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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Thermophysical Property Measurement and Materials Research in the NASA/MSFC Electrostatic Levitator

Containerless processing is an important tool for materials research. The freedom from a crucible allows processing of liquid materials in a metastable undercooled state, as well as allowing processing of high temperature and highly reactive melts. Electrostatic levitation (ESL) is a containerless method which provides a number of unique advantages, including the decoupling of positioning force from sample heating, the ability to operate in ultra-high vacuum or at moderate gas pressure (approx. 3 atm), and the ability to process non-conducting materials. ESL also has the potential to reduce internal flow velocities below those possible with electromagnetic, acoustic, or aero-acoustic techniques. In electrostatic levitation, the acceleration of gravity (or residual acceleration in reduced gravity) is opposed by the action of an applied electric field on a charged sample. Microgravity allows electrostatic levitation to work even more effectively. In microgravity, ESL can position larger samples than is possible on the ground, or it can position samples which maintain their charge poorly. Microgravity also reduces the effects of buoyant convection and sedimentation. The ESL facility at NASA's Marshall Space Flight Center (MSFC) is in use for thermophysical property measurements and materials research by a number of different internal and external investigators. The methods for obtaining access to the facility, as well as a summary of current capabilities and some future directions will be discussed.

Rogers, J. R.↗
NASA NTRS2009

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Balaban, Edward↗
NASA NTRS2013

Mitigation of Autoignition Due to Premixing in a Hypervelocity Flow Using Active Wall Cooling

Preinjection of fuel on the forebody of an airbreathing vehicle is a proposed method to gain access to hypervelocity flight Mach numbers. However, this creates the possibility of autoignition either near the wall or in the core of the flow, thereby consuming fuel prematurely as well as increasing the amount of pressure drag on the vehicle. The computational fluid dynamics code VULCAN was used to conduct three dimensional simulations of the reacting flow in the vicinity of hydrogen injectors on a flat plate at conditions relevant to a Mach 12 notional flight vehicle forebody to determine the location where autoignition occurs. Active wall cooling strategies were formulated and simulated in response to regions of autoignition. It was found that tangential film cooling using hydrogen or helium were both able to nearly or completely eliminate wall autoignition in the flow domain of interest.

Axdahl, Erik↗
NASA NTRS2019

Satellite Sounder Products in NASA GES DISC & Services Supporting Their Applications

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at the Jet Propulsion Laboratory (JPL), provides processing, archiving, and distribution services for remotely-sensed data acquired by satellite sounders. Supported data sets begin chronologically with the legacy TIROS Operational Vertical Sounder (TOVS) Pathfinder, continue to the Atmospheric Infrared Sounder (AIRS), a modern hyperspectral sounder onboard the Aqua satellite, and are followed by data from the subsequent Suomi-National Polar-orbiting Partnership Cross-track Infrared Sounder (CrIS) mission and the Joint Polar Satellite System (JPSS) series CrIS missions. These satellite sounders provide long-term global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. Applications of sounder data products cover a broad range of fields, including meteorology climatology, hydrology, and air quality. The GES DISC has developed many services to assist users, including simplified and efficient methods for searching, accessing, downloading, and analytically exploring these satellite sounder data products. We have also developed the Giovanni system, a broadly used Web-based application, which provides a simple and intuitive way to visualize, analyze, and access Earth science remote sensing data. In this presentation, we will introduce the standard and near-real time sounder data products, and demonstrate our services through some use cases. Highlights of our service capabilities include data subset, vertical profile plot, inter-comparison, multi-year monthly/seasonal mean, interannual monthly/seasonal time series, and anomaly analysis.

Ding, Feng↗
DOE OSTI2023

Deep learning methods for event verification and image re-purposing detection

Systems and methods herein describe accessing an image, generating a resized image, generating an image feature vector by applying an image classification neural network to the resized image, generating analysis of the image by processing the image feature vector using a machine-learning classifier trained to analyze the image feature vector, and based on the analysis, determining an event that is attributed to the image.

