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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

The 2024 Meteor Shower Activity Forecast for the Lunar Surface

The purpose of this document is to provide a forecast of major meteor shower activity on the lunar surface. While the predictions in this document are for the surface, spacecraft orbiting the Moon at low altitudes will encounter meteoroids at similar rates. Most annual showers are expected to display typical activity, but the eta Aquariids (ETA) are once again expected to exhibit more than double their typical activity level. A complete discussion of expected meteor shower activity in 2024 is available in the meteor shower activity forecast for low Earth orbit.

Althea Moorhead↗
NASA NTRS2023

Automated Global-Scale Detection and Characterization of Anthropogenic Activity using Multi-Source Satellite-Based Remote Sensing Imagery

Satellite-based remote sensing imagery is an effective means for detecting objects and structures in support of many applications. However, detecting the spatial and temporal bounds of a specific activity in satellite imagery is inherently more complex and research in this area is nascent. One reason for this is that describing an activity implies defining both spatial and temporal bounds and while activity is inherently continuous in nature, the geospatial (imagery) time series for any particular swath of ground provided by satellite imagery is relatively sparse and discrete in comparison. The IARPA Space-Based Machine Automated Recognition Technique (SMART)1 program is the first large-scale research program to target advancing the state of the art for automatically detecting, characterizing, and monitoring large-scale anthropogenic activity in global, multispectral satellite imagery. The program has two primary research objectives: 1) the “harmonization” of multiple imagery sources and 2) automated reasoning at scale to detect, characterize, and monitor activities of interest. This paper provides details on the goals, dataset, metrics, and lessons learned of the IARPA SMART program. By releasing the annotated dataset, the program aims to foster additional research in this area by the community at large.

Hirsh R Goldberg↗
NASA NTRS2000

Insulin-like growth factor-I extends in vitro replicative life span of skeletal muscle satellite cells by enhancing G1/S cell cycle progression via the activation of phosphatidylinositol 3'-kinase/Akt signaling pathway

Interest is growing in methods to extend replicative life span of non-immortalized stem cells. Using the insulin-like growth factor I (IGF-I) transgenic mouse in which the IGF-I transgene is expressed during skeletal muscle development and maturation prior to isolation and during culture of satellite cells (the myogenic stem cells of mature skeletal muscle fibers) as a model system, we elucidated the underlying molecular mechanisms of IGF-I-mediated enhancement of proliferative potential of these cells. Satellite cells from IGF-I transgenic muscles achieved at least five additional population doublings above the maximum that was attained by wild type satellite cells. This IGF-I-induced increase in proliferative potential was mediated via activation of the phosphatidylinositol 3'-kinase/Akt pathway, independent of mitogen-activated protein kinase activity, facilitating G(1)/S cell cycle progression via a down-regulation of p27(Kip1). Adenovirally mediated ectopic overexpression of p27(Kip1) in exponentially growing IGF-I transgenic satellite cells reversed the increase in cyclin E-cdk2 kinase activity, pRb phosphorylation, and cyclin A protein abundance, thereby implicating an important role for p27(Kip1) in promoting satellite cell senescence. These observations provide a more complete dissection of molecular events by which increased local expression of a growth factor in mature skeletal muscle fibers extends replicative life span of primary stem cells than previously known.

NASA Discipline Musculoskeletal↗
NASA NTRS2001

Cyclic strain increases protease-activated receptor-1 expression in vascular smooth muscle cells

