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NASA NTRSDate not supplied

VIPER: Introduction to the Resource Prospecting Mission

With the Artemis Program, NASA plans to return humans to the Moon to stay, which means if there are local materials available, they could be deployed to help support extended lunar stays. Since the moon’s polar regions have confirmed the presence of volatiles, as revealed by LCROSS, LRO and other lunar missions, the next step is to understand the nature and distribution of those candidate resources and how they might be extracted. Recent studies have even indicated local volatiles could be processed into propellants and human life-supporting resources, significantly aiding in sustaining humans on the Moon, and eventually and later to support missions to Mars. The Volatiles Investigating Polar Exploration Resource (VIPER) is an in-situ resource utilization (ISRU) mission within NASA’s Science Mission Directorate (SMD), based on the pathfinding development of the Resource Prospector (RP) mission concept. This clever mission is targeting late 2023 and may spend over 100 days mapping and surveying four different Ice Stability Regions to understand the nature and distribution of water and volatiles already confirmed to be there, including measuring mineralogical content such as silicon and light metals from lunar regolith. The knowledge attained by a mission like VIPER could have many-fold benefits for space exploration, but also commercial applications. VIPER is an essential, early mission supporting the “moon rush” which has developed over the past few years, with both governments and commercial entities making their cases for lunar exploration. VIPER aims to understand just how the water-ice and other volatiles are distributed, both horizontally and vertically, enabling creation of volatiles resource maps, which will guide what might be required to harvest those resources at scale. With sufficient infrastructural investment, led by governments and then optimized by the commercial marketplace, VIPER will be a pathfinder mission addressing key decadal lunar science and early strategic knowledge gaps.

Daniel Andrews↗
NASA NTRSDate not supplied

Growing the success of Small Satellite missions through community learning

The successful utilization of small satellites for scientific missions relies on continual infusion of technology innovations, creative approaches, and new capabilities, all of which advance at a very rapid pace. Achieving these advancements requires open and efficient exchange of results, experiences, and ideas. Community learning is particularly challenging in this fast-growing community involving an increasingly diverse set of players from all sectors: industry, academia, government, and the public at large. Building and cultivating a community of practices around small satellite technology development and mission implementation are key objectives for NASA’s Small Spacecraft Systems Virtual Institute (S3VI). The institute has developed and provides access to a large collection of products, tools, and activities to advance clear communications and coordination regarding small spacecraft undertakings across NASA, to provide mission enabling information to the smallsat research community, to engage with stakeholders in industry, government, academia and the general public, and to support the overall small spacecraft community. New and updated offerings by the S3VI include: The2021 NASA State of the Art Report of Small Spacecraft Technology, the Small Spacecraft Reliability Initiative Knowledge Base, and the “MISSION ACCOMPLISHED”webinar series. These and other institute products will help scientists and engineers planning future missions answer pertinent questions, such as: What is the state of the art of small spacecraft technology that can be used?What are some best practices that other experts and teams can recommend? What did previous missions accomplish? What lessons could be learned from previous missions? What flight-proven parts are available? What emerging technologies could be taken advantage of? A status will be presented on S3VI activities facilitating community learning within the small satellite science community through the collection, sharing, and exchange of experiences with small satellite mission development and execution across all NASA mission areas.

Moretto Jorgensen, T↗
NASA NTRSDate not supplied

IMPACT 1.0—Task Impairment: A Novel Approach for Assessing Impairment during Exploration-Class Missions

Exploration-class and International Space Station (ISS) missions have significantly different levels of associated medical risk for crewmembers. The Integrated Medical Model (IMM), the probabilistic risk assessment tool used for ISS medical trade-space analyses, uses a Functional Impairment (FI) metric to determine quality time lost should a crewmember be afflicted with a medical condition. While IMM-based FI has been successful for ISS operations, it has limitations when applied to exploration-class missions. As the National Aeronautics and Space Administration (NASA) looks ahead to Gateway, Artemis, and Martian missions, a novel, dynamic, and mission-appropriate impairment paradigm is necessary for accurate contingency planning. This paradigm, Task Impairment (TI), fulfills that need by utilizing mission-specific tasks. TI will allow future capability for a loss of mission metric, previously not available with IMM. TI serves as a replacement metric for FI within IMPACT, the next-generation trade-space analysis tool suite created to replace the IMM. IMPACT significantly increases the fidelity of probabilistic risk assessment for exploration-class missions. The Human Exploration of Mars Preliminary List of Crew Tasks (MTL, a source of 1100+ exploration-class mission-specific tasks for crewmembers) was used to calculate TI. Using the Task List, 18 individual Human System Categories were identified as being required to perform each task (e.g., Cardiopulmonary, Cognitive, etc.). Each of the 1200+ tasks were mapped to the Human System categories listed in the Task List. The total number of tasks in each category were tallied to determine how many tasks required each Human System. Lastly, each of the 120 medical conditions from the IMPACT condition list were mapped to the Human System categories to complete the TI calculation. NASA subject matter experts across five medical specialties established consensus for the mapping of each condition. The resulting total tasks impaired by each condition were used to calculate discrete TI values. This process was repeated for each of the four severity/resource utilization variants of each condition, and for each of the three phases of clinical care. Through this process, discrete TI values were calculated for each of the 120 IMPACT medical conditions and their variants. The Task Impairment metric provides higher fidelity, dynamic utility, and quicker analysis of medical impairment compared to the previous Functional Impairment metric used for the Integrated Medical Model. TI will be used for higher fidelity medical impairment analysis and contingency planning during Lunar, Martian, and other long-term exploration-class missions.

