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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Development of a Woven-Grid Quasi-Bipolar Battery

This report describes an analytical and experimental investigation of AeroVironment's Quasi-Bipolar battery concept. The modelling/battery design part of the study demonstrates that there is a trade-off between thermal and specified electrical performance. Even so, quasi-bipolar batteries can be designed, with ten times better thermal uniformity, that meet or exceed current state-of-the-art hybrid-electric vehicle battery pack performance, even using the same active materials. The thermal uniformity, power, and energy for these quasi-bipolar battery packs is projected to be very good. The experimental part of the investigation demonstrates the concept of the quasi-bipolar plate applied to a lead foil current collector wrapping around two sides of an inexpensive plastic film core. Approximately 50 quasi-biplate samples were fabricated using a hot laminating press. Hot lamination with "texture" between the plastic and lead shows some promise as a low cost method for fabricating the plates. Five of these plates were assembled into two cells plus one two-cell battery. Data from these test cells were compared with existing data for similar true bipolar batteries. The positive side of the plates exhibited corrosion where not protected by the active material.

Tokumaru, P.↗
NASA NTRS2005

Magnetoresistive Flux Focusing Eddy Current Flaw Detection

A giant magnetoresistive flux focusing eddy current device effectively detects deep flaws in thick multilayer conductive materials. The probe uses an excitation coil to induce eddy currents in conducting material perpendicularly oriented to the coil s longitudinal axis. A giant magnetoresistive (GMR) sensor, surrounded by the excitation coil, is used to detect generated fields. Between the excitation coil and GMR sensor is a highly permeable flux focusing lens which magnetically separates the GMR sensor and excitation coil and produces high flux density at the outer edge of the GMR sensor. The use of feedback inside the flux focusing lens enables complete cancellation of the leakage fields at the GMR sensor location and biasing of the GMR sensor to a location of high magnetic field sensitivity. In an alternate embodiment, a permanent magnet is positioned adjacent to the GMR sensor to accomplish the biasing. Experimental results have demonstrated identification of flaws up to 1 cm deep in aluminum alloy structures. To detect deep flaws about circular fasteners or inhomogeneities in thick multi-layer conductive materials, the device is mounted in a hand-held rotating probe assembly that is connected to a computer for system control, data acquisition, processing and storage.

Russell A Wincheski↗
NASA NTRS1996

NASA's SPICE System Models the Solar System

SPICE is NASA's multimission, multidiscipline information system for assembling, distributing, archiving, and accessing space science geometry and related data used by scientists and engineers for mission design and mission evaluation, detailed observation planning, mission operations, and science data analysis.

mission design↗
NASA NTRS2005

Magnetoresistive flux focusing eddy current flaw detection

A giant magnetoresistive flux focusing eddy current device effectively detects deep flaws in thick multilayer conductive materials. The probe uses an excitation coil to induce eddy currents in conducting material perpendicularly oriented to the coil's longitudinal axis. A giant magnetoresistive (GMR) sensor, surrounded by the excitation coil, is used to detect generated fields. Between the excitation coil and GMR sensor is a highly permeable flux focusing lens which magnetically separates the GMR sensor and excitation coil and produces high flux density at the outer edge of the GMR sensor. The use of feedback inside the flux focusing lens enables complete cancellation of the leakage fields at the GMR sensor location and biasing of the GMR sensor to a location of high magnetic field sensitivity. In an alternate embodiment, a permanent magnet is positioned adjacent to the GMR sensor to accomplish the biasing. Experimental results have demonstrated identification of flaws up to 1 cm deep in aluminum alloy structures. To detect deep flaws about circular fasteners or inhomogeneities in thick multilayer conductive materials, the device is mounted in a hand-held rotating probe assembly that is connected to a computer for system control, data acquisition, processing and storage.

Wincheski, Russell A.↗
NASA NTRS2006

LOX, GOX and Pressure Relief

Oxygen relief systems present a serious fire hazard risk with often severe consequences. This presentation offers a risk management solution strategy which encourages minimizing ignition hazards, maximizing best materials, and utilizing good practices. Additionally, the relief system should be designed for cleanability and ballistic flow. The use of the right metals, softgoods, and lubricants, along with the best assembly techniques, is stressed. Materials should also be tested if data is not available and a full hazard analysis should be conducted in an effort to minimize risk and harm.

