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This paper describes refinements to trajectory correction maneuvers, including contingency plans for addressing potential operational anomalies, as well as actual spacecraft flight performance during Earth approach.
This paper describes the initial plans for the New Frontiers Juno mission at Jupiter. It includes the considerable contingency planning for mission recovery if the Jupiter Orbit Insertion (JOI) burn to place Juno into a large capture orbit were interrupted or terminated on a burn timer setting, and the options for the mission if the Period Reduction Maneuver (PRM) burn to achieve the final orbit period were terminated early. The analyses were based on the assumption that 14-day orbits were the desired operational orbit period.
In the nearly two decades of Cassini flight, adaptations to navigation processes were applied as characteristics unique to Cassini were identified and spacecraft configuration changes were implemented. Additionally, operational experience was leveraged into more efficient processes, better modeling, and more robust contingency strategies. Trajectory adjustments were implemented to allow further investigation of surprising science discoveries meriting more attention. Unique analyses were performed to determine how to best accomplish atypical science observations while maintaining acceptable risk levels. Descriptions of the most significant adaptations are organized according to the affected navigation subsystems: trajectory design, orbit determination, optical navigation, and maneuver design.
Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACC to which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.
With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.
Advances in technology are enabling new concepts of operations that will trans-form aviation including increasingly autonomous capabilities to handle evolving complex dynamic ecosystems like those associated with Advanced Aerial Mobility. A major challenge is how to ensure today’s safety levels are maintained as the system scales for rapid detection and timely mitigation of safety issues. NASA has developed a concept of operation for In-Time Aviation Safety Management Systems (IASMS) that represents a system-of-system perspective on interconnected capabilities needed to proactively reduce risk in complex operational environments where unknown hazards may exist. As a result, NASA research priorities include under-standing how the balance between humans and automation changes in such envisioned systems, which may lead to novel human-machine interaction paradigms and human-autonomy teaming for informed contingency management.
With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.
In this paper we consider service placement problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, we estimate for each potential location the response time, consumed energy and total cost; formulate an optimization problem for cost minimization given the users QoS constraints and network infrastructure limitations; and solve it using nonlinear programming tools. The approach is applied to trajectory re-planning use case to handle a no-fly zone contingency in real time.
Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACCto which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.
The Artemis program established the goal to land the first woman and first person of color on the Moon, but that is only the beginning of the program. Artemis plans to move towards a sustainable phase, with four crew living on the lunar surface for roughly 30-day annual missions, operating from a Pressurized Rover (PR) and a Surface Habitat (SH). The crew will split up – two living and operating from the PR and the others in the SH, perhaps swapping places halfway through the surface mission. There is a significant degree of maturity surrounding PR operations due to the NASA Desert Research and Technology Studies field tests from 2007-2011. However, there is a degree of uncertainty surrounding activity in the SH, with anecdotal speculation among some Artemis lunar surface engineers that the SH crew might not be fully utilized. Contrary to this belief, there is evidence in US human spaceflight history that the SH crew may instead be extremely busy. In particular, portions of the STS-94 Microgravity Science Lab mission demonstrate a science-based use case for crew activity in the SH. Fifteen Spacelab missions (not including STS-83, which was terminated early due to a fuel cell problem and reflown as STS-94) and eight Spacehab missions used the previously mentioned modules as science labs to expand the science capability of shuttle orbital missions, most flown prior to the assembly of the International Space Station. STS-94 is selected as an example of these flights. STS-94 was a 15.7-day mission with a 7-person crew. The crew operated in split 12-hour shifts, enabling 24-hour science operations. STS-94 used the space shuttle Columbia with the Spacelab module and Extended Duration Orbiter pallet in the cargo bay. The STS-94 physical science investigations were intended to explore various physical aspects of microgravity. These same investigations can be conducted on the Moon to explore 1/6 gravity. The Spacelab module was outfitted with several key facilities to enable this research: Large Isothermal Furnace, Combustion Module-1, Droplet Combustion Experiment, EXPRESS Rack, TEMPUS, Gravity Measurement Devices, and Middeck Glovebox. The current reference concept for the SH is a hybrid inflatable in a vertical orientation. Fairly typical of hybrid inflatables, the SH has an aluminum core pressurized section and a larger inflatable volume, in this case attaching to the top of the core. Two crew will live in the SH at a time, though four can briefly occupy the habitat, such as for contingency or handover activities. This paper will discuss use of the STS-94 physical science equipment in the SH and options for the architectural layout of a resulting physics laboratory. It will also discuss how this laboratory may accompany other science facilities such as biology, human research, and geology. The person hours used by the STS-94 crew to conduct physical science research will be estimated and then mapped to a two-person SH crew, making it possible to determine how many days are required in the SH to complete the lunar gravity physical science investigations at varying levels of crew availability.
