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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 NTRS2011

An Interview with Joe McMann: Lessons Learned from Fifty Years of Observing Hardware and Human Behavior

Pica Kahn conducted "An Interview with Joe McMann: Lessons Learned in Human and Hardware Behavior" on August 16, 2011. With more than 40 years of experience in the aerospace industry, McMann has gained a wealth of knowledge. This presentation focused on lessons learned in human and hardware behavior. During his many years in the industry, McMann observed that the hardware development process was intertwined with human influences, which impacted the outcome of the product.

McMann, Joe↗
NASA NTRS1978

Prospects of a mathematical theory of human behavior in complex man-machine systems tasks

A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued.

Johannsen, G.↗
DOE OSTI2020

Quantifying Human Behavior and Decision Errors in Security Screening Operations

The potential for human errors in conducting security related screening operations can lead to inadvertent and adverse decision outcomes. This paper overviews an initial mathematical framework designed to model and quantify the various human factors and decision outcomes that may occur in conducting security screening operations, such as U.S. port of entry radiological and nuclear (rad/nuc) security screening. This framework is based on the Human Error Assessment and Reduction (HEART) technique. As applied here, the framework incorporates a set of rules for human engagement, including a prescribed concept of operations (CONOPS) and deviations that may occur from this established CONOPS due to inadvertent personnel decision errors. We also review some of the various factors that may adversely influence such decisions by security screening personnel. Some of these factors include current workload, environmental conditions, training, and various other intangible factors. Using the HEART methodology, we translate each of these factors into error producing conditions, their effects on error, an assessed proportion of effects, and finally the overall probability of human error at each stage of the screening process. We then include a small scale example to demonstrate the methodology and results based on an assumed set of input conditions at a notional port of entry.

Brigantic, Robert T.↗
NASA NTRS2011

Modeling Humans as Reinforcement Learners: How to Predict Human Behavior in Multi-Stage Games

This paper introduces a novel framework for modeling interacting humans in a multi-stage game environment by combining concepts from game theory and reinforcement learning. The proposed model has the following desirable characteristics: (1) Bounded rational players, (2) strategic (i.e., players account for one anothers reward functions), and (3) is computationally feasible even on moderately large real-world systems. To do this we extend level-K reasoning to policy space to, for the first time, be able to handle multiple time steps. This allows us to decompose the problem into a series of smaller ones where we can apply standard reinforcement learning algorithms. We investigate these ideas in a cyber-battle scenario over a smart power grid and discuss the relationship between the behavior predicted by our model and what one might expect of real human defenders and attackers.

Lee, Ritchie↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Human behavioral research in space: quandaries for research subjects and researchers

With the advent of long-duration spaceflight on board the International Space Station (ISS) and possible future missions beyond low Earth orbit (LEO) such as Mars, it is critical that those at NASA have a realistic assessment of the challenges that will face individuals on long-duration missions so that they can develop preventive and real-time countermeasures to behavioral health issues. While space travellers are very interested in having countermeasures to the deleterious effects of space missions, they have a powerful disincentive to participate in this research if they feel it could in any way negatively affect their flight status. The behavioral issues of isolation and confinement for extended-duration space missions are reviewed. Areas of basic and clinical behavioral research are listed. And the classical clinical model for research is not considered appropriate for the current configuration of the space program. The use of analogue environments and advanced statistical analysis are suggested as ways to address the limited spaceflight research opportunities. The challenge of research subject or patient confidentiality vs. mission safety and issues of personal flight status are addressed.

Review, Tutorial↗
NASA NTRS2007

Development of a Human Behavior and Performance Training Curriculum for ISS Astronauts

The paper will describe the DACUM process and summarize the core competencies that were agreed upon, internationally, as important for ISS astronauts. The paper will further discuss the ongoing work being completed by the subgroup, Human Behaviour and Performance Training Working Group, including defining the competencies and behavioural markers. Finally, an overview of remaining work will be provided, including determining which competencies require formal training and which require no formal training, developing training objectives, sequencing the training, and establishing how to assess training effectiveness. DISCUSSION: Designing a common set of goals for behavioural training has been the desire of the SHBP WG since its inception in 1998. This group, along with training specialists and astronauts, are making great strides toward defining these competencies. The road ahead will be exceedingly challenging as training objectives are defined and a training flow is proposed to the MCOP; with proposed ISS crews increasing to six people in the near future, such enhanced behavioural training may be all the more essential for mission success.

