BEST: Biomolecule Extraction and Sequencing Technology Utilizing the Station's Miniature Molecular Lab to Create Big Data
No abstract available
John, Kristen K.↗
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Results for “big”
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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Magnetospheric Constellation: Leveraging Space 2.0 for Big Science
Earth's magnetosphere is a large magnetic cavity formed through the interaction of the solar wind and Earth's intrinsic magnetic field. Solar wind energy enters this cavity through a boundary - the magnetopause - separating Earth's field from the solar wind. This energy leads to many forms of "space weather", including the aurora, geomagnetic storms, and energization of the Van Allen radiation belts. Despite decades of research, we still do not understand the extent of dayside reconnection sites, nor do we have a quantifiable understanding of how much energy enters the magnetosphere during different solar wind conditions - necessary for space weather prediction. On the nightside, impulsive flows at various spatial and temporal scales occur frequently during storms and substorms, and couple to the ionosphere through still unresolved physical mechanisms. Because the magnetosphere is so large, it has been understood since the dawn of the space age that a full understanding of this complex region could only be achieved with a large fleet of in situ spacecraft. NASA has studied one such constellation, the socalled "Magnetospheric Constellation" (MagCon), since the1990's, but it is deemed too expensive to implement using traditional approaches. The CubeSat/ SmallSat revolution represents a fundamental disruption to traditional mission architectures, and in this paper I will discuss how, by leveraging innovation in spacecraft subystems, advanced manufacturing, and access to space, we can finally realize this long-term vision of exploration and discovery. The proposed modular approach, utilizing rideshare and propulsive ESPAs, would also enable worldwide participation in the mission, and is applicable to any constellation mission, including Earth Science missions.
Kepko, Emil Larry↗
A Brief History of Space Climatology: From the Big Bang to the Present
Review of space climatology is presented with a view toward spacecraft electronics applications. The origins and abundances of space radiations are discussed and related to their potential effects. Significant historical developments are summarized leading to the inception of space climatology and into the space era. Energetic particle radiation properties and models of galactic cosmic rays, solar energetic and geomagnetic trapped particles are described. This includes current radiation effects issues that models face today.
Xapsos, Michael↗
Planetary Entry Vehicle Prototyping Using Cubesats (or How to Progress on a Shoe-String Budget and Hope to Play with the Big Guys): The Micro Return Capsule (MIRCA)
Imagine standing on the surface of an alien planet or satellite. High in the sky, a soft breeze is interrupted by the whistling sound of a tiny probe sent from Earth to study the atmosphere, or to land on some high-value target on the surface. Now imagine that this probe is followed by a dozen others, all entering in distributed locations throughout the geographic landscape. These probes are systematically and methodically being released from an orbiting spacecraft, perhaps having arrived months in advance. Or maybe the probes themselves are released systematically months in advance by and approaching mother-ship. Although probes have been sent to celestial neighbors before, what is unique is that these new vehicles had their genesis on the highly popular Cubesat specification… My dream is to make spaceflight so mundane, we can actually routinely leave the bounds of our planet to explore en masse our solar system. For that, we must create systems that allow us to bring space exploration within the realm of our everyday lives. No longer exquisite systems but just good enough, where failure is an option … and a new opportunity.
Esper, Jaime↗
What's My Prior? Baby Steps Toward Big Data
After four decades of single-event effects testing, radiation engineers face pressure to find alternatives to reduce or eliminate testing costs. Many of these alternatives focus on use of archival test data to bound SEE risk for similar parts. This presentation examines the challenges and limitations of such analyses and suggests analysis techniques and goals that are likely to be most appropriate for such efforts.
statistics and probability↗
Big Science in Small Packages: a Constellation of Cubesats to Search for Near Earth Asteroids
Astronomers for many decades have been searching for Near Earth Asteroids (NEA) that could potentially impact the Earth in the future. Large Synoptic Survey Telescope (LSST), when completed, would be by far the most powerful tool for a ground-based search for NEAs. In space, IR telescopes are undergoing detailed design studies. These facilities are projected to find 90% of potentially hazardous NEAs in about a dozen years. We introduce a different approach to search for these objects by using multiple micro- and nano-spacecraft distributed in orbit around the Sun. Their ability to faint moving objects with small telescopes is based on a new generation of low noise, fast-frame cameras combined with processors that can execute 100’s of gigaflops in a low power space environment.
