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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 NTRS2007

The Sensor Management for Applied Research Technologies (SMART) Project

NASA seeks on-demand data processing and analysis of Earth science observations to facilitate timely decision-making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep "learning curve" associated with each sensor, data type, and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output.

Goodman, Michael↗
NASA NTRS2009

Reliability of Maximal Strength Testing in Novice Weightlifters

The one repetition maximum (1RM) is a criterion measure of muscle strength. However, the reliability of 1RM testing in novice subjects has received little attention. Understanding this information is crucial to accurately interpret changes in muscle strength. To evaluate the test-retest reliability of a squat (SQ), heel raise (HR), and deadlift (DL) 1RM in novice subjects. Twenty healthy males (31 plus or minus 5 y, 179.1 plus or minus 6.1 cm, 81.4 plus or minus 10.6 kg) with no weight training experience in the previous six months participated in four 1RM testing sessions, with each session separated by 5-7 days. SQ and HR 1RM were conducted using a smith machine; DL 1RM was assessed using free weights. Session 1 was considered a familiarization and was not included in the statistical analyses. Repeated measures analysis of variance with Tukey fs post-hoc tests were used to detect between-session differences in 1RM (p.0.05). Test-retest reliability was evaluated by intraclass correlation coefficients (ICC). During Session 2, the SQ and DL 1RM (SQ: 90.2 }4.3, DL: 75.9 }3.3 kg) were less than Session 3 (SQ: 95.3 }4.1, DL: 81.5 plus or minus 3.5 kg) and Session 4 (SQ: 96.6 }4.0, DL: 82.4 }3.9 kg), but there were no differences between Session 3 and Session 4. HR 1RM measured during Session 2 (150.1 }3.7 kg) and Session 3 (152.5 }3.9 kg) were not different from one another, but both were less than Session 4 (157.5 }3.8 kg). The reliability (ICC) of 1RM measures for Sessions 2-4 were 0.88, 0.83, and 0.87, for SQ, HR, and DL, respectively. When considering only Sessions 3 and 4, the reliability was 0.93, 0.91, and 0.86 for SQ, HR, and DL, respectively. One familiarization session and 2 test sessions (for SQ and DL) were required to obtain excellent reliability (ICC greater than or equal to 0.90) in 1RM values with novice subjects. We were unable to attain this level of reliability following 3 HR testing sessions therefore additional sessions may be required to obtain an ICC of greater than or equal to 0.90. Future resistive exercise studies should consider the reliability of specific measures to ensure that changes in strength with training are attributable to training and not learning effects associated with 1RM testing.

Loehr, James A.↗
NASA NTRS2011

Oxygen Uptake Responses to Submaximal Exercise Loads Do Not Change During Long-Duration Space Flight

In previous publications we have reported that the heart rate (HR) responses to graded submaximal exercise tests are elevated during long-duration International Space Station (ISS) flights. Furthermore, the elevation in HR appears greater earlier, rather than later, during the missions. A potential confounder in the interpretation of HR results from graded exercise tests on ISS is that the cycle ergometer used (CEVIS) is vibration-isolated from the station structure. This feature causes the CEVIS assembly to sway slightly during its use and debriefing comments by some crewmembers indicate that there is a "learning curve" associated with CEVIS use. Therefore, one could not exclude the possibility that the elevated HRs experienced in the early stages of ISS missions were related to a lowered metabolic efficiency of CEVIS exercise that would raise the submaximal oxygen uptake (VO2) associated with graded exercise testing work rates.

Moore, Alan D., Jr.↗
NASA NTRS2011

Assembly of 5.5-Meter Diameter Developmental Barrel Segments for the Ares I Upper Stage