VanderArk, Steve↗
DOE OSTI2020

A review of select human-building interfaces and their relationship to human behavior, energy use and occupant comfort

In recent years, research has emerged to quantitatively and qualitatively understand occupants' interactions with buildings. However, there has been surprisingly little research on building interfaces and how their design, context (e.g., location), and underlying logic impact their usability and occupants’ perceived control, as well as the resulting comfort and energy performance. This means that research is needed to better understand how occupants interact with building interfaces in both commercial and residential applications; both applications are important to address as there are many differences in interface types, level of control and understanding, and even expectations of engagement. Herein, this paper provides a cursory review and discussion of select common building interfaces: windows, window shades/blinds, thermostats, and lighting controls. The goal of this paper is to review literature related to these human-building interfaces to explore interface characteristics, current design and use challenges, and relationships between building interfaces and occupants. Human-building interface interactions are complex, more research is needed to understand design, use, and characteristics. Common themes emerged throughout the literature review to explain occupant interactions (or lack of interactions) with building interfaces, which included thermal and visual comfort, ease and access of control, interface/control placement, poor interface/control design, lack of understanding, and social-behavioral dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Veggie on Ice: The Effects of Plant Production on Human Behavioral Health Long-Duration Antarctic Overwintering Missions

Exploration class missions pose an increased risk of adverse crew behavioral health and psychiatric conditions. Identifying and developing effective and efficient countermeasure strategies are necessary to maintain crew health and performance. Previous studies (VEG-04A and VEG-04B) in the Veggie vegetable-production system on the International Space Station have evaluated the behavioral health effects of caring for plants as a potential countermeasure for crew stresses in spaceflight. The presence of plants can augment sensory stimulation (visual, tactile, and olfactory), provide a psychological link to Earth, reduce stress, and increase happiness. However, further research is needed to understand this strategy for longer-duration missions in isolated, confined, extreme (ICE) environments. The Neumayer III Station in Antarctica is one such environment that hosts a small crew for fourteen-month missions, of which eight to nine months are the remote overwintering phase. Neumayer III also features EDEN ISS, a greenhouse facility with 12.5 m2 plant cultivation space that, like Veggie, currently supplements the crew diet with a variety of fresh produce. Up to nine crew members of the 2021 overwintering mission will complete behavioral health surveys that are designed to capture enjoyment and time spent conducting various plant-related activities, sensory stimulation, and active and passive psychological effects of having live plants and available fresh food in an ICE environment. Data will be collected once pre-mission, up to ten times in-mission at monthly increments, and once post-mission. This study aims to quantify the impact of plant care as a countermeasure strategy for human spaceflight and Antarctic exploration missions.

J M Bunchek↗
NASA NTRS2003

The psychology of isolated and confined environments. Understanding human behavior in Antarctica

Psychosocial adaptation to isolated and confined environments exhibits 4 distinct characteristics. First, it is seasonal: Variations in mood are associated with the altered diurnal cycle and psychological segmentation of the mission. Second, it is situational: Concurrent measures of personality, interpersonal needs, and coping styles are better predictors of mood and performance than are predeployment measures. Third, it is social: Members of expeditions with low social coherence report significantly more depression, anxiety, and anger than individuals belonging to expeditions with high social coherence. Fourth, it is salutogenic: Depressed mood is inversely associated with the severity of the physical environment of the station, and the winter-over experience is associated with reduced subsequent rates of hospital admissions, suggesting positive benefits for individuals seeking challenging experiences.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS1986