McLeod, Ken↗
NASA NTRS2014

Mechanisms and Observations of Coronal Dimming for the 2010 August 7 Event

Coronal dimming of extreme ultraviolet (EUV) emission has the potential to be a useful forecaster of coronal mass ejections (CMEs). As emitting material leaves the corona, a temporary void is left behind which can be observed in spectral images and irradiance measurements. The velocity and mass of the CMEs should impact the character of those observations. However, other physical processes can confuse the observations. We describe these processes and the expected observational signature, with special emphasis placed on the differences. We then apply this understanding to a coronal dimming event with an associated CME that occurred on 2010 August 7. Data from the Solar Dynamics Observatory's (SDO) Atmospheric Imaging Assembly (AIA) and EUV Variability Experiment (EVE) are used for observations of the dimming, while the Solar and Heliospheric Observatory's (SoHO) Large Angle and Spectrometric Coronagraph (LASCO) and the Solar Terrestrial Relations Observatory's (STEREO) COR1 and COR2 are used to obtain velocity and mass estimates for the associated CME. We develop a technique for mitigating temperature effects in coronal dimming from full-disk irradiance measurements taken by EVE. We find that for this event, nearly 100% of the dimming is due to mass loss in the corona.

Solar↗
NASA NTRS2017

Flux Cancelation: The Key to Solar Eruptions

Solar coronal jets are magnetically channeled eruptions that occur in all types of solar environments (e.g. active regions, quiet-Sun regions and coronal holes). Recent studies show that coronal jets are driven by the eruption of small-scare filaments (minifilaments). Once the eruption is underway magnetic reconnection evidently makes the jet spire and the bright emission in the jet base. However, the triggering mechanism of these eruptions and the formation mechanism of the pre-jet minifilaments are still open questions. In this talk, mainly using SDO/AIA (Solar Dynamics Observatory / Atmospheric Imaging Assembly) and SDO/HIM (Solar Dynamics Observatory / Helioseismic and Magnetic Imager) data, first I will address the question: what triggers the jet-driving minifilament eruptions in different solar environments (coronal holes, quiet regions, active regions)? Then I will talk about the magnetic field evolution that produces the pre-jet minifilaments. By examining pre-jet evolutionary changes in line-of-sight HMI magnetograms while examining concurrent EUV (Extreme Ultra-Violet) images of coronal and transition-region emission, we find clear evidence that flux cancelation is the main process that builds pre-jet minifilaments, and is also the main process that triggers the eruptions. I will also present results from our ongoing work indicating that jet-driving minifilament eruptions are analogous to larger-scare filament eruptions that make flares and CMEs (Coronal Mass Ejections). We find that persistent flux cancellation at the neutral line of large-scale filaments often triggers their eruptions. From our observations we infer that flux cancelation is the fundamental process from the buildup and triggering of solar eruptions of all sizes.

Panesar, Navdeep K.↗
NASA NTRS2019

Enhancing Battery Safety with Fractional Thermal Runaway Calorimetry

Effective thermal management systems, designed to handle the impacts of thermal runaway (TR) and to prevent cell-to-cell propagation, are key to safe operation of lithium-ion (Li-ion) battery assemblies. Critical factors for optimising these systems include the total energy released during a single cell TR event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A unique fractional thermal runaway calorimeter (FTRC), designed to characterise said critical factors, was utilised to examine the TR behaviour of Li-ion cells). Delegates will be provided with an in-depth discussion on what fractional thermal runaway calorimetry is and how it benefits the development of safe and optimised battery assemblies that protect against thermal runaway. Delegates will see calorimetry data associated with a variety of Li-ion cells. Data presented is relevant to any industry that utilises high-energy Li-ion cells in closed environments and has a need to focus on safety.

Walker, William↗
NASA NTRSDate not supplied

A Machine Learning Approach to Predict Martensitic Transition Temperatures for Shape Memory Alloys

Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature by varying the alloy composition. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions involving ternary, quaternary, or higher additions being considered. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches including machine learning. We present results from a developed machine learning model capable of accurately predicting the transition temperature of SMAs across a wide range of compositions. Our model has the added benefit of interpretability and even provides confidence intervals for our predictions. This model will make rapid screening and design of new SMA materials possible. Predictions from the machine learning model can be validated by empirical and/or atomistic scale modeling.

Shreyas Honrao↗
NASA NTRSDate not supplied

A Machine Learning Approach to Design Shape Memory Alloys for NASA Applications

Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions including ternary, quaternary, or higher additions being considered. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature of NiTi alloys by varying the alloy composition and processing conditions. In addition, low hysteresis and an acceptable recoverable transformation strain are required. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches. We present results from our machine learning approach for designing new SMAs with target properties within our range of interest. Our developed models are capable of accurately predicting the transition temperature, hysteresis, and transformation strain of SMAs across a wide range of compositions. This approach has the potential to significantly accelerate the discovery and design of new SMA materials.