Nataraj, Lakshmanan↗
DOE OSTI2020

Rapid Memory Footprint Access Diagnostics

Footprint and reuse distance measure temporal locality and therefore do not capture the significance of access patterns (spacial locality). A strided access pattern has the largest possible footprint but usually has the best performance. To highlight exposed memory latency, we separate footprint into strided (prefetchable) and irregular (non-prefetchable) access components and calculate the growth rate of each. To rapidly compute these footprint access diagnostics, we present two methods, whole-program and precise. Current footprint analyses can cause 200× or more slowdown with realistic inputs and are therefore impractical. Our whole-program method reduces the overhead to 10% by computing upper bounds, but still yields inter-procedural insight through a call path profile. Our precise method uses additional static analysis and profiling to refine the upper bounds for intra-procedural loop nests. We evaluate our approaches using benchmarks that vary access patterns (strided \vs unpredictable), sparsity (all words in a cache line \vs some), and reuse (varying and repeated accesses per element). Notably, for loop nests with unpredictable accesses, the precise method's accuracy is within 10% of ideal. The whole-program method has sufficient accuracy to diagnose bottlenecks.

data locality, memory footprint, footprint access ↗
NASA NTRS2015

Scheduled Peripheral Component Interconnect Arbiter

Systems and methods are described for arbitrating access of a communication bus. In one embodiment, a method includes performing steps on one or more processors. The steps include: receiving an access request from a device of the communication bus; evaluating a bus schedule to determine an importance of the device based on the access request; and selectively granting access of the communication bus to the device based on the importance of the device.

Nixon, Scott Alan↗
NASA NTRS2004

Realtime Knowledge Management (RKM): From an International Space Station (ISS) Point of View

We are developing automated methods to provide realtime access to spacecraft domain knowledge relevant a spacecraft's current operational state. The method is based upon analyzing state-transition signatures in the telemetry stream. A key insight is that documentation relevant to a specific failure mode or operational state is related to the structure and function of spacecraft systems. This means that diagnostic dependency and state models can provide a roadmap for effective documentation navigation and presentation. Diagnostic models consume the telemetry and derive a high-level state description of the spacecraft. Each potential spacecraft state description is matched against the predictions of models that were developed from information found in the pages and sections in the relevant International Space Station (ISS) documentation and reference materials. By annotating each model fragment with the domain knowledge sources from which it was derived we can develop a system that automatically selects those documents representing the domain knowledge encapsulated by the models that compute the current spacecraft state. In this manner, when the spacecraft state changes, the relevant documentation context and presentation will also change.

Robinson, Peter I.↗
DOE OSTI2021

Enhanced Reactivity of Accessible Protons in Sodalite Cages of Faujasite Zeolite

Abstract Faujasite (FAU) zeolites (with Si/Al ratio of ca. 1.7) undergo mild dealumination at moderate ion exchange conditions (0.01 to 0.6 M of NH 4 NO 3 solutions) resulting in protons circumscribed by sodalite cages becoming accessible for reaction without conspicuous changes to bulk crystallinity. The ratio of protons in sodalite cages (H SOD ) to supercages (H SUP ) can be systematically manipulated from 0 to ca. 1 by adjusting ammonium concentrations used in ion exchange. The fraction of accessible protons in the sodalite cages is assessed by virtue of infrared spectra for H‐D exchange of deuterated propane based on the band area ratio of OD 2620 /OD 2680 (OD SOD /OD SUP ). Protons in sodalite cages (H SOD ) show higher rate constants of propane dehydrogenation ( k D ) and cracking ( k C ) than protons in supercages (H SUP ) plausibly due to confinement effects being more prominent in smaller voids. Rate constants of dehydrogenation and cracking including k D / k C ratios are also augmented as the fraction of accessible protons in the sodalite cages is enhanced. These effects of accessibility and reactivity of protons in sodalite cages hitherto inconspicuous are revealed herein via methods that systematically increase accessibility of cations located in sodalite cages.