Cyclic strain regulates many vascular smooth muscle cell (VSMC) functions through changing gene expression. This study investigated the effects of cyclic strain on protease-activated receptor-1 (PAR-1) expression in VSMCs and the possible signaling pathways involved, on the basis of the hypothesis that cyclic strain would enhance PAR-1 expression, reflecting increased thrombin activity. Uniaxial cyclic strain (1 Hz, 20%) of cells cultured on elastic membranes induced a 2-fold increase in both PAR-1 mRNA and protein levels. Functional activity of PAR-1, as assessed by cell proliferation in response to thrombin, was also increased by cyclic strain. In addition, treatment of cells with antioxidants or an NADPH oxidase inhibitor blocked strain-induced PAR-1 expression. Preincubation of cells with protein kinase inhibitors (staurosporine or Ro 31-8220) enhanced strain-increased PAR-1 expression, whereas inhibitors of NO synthase, tyrosine kinase, and mitogen-activated protein kinases had no effect. Cyclic strain in the presence of basic fibroblast growth factor induced PAR-1 mRNA levels beyond the effect of cyclic strain alone, whereas no additive effect was observed between cyclic strain and platelet-derived growth factor-AB. Our findings that cyclic strain upregulates PAR-1 mRNA expression but that shear stress downregulates this gene in VSMCs provide an opportunity to elucidate signaling differences by which VSMCs respond to different mechanical forces.

NASA Discipline Cell Biology↗
NASA NTRS2000

Rac-1 and Raf-1 kinases, components of distinct signaling pathways, activate myotonic dystrophy protein kinase

Myotonic dystrophy protein kinase (DMPK) is a serine-threonine protein kinase encoded by the myotonic dystrophy (DM) locus on human chromosome 19q13.3. It is a close relative of other kinases that interact with members of the Rho family of small GTPases. We show here that the actin cytoskeleton-linked GTPase Rac-1 binds to DMPK, and coexpression of Rac-1 and DMPK activates its transphosphorylation activity in a GTP-sensitive manner. DMPK can also bind Raf-1 kinase, the Ras-activated molecule of the MAP kinase pathway. Purified Raf-1 kinase phosphorylates and activates DMPK. The interaction of DMPK with these distinct signals suggests that it may play a role as a nexus for cross-talk between their respective pathways and may partially explain the remarkable pleiotropy of DM.

NASA Discipline Musculoskeletal↗
NASA NTRS1996

Activation of a Ca(2+)-dependent protein kinase involves intramolecular binding of a calmodulin-like regulatory domain

Ca(2+)-dependent protein kinases (CDPKs) are regulated by a C-terminal calmodulin-like domain (CaM-LD). The CaM-LD is connected to the kinase by a short junction sequence which contains a pseudosubstrate autoinhibitor. To understand how the CaM-LD regulates a CDPK, a recombinant CDPK (isoform CPK-1 from Arabidopsis, accession no. L14771) was made as a fusion protein in Escherichia coli. We show here that a truncated CDPK lacking a CaM-LD (e.g. mutant delta NC-26H) can be activated by exogenous calmodulin or an isolated CaM-LD (Kact approximately 2 microM). We propose that Ca2+ activation of a CDPK normally occurs through intramolecular binding of the CaM-LD to the junction. When the junction and CaM-LD are made as two separate polypeptides, the CaM-LD can bind the junction in a Ca(2+)-dependent fashion with a dissociation constant (KD) of 6 x 10(-6) M, as determined by kinetic binding analyses. When the junction and CaM-LD are tethered in a single polypeptide (e.g. in protein JC-1), their ability to engage in bimolecular binding is suppressed (e.g. the tethered CaM-LD cannot bind a separate junction). A mutation which disrupts the putative CaM-LD binding sequence (e.g. substitution LRV-1444 to DLPG) appears to block intramolecular binding, as indicated by the restored ability of a tethered CaM-LD to engage in bimolecular binding. This mutation, in the context of a full-length enzyme (mutant KJM46H), appears to block Ca2+ activation. Thus, a disruption of intramolecular binding correlates with a disruption of the Ca2+ activation mechanism. CDPKs provide the first example of a member of the calmodulin superfamily where a target binding sequence is located within the same polypeptide.