Shao, Michael↗
Sylph - A SmallSat Probe Concept Engineered to Answer Europa's Big Question
Europa, the Galilean satellite second from Jupiter, contains a vast, subsurface ocean of liquid water. Recent observations indicate possible plume activity. If such a plume expels ocean water into space as at Enceladus, a spacecraft could directly sample the ocean by analyzing the plume’s water vapor, ice, and grains. Due to Europa’s strong gravity, such sampling would have to be done within 5 km of the surface to sample ice grains larger than 5 µm, expected to be frozen ocean spray and thus to contain non-volatile species critical to a biosignature-detection mission. By contrast, the planned Europa Multiple Flyby Mission’s closest planned flyby altitude is 25 km. Sylph is a concept for a SmallSat free-flyer probe that, deployed from the planned Europa Mission, would directly sample the large grains by executing a single ~2-km altitude plume pass. The 40-kg probe would be deployed by the Europa mission just before it executes a plume fly-through. Within the probe’s 16-hour lifespan, it would autonomously navigate to perform a parallel, simultaneous pass at the lower altitude. The Sylph flight system design concept combines SmallSat technologies with robust traditional components and advanced manufacturing technologies. Its payload would comprise Mini-SUDA (SUrface Dust Mass Analyzer), a dual-channel, miniature impact ionization mass spectrometer. Sylph represents a novel type of SmallSat concept: purpose-built configuration, optimized for the harsh environment at Europa and for planetary-protection requirements, and hybridized from both mainstream and SmallSat components.
Imken, Travis↗
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↗
Big Science in Small Packages: A Constellation of Cubesats to Search for near Earth Asteroids
No abstract available
Shao, Michael↗
Agile Big Data Analytics of High-Volume Geodetic Data Products for Improving Science and Hazard Response
No abstract available
Hua, Hook↗
App Store at OpenNEX: A Gateway to Help Find Apps over Big Data on the Cloud
In this on-going work, we report our efforts of building App Store at OpenNEX, which aims to provide a data analytics software search engine to help researchers find reusable software components to facilitate the development of their own algorithms.
Zhang, Jia↗
Spaceflight Microbiology From Small Things, Big Things One Day Come
No abstract available
Ott, C. Mark↗
Watershed Modeling with Remotely Sensed Big Data: MODIS Leaf Area Index Improves Hydrology and Water Quality Predictions
Traditional watershed modeling often overlooks the role of vegetation dynamics. There is also little quantitative evidence to suggest that increased physical realism of vegetation dynamics in process-based models improves hydrology and water quality predictions simultaneously. In this study, we applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershedin the midwestern United States. We modified the SWAT source code to automatically override the model’s built-in semiempirical LAI with spatially distributed and temporally continuous estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a “basic” traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that the overestimation or underestimation of LAI imparted a proportional cascading effect on how the model partitions hydrologic fluxes and nutrient pools. As such, assimilation of MODIS LAI data corrected the model’sLAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study fills the existing knowledge gap regarding vegetation dynamics in watershed modeling and confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.
Adnan Rajib↗
Ensemble-Based Deep Learning for Estimating PM2.5 over California with Multisource Big Data Including Wildfire Smoke
Estimating PM2.5 concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in natural (e.g. wildfires, dust) and anthropogenic emissions, meteorology, topography (e.g. desert surfaces, mountains, snow cover) and land use.
air quality↗
Small Scale Sequence Automation Pays Big Dividends
Galileo sequence design and integration are supported by a suite of formal software tools. Sequence review, however, is largely a manual process with reviewers scanning hundreds of pages of cryptic computer printouts to verify sequence correctness. Beginning in 1990, a series of small, PC-based sequence review tools evolved. Each tool performs a specific task but all have a common
sequence↗