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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology): Enabling Technology for Planetary Atmospheric Science Probes

Aerosols –clouds, hazes, and dusts –are a key part of planetary mass and energy balance, but difficult to study remotely. Current technology limits in situ measurements to once-in-a-lifetime flagship missions, which is not enough to characterize such highly dynamic systems. AERACEPT (AErosol Rapid Analysis Combined Entry Probe/sonde Technology) is an early-stage technology allowing asingle aeroshell body toact as both anentry vehicle and aerosol-samplingpassivedescent sonde, using the aeroshell’sown velocityto drive aerosol capture and separationthrough a series of embedded inlets.It takes advantage ofrecently developed thermal protection materials (3D-CC and 3MDCP)in combination withheritage aerosol sampling technologies fromboth planetary and airborne science (high-speed inlets and particle separation). By eliminating the need for heat shield separation, deployable parachutes, ordescent control, AERACEPT reducesthe mass, volume, and complexity ofplanetary aerosol sampling. Verifying AERACEPT’s performance involves modeling interdependencies between the size and geometry of the sampling inlets, the material response of the hypersonic phase of entry, the thermal conditions throughout the probe’s descent, the subsonic flow and particle sampling efficiency, the needed amount of sample, andthe cadence at which the sample can be analyzed. AERACEPT’s current predictions, using the Nephele Venus cloud mission concept (sampling between 63km to 39km, all subsonic) indicates AERACEPT can obtain >20 μL of particle material (roughly 10x the limit of detection) from droplets larger than 0.2 μm, with sample heating limited to <15 K above ambient. Validation testing for the thermal material response model has recently been performed at the UIUC Plasmatron facility, and for the flow and particle capture models is planned for this fall at the Ames Fluid Mechanics Laboratory.

AERACEPT↗
DOE OSTI2024

A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)

Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such machine learning tools can be difficult due to the challenges in procuring sufficiently large, high-quality training datasets from experiments. In this work, we introduce Construction Zone, a Python package for rapid generation of complex nanoscale atomic structures which enables fast, systematic sampling of realistic nanomaterial structures and can be used as a random structure generator for large, diverse synthetic datasets. Using Construction Zone, we develop an end-to-end machine learning workflow for training neural network models to analyze experimental atomic resolution HRTEM images on the task of nanoparticle image segmentation purely with simulated databases. Further, we study the data curation process to understand how various aspects of the curated simulated data—including simulation fidelity, the distribution of atomic structures, and the distribution of imaging conditions—affect model performance across three benchmark experimental HRTEM image datasets. Using our workflow, we are able to achieve state-of-the-art segmentation performance on these experimental benchmarks and, further, we discuss robust strategies for consistently achieving high performance with machine learning in experimental settings using purely synthetic data. Construction Zone and its documentation are available at https://github.com/lerandc/construction_zone.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Influence of Ga doping on magnetic properties, magnetocaloric effect, and electronic structure of pseudobinary GdZn 1 - x Ga x ( x = 0 - 0.1 )

Here, we explore the impact of introducing IIIA-group element Ga in place of IIB-group element Zn in binary intermetallic GdZn on its magnetic and magnetocaloric properties, as well as explicate the modified electronic band structure of the compound. The magnetic transition temperature of the compound decreases with the increase of Ga concentration in GdZn 1-x ⁢Ga x ⁢(x = 0–0.1) while the crystal structure (CsCl prototype) and lattice parameters remain unchanged. Our detailed analysis of magnetization and magnetocaloric data conclusively proves that long-ranged magnetic ordering exists in the sample, despite the magnetic interaction considerably weakening with the increase of Ga. The experimental data are rationalized using both a theoretical machine-learning model and first-principle density functional theory. The electronic band structure of GdZn is manifested with some unusual complex features which gradually diminish with Ga doping and the conventional sinusoidal feature of Ruderman-Kittel-Kasuya-Yosida-type interactions also disappears. A mean-field theory model is developed and can successfully describe the overall magnetocaloric behavior of the GdZn 1-x⁢ Ga x series of samples.

36 MATERIALS SCIENCE↗
DOE OSTI2023

BuildStockQuery [SWR-23-58]

BuildStockQuery is a python library designed to simplify and streamline the process of querying massive, terabyte-scale datasets generated by ResStock(TM). ResStock (SWR-19-15) is a U.S. DOE-supported, NREL-built, national residential building energy stock model that enables a new approach to large-scale residential energy analysis across the U.S. by combining large public and private data sources, statistical sampling, detailed sub-hourly building simulations, and high-performance computing. BuildStockQuery offers an intuitive Object-Oriented Programming (OOP) interface to the ResStock output dataset allowing users to easily perform common queries and receive results in familiar pandas DataFrame format, abstracting away the need for complex SQL query. By initializing a query object with the pertinent Athena database and table names, users can easily query for various kinds of insights, for example, timeseries electricity for an end use for a given state grouped by building types.