William L Fernandez↗
NASA NTRSDate not supplied

Growing the Success of Small Satellite Missions Through Community Learning

The successful utilization of small satellites for scientific missions relies on continual infusion of technology innovations, creative approaches, and new capabilities, all of which advance at a very rapid pace. Achieving these advancements requires open and efficient exchange of results, experiences, and ideas. Community learning is particularly challenging in this fast-growing community involving an increasingly diverse set of players from all sectors: industry, academia, government, and the public at large. Building and cultivating a community of practices around small satellite technology development and mission implementation are key objectives for NASA’s Small Spacecraft Systems Virtual Institute (S3VI). The institute has developed and provides access to a large collection of products, tools, and activities to advance clear communications and coordination regarding small spacecraft undertakings across NASA, to provide mission enabling information to the smallsat research community, to engage with stakeholders in industry, government, academia and the general public, and to support the overall small spacecraft community. New and updated offerings by the S3VI include: The2021 NASA State of the Art Report of Small Spacecraft Technology, the Small Spacecraft Reliability Initiative Knowledge Base, and the “MISSION ACCOMPLISHED” webinar series. These and other institute products will help scientists and engineers planning future missions answer pertinent questions, such as: What is the state of the art of small spacecraft technology that can be used? What are some best practices that other experts and teams can recommend? What did previous missions accomplish? What lessons could be learned from previous missions? What flight-proven parts are available? What emerging technologies could be taken advantage of? A status will be presented on S3VI activities facilitating community learning within the small satellite science community through the collection, sharing, and exchange of experiences with small satellite mission development and execution across all NASA mission areas.

Small Satellite↗
NASA NTRSDate not supplied

Overview of NASA’s Science Mission Directorate Small Satellites Programs and Advances in Transformative Science Measurements with Small Satellites

Small satellites have become an accepted platform for enabling high-quality science measurements and observations. NASA missions have leveraged advances in sensor miniaturization, technology innovations, and new small satellite mission architectures to support high spatial and temporal measurements, continuity measurements, and constellations in response to science objectives described in NASA’s Decadal Surveys. Across six divisions of the Science Mission Directorate (SMD), over 12 years, SMD has funded 88 CubeSat/ SmallSat Missions and 59 Studies to date. Currently, SMD has 53 small spacecraft science missions (87spacecraft) in implementation or formulation. This paper provides the background of efforts to promote the implementation of small satellites within NASA as a balanced portfolio for the agency’s science, technology, and exploration goals. We include analysis of SmallSat awards and trends funded by SMD through Research Opportunities in Space and Earth Sciences (ROSES), Small Innovative Missions for Planetary Exploration (SIMPLEx), and Small Explorer (SMEX) and Medium Explorer (MIDEX) calls over the last 12years. The data source of this assessment is a subset of the NASA SmallSat Coordination Group Database, a collection of all known funded NASA SmallSat and CubeSat missions and studies. This paper also provides an overview of small satellite programs and selected missions from SMD’s divisions: Astrophysics, Heliophysics, Earth Science, and Planetary Science, and describes SMD’s efforts in fostering an incremental and continuous path to achieve high-priority science through transformative science measurements. This paper recognizes the latest observations and trends of the NASA CubeSat / SmallSat Science missions with masses ranging between 1kg to 500kg.

