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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 19 records

Scheduling For Urban Air Mobility Using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗

Scheduling for Urban Air Mobility using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗

Compliant Task Execution and Learning for Safe Mixed-Initiative Human-Robot Operations

We introduce a novel task execution capability that enhances the ability of in-situ crew members to function independently from Earth by enabling safe and efficient interaction with automated systems. This task execution capability provides the ability to (1) map goal-directed commands from humans into safe, compliant, automated actions, (2) quickly and safely respond to human commands and actions during task execution, and (3) specify complex motions through teaching by demonstration. Our results are applicable to future surface robotic systems, and we have demonstrated these capabilities on JPL's All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robot.

multi-agent collaboration↗

L1 Adaptive Control with Switched Reference Models: Application to Learn-to-Fly

Learn-to-Fly (L2F) is a new framework that aims to replace the traditional iterative development paradigm for aerial vehicles with a combination of real-time aerodynamic modeling, guidance, and learning control. To ensure safe learning of the vehicle dynamics on the fly, this paper presents an L1 adaptive control (L1AC) based scheme, which actively estimates and compensates for the discrepancy between the intermediately learned dynamics and the actual dynamics. First, to incorporate the periodic update of the learned model within the L2F framework, this paper extends the L1AC architecture to handle a switched reference system subject to unknown time-varying parameters and disturbances. The paper also includes analysis of both transient and steady-state performance of the L1AC architecture in the presence of non-zero initialization error for the state predictor. Second, the paper presents how the proposed L1AC scheme is integrated into the L2F framework, including its interaction with the baseline controller and the real-time modeling module. Finally, flight tests on an unmanned aerial vehicle (UAV) validate the efficacy of the proposed control and learning scheme.

Steven Snyder↗

International Space Station Configuration Analysis and Integration

Ambitious engineering projects, such as NASA's International Space Station (ISS), require dependable modeling, analysis, visualization, and robotics to ensure that complex mission strategies are carried out cost effectively, sustainably, and safely. Learn how Booz Allen Hamilton's Modeling, Analysis, Visualization, and Robotics Integration Center (MAVRIC) team performs engineering analysis of the ISS Configuration based primarily on the use of 3D CAD models. To support mission planning and execution, the team tracks the configuration of ISS and maintains configuration requirements to ensure operational goals are met. The MAVRIC team performs multi-disciplinary integration and trade studies to ensure future configurations meet stakeholder needs.

Anchondo, Rebekah↗

Creating Formal Characterizations of Routine Contingency Management in Commercial Aviation

The identification, modelling, and analysis of root causes of accidents and incidents dominate conventional safety management approaches. However, the effect of humans’ safety-producing behavior on the overall resilience of the system is often neglected. Additionally, emerging aviation markets are giving rise to concepts of operation, such as urban air mobility and optionally piloted air cargo operations, that are leading to a shift in locus of control between humans and automation. Without an understanding of the human contribution to safety, it is difficult to assess the effects of these novel role allocations on overall system safety. In this work, safety-producing behaviors are identified and abstracted into resilient performance strategies. Production rules that encapsulate these strategies are then generated and classified in the Soar cognitive architecture. The strategies are then applied to a remotely-operated air cargo example to demonstrate how safe learning is facilitated. The learned rules and strategies are then formally verified.

Safety Critical Systems↗

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the identification of safe terrain from input digital elevation models (DEMs). However, performance for these methods can degrade for input DEMs with increased sensor noise. In the last decade, deep learning techniques have been developed for various applications. Nevertheless, their applicability to safety-critical space missions has often been limited due to concerns regarding their outputs’ reliability. In response to these limitations, this paper proposes an application of the Bayesian deep learning segmentation method for hazard detection. The developed approach enables reliable, safe landing site detection by i) generating simultaneously a safety prediction map and its uncertainty map via Bayesian deep learning and semantic segmentation, and ii) using the uncertainty map to filter out the uncertain pixels in the prediction map so that the safe site identification is performed only based on the certain pixels (i.e., pixels for which the model is certain about its safety prediction). Experiments are presented with simulated data based on a Mars HiRISE digital terrain model by varying uncertainty threshold and noise levels to demonstrate the performance of the proposed approach.

Kento Tomita↗

NASA Engineering and Safety Center Technical Bulletin No. 23-01: Including Key Design Features in Safety-Critical Pyrotechnic Firing Circuits

Pyrotechnic systems often fall into a unique category in that inadvertent activation of these systems resulting from a fault and/or lack of safe margins can lead directly to loss of crew. For example, untimely activation of pyrotechnics used for a flight termination system could override an abort capability. Over the years, NASA and the military have learned lessons about safe pyrotechnic circuit design and test, many of which are codified. However, with NASA’s recent efforts to move toward a development model than leans more heavily on Commercial Partners these requirements have not always been directly levied on projects and in some cases been misinterpreted. This bulletin describes key safety features of pyrotechnic firing circuit design and provides rationale for inclusion of each feature.

