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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 163 records · Page 9

Materials Science Experiments on the International Space Station

The Performance Goal for NASA's Microgravity Materials Science Program reads "Use microgravity to establish and improve quantitative and predictive relationships between the structure, processing and properties of materials." The advent of the International Space Station will open up a new era in Materials Science Research including the ability to perform long term and frequent experiments in microgravity. As indicated the objective is to gain a greater understanding of issues of materials science in an environment in which the force of gravity can be effectively switched off. Thus gravity related issues of convection, buoyancy and hydrostatic forces can be reduced and the science behind the structure/processing/properties relationship can more easily be understood. The specific areas of research covered within the program are (1) the study of Nucleation and Metastable States, (2) Prediction and Control of Microstructure (including pattern formation and morphological stability), (3) Phase Separation and Interfacial Stability, (4) Transport Phenomena (including process modeling and thermophysical properties measurement), and (5) Crystal Growth, and Defect Generation and Control. All classes of materials, including metals and alloys, glasses and ceramics, polymers, electronic materials (including organic and inorganic single crystals), aerogels and nanostructures, are included in these areas. The principal experimental equipment available to the materials scientist on the International Space Station (ISS) will be the Materials Science Research Facility (MSRF). Each of these systems will be accommodated in a single ISS rack, which can operate autonomously, will accommodate telescience operations, and will provide real time data to the ground. Eventual plans call for three MSRF racks, the first of which will be shared with the European Space Agency (ESA). Under international agreements, ESA and other partners will provide some of the equipment, while NASA covers launch and integration costs. The MSRF facilities will include modular components, which can be exchanged to provide inserts specifically matched to the engineering requirements of the particular Principal Investigator. To defray costs and avoid duplication of engineering effort NASA is also pursuing the possibility of using facilities provided by international partners. By this means it is anticipated that all of the types of research outlined in the previous paragraph can be done on the ISS.

Gillies, Donald C.↗

Autonomously generating operations sequences for a Mars Rover using AI-based planning

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.

Mars Rover↗

Autonomous Sensorweb Operations for Integrated Space, In-Situ Monitoring of Volcanic Activity

We have deployed and demonstrated operations of an integrated space in-situ sensorweb for monitoring volcanic activity. This sensorweb includes a network of ground sensors deployed to the Mount Saint Helens volcano as well as the Earth Observing One spacecraft. The ground operations and space operations are interlinked in that ground-based intelligent event detections can cause the space segment to acquire additional data via observation requests and space-based data acquisitions (thermal imagery) can trigger reconfigurations of the ground network to allocate increased bandwidth to areas of the network best situated to observe the activity. The space-based operations are enabled by an automated mission planning and tasking capability which utilizes several Opengeospatial Consortium (OGC) Sensorweb Enablement (SWE) standards which enable acquiring data, alerts, and tasking using web services. The ground-based segment also supports similar protocols to enable seamless tasking and data delivery. The space-based segment also supports onboard development of data products (thermal summary images indicating areas of activity, quicklook context images, and thermal activity alerts). These onboard developed products have reduced data volume (compared to the complete images) which enables them to be transmitted to the ground more rapidly in engineering channels.

Chien, Steve A.↗

The ISECG* Global Exploration Roadmap as Context for Robotic and Human Exploration Operations

The International Space Exploration Coordination Group (ISECG) Global Exploration Roadmap (GER) provides a broad international context for understanding how robotic missions and robotic assets can enable future human exploration of multiple destinations. This presentation will provide a brief high-level review of the GER with a focus on key robotic missions and robotic assets that can provide enabling technology advancements and that also raise interesting operational challenges in both the near-term and long-term. The GER presently features a variety of robotic missions and robotic assets that can provide important technology advancements as well as operational challenges and improvements, in areas ranging from: (a) leveraging the International Space Station, (b) planetary science robotic missions to potential human destinations, (c) micro-g body proximity operations (e.g. asteroids), (d) autonomous operations, (e) high and low-latency telerobotics, (f) human assisted sample return, and (g) contamination control. This presentation will highlight operational and technology challenges in these areas that have feed forward implications for human exploration.

telerobotics↗

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Medical Decision Support Systems↗