Adhikari, Rajendra↗
NASA NTRSDate not supplied

Development of the Thermal Interface Between the Dragonfly Mass Spectrometer and the DrACO Sample Delivery Carousel

Icy celestial bodies are an exciting new frontier for surface exploration and in-situ sampling and analysis. These destinations are inherently cryogenic in nature, and each body presents unique challenges related to thermal design. The Dragonfly mission to Titan is one such example. One of the most important requirements of a sampling system is to preserve the integrity of the surface material. The interface between the Dragonfly Mass Spectrometer (DraMS) and the Drill for Acquisition of Complex Organics (DrACO) is complicated by several competing requirements. Development of this interface has required the use of new enabling technologies such as 3D printing to achieve a successful design. This overview of the DraMS Cryogenic subsystem will show how the design meets all the requirements of the interface and preserves integrity of Titan surface samples.

Peter W. Barfknecht↗
NASA NTRSDate not supplied

Design and Analysis of Convolutional Neural Network for RF Signal Modulation Classification for In-Orbit Deployment

To effectively transmit data to and from satellites requires a complex and robust RF communication system. Commonly, several different types of signal modulations may be required to maximize satellite efficiency depending on a variety of unexpected channel impairments. We propose a neural network algorithm capable of learning these RF signal modulations using a supervised learning technique designed for low power, high-efficiency in-orbit deployment. The work presented demonstrates a convolutional neural network (CNN) capable of learning and recognizing a set of modulation schemes commonly used to transmit RF information. We are capable of recognizing the modulation scheme from the I and Q data channels directly, with no preprocessing or data conversion required other than breaking the incoming signal into a set of uniform normalized samples. We perform a network design and size analysis, showing that reasonably high accuracy can be obtained using networks with a relatively low number of trainable parameters. Given that a user of a system such as this may wish to receive a signal using a modulation scheme that the network has not previously learned, we demonstrate that transfer learning can learn new modulation schemes by retraining only the fully connected layers in the CNN. Thus, this type of network would excel in outer space deployment using high-efficiency transfer learning hardware. Modulation recognition can be performed through rapid feedforward computation, and the CNN training process is significantly simplified when learning new modulations is required.

CNN↗
DOE OSTI2020

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Advancing Elemental and Isotopic Analysis of Uranium Mineral Inclusions: Rapid Screening via Laser-Induced Breakdown Spectroscopy and High-Resolution Laser Ablation-ICP-MS Mapping

The work presented herein employs two laser-based analytical techniques (laser-induced breakdown spectroscopy (LIBS) and laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS)) to spatially determine the elemental and isotopic composition of uranium bearing minerals. Uniquely, this work leverages the high-speed applicability of LIBS to “screen” the sample(s) for their elemental constituents. After determining the location of the uranium inclusions (via LIBS), high-resolution LA-ICP-MS was employed to further characterize the inclusions. The high-resolution (sub-µm) capabilities of LA-ICP-MS were able to extract important information from the uranium minerals including discerning its chemical form (e.g., finchite from carnotite, Sr- and K-bearing uranyl vanadates, respectively) as well as their 235 U/ 238 U isotopic composition. This approach, LIBS followed by LA-ICP-MS, significantly reduces the analysis time (~95 %) in comparison to employing a LA-ICP-MS only approach. Furthermore, this work presented a novel approach to analyzing inclusions via a particle/inclusion analysis tool which is commercially available within the iolite 4 software. This tool allowed for a more accurate characterization of the isotopic distribution of the inclusions, as well as allowing for rapid sizing of the inclusions. Finally, this analytical approach could readily be applied to other sample types in which the target species (e.g., µm-sized inclusions) are embedded in complex matrices (e.g., cm-sized samples).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Microbiome characterization by high-throughput transfer RNA sequencing and modification analysis

Advances in high-throughput sequencing have facilitated remarkable insights into the diversity and functioning of naturally occurring microbes; however, current sequencing strategies are insufficient to reveal physiological states of microbial communities associated with protein translation dynamics. Transfer RNAs (tRNAs) are core components of protein synthesis machinery, present in all living cells, and are phylogenetically tractable, which make them ideal targets to gain physiological insights into environmental microbes. Here we report a direct sequencing approach, tRNA-seq, and a software suite, tRNA-seq-tools, to recover sequences, abundance profiles, and post-transcriptional modifications of microbial tRNA transcripts. Our analysis of cecal samples using tRNA-seq distinguishes high-fat-and low-fat-fed mice in a comparable fashion to 16S ribosomal RNA gene amplicons, and reveals taxon- and diet-dependent variations in tRNA modifications. Our results provide taxon-specific in situ insights into the dynamics of tRNA gene expression and post-transcriptional modifications within complex environmental microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

