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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Terrestrial Spaceflight Analogs: Antarctica

Alterations in immune cell distribution and function, circadian misalignment, stress and latent viral reactivation appear to persist during Antarctic winterover at Concordia Station. Some of these changes are similar to those observed in Astronauts, either during or immediately following spaceflight. Others are unique to the Concordia analog. Based on some initial immune data and environmental conditions, Concordia winterover may be an appropriate analog for some flight-associated immune system changes and mission stress effects. An ongoing smaller control study at Neumayer III will address the influence of the hypoxic variable. Changes were observed in the peripheral blood leukocyte distribution consistent with immune mobilization, and similar to those observed during spaceflight. Alterations in cytokine production profiles were observed during winterover that are distinct from those observed during spaceflight, but potentially consistent with those observed during persistent hypobaric hypoxia. The reactivation of latent herpesviruses was observed during overwinter/isolation, that is consistently associated with dysregulation in immune function.

Crucian, Brian↗
NASA NTRS2011

Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials

Composite structures are gaining importance for use in the aerospace industry. Compared to metallic structures their behavior is less well understood. This lack of understanding may pose constraints on their use. One possible way to deal with some of the risks associated with potential failure is to perform in-situ monitoring to detect precursors of failures. Prognostic algorithms can be used to predict impending failures. They require large amounts of training data to build and tune damage model for making useful predictions. One of the key aspects is to get confirmatory feedback from data as damage progresses. These kinds of data are rarely available from actual systems. The next possible resource to collect such data is an accelerated aging platform. To that end this paper describes a fatigue cycling experiment with the goal to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis showed distinct differences in the signatures of growing failures between data collected at conditions. Periodic X-radiographs were taken to assess the damage ground truth. Results after signal processing showed clear trends of damage growth that were correlated to damage assessed from the X-ray images.

composites↗
NASA NTRS2015

Estimating Planetary Boundary Layer Heights from NOAA Profiler Network Wind Profiler Data

An algorithm was developed to estimate planetary boundary layer (PBL) heights from hourly archived wind profiler data from the NOAA Profiler Network (NPN) sites located throughout the central United States. Unlike previous studies, the present algorithm has been applied to a long record of publicly available wind profiler signal backscatter data. Under clear conditions, summertime averaged hourly time series of PBL heights compare well with Richardson-number based estimates at the few NPN stations with hourly temperature measurements. Comparisons with clear sky reanalysis based estimates show that the wind profiler PBL heights are lower by approximately 250-500 m. The geographical distribution of daily maximum PBL heights corresponds well with the expected distribution based on patterns of surface temperature and soil moisture. Wind profiler PBL heights were also estimated under mostly cloudy conditions, and are generally higher than both the Richardson number based and reanalysis PBL heights, resulting in a smaller clear-cloudy condition difference. The algorithm presented here was shown to provide a reliable summertime climatology of daytime hourly PBL heights throughout the central United States.

Wind Profiler↗
NASA NTRS2016

Open Rotor Computational Aeroacoustic Analysis with an Immersed Boundary Method

Reliable noise prediction capabilities are essential to enable novel fuel efficient open rotor designs that can meet the community and cabin noise standards. Toward this end, immersed boundary methods have reached a level of maturity where more and more complex flow problems can be tackled with this approach. This paper demonstrates that our higher-order immersed boundary method provides the ability for aeroacoustic analysis of wake-dominated flow fields generated by a contra-rotating open rotor. This is the first of a kind aeroacoustic simulation of an open rotor propulsion system employing an immersed boundary method. In addition to discussing the methodologies of how to apply the immersed boundary method to this moving boundary problem, we will provide a detailed validation of the aeroacoustic analysis approach employing the Launch Ascent and Vehicle Aerodynamics (LAVA) solver. Two free-stream Mach numbers with M=0.2 and M=0.78 are considered in this analysis that are based on the nominally take-off and cruise flow conditions. The simulation data is compared to available experimental data and other computational results employing more conventional CFD methods. Spectral analysis is used to determine the dominant wave propagation pattern in the acoustic near-field.