Blockchain Application Within a Multi-Sensor Satellite Architecture

With the thrust towards multi-sensor satellite architectures for earth and space exploration, such as constellations and swarms, new technologies are required to enable the transition to this future capability. One of the areas of interest is establishing secure, efficient and prioritized data and command communication pathways among ground and space-based sources for such systems. This paper presents early research results on the potential role, capabilities and value of blockchain usage within constellation and swarm satellite architectures. It demonstrates the use of blockchain's smart contract and distributed ledger capabilities for secure and prioritized multi-sensor satellite collaborative data exchanges, as well as the logging and tracking of command and control events. Adapting and utilizing this emerging technology will aid in addressing technology gaps expected from future constellation flight architectures, such as managing collective computational operations (correlation), dynamic and autonomous observation planning, time-critical events, and provenance tied to ground and space-based autonomous operations and control recordkeeping. In this scenario blockchain is applied in encrypted command transmittal to multiple, yet specific, entities enabling acknowledgement transmittals, performance scalability, and automatic event-based triggering.

Mital, Rohit↗

Trajectory Generation for Noise-Constrained Autonomous Flight Operations

One of the major factors in acceptance of aircraft operating in urban areas is noise. In this work, we build on a framework for trajectory generation in order to account for limits on acousticmetrics at one ormore observer locations. The spatial trajectories are generated using Bézier polynomials and satisfy dynamic, acoustic, and mission constraints. The trajectories also guarantee spatial or temporal separation between vehicles for multi-vehicle operations. A simulation example is provided that demonstrates the reduction in noise levels at a set of measurement locations.

Ackerman, Kasey A.↗

Customizing the JPL Multimission Ground Data System: Lessons Learned

This paper will describe lessons learned in adapting JPL's Multimission Ground Data System (MGDS) to fly the Voyager, Galileo, and Mars Observer missions. We will explain how powerful, existing ground data systems can be adapted and packaged in a cost effective way for operations of small and large planetary missions. We will also describe how the MGDS was adapted to support operations within the Galileo Spacecraft Testbed. The Galileo testbed provided a unique opportunity to adapt MGDS to support command and control operations for a small autonomous operations team with a handful of engineers flying the Galileo Spacecraft flight system model.

ground↗

Performance of Two Battery Prognostic Applications used by Two Octocopters for Safe Low Altitude Autonomous Flight Operations

This paper addresses the problem of building trust in online predictions of the remaining available flying time for two different electric Unmanned Aerial Vehicles (eUAVs) powered by lithium-ion-polymer batteries. Flight tests for various automation research missions for the two vehicles were monitored using two on-board battery health management applications to make predictions of the remaining flying time (RFT) for each eUAV and to predict the state of the battery. Playback of the voltage, current and temperature profiles of the battery discharge were used to assess the accuracy of the estimation of the voltage and the charge states of the models as well as the estimate of the RFT. The reference ground truth values were the observed landing time and the measured battery pack resting pack voltage 20 minutes after the flight. The predicted RFT, state of charge (SoC), and state of energy (SoE) were compared with the observed results. Noise values of one standard deviation from the mean values of the internal charge states of the battery model during a reference run were used to vary the states during simulation. One application used an equivalent circuit model of the electrical dynamics of the battery pack, and the other application used a reduced-order electrochemistry model. The variation of the model state components was compared to the variation in the estimate of the RFT and the variation in the SoE to estimate a confidence factor. Variation in the estimates caused by factors affecting the off-line laboratory parameter identification experiments is considered. Variation in the estimates due to environmental factors are discussed.

Assurance↗

Impact of Traffic-Following on Order of Autonomous Airspace Operations

In this paper, we investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a dynamically updating traffic pattern map of the airspace by leveraging information about the consistency and frequency of flow directions used by current as well as preceding traffic. Informed by this map, an agent can discern the degree to which it is advantageous to follow traffic by trading off utilities such as time and order. We show that for the traffic levels studied, for low degrees of traffic-following behavior, there is minimal penalty in terms of aircraft travel times while improving the overall orderliness of the airspace. On the other hand, heightened traffic-following behavior may result in increased aircraft travel times, while marginally reducing the overall entropy of the airspace. Ultimately, the methods and metrics presented in this paper can be used to optimally and dynamically adjust an agent’s traffic-following behavior based on these trade-offs.

