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Charting a course to the sun: flight path control for Parker Solar Probe
The successful launch of the Parker Solar Probe (PSP) on August 12, 2018 with a Delta IV rocket and Star-48BV third stage has placed the spacecraft on a 7-year trajectory to study the Sun. The goals of PSP are to better characterize our solar environment and advance our understanding of the Sun at 9.86 Rs. A total of 42 trajectory correction maneuvers are planned. This paper documents trajectory correction maneuver analysis performed just prior to launch until just past the first solar encounter. The pre-launch analysis culminated in two final design cycles which analyzed 24 reference trajectories.
Flight Path Control Analysis for Parker Solar Probe
An unprecedented NASA mission to study the Sun, known as Parker Solar Probe (PSP), is under development. The primary objective of the PSP mission is to gather new data within 10 solar radii of the Sun’s center. The purpose of this paper is to review the statistical analysis of trajectory correction maneuvers (TCMs) for PSP’s baseline trajectory. The baseline mission includes a total of 42 TCMs that will be accomplished with a monopropellant propulsion system that consists of twelve 4.4 N thrusters. Assuming current navigation models, statistical analyses for each reference trajectory during the 20-day launch period result in a total V99 of less than 100 m/s.
On a path towards the reassessment of Antarctic volume change: synthesis of ESA radar and NASA airborne and satellite laser altimetry observations
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Trident: The Path to Triton on a Discovery Budget
This paper describes Trident, a proposed Discovery mission to Neptune’s moon Triton, 30 AU from the Sun. Triton formed in the Kuiper Belt but was captured by Neptune into a highly-inclined retrograde orbit, where tidal forces thawed its interior, forming an ocean that likely persists to the present day. Recent outer solar system missions like Cassini and New Horizons have yielded completely new models for processes on ocean worlds, active worlds, and KBOs. Triton isn’t just a key to solar system science, it’s a whole keyring: a singular captured KBO and evolved ocean world, with active plumes, an energetic ionosphere, and a young unique surface. The NASA OPAG Roadmap to Ocean Worlds identifies Triton as the highest priority candidate ocean world [1], ripe for investigation.
Commanding Curiosity from the couch: MSL remote operations, challenges, and path ahead
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Simulation of Radio Frequency Power Received by a UAV Along Its Flight Path
A ray-tracing electromagnetic simulation using ALTAIR WinProp software was performed to calculate the 2.4 GHz power received by a UAV in flight, both from the intended controller transmitter and from a fictitious interference source of equal power located near the ground. The signal-to-interference ratio was then calculated. For the chosen example, the received power from the controller varied from -88.3 to -70.1 dBm, while the signal-to-interference ratio varied from -10.9 to +11.4 db. This work was done in support of the System-Wide Safety Project Technical Challenge 2 - Emerging Operations at NASA Langley, which is studying methods to avoid interference of UAV control and data relay signals.
The Path to Crew Autonomy - Situational Awareness in Scheduling and Rescheduling Tasks for Novice Schedulers
To increase crew autonomy for long duration exploration-class missions (LDEM), certain mission support tasks need to be completed by crew. Currently, crew activities are scheduled over the course of several weeks by ground-based experts with years of experience-based training. These experts display extensive amounts of situational awareness (SA) throughout task execution by maintaining a mental model of additional factors during scheduling such as constraints (e.g. physical space/layout), abilities and skills of the crew, and crew preferences allowing them to anticipate and mitigate potential issues. Thus, situational awareness is a key component for crews to manage their own schedules. In this paper, we examined situational awareness in novice schedulers in both a scheduling and rescheduling task. Our findings indicate that there is no significant difference between scheduling and rescheduling tasks for the development of SA in novice schedulers. Additionally, our experiment shows that novice schedulers are less able to develop sufficient SA for constraints that are dependent on one or more activities. Thus, we propose that software aids may be useful to support novice schedulers and increase SA in scheduling/rescheduling tasks. This work is vital to ensure the successful transfer of mission support tasks to the crew for future LDEM.
CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS
Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.