Small Satellites, SMD SmallSat, CubeSat,↗
NASA NTRSDate not supplied

Using Open Standards and NASA Open Source Simulation Tools to Model Artemis Base Camp Mission Timelines

The United States’ National Aeronautics and Space Administration (NASA) has announced that the Artemis Program will return humans to the Moon, establishing a persistent presence with the Artemis Base Camp (ABC), and extend human exploration to Mars. The NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center is using internationally developed simulation interoperability standards and NASA open source simulation tools to support Artemis concept, analysis, designs, development, training, and ultimately operations. The NExSyS team has been tasked to support early ABC architecture and mission analysis using mission time lines developed by the crew operations mission planning team. The NExSyS team is developing a distributed simulation framework with initial Artemis element implementations to model the ABC mission timelines using the international simulation interoperability standard High Level Architecture (HLA), the Simulation Interoperability Standards Organization’s Space Reference Federation Object Model (SpaceFOM), the NASA open source Trick Simulation Environment, and another NASA open source interface package called TrickHLA. The ABC architecture is composed of a number of key surface elements and resources. Some examples of modeled elements (also known as entities) are landers, habitats, rovers, logistics carriers, and astronauts. Some examples of modeled transferable and consumable resources are power, water, oxygen, nitrogen, scientific samples, and food. These entities and resources are modeled in a collection of individual simulations called Federates. A coordinated collection of interoperable federates is called a Federation and when these federates are tied together in a coordinated simulation run, it is referred to as a Federation Execution. The federates communicate through HLA using data exchange formats defined by a collection of machine readable files called Federation Object Models (FOMs). These FOM files are based on extensions to the SpaceFOM. This enables the instantiation and sharing of objects and interactions between federates in the federation. These provide for entity and resource tracking, object transfer, and data collection. Federate interactions are used to trigger events and notify federates of entity or resource transfers. For the initial implementation, the constituent federates are Trick-based simulations that use TrickHLA to provide the required HLA-base interoperability. These Trick-based simulations provide the required modeling for the individual Artemis elements along with the associated element resources. These federates provide a means to explore traverses between surface elements and exploration sites as scheduled in a mission timeline and explore the affects traverse times have on the overall mission timeline. The mission time lines are modeled using a Trick input file event handling capabilities. Each timeline operation is handled as individual simulation events, and triggered based on previous event status, time of operation, and simulated task completions. In addition, the ABC Federation can be used to perform Monte Carlo analysis. The Monte Carlo tool can vary the inputs, timings, and malfunctions to show how various contingencies in the mission can affect the mission timeline.

Keaton Craig Dodd↗
NASA NTRSDate not supplied

Lunar Instrument Data Integration Into the Virtual Reality Mission Simulation System for Decision Communication and Situational Awareness

In situ resource utilization (ISRU) technologies are a key advancement required to make human habitation on the Moon and Mars viable. The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission will provide crucial correlations between volatiles and lunar geology to understand the water content available for ISRU on the moon. The mission will require the coordination of multi-disciplinary teams across the country making real time decisions based on rover instrument data. The virtual reality Mission Simulation System (vMSS) is a virtual reality platform designed at MIT by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team to provide teams with a collaboration interface for planetary missions like VIPER. Herein we determine the integration pathway for analog based datasets that are examples of VIPER's two main instruments, the near-infrared volatile spectrometer subsystem (NIRVSS) and the neutron spectrometer subsystem (NSS), into vMSS to provide the most valuable visualization tools. Focusing on improving situational awareness, decision making, reducing task load and incorporating comments from scientists working previous analogs and on the current VIPER mission, we recommend critical elements to implement into vMSS and the best approaches for data visualization. We present a review of relevant analogs and state of the art mission software. We have developed a design concept and path to flight of analysed instrument data integrated with data maps that allow for virtual manipulation and annotation between non-co-located team members. We focus on pre-mission mapping of a priori data for improved situational awareness, layering of analysed instrument data, correlative mapping and interactive capabilities for in-mission decision making, as well as archiving and annotation tools for post-mission analysis. Finally, we lay out the roadmap for the future development of immersive sample site visualization capabilities and the use of integrated instrument data in vMSS with automated temporal and geospatial planning.

