aerosol deposition for accurate predictions of particle dosimetry in the intrathoracic region of the lung.

Computational fluid dynamics (CFD), Inertial impac↗
NASA NTRS1993

Applications of active adaptive noise control to jet engines

During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

Shoureshi, Rahmat↗
NASA NTRS1994

Active thermal isolation for temperature responsive sensors

The detection of flow transition between laminar and turbulent flow and of shear stress or skin friction of airfoils is important in basic research for validation of airfoil theory and design. These values are conventionally measured using hot film nickel sensors deposited on a polyimide substrate. The substrate electrically insulates the sensor and underlying airfoil but is prevented from thermally isolating the sensor by thickness constraints necessary to avoid flow contamination. Proposed heating of the model surface is difficult to control, requires significant energy expenditures, and may alter the basic flow state of the airfoil. A temperature responsive sensor is located in the airflow over the specified surface of a body and is maintained at a constant temperature. An active thermal isolator is located between this temperature responsive sensor and the specific surface of the body. The total thickness of the isolator and sensor avoid any contamination of the flow. The temperature of this isolator is controlled to reduce conductive heat flow from the temperature responsive sensor to the body. This temperature control includes (1) operating the isolator at the same temperature as the constant temperature of the sensor; and (2) establishing a fixed boundary temperature which is either less than or equal to, or slightly greater than the sensor constant temperature. The present invention accordingly thermally isolates a temperature responsive sensor in an energy efficient, controllable manner while avoiding any contamination of the flow.

Martinson, Scott D.↗
DOE OSTI2025

Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP

In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
DOE OSTI2025

Chemo‐Mechanical Coupling in Hydrogels: Dynamics in the Diffusion‐Limited Regime

Hydrogels are characterized by substantial volume changes in response to external stimuli, making them promising candidates for developing smart materials with enhanced adaptability and responsiveness. By integrating chemical reactions, hydrogels acquire dynamic and tunable responsiveness to external stimuli through chemo‐mechanical coupling, expanding their potential in emerging applications. However, capturing their transient behavior remains challenging due to the complex interplay of chemical reactions, solvent transport, and polymer network deformation. Classical theories capture equilibrium swelling but fail to describe time‐dependent phenomena. To address this, a time‐dependent continuum model is developed that explicitly couples these processes. Volume phase transition in hydrogels with homogeneous chemical reactions is investigated, then the effects of reaction kinetics on these transitions are analyzed. The coupling of these mechanisms is further explored through a study of transient mechanical instabilities. To illustrate the impact of distinct reaction and diffusion timescales, a photo‐active gripper is studied for robotic applications. Finally, a photo‐active microswimmer that exhibits non‐reciprocal motion is proposed to highlight the solvent diffusion for locomotion at the micro‐ and nano‐ scales. The work establishes that transient dynamics of chemo‐mechanical hydrogels generate functions not accessible by steady state models and provides a predictive platform for designing adaptive materials in emerging applications.

chemo-mechanical coupling↗
DOE OSTI2023

Primer terminal ribonucleotide alters the active site dynamics of DNA polymerase η and reduces DNA synthesis fidelity

DNA polymerases catalyze DNA synthesis with high efficiency, which is essential for all life. Extensive kinetic and structural efforts have been executed in exploring mechanisms of DNA polymerases, surrounding their kinetic pathway, catalytic mechanisms, and factors that dictate polymerase fidelity. Recent time-resolved crystallography studies on DNA polymerase η (Pol η) and β have revealed essential transient events during the DNA synthesis reaction, such as mechanisms of primer deprotonation, separated roles of the three metal ions, and conformational changes that disfavor incorporation of the incorrect substrate. DNA-embedded ribonucleotides (rNs) are the most common lesion on DNA and a major threat to genome integrity. While kinetics of rN incorporation has been explored and structural studies have revealed that DNA polymerases have a steric gate that destabilizes ribonucleotide triphosphate binding, the mechanism of extension upon rN addition remains poorly characterized. Using steady-state kinetics, static and time-resolved X-ray crystallography with Pol η as a model system, we showed that the extra hydroxyl group on the primer terminus does alter the dynamics of the polymerase active site as well as the catalysis and fidelity of DNA synthesis. During rN extension, Pol η error incorporation efficiency increases significantly across different sequence contexts. Finally, our systematic structural studies suggest that the rN at the primer end improves primer alignment and reduces barriers in C2'-endo to C3'-endo sugar conformational change. Overall, our work provides further mechanistic insights into the effects of rN incorporation on DNA synthesis.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