Li, Xinyu↗
DOE OSTI2021

Enhanced Reactivity of Accessible Protons in Sodalite Cages of Faujasite Zeolite

We report Faujasite (FAU) zeolites (with Si/Al ratio of ca. 1.7) undergo mild dealumination at moderate ion exchange conditions (0.01 to 0.6 M of NH 4 NO 3 solutions) resulting in protons circumscribed by sodalite cages becoming accessible for reaction without conspicuous changes to bulk crystallinity. The ratio of protons in sodalite cages (H SOD ) to supercages (H SUP ) can be systematically manipulated from 0 to ca. 1 by adjusting ammonium concentrations used in ion exchange. The fraction of accessible protons in the sodalite cages is assessed by virtue of infrared spectra for H-D exchange of deuterated propane based on the band area ratio of OD 2620 /OD 2680 (OD SOD /OD SUP ). Protons in sodalite cages (H- SOD ) show higher rate constants of propane dehydrogenation (k D ) and cracking (k C ) than protons in supercages (H SUP ) plausibly due to confinement effects being more prominent in smaller voids. Rate constants of dehydrogenation and cracking including k D /k C ratios are also augmented as the fraction of accessible protons in the sodalite cages is enhanced. These effects of accessibility and reactivity of protons in sodalite cages hitherto inconspicuous are revealed herein via methods that systematically increase accessibility of cations located in sodalite cages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Investigating Deposition Sequence During Synthesis of Pd/Al2O3 Catalysts Modified with Organic Monolayers

Modification of supported metal catalysts with self-assembled monolayers (SAMs) has been shown to improve selectivity and turnover frequencies (TOFs) for many catalytic reactions. However, these benefits are often accompanied by a decrease in overall mass activity due to partial blocking of active sites by the monolayers. Therefore, a potential method for increasing site accessibility is to deposit the active metal (e.g., Pd) after deposition of a SAM modifier on the support material. In this work, Pd/Al2O3 catalysts were synthesized using both a conventional, "metal-first" sequence in which the phosphonic acid (PA) SAM was deposited on Pd/Al2O3 and a "SAM-first" technique in which the ligands were deposited onto the support prior to deposition of the metal. Although metal-first catalysts showed a significant increase in TOF during benzyl alcohol HDO, they exhibited only a modest increase in overall mass activity due to a decrease in the number of active sites. Meanwhile, SAM-first catalysts showed similar improvements in TOF and toluene selectivity but exhibited significantly improved HDO rates compared to metal-first catalysts. The rate increase was attributed to reduced site blocking as evidenced by CO chemisorption measurements. Additionally, analysis of catalysts having high Pd loadings using transmission electron microscopy (TEM) showed that SAM-first catalysts generally resulted in lower average particle sizes than traditionally modified and unmodified catalysts, suggesting that precoating the support surface with PAs changes the way that Pd is deposited during incipient wetness, leading here to improved activity.

catalytic reactions↗
DOE OSTI2021

Risk Informed Timelines (RIT) v.1.0

Risk Informed Timelines (RIT) is a more modern and holistic method for understanding how access delay timelines are developed and utilized in physical security system evaluations. The software utilizes Bayesian methods to combine subject matter expert judgement and small performance test datasets in a consistent and defensible way. It allows a more holistic view of delay performance that provides distributions of task times and task success probabilities to account for tasks that, if failed, would result in failure of the attack. The RIT methodology is meant to enable security risk managers to begin the transition into more comprehensive delay timeline analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8294 O

Noel, ToddG.↗
DOE OSTI2024

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. Ab initio methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations toward the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1979

Cost comparison of competing local distribution systems for communication satellite traffic

The boundaries of market areas which favor various means for distributing communications satellite traffic are considered. The distribution methods considered are: control Earth station with cable access, rooftop Earth stations, Earth station with radio access, and various combinations of these methods. The least cost system for a hypothetical region described by number of users and the average cable access mileage is discussed. The region is characterized by a function which expresses the distribution of users. The results indicate that the least cost distribution is central Earth station with cable access for medium to high density areas of a region combined with rooftop Earth stations or (for higher volumes) radio access for remote users.

Dopfel, F. E.↗
DOE OSTI2024

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗
DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