Non-NASA Center↗
NASA NTRS2006

Active Learning with Irrelevant Examples

Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there may exist unlabeled items that are irrelevant to the user's classification goals. Queries about these points slow down learning because they provide no information about the problem of interest. We have observed that when irrelevant items are present, active learning can perform worse than random selection, requiring more time (queries) to achieve the same level of accuracy. Therefore, we propose a novel approach, Relevance Bias, in which the active learner combines its default selection heuristic with the output of a simultaneously trained relevance classifier to favor items that are likely to be both informative and relevant. In our experiments on a real-world problem and two benchmark datasets, the Relevance Bias approach significantly improved the learning rate of three different active learning approaches.

machine learning↗
NASA NTRS2013

Analysis of the Effect of Water Activity on Ice Formation Using a New Theory of Nucleation

In this work a new theory of nucleation is developed and used to investigate the effect of water activity on the formation of ice within super-cooled droplets. The new theory is based on a novel concept where the interface is assumed to be made of liquid molecules trapped by the solid matrix. Using this concept new expressions are developed for the critical ice germ size and the nucleation work, with explicit dependencies on temperature and water activity. However unlike previous approaches, the new theory does not depend on the interfacial tension between liquid and ice. Comparison against experimental results shows that the new theory is able to reproduce the observed effect of water activity on nucleation rate and freezing temperature. It allows for the first time a theoretical derivation of the constant shift in water activity between melting and nucleation. The new theory offers a consistent thermodynamic view of ice nucleation, simple enough to be applied in atmospheric models of cloud formation.

Water Activity↗
NASA NTRS2016

Small Spacecraft Active Thermal Control: Micro-Vascular Composites Enable Small Satellite Cooling

The Small Spacecraft Integrated Power System with Active Thermal Control project endeavors to achieve active thermal control for small spacecraft in a practical and lightweight structure by circulating a coolant through embedded micro-vascular channels in deployable composite panels. Typically, small spacecraft rely on small body mounted passive radiators to discard heat. This limits cooling capacity and leads to the necessity to design for limited mission operations. These restrictions severely limit the ability of the system to dissipate large amounts of heat from radios, propulsion systems, etc. An actively pumped cooling system combined with a large deployable radiator brings two key advantages over the state of the art for small spacecraft: capacity and flexibility. The use of a large deployable radiator increases the surface area of the spacecraft and allows the radiation surface to be pointed in a direction allowing the most cooling, drastically increasing cooling capacity. With active coolant circulation, throttling of the coolant flow can enable high heat transfer rates during periods of increased heat load, or isolate the radiator during periods of low heat dissipation.

Deployable radiator↗
NASA NTRS2016

Active CryoCubeSat

The Active CryoCubeSat project will demonstrate an advanced thermal control system for a 6-Unit (6U) CubeSat platform. A miniature, active thermal control system, in which a fluid is circulated in a closed loop from thermal loads to radiators, will be developed. A miniature cryogenic cooler will be integrated with this system to form a two-stage thermal control system. Key components will be miniaturized by using advanced additive manufacturing techniques resulting in a thermal testbed for proving out these technologies. Previous CubeSat missions have not tackled the problem of active thermal control systems nor have any past or current CubeSat missions included cryogenic instrumentation. This Active CryoCubeSat development effort will provide completely new capacities for CubeSats and constitutes a major advancement over the state-of-the-art in CubeSat thermal control.

CubeSat↗
NASA NTRS2016

Microorganisms, Organic Carbon, and Their Relationship with Oxidant Activity in Hyper-Arid Mars-Like Soils: Implications for Soil Habitability

Soil samples from the hyper-arid region in the Atacama 23 Desert in Southern Peru (La Joya Desert) were analyzed for total and labile organic carbon (TOC & LOC), phospholipid fatty acids analysis (PLFA), quantitative real time polymerase chain reaction (qRT-PCR), 4',6- diamidino-2-phenylindole (DAPI)-fluorescent microscopy, culturable microorganisms, and oxidant activity, in order to understand the relationship between the presence of organic matter and microorganisms in these types of soils. TOC content levels were similar to the labile pool of carbon suggesting the absence of recalcitrant carbon in these soils. The range of LOC was from 2 to 60 micro-g/g of soil. PLFA analysis indicated a maximum of 2.3 x 10(exp 5) cell equivalents/g. Culturing of soil extracts yielded 1.1 x 10(exp 2)-3.7 x 10(exp 3) CFU/g. qRT-PCR showed between 1.0 x 10(exp 2) and 8 x 10(exp 3) cells/g; and DAPI fluorescent staining indicated bacteria counts up to 5 x 104 cells/g. Arid and semiarid samples (controls) showed values between 10(exp 7) and 10(exp 11) cells/g with all of the methods used. Importantly, the concentration of microorganisms in hyper-arid soils did not show any correlation with the organic carbon content; however, there was a significant dependence on the oxidant activity present in these soil samples evaluated as the capacity to decompose sodium formate in 10 hours. We suggest that the analysis of oxidant activity could be a useful indicator of the microbial habitability in hyper-arid soils, obviating the need to measure water activity over time. This approach could be useful in astrobiological studies on other worlds.