The Interior and Orbital Evolution of Charon as Preserved in Its Geologic Record

Pluto and its largest satellite, Charon, currently orbit in a mutually synchronous state; both bodies continuously show the same face to one another. This orbital configuration is a natural end-state for bodies that have undergone tidal dissipation. In order to achieve this state, both bodies would have experienced tidal heating and stress, with the extent of tidal activity controlled by the orbital evolution of Pluto and Charon and by the interior structure and rheology of each body. As the secondary, Charon would have experienced a larger tidal response than Pluto, which may have manifested as observable tectonism. Unfortunately, there are few constraints on the interiors of Pluto and Charon. In addition, the pathway by which Charon came to occupy its present orbital state is uncertain. If Charon's orbit experienced a high-eccentricity phase, as suggested by some orbital evolution models, tidal effects would have likely been more significant. Therefore, we determine the conditions under which Charon could have experienced tidally-driven geologic activity and the extent to which upcoming New Horizons spacecraft observations could be used to constrain Charon's internal structure and orbital evolution. Using plausible interior structure models that include an ocean layer, we find that tidally-driven tensile fractures would likely have formed on Charon if its eccentricity were on the order of 0.01, especially if Charon were orbiting closer to Pluto than at present. Such fractures could display a variety of azimuths near the equator and near the poles, with the range of azimuths in a given region dependent on longitude; east-west-trending fractures should dominate at mid-latitudes. The fracture patterns we predict indicate that Charon's surface geology could provide constraints on the thickness and viscosity of Charon's ice shell at the time of fracture formation.

Tectonics↗
NASA NTRS2002

A Systems Model for Power Technology Assessment

A computer model is under continuing development at NASA Glenn Research Center that enables first-order assessments of space power technology. The model, an evolution of NASA Glenn's Array Design Assessment Model (ADAM), is an Excel workbook that consists of numerous spreadsheets containing power technology performance data and sizing algorithms. Underlying the model is a number of databases that contain default values for various power generation, energy storage and power management and distribution component parameters. These databases are actively maintained by a team of systems analysts so that they contain state-of-art data as well as the most recent technology performance projections. Sizing of the power subsystems can be accomplished either by using an assumed mass specific power (W/kg) or energy (Wh/kg) or by a bottoms-up calculation that accounts for individual component performance and masses. The power generation, energy storage and power management and distribution subsystems are sized for given mission requirements for a baseline case and up to three alternatives. This allows four different power systems to be sized and compared using consistent assumptions and sizing algorithms. The component sizing models contained in the workbook are modular so that they can be easily maintained and updated. All significant input values have default values loaded from the databases that can be over-written by the user. The default data and sizing algorithms for each of the power subsystems are described in some detail. The user interface and workbook navigational features are also discussed. Finally, an example study case that illustrates the model's capability is presented.

Hoffman, David J.↗
DOE OSTI2024

Molecular-level insights into CO 2 activation on Ni(111) from in situ infrared spectroscopy

The activation of CO 2 on nickel surfaces is the first step of various CO 2 conversion processes. Consequently, understanding the surface intermediates formed during this step and their adsorption sites is crucial for elucidating reaction mechanisms. In this study, we employ in situ infrared spectroscopy to investigate the interaction of 1 mbar CO 2 with a model Ni(111) catalyst between 25°C and 300°C. Under these conditions, CO 2 is activated via a direct dissociation into CO and atomic oxygen, while the oxidation state of the Ni(111) surface is primarily determined by residual H 2 and O 2 . The high surface coverage of CO and oxygen at ambient CO 2 pressure induces a competitive adsorption mechanism on the energetically favored hollow sites. This mechanism leads to a temperature-dependent distribution of CO between top and hollow sites, potentially explaining the effect of reaction conditions on the adsorption site of CO intermediates in CO 2 conversion reactions.