Analysis↗
NASA NTRS2017

Biogeochemical Protocols and Diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF [subscript] 6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Carbon↗
NASA NTRS2015

Parallel Study of HEND, RAD, and DAN Instrument Response to Martian Radiation and Surface Conditions

Nuclear detection methods are being used to understand the radiation environment at Mars. JPL (Jet Propulsion Laboratory) assets on Mars include: Orbiter -2001 Mars Odyssey [High Energy Neutron Detector (HEND)]; Mars Science Laboratory Rover -Curiosity [(Radiation Assessment Detector (RAD); Dynamic Albedo Neutron (DAN))]. Spacecraft have instruments able to detect ionizing and non-ionizing radiation. Instrument response on orbit and on the surface of Mars to space weather and local conditions [is discussed] - Data available at NASA-PDS (Planetary Data System).

Mars↗
NASA NTRS2018

High Speed Bearing Wear Rate Measurements for Spacecraft Active Thermal Control Fluid Pumps with a Novel Pin on Disk Apparatus

A novel pin on disc tribometer was designed and constructed to generate a high-speed, wear coefficient database for hydrodynamic bearings that are typically used in canned motors found in the active thermal control circuits of robotic and inhabited spacecraft. The primary motivation for this work was the premature failure of the active external thermal control pump on the International Space Station in 2010. During the failure investigation of this incident, the root cause was postulated to be high speed wear of the bearings. Although a detailed forensic analysis gave credibility to this theory, the lack of wear coefficient data at relevant conditions prevented validation of this finding. The database generated from the new Extreme Environment Tribometer (EET) enabled a closure calculation within 5% of the observed wear from inspections of the failed hardware. Testing in anhydrous ammonia and surrogate fluid was performed to provide a means for simplified testing in the future and to populate a preliminary database for the design of future active thermal control systems on spacecraft. The EET and test techniques developed for the measurement of high-speed wear coefficients are available to future system designers.

thermal control↗
NASA NTRS2014

Afterbody Heat Flux Measurements in the NASA Ames HFFAF Ballistic Range

In order to measure afterbody heat fluxes over a model in the ballistic range, the required modifications to a proven technique for measuring forebody heat fluxes are described. This involves the use of an extended helium gas plume to remove the glowing wake and the use of special high conductivity, high temperature capable graphite-filled plastic for the afterbody. The models and test conditions are described. Data in the form of plots of the surface temperature of the models are presented. Finally, experimental and computational fluid dynamic (CFD) heat flux data for forebody and afterbody heat fluxes are presented and compared. Data are presented for a 45 degree sphere-cone (with a projecting rear stud) at 2.70 km/s and for a sphere at 4.76 km/s. Both models were launched into 76 Torr of CO2 gas. The experimental forebody heat fluxes were within 1.5% of the CFD values. The experimental afterbody heat fluxes were within 1% of the CFD values for the sphere, but only 51% of the CFD values for the sphere-cone.

Bogdanoff, David W.↗
NASA NTRS2019

Design and Acoustic Efficacy of a Broadband Liner for the Inlet of the DGEN Aero-Propulsion Research Turbofan

Advanced fan designs (including higher bypass ratios) and shorter engine nacelles have highlighted a need for increased fan noise reduction over a broader frequency range. With these observations in mind, an acoustic liner optimization process has been developed to achieve improved broadband liner designs. A series of advanced liner design studies at increasing technology readiness levels have been conducted as the overall optimization methodology has been enhanced. As part of the analysis, the overall design and evaluation capability was extended such that external observer locations may be included in the optimization process. This enhancement will provide a much wider design space in designing advanced broadband liners. In this work, further validation was pursued through the fabrication and testing of two liner designs for the NASA Glenn DGEN Aero-propulsion Research Turbofan (DART). The DART was used to document the efficacy of acoustic liners installed in the inlet of the DGEN380. An advanced Multi-Degree of Freedom Liner was designed, fabricated, and tested, along with a traditional Single-Degree-of-Freedom Liner, and those results compared to a hardwall baseline inlet. Farfield acoustic data were acquired from and external array, evaluated and reported herein terms of overall, broadband, and tonal components of the insertion loss. The predicted attenuation results generally matched expected trends of the measured data for the conditions considered.