Full scale assembly welding of Ares I Upper Stage 5.5-Meter diameter cryogenic tank barrel segments has been performed at the Marshall Space Flight Center (MSFC). One full-scale developmental article produced under the Ares 1 Upper Stage project is the Manufacturing Demonstration Article (MDA) Barrel. This presentation will focus on the welded assembly of this barrel section, and associated lessons learned. Among the MDA articles planned on the Ares 1 Program, the Barrel was the first to be completed, primarily because the process of manufacture from piece parts (barrel panels) utilized the most mature friction stir process planned for use on the Ares US program: Conventional fixed pin Friction Stir Welding (FSW). This process is in use on other space launch systems, including the Shuttle s External Tank, the Delta IV common booster core, the Delta II, and the Atlas V rockets. The goals for the MDA Barrel development were several fold: 1) to prove out Marshall Space Flight Center s new Vertical Weld Tool for use in manufacture of cylindrical barrel sections, 2) to serve as a first run for weld qualification to a new weld specification, and 3) to provide a full size cylindrical section for downstream use in precision cleaning and Spray-on Foam Insulation development. The progression leading into the welding of the full size barrel included sub scale panel welding, subscale cylinder welding, a full length confidence weld, and finally, the 3 seamed MDA barrel processing. Lessons learned on this MDA program have been carried forward into the production tooling for the Ares 1 US Program, and in the use of the MSFC VWT in processing other large scale hardware, including two 8.4 meter diameter Shuttle External Tank barrel sections that are currently being used in structural analysis to validate shell buckling models.

Carter, Robert W.↗
NASA NTRS2009

Experimental Results of Integrated Refrigeration and Storage System Testing

Launch operations engineers at the Kennedy Space Center have identified an Integrated Refrigeration and Storage system as a promising technology to reduce launch costs and enable advanced cryogenic operations. This system uses a close cycle Brayton refrigerator to remove energy from the stored cryogenic propellant. This allows for the potential of a zero loss storage and transfer system, as well and control of the state of the propellant through densification or re-liquefaction. However, the behavior of the fluid in this type of system is different than typical cryogenic behavior, and there will be a learning curve associated with its use. A 400 liter research cryostat has been designed, fabricated and delivered to KSC to test the thermo fluid behavior of liquid oxygen as energy is removed from the cryogen by a simulated DC cycle cryocooler. Results of the initial testing phase focusing on heat exchanger characterization and zero loss storage operations using liquid oxygen are presented in this paper. Future plans for testing of oxygen densification tests and oxygen liquefaction tests will also be discussed. KEYWORDS: Liquid Oxygen, Refrigeration, Storage

Notardonato, W. U.↗
NASA NTRS2014

Cost Analysis in a Multi-Mission Operations Environment

Spacecraft control centers have evolved from dedicated, single-mission or single mission-type support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multi-mission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the decreasing flight rate. This paper presents the issues encountered during the HOSC cost analysis process, and the associated lessons learned. These lessons can be used when planning for a new multi-mission operations center or in the transformation from a dedicated control center to multi-center operations, as an aid in defining processes that support future cost analysis and estimation. The lessons can also be used by mature service-oriented, multi-mission control centers to streamline or refine their cost analysis process.

Felton, Larry↗
NASA NTRS2014

Cost Analysis In A Multi-Mission Operations Environment

Spacecraft control centers have evolved from dedicated, single-mission or single missiontype support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multimission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the decreasing flight rate. This paper presents the issues encountered during the HOSC cost analysis process, and the associated lessons learned. These lessons can be used when planning for a new multi-mission operations center or in the transformation from a dedicated control center to multi-center operations, as an aid in defining processes that support future cost analysis and estimation. The lessons can also be used by mature serviceoriented, multi-mission control centers to streamline or refine their cost analysis process.

Newhouse, M.↗
NASA NTRS2016

Design, Development and Hotfire Testing of Monolithic Copper and Bimetallic Additively Manufactured Combustion Chambers

NASA and industry partners are working towards fabrication process development to reduce costs and schedules associated with manufacturing liquid rocket engine components with the goal of reducing overall mission costs. One such technique being evaluated is powder-bed fusion or selective laser melting (SLM) otherwise commonly referred to as additive manufacturing. The NASA Low Cost Upper Stage Propulsion (LCUSP) program was designed to develop processes and material characterization for the GRCop-84 copper-alloy commensurate with powder bed additive manufacturing, evaluate bimetallic deposition and complete testing of a full scale combustion chamber. As part of this development, the process has been transferred to industry partners to enable a long-term supply chain of monolithic copper combustion chambers. As a direct spin off of this program, NASA is working with industry partners to further develop the printing process for the GRCop-84 material in addition to the C-18150 (CuCrZr) material. To advance the process further and allow for optimization with multiple materials, NASA is also investigating the feasibility of bimetallic additively manufactured chambers. A 1.2k sized thrust-chamber was designed and developed to compare the printing process of the GRCop-84 and C-18150 SLM materials. A series of similar MCC liners also completed development with an Inconel 625 jacket bonded to the GRcop-84 liner evaluating direct metal deposition (DMD) laser and arc-based techniques. This paper describes the design, development, manufacturing and testing of these combustion chambers and associated lessons learned throughout the design and development process.