A strategy for analysis of thermal decomposition of polymeric materials

Some analytical methods developed in flammability research are reviewed. Computerized analytical systems are used to separate, identify, and quantify components of complex mixtures of low-boiling volatiles, high-boiling volatiles, and solid residues resulting from pyrolysis, oxidative degradation, and flaming combustion processes. To demonstrate the procedure for determining a material's response to a thermal flux administered under dynamic conditions, the treatment of data is reported for samples of an aromatic polyamide fabric which were degraded under isothermal conditions of 550 C following a dynamic heating rate of 100 C/min from ambient to final temperature.

Einhorn, I. N.↗
NASA NTRS1985

Using a data base management system for modelling SSME test history data

The usefulness of a data base management system (DBMS) for modelling historical test data for the complete series of static test firings for the Space Shuttle Main Engine (SSME) was assessed. From an analysis of user data base query requirements, it became clear that a relational DMBS which included a relationally complete query language would permit a model satisfying the query requirements. Representative models and sample queries are discussed. A list of environment-particular evaluation criteria for the desired DBMS was constructed; these criteria include requirements in the areas of user-interface complexity, program independence, flexibility, modifiability, and output capability. The evaluation process included the construction of several prototype data bases for user assessement. The systems studied, representing the three major DBMS conceptual models, were: MIRADS, a hierarchical system; DMS-1100, a CODASYL-based network system; ORACLE, a relational system; and DATATRIEVE, a relational-type system.

Abernethy, K.↗
NASA NTRS1996

Wavelet Techniques Applied to Modeling Transitional/Turbulent Flows in Turbomachinery

Computer simulation is an essential part of the design and development of jet engines for the aeropropulsion industry. Engineers concerned with calculating the flow in jet engine components, such as compressors and turbines, need simple engineering models that accurately describe the complex flow of air and gases and that allow them to quickly estimate loads, losses, temperatures, and other design parameters. In this ongoing collaborative project, advanced wavelet analysis techniques are being used to gain insight into the complex flow phenomena. These insights, which cannot be achieved by commonly used methods, are being used to develop innovative new flow models and to improve existing ones. Wavelet techniques are very suitable for analyzing the complex turbulent and transitional flows pervasive in jet engines. These flows are characterized by intermittency and a multitude of scales. Wavelet analysis results in information about these scales and their locations. The distribution of scales is equivalent to the frequency spectrum provided by commonly used Fourier analysis techniques; however, no localization information is provided by Fourier analysis. In addition, wavelet techniques allow conditional sampling analyses of the individual scales, which is not possible by Fourier methods.

Source record↗
NASA NTRS2013

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗
NASA NTRSDate not supplied

Non-Targeted Direct Infusion Soluble Organic Analysis on a Tarda Meteorite Extract

The differences in chemistry, mineralogy, and structure of chondrites demonstrate thevariations in time/space of their forming regions in the solar nebula. In contrast, the variationof the organic reserves in the solar nebula is unclear. Furthermore, their subsequent evolutionof organic matter on the parent body is still under debate. In a previous study on Tagish Lake(C2 ungrouped) we showed that the primordial soluble organic matter (SOM) could bedistinguished from the parent body's secondary alteration threw mass distribution. This studywill show the Tarda meteorite SOM primordial distribution, using the model from ourprevious study. We discuss its organic reservoirs and secondary alteration effects. We alsocompare the character of the SOM with previously analysed Orgueil (CI). Sample and method: Tarda (fall, 2020) was classified as a C2 ungroup carbonaceouschondrite. Its bulk three oxygen isotope composition is distinct from other chondrite groupsbut similar to CI-chondrite-like and Yamato-type-like [1] values. We analysed themethanol/toluene extract using the high-resolution Orbitrap mass spectrometer at the Institutede Planétologie et d’Astrophysique Grenoble (IPAG) by directly injecting and ionizing theSOM and the solvent using the Heated Electrospray Ionization (HESI) source. After thespectra acquisition, the in-house developed post-processing data analysis tools, Attributor [2],was used. Preliminary Result: The SOM mass distribution of Tarda was well-fitted by the modelinterpreted as the primordial SOM distribution in Tagish lake. This common distributionpattern implies the presence of a common organic reservoir or SOM formation mechanism.Orgueil’s mass spectrum showed a more complex mass-distribution and seemed to be affectedby secondary processes. In contrast to the mass-distribution, SOM’s elemental abundance wasdistinct. The Tarda extract was enriched in S-bearing organic compounds which was incontrast to the Tagish Lake extract consisting of mostly CHNO elements. The presentationwill also discuss the application of our technique to Ryugu or Bennu samples. [1] Meteoriticalbulletin database [2] Orthous-Daunay, F. R. et al. (2019) Geochemical Journal, 53(1), 21-32

