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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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Applied Multi-Mission Telemetry Processing and Display for Operations, Integration, Training, Playback and Event Reconstruction

Conveying spacecraft health and status information to mission engineering personnel during various mission phases, including mission operations, is a requirement to achieve a successful mission. For NASA/JPL spacecraft, that often means displaying hundreds of telemetry channels from a variety of sensors and components emitting data at rates varying from 1hz-100hz (and faster) in a way that allows the operations team to quickly evaluate the health of the vehicle, identify any off-nominal states and resolve any issues. In this paper we will discuss the system design, requirements and use cases of three telemetry processing and visualization systems recently developed and deployed by our team for NASA's Low Density Supersonic Decelerator (LDSD) test vehicle, NASA's Soil Moisture Active/Passive (SMAP) orbiter, and JPL's Sampling Lab Universal Robotic Manipulator (SLURM) test bed.

simulation↗
NASA NTRS2017

The Effects of Long-Duration Spaceflight on Training Retention and Transfer

Training our crew members for long duration, exploration-class missions will have to maximize long-term retention and transfer of the trained skills. The expected duration of the missions, our inability to predict all the possible tasks the crew will be called upon to perform, and the low training-to-mission time ratio require that the training be maximally effective such that the skills acquired during training will be retained and will be transferrable across a wide range of specific tasks that are different from the particular tasks used during training. However, to be able to design training that can achieve these ambitious goals, we must first understand the ways in which long-duration spaceflight affects training retention and transfer. Current theories of training retention and transfer are largely based on experimental studies conducted at university laboratories using undergraduate students as participants. Furthermore, all such studies have been conducted on Earth. We do not know how well the results of these studies predict the performance of crew members. More specifically, we do not know how well the results of these studies predict the performance of crew members in space and especially during long-duration missions. To address this gap in our knowledge, the current on-going study seeks to test the null hypothesis that performance of university undergraduate students on Earth on training retention and transfer tests do in fact predict accurately the performance of crew members during long-duration spaceflights. To test this hypothesis, the study employs a single 16-month long experimental protocol with 3 different participant groups: undergraduate university students, crew members on the ground, and crew members in space. Results from this study will be presented upon its completion. This poster presents results of study trials of the two tasks used in this study: a data entry task and a mapping task. By researching established training principles, by examining future needs, and by using current practices in spaceflight training as test beds, this research project is mitigating program risks and generating templates and requirements to meet future training needs.

ISS↗
NASA NTRS2017

ISS Training Best Practices and Lessons Learned

Training our crew members for long duration exploration-class missions (LDEM) will have to be qualitatively and quantitatively different from current training practices. However, there is much to be learned from the extensive experience NASA has gained in training crew members for missions on board the International Space Station (ISS). Furthermore, the operational experience on board the ISS provides valuable feedback concerning training effectiveness. Keeping in mind the vast differences between current ISS crew training and training for LDEM, the needs of future crew members, and the demands of future missions, this ongoing study seeks to document current training practices and lessons learned. The goal of the study is to provide input to the design of future crew training that takes as much advantage as possible of what has already been learned and avoids as much as possible past inefficiencies. Results from this study will be presented upon its completion. By researching established training principles, examining future needs, and by using current practices in spaceflight training as test beds, this research project is mitigating program risks and generating templates and requirements to meet future training needs.

ISS↗
NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms Using Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted; one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

nasa-dlr research collaboration↗
NASA NTRS2018

ISS Training Best Practices and Lessons Learned

Training our crew members for long-duration Deep Space Transport (DST) missions will have to be qualitatively and quantitatively different from current training practices. However, there is much to be learned from the extensive experience NASA has gained in training crew members for missions on board the International Space Station (ISS). Furthermore, the operational experience on board the ISS provides valuable feedback concerning training effectiveness. Keeping in mind the vast differences between current ISS crew training and training for DST missions, the needs of future crew members, and the demands of future missions, this ongoing study seeks to document current training practices and lessons learned. The goal of the study is to provide input to the design of future crew training that takes as much advantage as possible of what has already been learned and avoids as much as possible past inefficiencies. Results from this study will be presented upon its completion. By researching established training principles, examining future needs, and by using current practices in spaceflight training as test beds, this research project is mitigating program risks and generating templates and requirements to meet future training needs.