Shreyas Jaikumar Honrao↗
NASA NTRSDate not supplied

Examining the Early Onset of Selected Large Solar Eruptions During the 2024 May Superstorm Episode

Recent studies indicate that solar flares are preceded by a period of above-ambient coronal heating, along with an increase in coronal X-ray emissions (Hudson et al. 2021). Despite being extremely common, the cause of these enhanced preflare emissions has not yet been understood. Here, our team examines in detail several of the large eruptions during the May 2024 superstorm period that resulted in significant geomagnetic disturbances. We use data from the Solar Dynamics Observatory's (SDO) Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI), from the Hinode satellite, and from other sources. For several of the GOES X-class events on 8-10 May, we find that the preflare heating signature is more complex than in the case of flares occurring in less dynamic solar regions, but nonetheless distinct hot (>~ 10 MK) preflare coronal signatures are present. Understanding of the cause of such preflare activity prior to the onset of geoeffective solar eruptions is essential to developing an eventual robust prediction algorithm for warning of impending solar eruptions that threaten Space Weather consequences.

Alphonse C. Sterling↗
NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly Optical System Design, Alignment, and Environmental Test

The Ocean Color Instrument (OCI), which will be integrated with the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite, will collect science data that will be used to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared (SWIR) Detection Assembly (SDA), built and characterized by Utah State University Space Dynamics Laboratory (SDL), is a subsystem of OCI consisting of 32 channels covering seven discrete optical bands of interest. A total of 16 SWIR Detection Subassemblies (SDSs) compose the SDA and house the cold optical system. The science data optical input for each SDS is supplied by a 0.22 NA multimode fiber interfacing with a fiber adapter. The diverging light from the fiber is collimated, split by a dichroic beamsplitter to two separate channels, filtered by the science filter, and then reimaged onto the single-element detectors with a final 0.76 NA. Aspheric, diamond-turned powered elements are used throughout the optical design. Fabrication and alignment tolerance analysis/budgets are balanced to ensure the optical system meets throughput requirements. All systems are aligned at ambient temperature using an InSb camera and an in-line illumination microscope system to directly image the active detector area through the science filters. Compensators used during alignment are detector focus and decenter, which are adjusted via photoetched shims in increments of 25 µm. Average focus and centering errors were less than 8 µm among all 32 flight and 10 flight spare detectors. Each SDS spectral response and conversion gain was verified at operational temperature of -65°C in vacuum.

OCI↗
DOE OSTI2025

Metagenome-assembled-genomes recovered from the Arctic drift expedition MOSAiC

The Multidisciplinary Observatory for Study of the Arctic Climate (MOSAiC) expedition consisted of a year-long drifting survey of the Central Arctic Ocean. The ecosystems component of MOSAiC included the sampling of molecular data, with metagenomes collected from a diverse range of environments. The generation of metagenome-assembled-genomes (MAGs) from metagenomes are a starting point for genome-resolved analyses. This dataset presents a catalogue of MAGs recovered from a set of 73 samples from MOSAiC, including 2407 prokaryotic and 56 eukaryotic MAGs, as well as annotations of a near complete eukaryotic MAG using the Joint Genome Institute (JGI) annotation pipeline. The metagenomic samples are from the surface ocean, chlorophyll maximum, mesopelagic and bathypelagic, within leads and under-ice ocean, as well as melt ponds, ice ridges, and first- and second-year sea ice. This set of MAGs can be used to benchmark microbial biodiversity in the Central Arctic Ocean, compare individual strains across space and time, and to study changes in Arctic microbial communities from the winter to summer, at a genomic level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluation of Nominal Energy Storage at Existing Hydropower Reservoirs in the US

Long-term planning and operation of hydropower reservoirs require an understanding of both water and energy storage. As energy storage needs of the evolving grid increase, we must account for the water and energy storage potential of these reservoirs. Given the limitations of current data on existing hydropower, we compile statistics related to storage volume and hydraulic head from publicly available data sets and examine differences in descriptions of US hydropower storage. Assembled characteristics are used to calculate nominal energy storage capacity, a simple measure of potential to generate power from a given volume of water, not factoring in detailed constraints. Inventory-based estimates of energy storage are calculated at 2,075 dams, which helps put the potential for US hydropower to support energy storage in context with similar evaluations in other regions and with other energy storage technologies. The national energy storage capacity ranges between 34.5 and 45.1 TWh depending on the information used, with 52% of energy storage located at the 10 largest reservoirs in the US. Energy storage capacities are also calculated at 236 dams with historical volume and elevation data. Finally, reservoir inflows provide context for the storage volumes and sensitivities to hydrologic variability. Larger reservoirs with greater storage volume to inflow ratios are concentrated in the Western US, but the majority of hydropower reservoirs store less than the annual inflow. We address several infrastructure and water resource informatics challenges and highlight remaining issues, including representing seasonal or shorter variability in water volumes and representing connected hydropower facilities.