Cody Alison Paige↗
NASA NTRSDate not supplied

Rocket Lab Venus - Enabling Low-Cost Interplanetary Missions

Rocket Lab’s mission to Venus [1], launching in January 2025, aims to demonstrate that small launch vehicles, such as Electron, and high-energy small spacecraft, such as Photon, can enable a new paradigm of regular, low-cost interplanetary missions. The Electron launch vehicle will deliver the Photon spacecraft carrying the entry probe into low earth orbit, at which point Photon will take over and put both itself and the attached probe on an Earth-Venus transfer trajectory, with assistance from a Lunar flyby. The primary science objective of the mission is to sample the Venusian cloud layers between atitudes of 45 and 60 km above the surface with an autofluorescing nephelometer. The ~1kg scientific instrument will be carried by a small ~17 kg direct entry probe which will separate from the Photon spacecraft approximately 30 minutes prior to atmospheric entry. The probe outer mould line is a scaled down version of the Deep Space 2 probes [2]. NASA’s newly developed 3D Woven Carbon Phenolic, a derivative of the Heatshield for Extreme Entry Environment Technology (HEEET) material [3], is an enabling technology for this mission, and it will comprise the probe forebody heat shield.The probe will communicate directly back to the Earth during its descent via a small on-board radio frequency (RF) antenna. The hyperbolic Venus encounter will see the probe enter the Venusia atmosphere at approximately 11 km/s with an entry flight path angle (EFPA) of about 10°. This relatively low entry angle was selected to increase the duration of the descent phase, reduce the peak deceleration, and reduce the sensitivity of the nominal entry environments to navigational errors. For reference, the Pioneer Venus probes entered at EFPAs varying from about 25° to 70°, resulting in peak decelerations between around 220 and 450 g’s and peak stagnation point heat fluxes ranging from about 40 to 75 MW/m2 [4]. In comparison, the Rocket Lab Venus probe will experience a lower preak deceleration of around 60 g’s and a lower peak stagnation point heat flux of about 15 MW/m2, at the cost of a greater total heat load and correspondingly higher thermal protection system (TPS) mass fraction. This paper recounts the development history of the TPS for the Rocket Lab Venus probe, with a focus on the unique requirements of the mission. In particular, the effect on the TPS design of the mission’s tight budget, short development timeline, slim mass and RF link margins, and mild but long duration entry heating. Rocket Lab’s initial investigations into a ‘hybrid’ TPS [5] based on a scaled version of the Pioneer Venus full-density carbon phenolic forebody shield, and the abandonment of this approach in favour of NASA’s 3D Woven Carbon Phenolic is presented. Additionally, the leveraging of previous testing under the HEEET project at higher conditions and the associated TPS margining strategy that was adopted to avoid the need for extensive mission-specific arc jet testing is discussed. Finally, this paper concludes with a brief consideration of the feasibility of a future low-cost aerocapture technology demonstrator mission based on the 2025 Rocket Lab Venus mission and entry probe.

