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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 73 records · Page 4
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NASA NTRS2015

How to Enter, Fly In, and Exit the A-Train Constellation

The collaborative science obtained from the satellites in the A-Train is an unparalleled success. The constellation framework that has evolved is well-formulated and documented by its international members. Communication between teams is enhanced by a web-based Constellation Coordination System. Safety and correlated observations are ensured by defining independent control boxes with buffers in between. Each mission stays within its control box by regular drag makeup maneuvers. Annual inclination adjustments are coordinated by all missions to maintain their absolute and relative Mean Local Time of Ascending Node (MLTAN). Since the satellites are in different orbit planes their separation involves a three-dimensional triad made up of the along track separations, reference groundtracks and MLTAN's. For further safety, a Constellation Envelope has been defined to determine safe entry and exit orbits.

MLTAN↗
NASA NTRS1987

Training for long duration space missions

The successful completion of an extended duration manned mission to Mars will require renewed research effort in the areas of crew training and skill retention techniques. The current estimate of inflight transit time is about nine months each way, with a six month surface visit, an order of magnitude beyond previous U.S. space missions. Concerns arise when considering the level of skill retention required for highly critical, one time operations such as an emergency procedure or a Mars orbit injection. The factors responsible for the level of complex skill retention are reviewed, optimal ways of refreshing degraded skills are suggested, and a conceptual crew training design for a Mars mission is outlined. Currently proposed crew activities during a Mars mission were reviewed to identify the spectrum of skills which must be retained over a long time period. Skill retention literature was reviewed to identify those factors which must be considered in deciding when and which tasks need retraining. Task, training, and retention interval factors were identified. These factors were then interpreted in light of the current state of spaceflight and adaptive training systems.

Goldberg, Joseph H.↗
NASA NTRS1993

Conventional modeling of the multilayer perceptron using polynomial basis functions

A technique for modeling the multilayer perceptron (MLP) neural network, in which input and hidden units are represented by polynomial basis functions (PBFs), is presented. The MLP output is expressed as a linear combination of the PBFs and can therefore be expressed as a polynomial function of its inputs. Thus, the MLP is isomorphic to conventional polynomial discriminant classifiers or Volterra filters. The modeling technique was successfully applied to several trained MLP networks.

Chen, Mu-Song↗
NASA NTRS1996

The Hubble Space Telescope servicing missions: Past, present, and future operational challenges

The Hubble Space Telescope (HST) is a complex spacecraft designed to conduct leading edge scientific observations over a planned fifteen year mission lifetime. It was designed for servicing by the Space Shuttle to upgrade systems, replace failed components, and boost into a higher orbit. There are many operational challenges that must be addressed in preparing for and executing a Servicing Mission (SM) which range from both technical to managerial issues. This paper will be exploring the operational challenges faced by the HST Operations and Ground System Project in supporting the First Servicing Mission (FSM) and future Servicing Missions. We give special emphasis to those areas that helped ensure mission success. These areas include training, testing, and contingency planning.

William R Ochs↗
NASA NTRS2009

Remotely Piloted Vehicles for Experimental Flight Control Testing

A successful flight test and training campaign of the NASA Flying Controls Testbed was conducted at Naval Outlying Field, Webster Field, MD during 2008. Both the prop and jet-powered versions of the subscale, remotely piloted testbeds were used to test representative experimental flight controllers. These testbeds were developed by the Subsonic Fixed Wing Project s emphasis on new flight test techniques. The Subsonic Fixed Wing Project is under the Fundamental Aeronautics Program of NASA's Aeronautics Research Mission Directorate (ARMD). The purpose of these testbeds is to quickly and inexpensively evaluate advanced concepts and experimental flight controls, with applications to adaptive control, system identification, novel control effectors, correlation of subscale flight tests with wind tunnel results, and autonomous operations. Flight tests and operator training were conducted during four separate series of tests during April, May, June and August 2008. Experimental controllers were engaged and disengaged during fully autonomous flight in the designated test area. Flaps and landing gear were deployed by commands from the ground control station as unanticipated disturbances. The flight tests were performed NASA personnel with support from the Maritime Unmanned Development and Operations (MUDO) team of the Naval Air Warfare Center, Aircraft Division

Motter, Mark A.↗
NASA NTRS2009

Evolvable Neural Software System

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Curtis, Steven A.↗
NASA NTRSDate not supplied