Gradl, Paul↗
NASA NTRS2017

Development and Hot-fire Testing of Additively Manufactured Copper Combustion Chambers for Liquid Rocket Engine Applications

NASA and industry partners are working towards fabrication process development to reduce costs and schedules associated with manufacturing liquid rocket engine components with the goal of reducing overall mission costs. One such technique being evaluated is powder-bed fusion or selective laser melting (SLM), commonly referred to as additive manufacturing (AM). The NASA Low Cost Upper Stage Propulsion (LCUSP) program was designed to develop processes and material characterization for GRCop-84 (a NASA Glenn Research Center-developed copper, chrome, niobium alloy) commensurate with powder-bed AM, evaluate bimetallic deposition, and complete testing of a full scale combustion chamber. As part of this development, the process has been transferred to industry partners to enable a long-term supply chain of monolithic copper combustion chambers. To advance the processes further and allow for optimization with multiple materials, NASA is also investigating the feasibility of bimetallic AM chambers. In addition to the LCUSP program, NASA has completed a series of development programs and hot-fire tests to demonstrate SLM GRCop-84 and other AM techniques. NASA's efforts include a 4K lbf thrust liquid oxygen/methane (LOX/CH4) combustion chamber and subscale thrust chambers for 1.2K lbf LOX/hydrogen (H2) applications that have been designed and fabricated with SLM GRCop-84. The same technologies for these lower thrust applications are being applied to 25-35K lbf main combustion chamber (MCC) designs. This paper describes the design, development, manufacturing and testing of these numerous combustion chambers, and the associated lessons learned throughout their design and development processes.

Gradl, Paul R.↗
NASA NTRS2017

Development and Hotfire Testing of Additively Manufactured Copper Combustion Chambers for Liquid Rocket Engine Applications

NASA and industry partners are working towards fabrication process development to reduce costs and schedules associated with manufacturing liquid rocket engine components with the goal of reducing overall mission costs. One such technique being evaluated is powder-bed fusion or selective laser melting (SLM), commonly referred to as additive manufacturing (AM). The NASA Low Cost Upper Stage Propulsion (LCUSP) program was designed to develop processes and material characterization for GRCop-84 (a NASA Glenn Research Center-developed copper, chrome, niobium alloy) commensurate with powder bed AM, evaluate bimetallic deposition, and complete testing of a full scale combustion chamber. As part of this development, the process has been transferred to industry partners to enable a long-term supply chain of monolithic copper combustion chambers. To advance the processes further and allow for optimization with multiple materials, NASA is also investigating the feasibility of bimetallic AM chambers. In addition to the LCUSP program, NASA’s Marshall Space Flight Center (MSFC) has completed a series of development programs and hot-fire tests to demonstrate SLM GRCop-84 and other AM techniques. MSFC’s efforts include a 4,000 pounds-force thrust liquid oxygen/methane (LOX/CH4) combustion chamber. Small thrust chambers for 1,200 pounds-force LOX/hydrogen (H2) applications have also been designed and fabricated with SLM GRCop-84. Similar chambers have also completed development with an Inconel 625 jacket bonded to the GRCop-84 material, evaluating direct metal deposition (DMD) laser- and arc-based techniques. The same technologies for these lower thrust applications are being applied to 25,000-35,000 pounds-force main combustion chamber (MCC) designs. This paper describes the design, development, manufacturing and testing of these numerous combustion chambers, and the associated lessons learned throughout their design and development processes.

Gradl, Paul R.↗
NASA NTRS2018

Using Board Games as Subject Matter for Developing Expertise in Model-Based Systems Engineering

As more organizations transition from traditional document-centric systems engineering to a model-based approach, many are challenged to train their staff in new languages, tools, and methodologies, while managing the expectations of stakeholders and their expected model outcomes. In particular, challenges associated with learning a new modeling language and developing skills in the 'art' of modeling present organizations with formidable obstacles to realizing this transition. This paper hypothesizes that systems engineers may more readily learn how to correctly model with SysML, and develop intuition about the art of modeling and using patterns, if their learning references a commonly and thoroughly-understood subject, such as a board game. This paper presents a case for the use of board games as subject matter for new modelers. It demonstrates the concept with a sample model of Hasbro's popular board game, Monopoly, and discusses the limitations of this approach and potential adaptations that may broaden the applicability of the learned skills to projects. Finally, results from a small feasibility assessment and concepts for more formal study to evaluate the hypothesis are presented.