The global coverage and temporal frequency that satellites provide offers a unique opportunity to estimate landslide hazard and exposure throughout the disaster lifecycle, from pre-event planning and forecasting to post-event mapping and impact assessment, and finally to recovery and mitigation. The relevance of satellite-derived data and model products is largely contingent on the spatiotemporal sampling, the hazard characteristics, and the needs from the research or applications community. This work presents an advanced Landslide Hazard Assessment for Situational Awareness (LHASA) framework that brings together satellite and model products with new machine learning techniques and global inventory data to better model landslide hazard and exposure. We present several new ways to map, model, and assess landslide hazard using a range of satellite data. Two new thrusts of this work are to better account for the exacerbating impacts of fires and to provide a multi-day forecast of potential hazard. Together, these additional components blend information from a suite of satellite and model sources to improve early warning of potentially hazardous areas, identify landslide occurrence and impacts in near real-time, and better characterize the spatiotemporal patterns of landslide hazard and exposure more broadly for future awareness and planning. This suite of tools and products is open to the public and provides information to better assess the potential occurrence and impacts of landslides within different regions of the world. This presentation explores both the architecture behind this framework and examples of how the model components and products have been used by different stakeholders around the world.
The success of current and future NASA missions relies in great part on the performance reliability and robustness of the communication circuits and systems of said missions. Some of the manifestations of reliability and robustness are comprised by properties such as graceful degradation, which provide redundancy and potentially longer life to the mission, and the ability to perform efficiently in harsh environments destinations such as Venus and the Jovian and Saturnian moons Europa and Enceladus, respectively. While several approaches have been considered or are currently underway to develop communications circuitry capable of performing in harsh environments, they lack the flexibility to enable reconfigurability to preserve functionality under adverse or contingency scenarios. This paper discusses some examples of self-healing RF/Microwave communications circuits and systems that could provide advantageous options in support of NASA missions.
The International Space Exploration Coordination Group (ISECG) is a voluntary, non-binding coordination forum of 26 space agencies. Building on the 2018 Global Exploration Roadmap (GER) and on growing global interest in space exploration, ISECG’s GER Supplement (Aug 2020) captures the latest developments in lunar exploration planning in an updated Lunar Surface Exploration Scenario. The updated Lunar Surface Exploration Scenario describes a phased approach to implementing infrastructure and exploration on the lunar surface to meet the goals and objectives defined by the ISECG. The updated scenario starts with Boots on the Moon, where space agencies focus on sending humans to the Moon beginning in 2024 and robotic exploration missions to support the 2024 goal and later phases. Next is Phase 2, Lunar Exploration—Expanding and Building, with an emphasis on completion of the proposed lunar surface objectives by exploring the lunar surface diversely and ultimately settling at the most beneficial site. Initial focus is on lunar surface exploration objectives pertaining to human landing and ascent, logistic cargo landers, and long-range traverses. The later focus is on lunar surface exploration objectives pertaining to long duration habitation, crew health and performance, and in-situ resource utilisation (ISRU). The third phase, Sustained Lunar Opportunities, envisages laying the foundation for a sustained and vibrant lunar presence in the coming decades through partnerships with international governments, academia and industry. During this phase, governments would shift their investment focus to further expand the frontier, including Mars exploration missions. This paper will describe the concept of operations by phase that supported the development of the updated scenario, along with refinements to those concepts of operations since the release of the updated scenario. By phase, the paper will describe the scenario, give an overview of the applicable architecture elements, identify functional requirements/needs of those elements, and include a discussion of nominal operations and contingency scenarios.