Introducing Tropical Geometric Approaches to Delay Tolerant Networking Optimization

Delay Tolerant Networking (DTN) is the standard approach to the networking of space systems with the goal of supporting the Solar System Internet (SSI). Current space networks have a small scale and often depend on rigorously scheduled (pre-determined) contact opportunities; this manual approach inhibits scalability. The goal of this paper is to recast these scheduling problems in order to apply the optimization machinery of tropical geometry. Contact opportunities in space are dependent on such factors as orbital mechanics and asset availability, which induce time-varying connectivity; indeed, end-to-end connectivity might never occur. Routing optimization within this structure is classically difficult and typically utilizes Dijkstra's algorithm as applied to contact graphs. Alternatively, we follow the successes of tropical geometry in train schedule optimization, job assignments, and even traditional networking, by extending this approach to this more general (i.e. disconnected) problem space. These successes imply tropical geometry provides a useful framework in the context of DTNs, starting with applications to queuing theory and long-haul links. Recently, tropical geometry has been applied to parametric path optimization on graphs with variable edge weights. In this work, we extend these advances to account for the problem of routing in a space network, and find that tropical geometry is well-suited to the challenges offered by this new setting, including contact schedules featuring probabilities. Our approach leverages the combinatorial nature of the problem to give feasible shortest path trees in the presence of variable channel conditions and latency, evolving topologies, and uncertainty inherent in space routing. We discuss our tropical approach to DTN for two Python implementations, a Verilog Tropical ALU implementation, tropical frameworks for other parametric graph problems, and solution stability. Lastly, a program for future work is included to illuminate the path ahead.

Delay Tolerant Networking↗
NASA NTRS1989

Intelligent scenario generation for simulation-based training

A training scenario generator object database was developed to serve as a general-purpose mechanism for constructing the context needed to define a simulation scenario. It is found that the ability to automate the development of the input parameters required to produce a challenging simulation scenario targeted at a specific trainee can greatly enhance the efficiency of intelligent training systems. The approach described was used successfully in the payload-assist module deploy/intelligent computer-aided training system.

Loftin, R. Bowen↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗
NASA NTRS2006

Moving from Bilateral to Multilateral Medical Operations

When the ISS Integrated Medical Group moved to a multilateral configuration for the ASTROLAB mission, several challenges were encountered and overcome that allowed for a streamlined operational experience. Dating back to the early 1990s, the European Space Agency (ESA) has sent flight surgeon and Biomedical Engineering (BME) personnel to NASA-JSC and Russia to train for space flight operational support. This training was tailored towards the needs of particular Shuttle/Soyuz missions, and more generally for eventual ISS support. With the announcement of the ASTROLAB mission, NASA and ESA personnel worked together to develop a detailed training template for ESA BMEs to ensure successful support of the mission from the European Astronaut Center (EAC). This training included the deployment of ESA BMEs to JSC, as well as the development of a rotation of ISS-certified NASA BMEs to the EAC. In addition to training, NASA, ESA, and the Russian Federal Space Agency (FSA) worked together preflight to develop multilateral flight control support concepts and implementation plans. This resulted in flight control support schedules, operational rules of engagement, and the delineation of responsibilities. NASA also assisted ESA with the development and deployment of workstation displays to allow the ESA medical flight control team to monitor ISS telemetry from the EAC. The goal of this presentation is to provide details of the preflight preparation and in-flight support of the ASTROLAB mission by the ESA, NASA, and FSA medical support teams. In addition, it will identify lessons learned that will be implemented for future multilateral endeavors.