Airspace Operations↗

Impact of Traffic-Following on Order of Autonomous Airspace Operations

We investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a dynamically updating traffic pattern map of the airspace by leveraging information about the consistency and frequency of flow directions used by current as well as preceding traffic. Informed by this map, an agent can discern the degree to which it is advantageous to follow traffic by trading off utilities such as time and order. We show that for the traffic levels studied, for low degrees of traffic-following behavior, there is minimal penalty in terms of aircraft travel times while improving the overall orderliness of the airspace. On the other hand, heightened traffic-following behavior may result in increased aircraft travel times, while marginally reducing the overall entropy of the airspace. Ultimately, the methods and metrics presented in this paper can be used to optimally and dynamically adjust an agent’s traffic-following behavior based on these trade-offs.

Airspace Operations↗

Autonomous onboard crew operations: A review and developmental approach

A review of the literature generated by an intercenter mission approach and consolidation team and their contractors was performed to obtain background information on the development of autonomous operations concepts for future space shuttle and space platform missions. The Boeing 757/767 flight management system was examined to determine the relevance for transfer of the developmental approach and technology to the performance of the crew operations function. In specific, the engine indications and crew alerting system was studied to determine the relevance of this display for the performance of crew operations onboard the vehicle. It was concluded that the developmental approach and technology utilized in the aeronautics industry would be appropriate for development of an autonomous operations concept for the space platform.

Rogers, J. G.↗

Astrobee: Completed, Current, and Future Research using Free Flying Robots on the International Space Station

After four years on the International Space Station (ISS), the Astrobee Research Facility, has completed over 130 Test Sessions logging over 1000 hours of operations. Managed by the NASA ISS Program OZ office and supported by NASA Ames Research Center (ARC) in California, the Astrobee Team maintains three identical free-flying Astrobee robots for research on the ISS. As a technology demonstration platform, the Astrobee Robots are available for Guest Scientists to use for a spectrum of research capabilities. Astrobee, propelled by battery-operated fans, is designed to autonomously operate throughout most of the USOS (US Orbital Segment), with the objective of minimizing astronaut support. Astrobee carries a suite of six cameras, a two degree-of-freedom (DOF) arm with a gripper that can grasp ISS handrails and other objects, and three payload bays that provide power and data for guest science hardware. Astrobee can autonomously execute hours-long flight plans or be teleoperated from the ground or by astronauts. While the Astrobee Team continues to improve mapping and autonomous flight capabilities, one of the main goals of Astrobee Robots is to provide research opportunities for Guest Scientists. The Astrobee Robot Software (ARS) makes extensive use of the open-source Robot Operating System (ROS). The ARS can be used interchangeably with an Astrobee Simulator or as Astrobee’s onboard software. ARS features include autonomous docking and perching, real-time teleoperations from the ground, plan based autonomous tasks, multi Astrobee communication, among other capabilities. Through simulation software and ground testing laboratories, the Astrobee Team is available to support Guest Scientists during development and testing and lead real-time ISS operations. Guest Scientists can participate in this research opportunity following the Guest Science Lifecycle (GSL) shown in Figure 1: Guest Science Lifecycle below. The Astrobee Team and Guest Scientists have complete research including Gecko materials studies, RFID and sound sensing capabilities, student Robotics Programming Challenges, and Free Flyer formation flight investigations. Current science with the Astrobee Robots includes Free Flyer self-toss studies, new docking capabilities, advanced mapping resolution capabilities, and high resolution panoramic imagery. Future Guest scientists and Astrobee Team research will focus on robotics applications for future NASA missions such as Gateway and Artemis and potential experiments involving human-robot interactions. This presentation will focus on four main subjects, 1) completed, current, and future planned research using the Astrobee robots, 2) how Guest Scientist get from conception to the ISS, 3) Astrobee Facility resources available for Guest Science ground testing and real-time ISS operations support, and 4) lessons learned from four years of ISS operations.

Astrobee↗

Target Trailing With Safe Navigation With Colregs for Maritime Autonomous Surface Vehicles

Systems and methods for operating autonomous waterborne vessels in a safe manner. The systems include hardware for identifying the locations and motions of other vessels, as well as the locations of stationary objects that represent navigation hazards. By applying a computational method that uses a maritime navigation algorithm for avoiding hazards and obeying COLREGS using Velocity Obstacles to the data obtained, the autonomous vessel computes a safe and effective path to be followed in order to accomplish a desired navigational end result, while operating in a manner so as to avoid hazards and to maintain compliance with standard navigational procedures defined by international agreement. The systems and methods have been successfully demonstrated on water with radar and stereo cameras as the perception sensors, and integrated with a higher level planner for trailing a maneuvering target.

Kuwata, Yoshiaki↗