The Robotic Refueling Mission (RRM) was a multi-phased technology development effort by the National Aeronautics & Space Administration (NASA) and the Canadian Space Agency (CSA). The program leveraged the existing robotic systems and expertise of the International Space Station (ISS) program and the tool design and satellite servicing expertise of NASA’s Exploration & In-space Services (NExIS) Projects Division at Goddard Space Flight Center (GSFC) to evaluate new hardware and techniques for on-orbit telerobotic servicing. Between 2011 and 2021, two external ISS payloads housed over a dozen robotic tools and adapters designed to service a variety of existing and novel satellite interfaces. Robot operators at NASA’s Johnson Space Center (JSC) and CSA used the Special Purpose Dexterous Manipulator (SPDM) to retrieve and operate these tools for tasks such as cutting wires or multi-layer insulation blanketing, removing valve caps, mating electrical connectors, transferring fluids, and performing visual inspections inside a vehicle. Each phase of RRM involved years of preparation. Tool and interface designs were prototyped and evaluated using both NASA and Canadian ground robotic systems. Procedures were developed by GSFC engineers and vetted in partnership with JSC and CSA robot operators. GSFC engineers were trained to provide real-time support during on-orbit operations. These preparatory efforts and the successful on-orbit evaluations yielded an array of lessons for future in-space telerobotic missions. Designing robotic tools for the space environment requires special consideration of materials, indicators, and differences between ground and flight use cases and environments. When there is a limited window for on-orbit operations, devoting time and high-fidelity hardware to ground testing can be critical. Needs during potential troubleshooting are more essential to camera view quality, frame rate, and position requirements more than nominal operations. Detailed hardware manuals, nominal and contingency procedures, along with clearly defined operations team roles and protocols are vital for efficiency. RRM also demonstrated how the ISS can be utilized to increase the technology readiness levels required for future missions and led to additional technology partnerships between NExIS and the ISS program. The lessons from RRM are currently being applied to designs, operations concepts, and ground test methodology for missions such as On-orbit Servicing, Assembly, and Manufacturing1(OSAM-1)and Mars Sample Return.
The success of current and future NASA missions relies in great part on the performance reliability and robustness of the communication circuits and systems of said missions. Some of the manifestations of reliability and robustness are comprised by properties such as graceful degradation, which provide redundancy and potentially longer life to the mission, and the ability to perform efficiently in harsh environments destinations such as Venus and the Jovian and Saturnian moons Europa and Enceladus, respectively. While several approaches have been considered or are currently underway to develop communications circuitry capable of performing in harsh environments, they lack the flexibility to enable reconfigurability to preserve functionality under adverse or contingency scenarios. This paper discusses some examples of self-healing RF/Microwave communications circuits and systems that could provide advantageous options in support of NASA missions.
In early 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) will conduct a manned, human-in-the-loop (HITL) simulation. This part task HITL will begin the lab’s Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The goals will be to assess levels of automation for manned, electric vertical takeoff and landing (eVTOL) aircraft. This simulation will test manual and automated Resolution Advisory (RA) responses and return-to-course (RTC) maneuvers for the first version of the Airborne Collision Avoidance System’s (ACAS) rotary-wing (Xr) variant. This will be conducted on a fixed-based simulator designed to fly eVTOL aircraft while maneuvering for intruding traffic. Variables for this study include levels of autonomy (i.e., manual and automated) as well as the types of alerts at the onset of conflicts (i.e., Corrective and RA). The data collected will include response times, losses of well clear, and maneuver sizes and durations as well as subjective ratings like acceptability, perceived workload, and meaningful human control. Additional details and future anticipations are also discussed.
An in-space propulsion technology, nuclear thermal propulsion (NTP) has the potential to enable faster interplanetary transit times compared to traditional chemical propulsion methods due to its capacity for high specific impulse (900+ s) and thrust (~10 – 100 klbf). Because of these performance attributes, NTP is currently one of several advanced propulsion technologies currently under consideration by the National Aeronautics and Space Administration (NASA) for future crewed Mars missions. The performance of NTP systems is directly contingent upon the development of a robust fuel form capable of withstanding high-power densities and operation in a hydrogen environment at temperatures in excess of 2500 K. This presentation will overview development needs for fuels in NTP systems, historic and current NTP fuel system options, and their remaining challenges prior to successful implementation.
Fewer than 20 extravehicular activities were completed during the Apollo program. The lunar environment has consistent unknowns to address particularly that of suited performance in partial gravity. The moon has altered gravity that is 1/6th that of Earth’s. This study is focused to investigate validation of the regression techniques identified in subsequent chapters and look to improve predictive outcomes during simulated lunar EVA tasks. Heart rate predictions of metabolic energy expenditure are investigated to predict workload throughout simulated lunar EVA conducted in the active response gravity offload system (ARGOS) with in the NASA Mark III space suit. Heart rate variability metrics are utilized to identify periods of high workload. Continually, the lunar offload capacity is further characterized to aid in improving the cardiothermal prediction models including predictions of core temperature, skin temperature and heat storage using heart rate, metabolic rates and suit thermal data during the simulated EVA. The outcome of this model provides an application for future use in contingency predictions of energy expenditure during Lunar EVAs and provide a suite of instrumentation to predict workload during training scenarios.