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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Critical Team Composition Issues for Long-Distance and Long-Duration Space Exploration: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research

Prevailing team effectiveness models suggest that teams are best positioned for success when certain enabling conditions are in place (Hackman, 1987; Hackman, 2012; Mathieu, Maynard, Rapp, & Gilson, 2008; Wageman, Hackman, & Lehman, 2005). Team composition, or the configuration of member attributes, is an enabling structure key to fostering competent teamwork (Hackman, 2002; Wageman et al., 2005). A vast body of research supports the importance of team composition in team design (Bell, 2007). For example, team composition is empirically linked to outcomes such as cooperation (Eby & Dobbins, 1997), social integration (Harrison, Price, Gavin, & Florey, 2002), shared cognition (Fisher, Bell, Dierdorff, & Belohlav, 2012), information sharing (Randall, Resick, & DeChurch, 2011), adaptability (LePine, 2005), and team performance (e.g., Bell, 2007). As such, NASA has identified team composition as a potentially powerful means for mitigating the risk of performance decrements due to inadequate crew cooperation, coordination, communication, and psychosocial adaptation in future space exploration missions. Much of what is known about effective team composition is drawn from research conducted in conventional workplaces (e.g., corporate offices, production plants). Quantitative reviews of the team composition literature (e.g., Bell, 2007; Bell, Villado, Lukasik, Belau, & Briggs, 2011) are based primarily on traditional teams. Less is known about how composition affects teams operating in extreme environments such as those that will be experienced by crews of future space exploration missions. For example, long-distance and long-duration space exploration (LDSE) crews are expected to live and work in isolated and confined environments (ICEs) for up to 30 months. Crews will also experience communication time delays from mission control, which will require crews to work more autonomously (see Appendix A for more detailed information regarding the LDSE context). Given the unique context within which LDSE crews will operate, NASA identified both a gap in knowledge related to the effective composition of autonomous, LDSE crews, and the need to identify psychological and psychosocial factors, measures, and combinations thereof that can be used to compose highly effective crews (Team Gap 8). As an initial step to address Team Gap 8, we conducted a focused literature review and operational assessment related to team composition issues for LDSE. The objectives of our research were to: (1) identify critical team composition issues and their effects on team functioning in LDSE-analogous environments with a focus on key composition factors that will most likely have the strongest influence on team performance and well-being, and 1 Astronaut diary entry in regards to group interaction aboard the ISS (p.22; Stuster, 2010) 2 (2) identify and evaluate methods used to compose teams with a focus on methods used in analogous environments. The remainder of the report includes the following components: (a) literature review methodology, (b) review of team composition theory and research, (c) methods for composing teams, (d) operational assessment results, and (e) recommendations.

Bell, Suzanne T.↗
NASA NTRS2010

Interplanetary Transit Simulations Using the International Space Station

We evaluated the space life sciences utility of the International Space Station (ISS) to simulate the outbound transit portion of missions to Mars and Near Earth Asteroids (NEA) to investigate biomedical and psychological aspects of such transits, to develop and test space operation procedures compatible with communication delays and outages, and to demonstrate and validate technologies and countermeasures. Two major categories of space life sciences activities can capitalize on ISS capabilities. The first includes studies that require ISS (or a comparable facility), typically for access to prolonged weightlessness. The second includes studies that do not strictly require ISS but can exploit it to maximize their scientific return more efficiently and productively than in ground-based simulations. For these studies, ISS offers a high fidelity analog for fundamental factors on future missions, such as crew composition, mission control personnel, operational tasks and workload, real-world risk, and isolation, and can mimic the effects of distance and limited accessibility. In addition to conducting Mars- and NEA-transit simulations on 6-month ISS increments, extending the current ISS increment duration from 6 months to 9 or even 12 months will provide opportunities for enhanced and focused research relevant to long duration Mars and NEA missions. Increasing the crew duration may pose little additional risk to crewmembers beyond that currently accepted on 6-month increments, but additional medical monitoring capabilities will be required beyond those currently used for ISS operations. Finally, while presenting major logistical challenges, such a simulation followed by a post-landing simulation of Mars exploration could provide quantitative evidence of capabilities in an actual mission. Thus, the use of ISS to simulate aspects of Mars and NEA missions seems practical. If it were to be implemented without major disruption of on-going ISS activities, then planning should begin soon, in close consultation with all international partners.