Pyrotechnic Firing Curcuits↗

In Vitro Disease Model of Microgravity Conditioning on Human Energy Metabolism

NASA and its partners are committed to introducing appropriate new technology to enable learning and living safely beyond the Earth for extended periods of time in a sustainable and possibly indefinite manner. In the responsible acquisition of that goal, life sciences is tasked to tune and advance current medical technology to prepare for human health and wellness in the space environment. The space environment affects the condition and function of biological systems from organ level function to shape of individual organelles. The objective of this paper is to study the effect of microgravity on kinetics of drug metabolism. This fundamental characterization is meaningful to (1) scientific understanding of the response of biology to microgravity and (2) clinical dosing requirements and pharmacological thresholds during long term manned space exploration. Metabolism kinetics of the anti-nausea drug promethazine (PMZ) were determined by an in vitro ground model of 3-dimensional aggregates of human hepatocytes conditioned to weightlessness using a rotating wall bioreactor. The authors observed up-regulated PMZ conversion in model microgravity conditions and attribute this to effect to model microgravity conditioning acting on metabolic mechanisms of the cells. Further work is necessary to determine which particular cellular mechanisms are governing the experimental observations, but the authors conclude kinetics of drug metabolism are responsive to gravitational fields and further study of this sensitivity would improve dosing of pharmaceuticals to persons exposed to a microgravity environment.

Snyder, Jessica↗

Paving the Path for Human Space Exploration: The Challenges and Opportunities

Lauri Hansen, Director of Engineering at NASA Johnson Space Center will discuss the challenges of human space exploration. The future of human exploration begins with our current earth reliant missions in low earth orbit. These missions utilize the International Space Station to learn how to safely execute deep space missions. In addition to serving as an exploration test bed and enabling world class research, the International Space Station enables NASA to build international and commercial partnerships. NASA's next steps will be to enable the commercialization of low earth orbit while concentrating on developing the spacecraft and infrastructure necessary for deep space exploration and long duration missions. The Orion multi-purpose crew vehicle and the Space Launch System rocket are critical building blocks in this next phase of exploration. There are many challenges in designing spacecraft to perform these missions including safety, complex vehicle design, and mass challenges. Orion development is proceeding well, and includes a significant partnership with the European Space Agency (ESA) to develop and build the Service Module portion of the spacecraft. Together, NASA and ESA will provide the capability to take humans further than we have ever been before - 70,000 km past the moon. This will be the next big step in expanding the frontiers of human exploration, eventually leading to human footprints on Mars.

Hansen, Lauri↗

Hazard Contribution Modes of Machine Learning Components

Amongst the essential steps to be taken towards developing and deploying safe systems with embedded learning-enabled components (LECs) i.e., software components that use ma- chine learning (ML)—are to analyze and understand the con- tribution of the constituent LECs to safety, and to assure that those contributions have been appropriately managed. This paper addresses both steps by, first, introducing the notion of hazard contribution modes (HCMs) a categorization of the ways in which the ML elements of LECs can contribute to hazardous system states; and, second, describing how argumentation patterns can capture the reasoning that can be used to assure HCM mitigation. Our framework is generic in the sense that the categories of HCMs developed i) can admit different learning schemes, i.e., supervised, unsupervised, and reinforcement learning, and ii) are not dependent on the type of system in which the LECs are embedded, i.e., both cyber and cyber-physical systems. One of the goals of this work is to serve a starting point for systematizing L analysis towards eventually automating it in a tool.

Smith, Colin↗

Lessons learned - Americans in space

Milestones in the learning process during development of spaceflight capability for different NASA missions are traced from the initial launch of the Mercury escape rocket to the advent of the Shuttle. A detached heat shield on the first manned Mercury orbital flight led to a decision for reentry with retrorockets attached, a situation which demonstrated a need for on-line communications with the spacecraft construction engineers. The Gemini program served to develop EVA techniques and docking procedures essential for the Apollo missions. Apollo 8 circled the moon after only one manned test flight of the equipment due to the success of the first flight. Lunar landing simulation training exposed the astronauts to situations beyond the human ability to respond. The training was justified when computer overload required the pilot to retake manual control of some spacecraft functions during the successful first lunar landing. All lessons previously learned were used to safely return the damaged Apollo 13 to earth. The Skylab missions provided an opportunity to maintain rotating teams of flight controllers on a 24-hr/day basis for periods of months. Finally, the six-year hiatus of U.S. manned space activities between the end of the Skylab missions and the first Shuttle flight provided time for incorporating previous lessons into new procedures, training strategies, and data resources.