Lyle Campbell↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

From May 8th to June 9th, 2023, I had the opportunity to participate in an experiential learning experience at Johnson Space Center in Houston, TX with Exploration Medical Capability (ExMC), an element of the NASA Human Research Program. During this research experience, I was not only able to work on the above titled research project, but also gain an immense exposure to the field of aerospace medicine, make numerous connections within the field, tour NASA facilities, as well as travel to the Aerospace Medical Association Annual Conference (AsMA) in New Orleans. To briefly introduce my project, it is well understood that the medical capabilities available to crew medical officers (CMOs) on the International Space Station will be different than the capabilities available and needed during deep space exploration missions to the Moon, Mars, and beyond. Ground support is particularly limited due to distance, communication delays (or lack of communication), and lack of resupply. Therefore, to support medical care by CMOs on these missions, robust clinical decision support systems (CDSSs) must be designed. The recent publication and public launch of generative artificial intelligence (AI) tools based upon large language models (LLM) such as ChatGPT provides the opportunity to create a smart assistant for onboard triage, diagnosis, and treatment of medical conditions. Ultimately, the overall purpose of the project was to research what AI tools currently exist or are in development, and to see how they might be implemented onboard during exploration class spaceflights of the future. The ExMC element is actively developing several tools to be used in preparation for and during deep space exploration missions. One of those tools, known as IMPACT, is a probabilistic risk assessment model which can be used to propose a desired medical system (based on mass and volume) and suggest the clinical outcomes likely to occur for a design reference mission (DRM). The group recently presented the IMPACT model and a DRM of interest titled “Modified Long Duration Lunar Orbital and Lunar Surface” (mLDLOLS) at the recent AsMA conference. The mLDLOLS mock mission is a 9 month and 6-day deep space exploration mission consisting of time in Moon’s orbit (3 months on the Gateway space station), on the lunar surface (3 months within habitat), and another 3 months on Gateway before return to Earth. For this DRM, IMPACT ultimately outlined a preferred medical system that was then associated with medical conditions considered to be most likely based on frequency, most likely to cause astronaut task time loss (TTL), most likely to cause return to definitive care (RTDC), and most likely cause loss of crew life (LOCL). IMPACT also highlighted the medical capabilities/skills that would be required to care for those medical conditions, such as performing a history of present illness or musculoskeletal exam with ultrasound. The primary objective of the project was to perform a survey of the AI tools and systems applicable to the conditions outlined for the proposed mLDLOLS mission. Using PubMed (including most relevant MeSH terms) and Google Scholar, we then created a robust annotated bibliography organized by condition. The 56-page and over 500 reference annotated bibliography was subsequently used to create a review outline that would become the basis for drafting of a future publication. For the review outline, we took those medical conditions researched within the annotated bibliography (condition-based approach) and deployed a systems-based approach, combining those medical conditions and related tools into ten categories. These categories included general/all-purpose CDSSs, tools to diagnose or manage respiratory, dermatologic, neurologic, auditory and vestibular, ophthalmic, musculoskeletal, infection-associated, and gynecologic conditions, as well as tools that could be deployed in the setting of trauma/emergency. With the completion of the 30-page outline, we then began drafting the review paper. To conclude the research experience, I presented the findings from our survey to the ExMC Clinical and Science team. With these objectives, I ultimately learned about the number of AI tools that exist today to assist medical professionals with the triage, diagnosis, and management of several medical conditions. These tools can span from chatbot assistants to help triage knee pain to vision transformer models that can identify ophthalmic conditions based on ocular surface images captured with a cell phone. We also highlighted the current gaps that exist in the literature alongside the advancements that are needed to make the desired CDSS for deep space exploration missions. With this experience, I certainly confirmed an existing career goal and identified several additional skills needed to become an aerospace medical doctor including knowledge of critical care in an extreme medicine setting, aerospace engineering and human integration systems, artificial intelligence, machine learning, and risk models. I also identified numerous transferable skills for this career goal including the basic knowledge of medicine (MD), deployment of the scientific method for critical thought about new scientific questions (PhD), review of published literature, including creating an annotated bibliography (PhD), as well as detailed scientific writing (PhD). The results of my research will likely guide the design of an all-encompassing onboard medical assistant for use during deep space exploration missions of the future. I plan on sharing the outcomes from this experience with my peers at a student seminar in the Fall semester on August 30th. During the seminar, I will detail the project, my experience at NASA and AsMA, as well as offer best practice guidelines for students entertaining similar experiences or careers. In conclusion, I would like to thank the WVU School of Medicine, Research and Graduate Education office, as well as NASA ExMC for the unwavering support of this life-changing experience.

Ryan A. Lacinski↗
NASA NTRSDate not supplied

What You Need to Know about Planetary Protection Categorization for Your Mission

Planetary protection mission categorization helps to define the risk posture for requirements definition and implementation practices on space flight projects with planetary protection considerations. NASA has recently updated it’s planetary protection policy (NPR 8715.24), and with the update comes a major change in how the planetary protection categorization process is performed for NASA missions. Previously, projects would request the NASA Planetary Protection Officer (PPO) provide a categorization letter documenting the planetary protection category assigned to the proposed mission. Under the new policy the project manager (PM) proposes the planetary protection category for their mission. Depending on the level of the category, the PPO either concurs or recommends concurrence to the Chief of Safety and Mission Assurance (SMA) before forwarding to the Mission Directorate Associate Administrator (MDAA) for final approval prior to the system requirements review (SRR). But what topics must be considered for categorization? This presentation will provide key considerations for planetary protection mission categorization including the target solar system body to be explored, the trajectory to get to the target body, and the operations to be performed at the target body. Additional unique scenarios such as secondary and auxiliary payloads, encountering other solar system bodies on the way to the target body, and sample return missions will also be discussed to share lessons learned from missions that have been through the new categorization process.