training↗
NASA NTRS2018

The Effects of Long-Duration Spaceflight on Training Retention and Transfer

Training our crew members for long duration, exploration-class missions will have to maximize long-term retention and transfer of the trained skills. The expected duration of the missions, our inability to predict all the possible tasks the crew will be called upon to perform, and the low training-to-mission time ratio require that the training be maximally effective such that the skills acquired during training will be retained and will be transferrable across a wide range of specific tasks that are different from the particular tasks used during training. However, to be able to design training that can achieve these ambitious goals, we must first understand the ways in which long-duration spaceflight affects training retention and transfer. Current theories of training retention and transfer are largely based on experimental studies conducted at university laboratories using undergraduate students as participants. Furthermore, all such studies have been conducted on Earth. We do not know how well the results of these studies predict the performance of crew members. More specifically, we do not know how well the results of these studies predict the performance of crew members in space and especially during long-duration missions. To address this gap in our knowledge, the current on-going study seeks to test the null hypothesis that performance of university undergraduate students on Earth on training retention and transfer tests do in fact predict accurately the performance of crew members during long-duration spaceflights. To test this hypothesis, the study employs a single 16-month long experimental protocol with 3 different participant groups: undergraduate university students, crew members on the ground, and crew members in space. Results from this study will be presented upon its completion. This poster presents results of study trials of the two tasks used in this study: a data entry task and a mapping task. By researching established training principles, by examining future needs, and by using current practices in spaceflight training as test beds, this research project is mitigating program risks and generating templates and requirements to meet future training needs.

training↗
NASA NTRS2012

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U.S. Southern Great Plains

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation is applied to the dry/wet regimes exhibited in this region, and in the process, a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling test bed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger toward the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g., reanalysis products) in the context of their integrated impacts on the process chain connecting the land surface to the PBL and in support of hydrological anomalies.

southern plains↗
NASA NTRS2018

Water Capture Device Signal Integration Board

I am a junior in electrical engineering at Arizona State University, and this is my second internship at Johnson Space Center. I am an intern in the Command and Data Handling Branch of Avionics Division (EV2), my previous internship was also in EV2. During my previous internship I was assigned to the Water Capture Device payload, where I designed a prototype circuit board for the electronics system of the payload. For this internship, I have come back to the Water Capture Device project to further the work on the electronics design I completed previously. The Water Capture Device is an experimental payload to test the functionality of two different phase separators aboard the International Space Station (ISS). A phase separator sits downstream of a condensing heat exchanger (CHX) and separates the water from the air particles for environmental control on the ISS. With changing CHX technology, new phase separators are required. The goal of the project is to develop a test bed for the two phase separators to determine the best solution.

Chamberlin, Kathryn J.↗
NASA NTRS2018

A Selection of Current NASA and Other Space Related Work in Christchurch and the Antarctic with Ideas for the Future

Outline: A brief (extremely) overview of NASA missions and how they relate to Christchurch and the Antarctic; Airborne missions operating out of Christchurch - SOFIA - DC-8 - ER-2 - Super Pressure Balloons; Uses of the Antarctic by NASA and others, examples - mega dunes, a Mars topological analog in the Antarctic - The Don Juan Pond, geology, geography and weather interaction to Mars - jurisdictional analog for a Mars Station - Human Research Program - Balloons on Ice; Looking Forward - Europa mission tests - Technology test beds for Lunar/Martian stations - Earth science.

outreach↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2018

Second-Generation Design of Micro-Spec: A Medium-Resolution, Submillimeter-Wavelength Spectrometer-on-a-Chip

Micro-Spec (μ-Spec) is a direct-detection spectrometer which integrates all the components of a diffraction-grating spectrometer onto a ∼10-cm2 chip through the use of superconducting microstrip transmission lines on a single-crystal silicon substrate. A second-generation μ-Spec is being designed to operate with a spectral resolution of 512 in the submillimeter (500-1000 μm, 300-600 GHz) wavelength range, a band of interest for several spectroscopic applications in astrophysics. High altitude balloon missions would provide the first test bed to demonstrate the μ-Spec technology in a space-like environment and would be an economically viable venue for multiple observation campaigns. This work reports on the current status of the instrument design and will provide a brief overview of each instrument subsystem. Particular emphasis will be given to the design of the spectrometer's two-dimensional diffractive region, through which the light of different wavelengths is focused on the detectors along the focal plane. An optimization process is employed to generate geometrical configurations of the diffractive region that satisfy specific requirements on spectrometer size, operating spectral range, and performance. An optical design optimized for balloon missions will be presented in terms of geometric layout, spectral purity, and efficiency.