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

Quantum annealing-assisted lattice optimization

High Entropy Alloys (HEAs) have drawn great interest due to their exceptional properties compared to conventional materials. The configuration of HEA system is considered a key to their superior properties, but exhausting all possible configurations of atom coordinates and species to find the ground energy state is extremely challenging. In this work, we proposed a quantum annealing-assisted lattice optimization (QALO) algorithm, which is an active learning framework that integrates the Field-aware Factorization Machine (FFM) as the surrogate model for lattice energy prediction, Quantum Annealing (QA) as an optimizer and Machine Learning Potential (MLP) for ground truth energy calculation. By applying our algorithm to the NbMoTaW alloy, we reproduced the Nb depletion and W enrichment observed in bulk HEA. We found our optimized HEAs to have superior mechanical properties compared to the randomly generated alloy configurations. Our algorithm highlights the potential of quantum computing in materials design and discovery, laying a foundation for further exploring and optimizing structure-property relationships.

36 MATERIALS SCIENCE↗
NASA NTRS1980

A direct method for synthesizing low-order optimal feedback control laws with application to flutter suppression

A direct method of synthesizing a low-order optimal feedback control law for a high order system is presented. A nonlinear programming algorithm is employed to search for the control law design variables that minimize a performance index defined by a weighted sum of mean square steady state responses and control inputs. The controller is shown to be equivalent to a partial state estimator. The method is applied to the problem of active flutter suppression. Numerical results are presented for a 20th order system representing an aeroelastic wind-tunnel wing model. Low-order controllers (fourth and sixth order) are compared with a full order (20th order) optimal controller and found to provide near optimal performance with adequate stability margins.

Mukhopadhyay, V.↗
NASA NTRS1983

Magnetospheric and interplanetary physics 1979-1982

Major trends in the study of magnetospheric and interplanetary physics during the 1979-1982 period are surveyed. Topics discussed include the exploration of the Saturnian and Jovian magnetospheres by Voyagers 1 and 2, the behavior of different ions in the earth magnetosphere, auroral kilometric radiation, computer modeling of global magnetospheric MHD flow, the magnetic substorm, the quiet state, the earth's bow shock, the heliospheric current sheet, and new techniques such as electron beam experiments, 'active' injection experiments, auroral radars, and observations of the earth's distant magnetic tail. The future of this area of research is seen in the combination of data from different spacecraft and ground observations in a single correlated data set, and in the consolidation of past gains by analysis of the large data backlog, while a small number of new missions goes forward.

Stern, D. P.↗
NASA NTRS2013

Cirrus Cloud Seeding has Potential to Cool Climate

Cirrus clouds, thin ice clouds in the upper troposphere, have a net warming effect on Earth s climate. Consequently, a reduction in cirrus cloud amount or optical thickness would cool the climate. Recent research indicates that by seeding cirrus clouds with particles that promote ice nucleation, their lifetimes and coverage could be reduced. We have tested this hypothesis in a global climate model with a state-of-the-art representation of cirrus clouds and find that cirrus cloud seeding has the potential to cancel the entire warming caused by human activity from pre-industrial times to present day. However, the desired effect is only obtained for seeding particle concentrations that lie within an optimal range. With lower than optimal particle concentrations, a seeding exercise would have no effect. Moreover, a higher than optimal concentration results in an over-seeding that could have the deleterious effect of prolonging cirrus lifetime and contributing to global warming.

Storelvmo, T.↗