Roden, S.↗
NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS The following study seeks to inform the risk associated with altered sensorimotor and vestibular function impacting critical mission tasks. We aim to characterize the effects of short and long-duration weightlessness on manual control following G-transitions using simulated lunar landing on a six-degree-of-freedom (6DOF) motion base, a fixed base simulation, and a supervisory control tablet task. The primary goal is to understand the impact of spaceflight on crew ability to perform manual crew override and supervisory control. This aim will be assessed by comparing pre- versus postflight simulation performance in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). We hypothesize there will be postflight increases in the percent time that pilots are outside of the acceptable range for recommended vehicle state parameters and the reaction time for secondary cognitive tasks. Ground-based control subjects, who are demographically matched to the crew considering age (± 5 years) and gender, will undergo the same testing schedule as the crew to examine the effects of flight phase independent of microgravity exposure. The second aim is to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency. Crew performance for a sensorimotor perceptual test battery will evaluate motion perception tracking, roll nulling, and/or vection sensitivity using the 6DOF motion base. We hypothesize that a higher severity of vestibular alterations will be associated with increased percent time outside of guidance limits. Motion sickness severity and sleepiness will also be evaluated. To determine the impact of “just-in-time” training, the third aim seeks to compare performance during on-board lunar landing tasks conducted late in-flight to early postflight. We hypothesize that proficiency on the “just-in-time” laptop trainer late in mission will be positively correlated with early postflight proficiency on the same task. The final aim will establish assessments of performance, training protocols, and the learning progression in a ground-control cohort of first-time users. RESULTS The assessment of the learning progression associated with the piloting task on the motion base system with thirty ground subjects will be reported. Learning curves will be established across four distinct sessions and within session considering trial difficulty. The difficulty of the landing task can be modulated with the landing divert distance and cross or downrange difficulty. Results may include changes in performance across multiple trials of a multi-attribute lunar tablet supervisory control task. Preliminary investigations of eighteen subjects who completed vestibular threshold and motion perception tasks offer expected performance ranges for upcoming preflight crew evaluations. The results yielded an average roll threshold of 0.46 ± 0.30 deg/s and an average roll nulling root mean square error performance of 2.52 ± 0.52 deg/s. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the manual control risks associated with sensorimotor alterations. Ground testing will evaluate learning progression, refine training protocols, and serve as a control cohort for comparisons to crew performance. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, the Dynamic Skills Trainer (DST) Lab, and the Software, Robotics, and Simulation Division toward the development of the lunar landing simulation platforms. This project is funded by the Human Health Countermeasures Element.

Hannah M. Weiss↗
NASA NTRSDate not supplied

Supervisory Control with Dual Tasking in Post G-Transition Vehicle Landings

BACKGROUND Landing during exploration spaceflight may consist of both planned automated supervisory control and unplanned crew override. Supervisory control, particularly when performed under cognitive load with additional monitoring tasks, is essential for ensuring overall mission success during landing contingencies. Evaluating performance in a relevant Human Landing System (HLS) supervisory landing task after long-duration microgravity exposure can help identify potential risks from human error and sensorimotor alterations. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. Although training and landing aids facilitate successful landings despite disorientation, these adaptive changes may heighten cognitive demand, which must be considered in the landing strategy. It is important to characterize these effects as soon as possible following the G-transition while the sensorimotor system remains in a state of adaptive flux to inform appropriate countermeasures. METHODS A Multi-attribute Lunar Table Battery (MALTB) task was developed for an iOS tablet device to provide flexible crew testing and training capabilities in-flight and on the ground. Elements of the tablet task were derived from the Multi-Attribute Task Battery (MATB, Cegarra et al. 2020). The task requires crew members to study a map of a planned landing site and memorizing the terrain and surface landmarks to inform potential divert maneuvers during landing. The user will oversee a series of approaches through touchdown simulations on the tablet with an external camera view of the Lunar surface. The primary responsibility of the crew member will be to execute a divert if the guidance recommended site is erroneous (e.g., the guidance projected landing target is not within 10m of the planned landing site center), or the projected landing site is no longer suitable due to surface obstacles. Considering vehicle maneuverability and fuel reserves, the divert capabilities will diminish as the task progresses. In cases where a divert is initiated, a new landing target will need to be designated by the user and will be evaluated for the proximity to the original pre-planned site. A secondary operational monitoring task will challenge the user's cognitive reserve by requiring the user to maintain several gauges within acceptable limits and respond to a visual indicator while completing the landing approach. Outcome measures include distance from the planned landing site to the user-initiate divert landing location, ground slope at the new landing site, time to divert, the ability to accomplish the secondary monitoring tasks, and perceived workload. The tablet task is being evaluated in a ground-based study to determine the learning effect of first-time users. The tablet task will be utilized in a flight study to test performance multiple times postflight. Future potential testing in-flight have been identified for capsules with iOS tablet devices. Multi-attribute Lunar Table Battery Task MALTB comprises video footage of thirty distinct landing conditions. The landing scenarios feature various landing sites (n = 3), hazardous object sizes (n = 6), sun azimuth degrees (n = 4), camera modes (i.e., fixed or gimbaled), and navigation bias (i.e., true or false). Each seventy second trial uses a sixty-degree constant glideslope trajectory. The application architecture and layout include user identification setup and data storing, a guided walkthrough of the task and interface components, practice mode for task familiarization, and a modified Bedford workload scale administered following task completion. The time-based dependent measures are saved locally to the iOS Files application and post-processing scripts have been developed to evaluate the remaining measures of performance. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the landing risks associated with sensorimotor alterations. ACKNOWLEDGEMENTS: This project is funded by NASA’s Human Research Program Human Health Countermeasures Element. REFERENCES Cegarra J, Valery B, Avril E, Calmettes C, Navarro J (2020) OpenMATB: A Multi-Attribute Task Battery promoting task customization, software extensibility and experiment replicability. Behav Res Methods 52:1980-1990 doi: 10.3758/s13428-020-01364-w