Elaine Seasly↗
NASA NTRSDate not supplied

BioSentinel: Leading the Way for Deep Space CubeSat Missions

Flagship science missions are not alone in Deep Space thanks to BioSentinel, a 6U spacecraft launched on Artemis-1. BioSentinel is one of the longest operating CubeSats beyond cislunar space. The subsystems and COTS components of the BioSentinel bus are a template for future deep space missions, and the lessons learned from over a year of operations will enable improved performance for the next missions. BioSentinel achieved its unprecedented performance for an SLS secondary payload due to preparation, planning, and a robust design. Pre-launch antenna and interface testing with both DSN and ESA confirmed command and data pathways and allowed for operational flexibility in the critical early hours post-deployment. Mission Operations simulations prior to launch identified potential risks and primed operators to respond in flight, preparing the team to react quickly to successfully detumble the spacecraft and enter a power-positive state. The spacecraft would not have survived without the inclusion of the trailblazing 3D-printed composite cold gas propulsion system. The non-standard tank geometry enabled efficient use of the limited space available in the CubeSat, as well as the capability to detumble the spacecraft and manage momentum, while providing sufficient margin to execute potential delta-V maneuvers. The Iris radio has operated for over 18 months with no significant issues. Initial Iris performance estimates have been accurate throughout the mission. BioSentinel continues to collect data on thermal conditions and to validate our performance models with real-world knowledge. We have received exemplary support from our DSN partners. Following the conclusion of the primary science mission, the Linear Energy Transfer (LET) Spectrometer continued to collect solar and galactic radiation data from its location in heliocentric orbit. The free space dataset offered by the BioSentinel LET is a valuable source of data for model validation and future mission planning. As the spacecraft travels farther from Earth it is poised to provide longitudinally distributed measurements of solar particle events during solar maximum. The lessons learned from BioSentinel suggest key areas to enhance performance. The ability to upload modified flight software can increase the stability of memory management. Additional heaters in the propulsion system design have already proven successful on the Starling mission. Streamlining mission operations can reduce costs, increase data return, and better utilize DSN time. Enhancements such as these will facilitate reliable, long-duration deep space exploration using the proven BioSentinel 6U CubeSat bus.

BioSentinel↗
NASA NTRSDate not supplied

BioSentinel: Forging the path for Deep Space CubeSat Missions

The BioSentinel mission was launched in 2022 aboard the SLS launch vehicle as part of the Artemis-I campaign and continues mission operations into 2024. The 6U CubeSat has been characterizing deep space radiation at large distances from Earth. This presentation gives a status of the mission performance to date, as well as some of the lessons learned from project. BioSentinel has achieved unprecedented performance as an SLS secondary payload due to preparation, planning, and a robust design. Pre-launch antenna and interface testing with both DSN and ESA confirmed command and data pathways and allowed for operational flexibility in the critical early hours post-deployment. Mission Operations simulations prior to launch identified potential risks and trained operators to respond in flight, preparing the team to react quickly and successfully to detumble the spacecraft and enter a power-positive state. The spacecraft would not have survived without the inclusion of the trailblazing 3D-printed composite cold gas propulsion system. The non-standard tank geometry enabled efficient use of the limited space available in the CubeSat form factor as well as the capability to detumble the spacecraft and manage momentum for extended mission durations, while providing sufficient margin to execute potential delta-V maneuvers. Following the conclusion of the primary science mission, the Linear Energy Transfer (LET) Spectrometer has continued to collect solar and galactic radiation data from its unique location in heliocentric orbit. The free space dataset offered by the BioSentinel LET is a valuable source of data for both model validation and future mission planning. As the spacecraft travels farther from Earth it is poised to provide longitudinally distributed measurements of solar particle events during solar maximum. NASA Ames led development of the BioSentinel spacecraft to operate for long durations in deep space. The novel subsystems and COTS components that comprise the BioSentinel bus can serve as a template for future deep space missions, while the lessons the team has learned from well over a year of continuous operations will enable improved performance in the generation of deep space CubeSat missions.

BioSentinel↗
NASA NTRS2024

The Active Volcanoes of Kamchatka as Suitable Terrestrial Analogs Within the AVENGERS Initiative: An Opportunity for In-Situ Operational Tests for Future Landing Venus Missions