13 HYDRO ENERGY↗
NASA NTRS2013

What are the Progenitors of Compace, Massive, Quiescent Galaxies at z (equals) 2.3? The Population of Massive Galaxies at z (greater than) 3 From NMBS AND CANDELS

Using public data from the NEWFIRM Medium-Band Survey (NMBS) and the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS), we investigate the population of massive galaxies at z > 3. The main aim of this work is to identify the potential progenitors of z ∼ 2 compact, massive, quiescent galaxies (CMQGs), furthering our understanding of the onset and evolution of massive galaxies. Our work is enabled by high-resolution images from CANDELS data and accurate photometric redshifts, stellar masses, and star formation rates (SFRs) from 37-band NMBS photometry. The total number of massive galaxies at z > 3 is consistent with the number of massive, quiescent galaxies (MQGs) at z ∼ 2, implying that the SFRs for all of these galaxies must be much lower by z ∼ 2. We discover four CMQGs at z > 3, pushing back the time for which such galaxies have been observed. However, the volume density for these galaxies is significantly less than that of galaxies at z < 2 with similar masses, SFRs, and sizes, implying that additional CMQGs must be created in the intervening ∼1 Gyr between z = 3 and z = 2. We find five star-forming galaxies at z ∼ 3 that are compact (Re < 1.4 kpc) and have stellar mass M∗ > 1010.6M; these galaxies are likely to become members of the massive, quiescent, compact galaxy population at z ∼ 2. We evolve the stellar masses and SFRs of each individual z > 3 galaxy adopting five different star formation histories (SFHs) and studying the resulting population of massive galaxies at z = 2.3. We find that declining or truncated SFHs are necessary to match the observed number density of MQGs at z ∼ 2, whereas a constant delayed-exponential SFH would result in a number density significantly smaller than observed. All of our assumed SFHs imply number densities of CMQGs at z ∼ 2 that are consistent with the observed number density. Better agreement with the observed number density of CMQGs at z ∼ 2 is obtained if merging is included in the analysis and better still if star formation quenching is assumed to shortly follow the merging event, as implied by recent models of the formation of MQGs.

Massive↗
DOE OSTI2020

MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Photonic Doppler Velocimetry for Valve Analysis and Surveillance

This study is an experimental evaluation to measure and surveil the velocity of stainless steel (Carpenter 455) pistons within a forged 21-6-9 stainless steel valve body. The velocity of the piston “stroke” will be identified using Photonic Doppler Velocimetry (PDV). The piston velocity will be the measured variable of interest. The outcome of this testing series provides further understanding to whether the extracted piston velocity can provide enough information to determine valve integrity. PDV has been identified as a diagnostic of interest as it can detect surface motion at high speeds with reliable accuracy. Through preliminary studies conducted with velocity interferometer system for any reflector (VISAR), the velocity of the piston is expected to stroke with a speed of 135 m/s. The PDV technique is much more reliable and repeatable than the VISAR technique because of its high-speed precision and accuracy, so it will not only validate the preliminary data, but also provide a testing technique that is capable of being used in future valve qualification efforts. The initial testing was completed using valves that were assembled per qualified procedures in a pristine condition. These initial tests were conducted to provide baseline data. This baseline data was then compared to data collected from valves where man-made defects were introduced. These defects are discussed in later sections. Lastly, actuators used to operate the valves were loaded with varied amounts of high explosives to identify if velocity is a function of the amount of explosive in an actuator. These parameters were adjusted to conclusively determine and identify if PDV can be used as a method to assess valve integrity. It was concluded through the testing discussed in this paper that in fact, PDV is capable of measuring the differences in piston velocities based on varied parameters. As far as understanding the PDV accuracy of the measured differences, this is ongoing and will have to be assessed in continued testing series.

42 ENGINEERING↗
NASA NTRS2012

A Large-Scale Design Integration Approach Developed in Conjunction with the Ares Launch Vehicle Program

This paper presents a method for performing large-scale design integration, taking a classical 2D drawing envelope and interface approach and applying it to modern three dimensional computer aided design (3D CAD) systems. Today, the paradigm often used when performing design integration with 3D models involves a digital mockup of an overall vehicle, in the form of a massive, fully detailed, CAD assembly; therefore, adding unnecessary burden and overhead to design and product data management processes. While fully detailed data may yield a broad depth of design detail, pertinent integration features are often obscured under the excessive amounts of information, making them difficult to discern. In contrast, the envelope and interface method results in a reduction in both the amount and complexity of information necessary for design integration while yielding significant savings in time and effort when applied to today's complex design integration projects. This approach, combining classical and modern methods, proved advantageous during the complex design integration activities of the Ares I vehicle. Downstream processes, benefiting from this approach by reducing development and design cycle time, include: Creation of analysis models for the Aerodynamic discipline; Vehicle to ground interface development; Documentation development for the vehicle assembly.

Redmon, John W.↗