Charles, John B.↗
DOE OSTI2022

Agent-Based Modeling for the Circular Economy: Lessons Learned From Three Case Studies

The circular economy (CE) aims at decoupling human activities from resource use, creating wealth in the process. Recently, many scholars have questioned the link between increased circularity and sustainability, resulting in many methodological approaches being developed for that purpose. This presentation summarizes the insights gained from the application of agent-based modeling (ABM) to study the techno-economic and social conditions promoting circularity and sustainability of three technologies: photovoltaic (PV) modules, hard disk drives (HDDs), and wind blades. Four main categories of agents are defined in the ABM: asset owners, service providers (e.g., refurbishers), recyclers, and manufacturers. Two main CE strategies are represented: lifetime extension (through repair or reuse) and recycling. The developed models start by projecting installed capacities and end-of-life (EOL) quantities. Then the theory of planned behavior - a social psychology model explaining behavior adoption based on attitude, peer influence, and costs - is used to model the asset owners' EOL decision (i.e., landfill, recycle or extend the lifetime of the asset). Then, the quantities of assets flowing to the recycler and service provider agents and quantities of materials flowing to manufacturers are computed. Recyclers' economies of scale are dynamically modeled, and the value generated by the CE strategies for the recyclers, service providers, and manufacturers is computed within the model. When data are available, avoided greenhouse gas emissions resulting from the CE strategies adoption are calculated exogenously from the ABM simulations. Results show that with improved used PV modules warranties, the reuse CE strategy adoption increases from 1% to 23% between 2020 and 2050. Similarly, improved standards could enhance HDDs end-users trust in data-wiping - a prerequisite to reuse - leading to a 3-fold increase in the reuse rate and avoid about 5 million tons of CO2 eq by 2050. Regarding wind blades, 5-15 years lifetime extension could reduce EOL blade quantities by 13%. High costs and logistic issues prevent blades from being recycled in greater quantities. One insight from the case studies is the necessity to have mature secondary markets for reuse to be a viable option. Interestingly, PV reuse is limited by the willingness of PV owners to purchase used modules (on the demand side), while HDDs reuse is constrained by the lack of trust toward data-wiping (limiting the supply of used HDDs). The six limits of the CE concepts presented by Korhonen et al. (2018) are finally used to interpret the results. The HDD case study is an exemplary lock-in, where the first accepted practice (shredding) retains most of the market. The PV results illustrate the technical limitation to reuse, as the growing demand cannot be supplied entirely with used PV modules. The wind case study shows the relevance of clearly defining physical flows - what type of waste should wind blades be considered, how should they be transported and landfilled? - a crucial consideration that also applies to PV modules. Finally, the three case studies highlight the relevance of studying a technology's technical, economic, and market material efficiency potentials altogether and the potential benefit of coupling ABM to life cycle assessment.

agent-based modeling↗
NASA NTRSDate not supplied

Prospects for Future Human Space Flight Missions to Near-Earth Asteroids

The forthcoming Near-Earth Object (NEO) Surveyor space telescope is a foundational asset designed to complete NASA’s congressionally-mandated goal of cataloging ≥90% of NEOs ≥140 meters in size as soon as practical, and discover Earth impactors far in advance. NEO Surveyor is also critical to near-Earth asteroid (NEA) exploration because it will find suitable low-Δv NEAs for robotic and human missions, often on Earth-like orbits with long synodic periods. Such NEAs have usually not been detected until imminent Earth launch opportunities because they were not observable until close to Earth. Discovering them far enough in advance to deploy missions requires a deep-space infrared survey telescope such as NEO Surveyor. In addition to posing hazards and being scientifically important, NEAs contain resources, such as water (OH), that could be utilized off-Earth. They also offer unique opportunities for the most ambitious human voyages ever undertaken. The Apollo program forever changed humanity’s perspective by showing us Earthrise from our Moon through human eyes. Crewed missions to NEAs will forever change our perspective again by showing us Earth as a distant point of light in the heavens as seen from an asteroid by astronauts. Planetary defense endeavors to understand asteroid and comet impact risks and develop mitigation capabilities. NEA exploration is synergistic in multiple ways. NEO Surveyor will discover and help characterize Earth impactors and accessible NEAs. Heavy-lift launch is highly enabling for both human NEA missions and planetary defense. Reconnaissance missions for planetary defense can also characterize NEAs prior to crewed missions. In situ resource utilization (ISRU) systems may be applicable to deflecting or destroying hazardous NEAs. NEA characterization data critically inform planetary defense efforts and indicate NEA types suitable for human exploration or ISRU. In 2010, NASA performed the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS), creating an automated online system monitoring mission accessibility of NEAs 2 . NHATS database NEAs meet criteria that require less total mission Δv and/or round-trip mission duration than the Martian surface or even Mars orbit. There are currently 4,658 NHATS NEAs, and many rival or exceed lunar orbit/surface accessibility. Thus, NHATS NEAs could be explored by humans prior to attempting a Mars mission. Human missions to NEAs would test human-rated spacecraft systems with less cost and risk than Mars missions. Thus, human missions to NEAs are compelling in their own right while also providing prudent preparation for more demanding Mars missions. Lunar missions can offer similar opportunities, but they differ from NEA missions in important ways. Lunar missions pose less demanding psychological challenges to crew and ground staff. Earth light-time delay for communications is significantly longer during NEA missions. NEA missions are available that require more propulsion system consumables than lunar missions but less than Mars missions. In this paper, we summarize NEA accessibility for human missions, discuss motivations for such missions, survey knowledge about NEAs that informs future human missions, present exemplar mission opportunities to the currently known NHATS NEAs, and describe future work towards enabling human NEA missions.

Near-Earth asteroids↗
NASA NTRS2004

Perceptual learning through optimization of attentional weighting: human versus optimal Bayesian learner

Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.

Non-NASA Center↗