The next decade will see the return to Venus thanks to a number of missions which have been recently selected and proposed for launch. The Roscosmos Venera-D mission, along with the NASA DAVINCI, NASA VERITAS, ESA EnVision, the ISRO Shukrayaan-1, and the CNSA VOICE missions will open a new era for the exploration of the Earth’s hellish twin planet. The next missions to Venus should be able to shed new light on the science questions such as: a) whether the volcanic activity on this planet is locally constrained, or volcanism acts on a global scale, b) the rate of the present-day volcanic activity, and c) the style of volcanism on Venus, whether it is predominantly effusive, or the occurrence of local episodes of pyroclastic volcanism is also possible. In preparation for the future missions to Venus, the Analogs for VENus’ Geologically Recent Surfaces (AVENGERS) initiative will select and analyze a number of active terrestrial volcanoes as suitable analogs for the identification and analysis of active volcanism on Venus. Among the future missions to Venus, the Roscosmos Venera-D is the only one to be equipped with a lander which will analyze the elemental and mineralogical composition of the surface. As the young topographic rises (areas characterized by recent volcano-tectonic activity) on Venus are being proposed as one of the possible terrain types for the Venera-D landing, it is crucial to look for volcanic areas on Earth where to perform operational tests such as surface drilling and in-situ elemental composition analysis. To this regard, we propose here the analysis of the active volcanoes of the Kamchatka Peninsula in Russia as a very suitable analog for the Venera-D mission, as well as for the analysis of surface change detection due to ongoing eruptions. The Kamchatka Peninsula is located on the eastern margin of the Eurasia plate, in proximity of the Kuril-Kamchatka subduction zone. The volcanoes of the Kamchatka Peninsula are among the most active volcanoes of the world, making them a suitable terrestrial analog in the search for active volcanism on Venus. Moreover, the volcanoes of Kamchatka are characterized by pyroclastic activity. Since the previous Soviet Venera and Vega missions landed over areas which elemental composition was most likely consistent with that of tholeiitic basalts, performing operational tests over areas characterized by pyroclastic activity also offers the unique opportunity to provide us the tools to potentially interpret the diverse output given by landing over portions of the surface of Venus possibly characterized by explosive volcanic products. Finally, the frequent eruptions characterizing the volcanoes of the Kamchatka Peninsula make them also a suitable terrestrial analog for the possible detection of ongoing eruptions on Venus by future missions, which can be achieved by comparing two (or more) radar images of the same volcano (and its surroundings) in two (or more) different moments of time.

Planetary Geology↗
NASA NTRS2024

Cognitive Performance in ISS Astronauts on 6-Month Low Earth Orbit Missions

Introduction: Current and future astronauts will endure prolonged exposure to spaceflight hazards and environmental stressors that could compromise cognitive functioning, yet cognitive performance in current missions to the International Space Station remains critically under-characterized. We systematically assessed cognitive performance across 10 cognitive domains in astronauts on 6-month missions to the ISS. Methods: Twenty-five professional astronauts were administered the Cognition Battery as part of National Aeronautics and Space Administration (NASA) Human Research Program Standard Measures Cross-Cutting Project. Cognitive performance data were collected at five mission phases: pre-flight, early flight, late flight, early post-flight, and late post-flight. We calculated speed and accuracy scores, corrected for practice effects, and derived z-scores to represent deviations in cognitive performance across mission phases from the sample’s mean baseline (i.e., pre-flight) performance. Linear mixed models with random subject intercepts and pairwise comparisons examined the relationships between mission phase and cognitive performance. Results: Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. There was slowed performance observed in early flight on tasks of processing speed, visual working memory, and sustained attention. We observed a decrease in risk-taking propensity during late flight and post-flight mission phases. Beyond examining group differences, we inspected scores that represented a significant shift from the sample’s mean baseline score, revealing that 11.8% of all flight and post-flight scores were at or below 1.5 standard deviations below the sample’s baseline mean. Finally, exploratory analyses yielded no clear pattern of associations between cognitive performance and either sleep or ratings of alertness. Conclusions: There was no evidence for a systematic decline in cognitive performance for astronauts on a 6-month missions to the ISS. Some differences were observed for specific subtests at specific mission phases, suggesting that processing speed, visual working memory, sustained attention, and risk-taking propensity may be the cognitive domains most susceptible to change in Low Earth Orbit for high performing, professional astronauts. We provide descriptive statistics of pre-flight cognitive performance from 25 astronauts, the largest published preliminary normative database of its kind to date, to help identify significant performance decrements in future samples.

Data curation↗
NASA NTRSDate not supplied

Using Artificial Intelligence and Machine Learning to Enhance Mission Design and Operations of the Habitable Worlds Observatory (HWO)

One key aspect in the development of HWO is the early deployment of artificial intelligence (AI) and machine learning (ML) to enhance mission science and operations. Our subtask group is part of the HWO AI/ML working group and focuses on AI and ML for mission operations. Our task group seeks to educate other HWO working groups about AI and ML capabilities for mission operations, investigate how to bridge technology gaps, and enable new capabilities particularly in the areas of observational scheduling, instrument health monitoring, and downlink operations. We focus on mission tasking / scheduling both for mission analysis in development and operations. AI and ML for mission scheduling includes: tools to support proposal calls and review, ensuring fairness in calls for proposals, community peer reviews and ease workloads, as well as in-flight and ground software development (e.g., using natural language processing (NLP) to support process automation from requirements). AI and ML for the mission’s development and operations include 1) anomaly detection and prediction (from onboard and ground based tools) to monitor the spacecraft’s health, 2) ground-based automated scheduling for mission operations including long-term and short-term planning and maintenance, and 3) flight system flexible execution (as flight proven for Spitzer and JWST) to enable robust execution despite execution variations, and 4) data analysis for prioritization (e.g., real-time data evaluation leading to autonomous actions and adjustments, high-priority identification, onboard data compression, etc.). Incorporation of ML and AI will enable HWO to address the major science questions related to exoplanet characterization, general astrophysics, and solar system exploration and also extend the boundaries of space mission technologies.