Model-Based Systems Engineering↗
NASA NTRS2018

Using Board Games as Subject Matter for Developing Expertise in Model-Based Systems Engineering

As more organizations transition from traditional document-centric systems engineering to a model-based approach, many are challenged to train their staff in new languages, tools, and methodologies, and manage the expectations of stakeholders and their expected model outcomes. In particular, challenges associated with learning a new modeling language and developing skills in the 'art' of modeling present organizations with formidable obstacles to realizing this transition. This paper hypothesizes that systems engineers may more readily learn how to correctly model with SysML, and develop intuition about the art of modeling and using patterns, if their learning references a commonly and thoroughly-understood subject matter, such as a board game. This paper presents a case for the use of board games as subject matter for new modelers, demonstrates the concept with a sample model of Hasbro's popular board game, Monopoly, and discusses the limitations of this approach and potential adaptations that may broaden the applicability of the learned skills to projects.

Systems Engineering↗
NASA NTRSDate not supplied

Search Enhancements using Natural Language Processing Techniques

NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) is one of the 12 NASA Science Mission Directorate Data Centers. The main goal of GESDISC is to provide earth science data, information, and services to the earth science data community. Consequently, data discovery is at the center of our mission and our search engine is the primary tool for our users to interact, find, and access our data. Existing search approaches are largely focused on hard-matching of keywords in the search query with dataset metadata. Here we propose to expand the search by introducing a complementary natural language processing (NLP) search. At the heart of our proposed NLP search, we trained a joint embedding using scientific text corpus and a curated set of dataset metadata. The embedding learns the association between words in our dataset metadata and those of the scientific text corpus. This enables us to go beyond simple hard-matching of a query and data set metadata and have a notion of “similarity” between the search query and the datasets. We further integrated our NLP search into the Elastic Search (ES) framework leveraging similarity search capabilities offered through the “dense_vector” field type. Our preliminary evaluations show that our proposed NLP search has the potential to be utilized to complement the existing search engine and serve as a base for a dataset recommendation system.

Armin Mehrabian↗
NASA NTRSDate not supplied

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗
NASA NTRSDate not supplied

Uncertainty in Servicing and Assembly Tasks for Space Robotic Manipulators

This presentation will discuss a subset of the sources of uncertainty that impact autonomous in-space servicing, assembly, and manufacturing missions. These include robotic manipulator modeling uncertainties in both kinematics and dynamics, perception error associated machine learning models for pose estimation, and sensor noise. Mitigation strategies will be discussed including the incorporation of capture envelopes in the design of robotic tools and selection of robot goal poses to minimize end-effector sensitivity in manipulators with redundant degrees of freedom.

robotics↗
NASA NTRSDate not supplied

Big Data Challenges at CCMC

Like other research centers, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) at NASA Goddard Space Flight Center (GSFC) is also experiencing the big data challenges. CCMC hosts over 80 space weather models for Runs On Request (ROR), Continuous Runs and Instant Runs simulation services for the research community. In addition, CCMC has started to support simulation output onboarding in response to the Open Science initiative. Overall, we have accumulated over petabytes of simulation output data and are rapidly growing. In this presentation, we will discuss our data and storage challenges. We will present our attempts to address our challenges and any associated lessons learned. CCMC uses Apache Airflow to ensure data transfer is consistent. We will give a brief overview on how we leverage Apache Airflow to enhance our environment.

space weather↗
NASA NTRSDate not supplied

Big Data Challenges at the Community Coordinated Modeling Center (CCMC)

Like other research centers, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) at NASA Goddard Space Flight Center (GSFC) is also experiencing the big data challenges. CCMC hosts over 80 space weather models for Runs On Request (ROR), Continuous Runs and Instant Runs simulation services for the research community. In addition, CCMC has started to support simulation output onboarding in response to the Open Science initiative. Overall, we have accumulated over petabytes of simulation output data and are rapidly growing. In this presentation, we will discuss our data and storage challenges. We will present our attempts to address our challenges and any associated lessons learned. CCMC uses Apache Airflow to ensure data transfer is consistent. We will give a brief overview on how we leverage Apache Airflow to enhance our environment.

space weather↗
NASA NTRS1990

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Chen, Alexander Y.↗