Mars-like soils↗
NASA NTRS2017

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

software↗
NASA NTRS2017

Ask-the-Expert: Active Learning Based Knowledge Discovery Using the Expert

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the back end. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

GUI↗
NASA NTRS2019

Ask-The-Expert: Minimizing Human Review for Big Data Analytics Through Active Learning

In this CIF project, we worked toward semi-automating knowledge discovery from anomaly detection algorithms through the use of active learning. Active learning is an area of research within machine learning that uses an "expert in the loop" to learn from large data sets that have very few annotations or labels available, and where providing such labels is expensive. In our case, the task can be defined as the identification of safety events from flight operational data. Since traditional anomaly detection algorithms cannot differentiate between operationally relevant and irrelevant statistical anomalies, Subject Matter Experts (SMEs) have a lengthy and expensive burden of investigating every example identified by the detection algorithm, classifying and labeling them as relevant or irrelevant. Active learningidentifies the unlabeled example for which a label would most improve the classifier, asks the domain expert for a label, and repeats this process until there are no more resources (time, budget) available for labeling or a minimum required performance is reached. A positive label indicates an operationally significant safety event whereas a negative label indicates otherwise. Based on these few labels we propose to build an active learning system that utilizes the SME's time in the most effective manner by iteratively asking for labels for as few informative instances as possible. Our work was proposed to be a stepping stone toward implementation and deployment of the system with user interface to be pursued by the Aviation Operations and Safety Program (AOSP) given its interest in safety monitoring and discovery of safety incidents.

aviation safety↗
NASA NTRS2021

US Tropical Cyclone Activity in the 2030s Based on Projected Changes in Tropical Sea-Surface Temperature

We use a statistical tropical cyclone (TC) model, the North Atlantic Stochastic Hurricane Model (NASHM), in combination with sea-surface temperature (SST) projections from climate models, to estimate regional changes in US TC activity into the 2030s. NASHM is trained on historical variations in TC characteristics with two SST indices: global-tropical mean SST and the difference between tropical North-Atlantic (NA) SST and the rest of the global tropics, often referred to as “relative SST.” Testing confirms the model’s ability to reproduce historical US TC activity, as well as to make skillful predictions. When NASHM is driven by SST projections into the 2030s, overall NA annual TC counts increase, and the fractional increase is the greatest at the highest wind intensities. However, an eastward anomaly in mean TC tracks and an eastward shift in TC formation region result in a geographically-varied signal in US coastal activity. Florida’s Gulf coast is projected to see significant increases in TC activity, compared to the long-term historical mean, and these increases are fractionally greatest at the highest intensities. By contrast, the northwestern US Gulf and the US East Coast will see little change.

tropical cyclone (TC) model↗
NASA NTRSDate not supplied

Implementation of active sites to capture pitting of oxidizing carbon materials in DSMC.