J Isa↗
NASA NTRS1995

Performance modeling & simulation of complex systems (A systems engineering design & analysis approach)

Modeling of the Multi-mission Image Processing System (MIPS) will be described as an example of the use of a modeling tool to design a distributed system that supports multiple application scenarios. This paper examines: (a) modeling tool selection, capabilities, and operation (namely NETWORK 2.5 by CACl), (b) pointers for building or constructing a model and how the MIPS model was developed, (c) the importance of benchmarking or testing the performance of equipment/subsystems being considered for incorporation the design/architecture, (d) the essential step of model validation and/or calibration using the benchmark results, (e) sample simulation results from the MIPS model, and (f) how modeling and simulation analysis affected the MIPS design process by having a supportive and informative impact.

Hall, Laverne↗
NASA NTRS1988

Luminosity excesses in low-mass young stellar objects - A statistical study

This paper presents a statistical study in which the observed total luminosity is compared quantitatively with an estimate of the stellar luminosity for a sample of 59 low-mass young stellar objects (YSOs) in the Taurus-Auriga complex. In 13 of the analyzed YSOs, luminosity excesses greater than 0.20 are observed together with greater than 0.6 IR excesses, which typically contribute the bulk of the observed excess luminosity and are characterized by spectral energy distributions which are flat or rise toward long wavelengths. The analysis suggests that YSOs showing the largest luminosity excesses typically power optical jets and/or molecular outflows or have strong winds, as evidenced by the presence of O I emission, indicating a possible correlation between accretion and mass-outflow properties.

Strom, Karen M.↗
NASA NTRS2026

Impact Testing of 410 Stainless Steel for Material Impact Model Development

A project is underway to develop a consistent set of material properties, impact test data, and failure analysis for a variety of metallic aircraft materials that can be used to develop improved impact failure and deformation models. This project is jointly funded by the NASA Glenn Research Center and the Federal Aviation Administration William J. Hughes Technical Center. Particular features of this set of data are that all material property and impact test data are obtained using traceable material, the test methods and procedures are extensively documented, and all the raw data are available. Four parallel efforts are currently underway: measurement of material deformation and failure response over a wide range of strain rates and temperatures, failure analysis of material property specimens and impact test articles, development of improved numerical modeling techniques for deformation and failure, and impact testing of flat panels and substructures for model validation. This report describes impact testing performed on 410 stainless steel sheet and plate samples of different thicknesses with two different types of projectiles, one a regular cylinder and one with a more complex geometry incorporating features representative of a jet engine fan blade. Data from this testing will be used in validating material models developed under this program. The material tests and the material models developed in this program will be published in separate reports.

410 Stainless Steel↗
NASA NTRS2026

Radiation-Conditioned Ti–hBN Coatings for Space Mechanisms: Bridging Tribology and Irradiation Effects from Laboratory to Low-Earth Orbit

The longevity of tribological components in extraterrestrial environments is challenged by abrasive regolith, extreme temperatures, and ionizing radiation. This study evaluates the performance of vacuum plasma sprayed (VPS) Ti-2vol.% hexagonal boron nitride (hBN) coatings applied to joint mechanisms such as rod and slot, ball and socket, and hinge assemblies, fabricated from Al6061 and Ti6Al4V for planetary structures. Coated and uncoated samples were tested under vacuum with lunar regolith simulant (JSC-1A), followed by environmental exposures including electron radiation and thermal cycling. Results show that coated samples consistently outperformed uncoated counterparts across all configurations. Wear depth in coated components was reduced by over 80%, as confirmed by 3D profilometry and surface imaging. SEM analysis revealed severe abrasion and localized plastic deformation in uncoated surfaces, while coated samples retained structural integrity due to synergy of hard protective phases formed during deposition and retained hBN providing solid lubrication in the sliding surface. Coated and exposed samples exhibited smoother actuation profiles and reduced friction, indicating a beneficial "conditioning" effect from environmental exposure. The coatings-maintained performance even on complex geometries with minimal delamination. These findings demonstrate the potential of VPS Ti-hBN coatings to extend the operational life of lunar mechanisms, bridging laboratory-scale tribology with flight-relevant mechanical applications.

tribology↗