Foods and food constituents that affect the brain and human behavior

Until recently, it was generally believed that brain function was usually independent of day-to-day metabolic changes associated with consumption of food. Although it was acknowledged that peripheral metabolic changes associated with hunger or satiety might affect brain function, other effects of foods on the brain were considered unlikely. However, in 1971, Fernstrom and Wurtman discovered that under certain conditions, the protein-to-carbohydrate ratio of a meal could affect the concentration of a particular brain neurotransmitter. That neurotransmitter, serotonin, participates in the regulation of a variety of central nervous system (CNS) functions including sleep, pain sensitivity, aggression, and patterns of nutrient selection. The activity of other neurotransmitter systems has also been shown to be, under certain conditions, affected by dietary constituents which are given either as ordinary foods or in purified form. For example, the CNS turnover of two catecholamine neurotransmitters, dopamine and norepinephrine, can be altered by ingestion of their amino acid precursor, tyrosine, when neurons that release these monoamines are firing frequently. Similarly, lecithin, a dietary source of choline, and choline itself have been shown to increase the synthesis of acetylcholine when cholinergic neurons are very active. It is possible that other neurotransmitters could also be affected by precursor availability or other, as yet undiscovered peripheral factors governed by food consumption. The effects of food on neurotransmitters and behavior are discussed.

Lieberman, Harris R.↗
NASA NTRS2004

Anticipatory Eye Movements in Interleaving Templates of Human Behavior

Performance modeling has been made easier by architectures which package psychological theory for reuse at useful levels of abstraction. CPM-GOMS uses templates of behavior to package at a task level (e.g., mouse move-click, typing) predictions of lower-level cognitive, perceptual, and motor resource use. CPM-GOMS also has a theory for interleaving resource use between templates. One example of interleaving is anticipatory eye movements. This paper describes the use of ACT-Stitch, a framework for translating CPM-GOMS templates and interleaving theory into ACT-R, to model anticipatory eye movements in skilled behavior. The anticipatory eye movements explain performance in a well-practiced perceptual/motor task, and the interleaving theory is supported with results from an eye-tracking experiment.

Matessa, Michael↗
NASA NTRS2010

Propagation of New Innovations: An Approach to Classify Human Behavior and Movement from Available Social Network Data

It is interesting to observe new innovations, products, or ideas propagating into the society. One important factor of this propagation is the role of individual's social network; while another factor is individual's activities. In this paper, an approach will be made to analyze the propagation of different ideas in a popular social network. Individuals' responses to different activities in the network will be analyzed. The properties of network will also be investigated for successful propagation of innovations.

Mahmud, Faisal↗
NASA NTRS2011

Fifty Years of Observing Hardware and Human Behavior

During this half-day workshop, Joe McMann presented the lessons learned during his 50 years of experience in both industry and government, which included all U.S. manned space programs, from Mercury to the ISS. He shared his thoughts about hardware and people and what he has learned from first-hand experience. Included were such topics as design, testing, design changes, development, failures, crew expectations, hardware, requirements, and meetings.

McMann, Joe↗
NASA NTRSDate not supplied

Algorithmic Analysis of the Effect of Human Behavior on Future Urban Air Mobility Operations

The demand for a ride to work without running into the inefficiencies of traffic in a bustling, metropolitan area beckons for a system to tackle on-the ground traffic congestion, thus fueling the need for Urban Air Mobility (UAM). The instant gratification culture, notably its effect on Generation Z, has given way to the nature of impulsive decision making. The 2020 COVID-19 crisis, with its use of tap-to-gratify technology, highlights passengers preferring late booking. This last-minute airport reorganization crisis spearheaded our research goal to create a more user-personalized assessment of cancellation rates. Our research highlights that there will be a market in the 2030s for UAM, short-distance air transportation, and the world must prepare for the challenges that come with this new market. Through a two-part model, we obtained two randomized sets of profiles of user-specific and ridership attributes and their relationship with cancellations. Recommendations for future research include factoring this personalized aspect into cancellation projections to provide reasoned user discounts as well as a remedy for the scheduling chaos that stems from the airport organizational crisis.

Harbani Jaggi↗