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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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The traditional centralized planning and scheduling of complex fast moving projects are value-added activites. However, centralized scheduling has some severe deficiencies that have plagued managers since the Polaris project when PERT analysis was invented.
NASA Ames has flown a series of Bio-CubeSats that performed biology experiments supported by automated fluidic systems. Since Genesat-1 in 2006, these payloads have increased in complexity and functionality, building upon previous successes, and applying lessons learned. BioSentinel was the most recent of this series, launched into heliocentric orbit onboard Artemis-1 in 2022. This presentation will discuss how the fluidic technology developed for these Bio-CubeSat missions, including the multi-layer polycarbonate manifolds at the heart of the BioSentinel BioSensor, have spurred the development of several additional projects. Most directly is the modified BioSensor that will be a part of LEIA, which will perform its Lunar biology experiment onboard a Commercial Lunar Payload Services lander. Several search-for-life manifolds have been designed to prepare samples from icy moons for downstream analyses. Two early career Polaris projects are developing fluidics to perform genetic sequencing on samples from multigenerational cell culture and to extract and quantify target miRNAs to support astronaut radiation health assessment. Improving the readiness of these systems has been accelerated by adopting the established flight heritage and microgravity-compatibility of the Bio-CubeSat fluidic hardware and designs, while focusing development efforts on the integration of novel functionalities and components.
BACKGROUND The commercialization of space will increasingly include individuals that are not rigorously-selected, highly-trained professional astronauts. Private astronaut missions (PAMs), such as Axiom-1 in 2022, will continue to travel to the International Space Station in the coming years, but the risk of integrating private astronauts with NASA astronauts has not been clearly quantified nor mitigated. An earlier internal NASA operations assessment, which consisted of a comprehensive literature review and interviews of current NASA experts, found that PAMs are likely to increase the risk to NASA astronauts during integrated missions (Landon, Whiting, Russell, Schorn, Passmore, & Roma, 2022). There are ongoing efforts at NASA to mitigate concerns from a medical, psychological, and technical perspective. NASA experts are working closely with PAM providers to offer recommendations and best practices beyond the limits of requirements to ensure crew health and safety. However, efforts are siloed between groups to some extent, and with the rate of PAMs likely to increase, a more comprehensive and integrated process is needed to reduce the burden on NASA resources. AIMS The purpose of this project is to understand private astronauts’ motivations for journeying to space, their pre-mission preparation period, and their experiences in space. Data will be collected via private astronaut post-mission debrief interviews. This data will inform training needs and in-mission support needed for missions that include private astronauts; the preparation NASA astronauts and mission support personnel will need to work with these integrated crews; and gaps in knowledge to guide research and countermeasure development. Our study aims to (1) Characterize risks posed by commercialization and private astronaut crew integration in spaceflight operations, as it relates to Team, Human Systems Integration Architecture (HSIA), and Behavioral Medicine (BMed) Risks, (2) Recommend potential countermeasures and identify gaps in current research. Countermeasures may be related to crew selection and composition, training, crew support systems (e.g., medical/psychological support, support from Mission Control, on-board resources), and habitability and human factors design. METHOD The BHP Lab will conduct 30-minute interviews with up to eight (8) private astronaut mission (PAM) astronauts (e.g., Axiom) and spaceflight participants (e.g., SFPs or “free flyers” on Polaris Dawn) per year from 2024-2030 to discuss knowledge gaps and needs related to selection and assessment, crew composition, training, crew support systems (e.g., medical/psychological support, support from Mission Control, onboard resources), and habitability and human factors design, which may influence the risk to NASA astronauts. Interviews will then be coded using thematic analysis and interpreted with the assistance of lexical analysis software (e.g., LIWC). As of the end of 2024, we have collected data from one PAM crew. At the conclusion of data collection in 2030, a final report will be prepared integrating all data collected by 2031. SUMMARY Post-return interviews of private astronauts are being conducted to understand their experiences and inform training and countermeasures to ensure the safety of all who journey to the ISS.
The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.
The Radiation Tolerant Displays project aims to develop a reference design for a display system that can withstand and mitigate the effects of radiation in deep space. Radiation Tolerant Displays seeks to deliver on this goal through a collaboration across industry and agency and by building upon the Mars Campaign Office’s (MCO) Project Polaris Radiation Tolerant Displays effort.
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The Tall Lunar Tower (TLT) In-Space Assembly (ISA) team aims to design, model, fabricate, autonomously assemble, and characterize a TLT engineering development unit (EDU). Cross-cutting truss assembly technology will be developed enabling construction of infrastructure in the lunar environment.
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Tall towers enable a wide-ranging set of capabilities on the lunar surface including communication, navigation, surveillance, power generation, and more. The Tall Lunar Tower project at NASA Langley Research Center is focused on the design, modeling, fabrication, and testing of an engineering development unit to assemble a tall tower through supervised autonomous operations. In this paper, the software design for the supervised autonomous assembly of a tall lunar tower is presented. The paper includes a high-level description of the concept of operations, the agents, and an overview of the software architecture.