In this work we demonstrate a newly developed capability to capture pitting of carbon fibers in DSMC simulations, specifically using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code [1]. State-of-the-art reactive surface models in DSMC compute collision dependent carbon consumption rates (usually through desorption of CO) based on a set of surface reactions that has been derived from molecular beam experiments [2]. The reactivity on each carbon surface element is constant in those models, such that the carbon surface recedes uniformly as a result of ablation. However, it is well known that in reality the carbon surface has locally different reaction rates due to the presence of defects at the atomic scale [3]. These defective sites have a much higher reactivity than the average sites (2-3 orders of magnitude) and are first to react during ablation leading to its removal. This causes all the neighboring atoms to be defective and increase their reactivity, thus leading to the localized carbon removal around these ”active” sites (as shown in Fig. 1). In this manner, these highly reactive defective sites serve as nucleation sites for the formation and growth of etch pits with potentially detrimental effects on the structural integrity. Recently a detailed surface chemistry framework was developed in SPARTA, capable of incorporating various reaction mechanisms such as adsorption, desorption, Eley-Rideal (ER) and Langmuir-Hinshelwood (LH) mechanisms [4]. Within this framework, we have implemented the capability of a single surface having multiple site sets with different reactivities. Using this feature, we can simulate the presence of active sites on carbon surfaces, whose reactivity is much greater than an average site as a result of defects. We have implemented the active site fraction as a property of surface elements within SPARTA, which is directly proportional to the local reactivity of each surface element. By introducing an initial distribution of the active site fraction across the carbon surface, and propagating it in a manner that mimics the evolution of real reacting carbon surfaces, we are able to capture the formation and growth of etch pits as a result of surface consumption reactions such as oxidation.

DSMC↗
NASA NTRSDate not supplied

Implementation of Active Sites in DSMC to Capture Pitting of Oxidizing Carbon Materials

In this work we demonstrate a newly developed capability to capture pitting of carbon fibers in DSMC simulations, specifically using the Stochastic PArallel Rarefied-gas Time-accurate Analyzer (SPARTA) code. State-of-the-art reactive surface models in DSMC compute collision dependent carbon consumption rates (usually through desorption of CO) based on a set of surface reactions that has been derived from molecular beam experiments. The reactivity on each carbon surface element is constant in those models, such that the carbon surface recedes uniformly as a result of ablation. However, it is well known that in reality the carbon surface has locally different reaction rates due to the presence of defects at the atomic scale. These defective sites have a much higher reactivity than the average sites (2-3 orders of magnitude) and are first to react during ablation leading to its removal. This causes all the neighboring atoms to be defective and increase their reactivity, thus leading to the localized carbon removal around these ”active” sites. In this manner, these highly reactive defective sites serve as nucleation sites for the formation and growth of etch pits with potentially detrimental effects on the structural integrity. Recently a detailed surface chemistry framework was developed in SPARTA, capable of incorporating various reaction mechanisms such as adsorption, desorption, Eley-Rideal (ER) and Langmuir-Hinshelwood (LH) mechanisms. Within this framework, we have implemented the capability of a single surface having multiple site sets with different reactivities. Using this feature, we can simulate the presence of active sites on carbon surfaces, whose reactivity is much greater than an average site as a result of defects. We have implemented the active site fraction as a property of surface elements within SPARTA, which is directly proportional to the local reactivity of each surface element. By introducing an initial distribution of the active site fraction across the carbon surface, and propagating it in a manner that mimics the evolution of real reacting carbon surfaces, we are able to capture the formation and growth of etch pits as a result of surface consumption reactions such as oxidation.

DSMC↗
NASA NTRS2023

Spatially-Coordinated Airborne Data and Complementary Products for Aerosol, Gas, Cloud, and Meteorological Studies: the Nasa Activate Dataset

The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions, with applications extending from process-based studies to multi-scale model intercomparison and improvement as well as to remote-sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean, resulting in 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the HU-25 Falcon and King Air, respectively. The HU-25 Falcon conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. Under cloud-free conditions, the HU-25 Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flying aircraft) flew at approximately ∼ 9 km and conducted remote sensing with a lidar and polarimeter while also launching dropsondes (785 in total). Collectively, simultaneous data from both aircraft help to characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the HU-25 Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product's start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes. The data are publicly accessible through https://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001 (ACTIVATE Science Team, 2020).

Aerosol Cloud meTeorology Interactions oVer the we↗