Kranz, E.↗

Space Resource Utilization: Near-Term Missions and Long-Term Plans for Human Exploration

NASA's Human Exploration Plans: A primary goal of all major space faring nations is to explore space: from the Earth with telescopes, with robotic probes and space telescopes, and with humans. For the US National Aeronautics and Space Administration (NASA), this pursuit is captured in three important strategic goals: 1. Ascertain the content, origin, and evolution of the solar system and the potential for life elsewhere, 2. Extend and sustain human activities across the solar system (especially the surface of Mars), and 3. Create innovative new space technologies for exploration, science, and economic future. While specific missions and destinations are still being discussed as to what comes first, it is imperative for NASA that it foster the development and implementation of new technologies and approaches that make space exploration affordable and sustainable. Critical to achieving affordable and sustainable human exploration beyond low Earth orbit (LEO) is the development of technologies and systems to identify, extract, and use resources in space instead of bringing everything from Earth. To reduce the development and implementation costs for space resource utilization, often called In Situ Resource Utilization (ISRU), it is imperative to work with terrestrial mining companies to spin-in/spin-off technologies and capabilities, and space mining companies to expand our economy beyond Earth orbit. In the last two years, NASA has focused on developing and implementing a sustainable human space exploration program with the ultimate goal of exploring the surface of Mars with humans. The plan involves developing technology and capability building blocks critical for sustained exploration starting with the Space Launch System (SLS) and Orion crew spacecraft and utilizing the International Space Station as a springboard into the solar system. The evolvable plan develops and expands human exploration in phases starting with missions that are reliant on Earth, to performing ever more challenging and longer duration missions in cis-lunar space and beyond, to eventually being independent from Earth. The goal is no longer just to reach a destination, but to enable people to work, learn, operate, and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite.

Sanders, Gerald B.↗

Proving Ground Potential Mission and Flight Test Objectives and Near Term Architectures

NASA is developing a Pioneering Space Strategy to expand human and robotic presence further into the solar system, not just to explore and visit, but to stay. NASA's strategy is designed to meet technical and non-technical challenges, leverage current and near-term activities, and lead to a future where humans can work, learn, operate, and thrive safely in space for an extended, and eventually indefinite, period of time. An important aspect of this strategy is the implementation of proving ground activities needed to ensure confidence in both Mars systems and deep space operations prior to embarking on the journey to the Mars. As part of the proving ground development, NASA is assessing potential mission concepts that could validate the required capabilities needed to expand human presence into the solar system. The first step identified in the proving ground is to establish human presence in the cis-lunar vicinity to enable development and testing of systems and operations required to land humans on Mars and to reach other deep space destinations. These capabilities may also be leveraged to support potential commercial and international objectives for Lunar Surface missions. This paper will discuss a series of potential proving ground mission and flight test objectives that support NASA's journey to Mars and can be leveraged for commercial and international goals. The paper will discuss how early missions will begin to satisfy these objectives, including extensibility and applicability to Mars. The initial capability provided by the launch vehicle will be described as well as planned upgrades required to support longer and more complex missions. Potential architectures and mission concepts will be examined as options to satisfy proving ground objectives. In addition, these architectures will be assessed on commercial and international participation opportunities and on how well they develop capabilities and operations applicable to Mars vicinity missions.

Smith, R. Marshall↗

Space Resource Utilization: Near-Term Missions and Long-Term Plans for Human Exploration

A primary goal of all major space faring nations is to explore space: from the Earth with telescopes, with robotic probes and space telescopes, and with humans. For the US National Aeronautics and Space Administration (NASA), this pursuit is captured in three important strategic goals: 1. Ascertain the content, origin, and evolution of the solar system and the potential for life elsewhere, 2. Extend and sustain human activities across the solar system (especially the surface of Mars), and 3. Create innovative new space technologies for exploration, science, and economic future. While specific missions and destinations are still being discussed as to what comes first, it is imperative for NASA that it foster the development and implementation of new technologies and approaches that make space exploration affordable and sustainable. Critical to achieving affordable and sustainable human exploration beyond low Earth orbit (LEO) is the development of technologies and systems to identify, extract, and use resources in space instead of bringing everything from Earth. To reduce the development and implementation costs for space resource utilization, often called In Situ Resource Utilization (ISRU), it is imperative to work with terrestrial mining companies to spin-in/spin-off technologies and capabilities, and space mining companies to expand our economy beyond Earth orbit. In the last two years, NASA has focused on developing and implementing a sustainable human space exploration program with the ultimate goal of exploring the surface of Mars with humans. The plan involves developing technology and capability building blocks critical for sustained exploration starting with the Space Launch System (SLS) and Orion crew spacecraft and utilizing the International Space Station as a springboard into the solar system. The evolvable plan develops and expands human exploration in phases starting with missions that are reliant on Earth, to performing ever more challenging and longer duration missions in cis-lunar space and beyond, to eventually being independent from Earth. The goal is no longer just to reach a destination, but to enable people to work, learn, operate, and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite.

Sanders, Gerald B.↗

Tethered system/space platform integration - TSS lessons learned

Tethered spacecraft systems must be integrated with their user platforms in a way that allows both to carry out their design functions efficiently and safely. This paper describes the lessons learned about tethered system integration with a space platform from the NASA/PSN Tethered Satellite System. Items discussed include platform attitude control, induced voltage and current control, satellite tracking and tether length measurement, satellite communications and system operations sensitivities. A number of engineering issues yet to be resolved are noted. Tethered systems are complex and require careful design to ensure successful operation.

Rudolph, L. K.↗