Matthew McDonnell↗
NASA NTRS2010

3D Online Visualization and Synergy of NASA A-Train Data Using Google Earth

This poster presentation reviews the use of Google Earth to assist in three dimensional online visualization of NASA Earth science and geospatial data. The NASA A-Train satellite constellation is a succession of seven sun-synchronous orbit satellites: (1) OCO-2 (Orbiting Carbon Observatory) (will launch in Feb. 2013), (2) GCOM-W1 (Global Change Observation Mission), (3) Aqua, (4) CloudSat, (5) CALIPSO (Cloud-Aerosol Lidar & Infrared Pathfinder Satellite Observations), (6) Glory, (7) Aura. The A-Train makes possible synergy of information from multiple resources, so more information about earth condition is obtained from the combined observations than would be possible from the sum of the observations taken independently

Chen, Aijun↗
NASA NTRS2004

Results of a NASA Kennedy Space Center Earned Value Management Pilot Project

The Earn Value Management Pilot provided a tremendous amount of data on the strengths and weaknesses of the new financial system, the ability to support EVM from many viewpoints, the lack of tools for small to medium projects implementing EVM, and the training and environment necessary to successfully deploy EVM to all projects. This data along with other pilots will prove invaluable. Deploying EVM should not be taken lightly - a full assessment of capabilities and supporting infrastructure should be done prior to any deployment, and some very basic questions should be asked. For instance, will sufficient training be provided? Can the project managers readily and easily obtain all the necessary data? If EVM is to thrive in all projects regardless of cost, the transition should be as seamless as possible, minimizing cost and effort, and with the end user in mind. In setting up an EVM implementation, the question, "How does the project manager benefit from this process?" must remain at the forefront. Further research in this area is needed to answer the question,"Is EVM cost effective in small projects?" The authors welcome knowledge sharing with other organizations that are striving to gain the benefits of EVM on small projects.

Delgado, Hector N.↗
NASA NTRS1989

Space Station Freedom crew training

The nature of the Space Station Freedom Program presents an array of new and enhanced challenges which need to be addressed en route to developing an effective and affordable infrastructure for crew training. Such an infrastructure is essential for the safety and success of the program. The three major challenges that affect crew training are the long lifetime of the program (thirty years), the interdependence of successive increments, and the participation of the three International Partners (Canada, European Space Agency, and Japan) and a myriad of experimenters. This paper addresses these major challenges as they drive the development of a crew training capability and the actual conduct of crew training.

Bobko, Karol J.↗
NASA NTRS1990

Space Station Freedom crew training

The nature of the Space Station Freedom Program presents an array of new and enhanced challenges which need to be addressed en route to developing an effective and affordable infrastructure for crew training. Such an infrastructure is essential for the safety and success of the program. The three major challenges that affect crew training are the long lifetime of the program (thirty years), the interdependence of successive increments, and the participation of the three International Partners (Canada, European Space Agency, and Japan) and a myriad of experimenters. This paper addresses these major challenges as they drive the development of a crew training capability and the actual conduct of crew training.

Space Flight/education/organization & administrati↗
NASA NTRS1992

Formal methods technology transfer: Some lessons learned

IBM has a long history in the application of formal methods to software development and verification. There have been many successes in the development of methods, tools and training to support formal methods. And formal methods have been very successful on several projects. However, the use of formal methods has not been as widespread as hoped. This presentation summarizes several approaches that have been taken to encourage more widespread use of formal methods, and discusses the results so far. The basic problem is one of technology transfer, which is a very difficult problem. It is even more difficult for formal methods. General problems of technology transfer, especially the transfer of formal methods technology, are also discussed. Finally, some prospects for the future are mentioned.

Hamilton, David↗