Cataldo, G.↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES- Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2018

In-Space Manufacturing at NASA Marshall Space Flight Center: A Portfolio of Fabrication and Recycling Technology Development for the International Space Station

The in-space manufacturing project at NASA Marshall Space Flight Center seeks to mature the manufacturing capabilities which will be needed on long duration, long endurance human spaceflight missions. The ability to manufacture materials and parts in space rather than launching them from earth has the potential to reduce logistics requirements and enhance crew safety. The International Space Station serves as a unique orbiting test bed for in-space manufacturing technology development for NASA and its commercial partners. This paper provides an overview of the projects currently in the in-space manufacturing technology portfolio and key technology development efforts in the past year.

Prater, Tracie↗
NASA NTRS2018

Bigelow Expandable Activity Module (BEAM) ISS Year - Two

Bigelow Expandable Activity Module's (BEAM) life has been extended and in addition to being a test bed of the first human-rated expandable space module, BEAM will be utilized as an ISS (International Space Station) stowage module. Hear about BEAM's on-orbit performance as well as highlights of BEAM's use on ISS as a technology demonstration.

BEAM↗
NASA NTRS2016

Synthetic Biologic Membrane

The International Space Station (ISS) is a test bed for the technologies that will be used to travel to Mars and beyond. The lessons learned from operating the ISS provide valuable direction to future research and technology development programs. One of the most critical and complicated subsystems on ISS is the life support system. The life support system keeps the crew alive by recycling both air and water. The ISS water recycling system has been operating since 2009 and one of the main lessons learned is that reliability is a key technology performance metric. In the long run reliability is a key cost driver and is a critical factor in insuring crew safety. For long duration missions such as the exploration of Mars, where resupply of spare parts from Earth is difficult if not impossible, reliability is even more important. This presentation will cover research into improving the reliability of ISS systems. It will discuss research into the development of a biomimetic membrane materials that provides self-regeneration capabilities for water recycling systems. It will also cover research into past failures of the ISS water recycling system caused by astronaut bone loss and the build-up of trace contaminates in the cabin.

Biology↗
NASA NTRS2016

From Rural to Urban Environments: Human/Systems Simulation Research for Low Altitude UAS Traffic Management (UTM)

This paper describes the human/systems simulation research within NASA's UAS (Unmanned Aircraft System) Traffic Management (UTM) project. The paper starts with a short description of the UTM project, then presents the UTM development schedule briefly, before leading into more detailed discussions of the simulation test beds current capabilities, as well as the ongoing and planned human/systems research activities.

unmanned aircraft systems↗
NASA NTRS2019

An Initial Analysis of Automating Conjunction Assessment and Collision Avoidance Planning in Space Traffic Management

We introduce a framework that automates the process of assessing potential satellite conjunctions in space, and generating collision avoidance maneuvers to support mitigation efforts within a novel space traffic management (STM) architecture. A software implementation of the framework was developed in a MATLAB-STK integrated environment, however, the concept and framework is agnostic to the language or environment. The software pulls from existing catalogs of spaceborne objects and ingests user-defined parameters to produce conjunction data, which could potentially aid collision avoidance planning in the STM architecture. The utility of the software in maneuver planning and exploring a performance-based tradespace of actions is demonstrated using three example cases: one-to-one conjunction, one-versus-four conjunctions, and a near head-on collision. The framework also provides a test-bed for the use of application programming interfaces (APIs) to demonstrate machine-to-machine communication between entities in our proposed STM architecture. Results from this software implementation are expected to aid distributed decision-making among various stakeholders, and inform efficient, autonomous, structured but flexible concept of operations within STM.

Space Systems Engineering↗
NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗

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