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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 847 records · Page 47

Association Between Cardiovascular and Intraocular Pressure Changes in a 14-day 6 deg Head Down Tilt (HDT) Bed Rest Study: Possible Implications in Retinal Anatomy

Mean IOP significantly increased while at 6deg HDT and returned towards pre-bed rest values upon leaving bed rest. While mean IOP increased during bed rest, it remained within the normal limits for subject safety. A diuretic shift and cardiovascular deconditioning occurs during in-bed rest, as expected. There was no demonstrable correlation between the largest change in IOP (pre/post) and cardiovascular measure changes (pre/post). Additional mixed effects linear regression modeling may reveal some subclinical physiological changes that might assist in describing the VIIP syndrome pathophysiology.

Cromwell, R. L.↗

Countermeasures and Functional Testing in Head-Down Tilt Bed Rest (CFT 70)

This 70‐day bed rest campaign was comprised of 6 integrated studies and conducted at the NASA Flight Analogs Research Unit (FARU). The FARU is located at the University of Texas Medical Branch, Galveston, Texas and is a satellite unit of the Institute for Translational Sciences - Clinical Research Center. This presentation will describe the FARU, discuss the utility of the bed rest platform for use in these studies, and introduce the studies that participated in the CFT 70 bed rest campaign. Information in this presentation will serve as the background for subsequent talks from each individual study. Individual study presentations will discuss preliminary results from completed subjects. Studies included in CFT70 were:  Physiological Factors Contributing to Post Flight Changes in Functional Performance. J. Bloomberg, NASA  Integrated Resistance and Aerobic Training Study. L. Ploutz‐Snyder, USRA  Testosterone Supplementation as a Countermeasure Against Musculoskeletal losses during Space Exploration. R. Urban, University of Texas Medical Branch  Effects of Retronasal Smelling, Variety and Choice on Appetite & Satiety. J. Hunter, Cornell University  AD ASTRA: Automated Detection of Attitudes and States through Transaction Recordings Analysis. C. Miller, Smart Information Flow Technologies, LLC  Bed Rest as a Spaceflight Analog to Study Neuro‐cognitive Changes: Extent, Longevity, and Neural Bases. R. Seidler, University of Michigan

Cromwell, Ronita L.↗

Analysis of Arterial Mechanics During Head-Down-Tilt Bed Rest

Carotid, brachial, and tibial arteries reacted differently to HDTBR. Previous studies have not analyzed the mechanical properties of the human brachial or anterior tibial arteries. After slight variations during bed-rest, arterial mechanical properties and IMT returned to pre-bed rest values, with the exception of tibial stiffness and PSE, which continued to be reduced post-bed rest while the DC remained elevated. The tibial artery remodeling was probably due to decreased pressure and volume. Resulting implications for longer duration spaceflight are unclear. Arterial health may be affected by microgravity, as shown by increased thoracic aorta stiffness in other ground based simulations (Aubert).

Elliott, Morgan B.↗

Aerosol Remote Sensing from Space - Where We Stand, Where We're Heading

The MISR and MODIS instruments aboard the NASA Earth Observing System's Terra Satellite have been collecting data containing information about the state of Earth's atmosphere and surface for over eleven years. Among the retrieved quantities are amount and type of wildfire smoke, desert dust, volcanic effluent, urban and industrial pollution particles, and other aerosols. However, the broad scientific challenges of understanding aerosol impacts on climate and health place different, and very exacting demands on our measurement capabilities. And these data sets, though much more advanced in many respects than previous aerosol data records, are imperfect. In this presentation, I will summarize current understanding of MISR and MODIS aerosol product strengths and limitations, discuss how they relate to the bigger aerosol science questions we must address, and give my view of the way forward.

MISR↗

Ethernet for Aerospace Applications - Ethernet Heads for the Skies

One of the goals of aerospace applications is to reduce the cost and complexity of avionic systems. Ethernet is a highly scalable, flexible, and popular protocol. The aerospace market is large, with a forecasted production of over 50,000 turbine-powered aircraft valued at $1.7 trillion between 2012 and 2022. Boeing estimates demand for commercial aircraft by 2033 to total over 36,000 with a value of over $5 trillion. In 2014 US airlines served over 750 million passengers and this is growing over 2% yearly. Electronic fly-by-wire is now used for all airliners and high performance aircraft. Although Ethernet has been widely used for four decades, its use in aerospace applications is just beginning to become common. Ethernet is the universal solution in commercial networks because of its high bandwidths, lower cost, openness, reliability, maintainability, flexibility, and interoperability. However, when Ethernet was designed applications with time-critical, safety relevant and deterministic requirements were not given much consideration. Many aerospace applications use a variety of communication architectures that add cost and complexity. Some of them are SpaceWire, MIL-STD-1553, Avionics Full Duplex Switched Ethernet (AFDX), and Time-Triggered Ethernet (TTE). Aerospace network designers desire to decrease the number of networks to reduce cost and effort while improving scalability, flexibility, openness, maintainability, and reliability. AFDX and TTE are being considered more for critical aerospace systems because they provide redundancy, failover protection, guaranteed timing, and frame priority and are based on Ethernet IEEE 802.3. This paper explores the use of AFDX and TTE for aerospace applications.

Ethernet↗

Heading for 20 Years of Quasi-Global Precipitation with the New Version 06 IMERG

The U.S. Global Precipitation Measurement mission (GPM) science team is developing a long-term dataset based on intercalibrated estimates from the international constellation of precipitation-relevant satellites and other data. The Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product (IMERG) is computed at the half hour, 0.1° x 0.1° resolution globally in three "Runs"—Early, Late, and Final (4 hours, 14 hours, and 3.5 months after observation time, respectively). GPM is well into computing the new Version 06, which will be the first time IMERG covers the last two decades and routinely provides morphed estimates in polar regions where the surface is snow- and ice-free.A few salient features of the IMERG algorithm will be summarized, then representative examples of IMERG products will be shown. This starts with basic results, such as animations of maps, then extends to preliminary analyses of dataset characteristics. For example, the diurnal cycle demonstrates improvements over V05.

Huffman, George J.↗

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