Liners↗
NASA NTRS2019

Mars Phoenix EDL Trajectory and Atmosphere Reconstruction Using NewSTEP

This document describes the trajectory and atmosphere reconstruction of the Mars Phoenix Entry, Descent, and Landing using the New Statistical Trajectory Estimation Program. The approach utilizes a Kalman filter to blend inertial measurement unit data with initial conditions and radar altimetry to obtain the inertial trajectory of the entry vehicle. The nominal aerodynamic database is then used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state. The reconstructed atmosphere pro le is then blended with pre-flight models to construct an estimate of the as-flown atmosphere.

Karlgaard, Christopher D.↗
NASA NTRS2020

Real Time Optical Receiver Project

The goals for the Real Time Optical Receiver project are to Infuse Consultative Committee for Space Data Systems High Photon Efficiency standard into missions, such as Artemis and to provide a real time ground receiver solution (fiber device, detector, real time FPGA-based receiver) that is: (1) Scalable: data rate, atmosphere conditions, telescope aperture, etc., and (2) Uses COTS components when available and work with companies to move custom parts to COTS.

Katz, Evan J.↗
NASA NTRSDate not supplied

Vanadium Valence in MgAl2O4 Spinels at Reducing Conditions (IW to IW-5)

Vanadium is commonly a major or minor element in spinel structured oxides from a wide range of planetary materials [1-3]. Vanadium is stable in multiple valence states of 5+, 4+, 3+, and 2+ in natural systems, and spinel-structured oxides are known to host vanadium in 4+, 3+, and 2+ [4-6]. However, the understanding of 2+ stability at lower fO2 conditions has been hindered by lack of experiments at or below IW-1 conditions [5]. Insufficient experimental data is available due to the difficulty in controlling fO2 at low conditions in general, and the lack of appropriate standards for comparison to natural materials. Our progress on controlling fO2 in high pressure experimental samples has allowed us to create reducing conditions that are appropriate to studying V valence in spinels at fO2 relevant to natural reducing systems [7]. Here we extend this approach to study V in reduced conditions, at high temperatures. After at-tempting shorter durations and lower temperatures, we demonstrated the need for equilibration times > 6 hours at 1600 °C in order to approach equilibrium. Only then can we produce highly equilibrated samples that provide new insights into V valence at low fO2.

oxygen fugacity↗
NASA NTRS2021

Mars Exploration Rovers EDL Trajectory and Atmosphere Reconstruction using NewSTEP

This document describes the trajectory and atmosphere reconstruction of the Mars Exploration Rovers (Spirit and Opportunity) Entry, Descent, and Landing using the New Statistical Trajectory Estimation Program. The approach utilizes a Kalman filter to blend inertial measurement unit data with initial conditions and radar altimetry to obtain the inertial trajectory of the entry vehicle. The nominal aerodynamic database is then used in combination with the sensed accelerations to obtain estimates of the atmosphere-relative state. The reconstructed atmosphere profile is then blended with pre-flight models to construct an estimate of the as-flown atmosphere.

EDL↗
NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D CNN architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization are described as well as the results of application to three separate arc jet data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation.

Machine learning↗
NASA NTRSDate not supplied

1d-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D CNN architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization are described as well as the results of application to three separate arc jet data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation.

Machine learning↗
NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization are described as well as the results of application to three separate arc jet data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation.

Machine learning↗
NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗
NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