Mark Moussa↗
NASA NTRS2007

JPL Power Systems for Current Planned Missions

The viewgraph presentation includes fact sheets, instrument lists, and mission parameters for 13 future missions. Those missions include Moon Mineralogy Mapping (MMM), Space Interferometry Mission (SIM), New Millennium--Space Technology-8 (ST-8), Ocean Salinity Mapping Orbiter (Aquarius), Ocean Surface Topology Mission (OSTM), Asteroid Rendezvous Mission-SEP (Dawn), Mars Scout Lander Mission (Phoenix), Solar Powered Jupiter Orbiter (Juno), Earth orbiting carbon observatory (OCO), planet finder observatory (Kepler), far infrared/sub-millimeter telescope (Hershel), Wide-field Infrared Survey Explorer (WISE), and Mars Science Laboratory-Rover (MSL). The presentation also contains a table of current missions and instruments.

Phoenix↗
NASA NTRS1994

(abstract) Science-Project Interaction in the Low-Cost Mission

Large, complex, and highly optimized missions have performed most of the preliminary reconnaisance of the solar system. As a result we have now mapped significant fractions of its total surface (or surface-equivalent) area. Now, however, scientific exploration of the solar system is undergoing a major change in scale, and existing missions find it necessary to limit costs while fulfilling existing goals. In the future, NASA's Discovery program will continue the reconnaisance, exploration, and diagnostic phases of planetary research using lower cost missions, which will include lower cost mission operations systems (MOS). Historically, one of the more expensive functions of MOS has been its interaction with the science community. Traditional MOS elements that this interaction have embraced include mission planning, science (and engineering) event conflict resolution, sequence optimization and integration, data production (e.g., assembly, enhancement, quality assurance, documentation, archive), and other science support services. In the past, the payoff from these efforts has been that use of mission resources has been highly optimized, constraining resources have been generally completely consumed, and data products have been accurate and well documented. But because these functions are expensive we are now challenged to reduce their cost while preserving the benefits. In this paper, we will consider ways of revising the traditional MOS approach that might save project resources while retaining a high degree of service to the Projects' customers. Pre-launch, science interaction can be made simplier by limiting numbers of instruments and by providing greater redundancy in mission plans. Post launch, possibilities include prioritizing data collection into a few categories, easing requirements on real-time of quick-look data delivery, and closer integration of scientists into the mission operation.

mission operation science community interaction co↗
NASA NTRS1994

(abstract) Follow-on Missions for the Pluto Spacecraft

The Pluto Fast Flyby mission development baseline consists of 2 identical spacecraft (120 - 165 kg) to be launched to Pluto/Charon in the late 1990s. These spacecraft are intended to fly by Pluto and Charon in order to perform various remote-sensing scientific investigations and have a mission development cost less than $400M (FY92$) through launch plus 30 days. The long-life (6 - 10 years) mission duration and lightweight design make the Pluto spacecraft a good candidate for a number of other flyby missions to objects in the outer Solar System, and some of these were investigated by JPL in cooperation with NASA Code SL's (Solar System Exploration) Outer Planets Science Working Group (OPSWG) in 1993. The JPL team looked at what it would mean to fly one of these missions (if a third spacecraft were available) in terms of flight time, spacecraft modifications, and science payload resources; the OPSWG recommended science investigation modifications for the different targets based on the available resources. The missions could, in many cases, utilize less capable launch vehicles, thereby reducing life-cycle cost of the mission. Examples of the sort of targets which were investigated and looked attractive in terms of flight time are: Uranus, Neptune, Uranus/Neptune dual-mission, Trojan asteroids (624 Hektor, 617 Patroclus, others), 5145 Pholus (the reddest object known in the solar system), and Kuiper Belt objects (i.e., 1992 QB1) . This paper will present the results of this investigation in terms of potential science return, performance, and the potential for life-cycle cost reductions through inheritance from Pluto Fast Flyby .

Pluto Charon flyby follow-on missions↗