Search NASA⌕ Search

SEARCH · Search NASA

Results for “Motivation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Finite Element Modeling of Extravehicular Mobility Units for Use With Human Body Models – Motivation, Major Challenges, Use Cases and Preliminary Work

Finite element modeling of pressurized spacesuits and implementation with human body models offers many advantages over physical experimentation, but also presents significant challenges. A model of pressurized spacesuit softgoods was developed, integrated with an existing hardgoods model, and fitted to a human body model. Two representative loading scenarios were simulated: dynamic external suit loading and internal occupant-driven loading, to serve as proof-of-concept for the modeling techniques employed. The modeled interactions behaved as intended and illustrate that finite element models of pressurized spacesuits can be used in conjunction with human body models to assess the biomechanical behavior. Further model development and experimental validation are needed.

Finite Element↗
DOE OSTI2021

Validation of Maui PSCAD Model: Motivation, Methodology, and Lessons Learned: Preprint

As power systems become increasingly dependent on inverter-based resources, the dominant physical and control interactions that determine system stability may no longer be accurately captured in positive sequence dynamic simulation tools; electromagnetic transient (EMT) simulations may be needed. This paper describes the process of creating and validating an EMT model of the entire Maui island transmission system in PSCAD software. The model is validated against the utility's PSSE model and against field data for an event that consisted of a single-phase fault followed by a generation trip. The methodology and lessons learned are summarized here.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Proactive and Reactive Thermal Comfort Behaviors

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet these challenges; however, experience shows that occupant overrides in DRPs compromises their effectiveness. There is a lack of formal understanding of how discomfort, routines, and other motivations affect DRP overrides and other related human building interactions (HBI). This paper reports preliminary findings from a study of 20 households in Colorado and Massachusetts, US over three months. Participants responded to ecological momentary assessments (EMA) triggered by thermostat interactions and at random times throughout the day. EMAs included Likert-scale questions of thermal preference, preference intensity, and changes to 7 different activity types that could affect thermal comfort, and an opened ended question about motivations of such actions. Twelve tags were developed to categorize motivation responses and analyzed statistically to identify associations between motivations, preferences, and HBI actions. Reactions to changes in the thermal environment were the most frequently observed motivation (118 of 220 responses). On the other hand, almost half (47%) responses were at least partially motivated by non-thermal factors, suggesting limited utility for occupant behavior models founded solely on thermal comfort. Changes in activity level and clothing were less likely to be reported when EMAs were triggered by thermostat interactions, while fan interactions were more likely. Windows, shades, and portable heater interactions had no significant dependence on how the EMA was triggered. These results suggest that better understanding of motivations for HBI may improve effectiveness of demand response programs.

Pathak, Maharshi↗
NASA NTRS2003

Exercise load index and changes in body weight during long-duration confinement in an isolated environment

PURPOSE: The objectives of this project were to investigate exercise load and body weight related to long-duration confinement in a closed environment simulating ISS flight conditions, and to evaluate subjects' motivation to continue the experiment and their adaptation to isolation. METHODS: Four Russian male subjects participated in a 240-d experiment (Group I), and four subjects (three male subjects and one female subject) from Austria, Canada, Japan, and Russia participated in a 110-d experiment (Group II). Exercise load was estimated during confinement using a modified Rating of Perceived Exertion scale. Free reports were used to determine subjects' motivation. Body weight was measured before, during, and after confinement. RESULTS: Group I achieved their lowest exercise loads during their first month of isolation; problems with adaptation to the isolation environment were also reported during this first month. Group II exercise load was significantly lower in the second month due to crewmember problems; loss of motivation could be noted from their free reports. The subject with the lowest exercise load retired from the isolation experiment earlier than scheduled. Exercise load was not correlated with prior exercise habits. Significant differences in body weight was observed between group I and II and between Russian and non-Russian subjects. One subject in Group I experienced a significant increase in his body weight. CONCLUSION: Exercise load may be a good indicator for adaptation problems and motivation changes in closed environments. Immobility, lack of space, and smoking cessation in general did not induce significant body weight changes.

Exercise/physiology↗
DOE OSTI2020

On‐site surrogates for large‐scale calibration

Abstract Motivated by a computer model calibration problem from the oil and gas industry, involving the design of a honeycomb seal, we develop a new Bayesian methodology to cope with limitations in the canonical apparatus stemming from several factors. We propose a new strategy of on‐site design and surrogate modeling for a computer simulator acting on a high‐dimensional input space that, although relatively speedy, is prone to numerical instabilities, missing data, and nonstationary dynamics. Our aim is to strike a balance between data‐faithful modeling and computational tractability in a calibration framework—tailoring the computer model to a limited field experiment. Situating our on‐site surrogates within the canonical calibration apparatus requires updates to that framework. We describe a novel yet intuitive Bayesian setup that carefully decomposes otherwise prohibitively large matrices by exploiting the sparse blockwise structure. Empirical illustrations demonstrate that this approach performs well on toy data and our motivating honeycomb example.

Huang, Jiangeng↗
NASA NTRS2005

MEMS CLOSED CHAMBER HEAT ENGINE AND ELECTRIC GENERATOR

A heat engine, preferably combined with an electric generator, and advantageously implemented using micro-electromechanical system (MEMS) technologies as an array of one or more individual heat engine/generators. The heat engine is based on a closed chamber containing a motive medium, preferably a gas; means for alternately enabling and disabling transfer of thermal energy from a heat source to the motive medium; and at least one movable side of the chamber that moves in response to thermally-induced expansion and contraction of the motive medium, thereby converting thermal energy to oscillating movement. The electrical generator is combined with the heat engine to utilize movement of the movable side to convert mechanical work to electrical energy, preferably using electrostatic interaction in a generator capacitor. Preferably at least one heat transfer side of the chamber is placed alternately into and out of contact with the heat source by a motion capacitor, thereby alternately enabling and disabling conductive transfer of heat to the motive medium.

Landis, Geoffrey A.↗
DOE OSTI2024

Experiments and Project-Based Enhancements for STEM Learning: Preprint

Motivating k-12 students to pick a career in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent attention. At different points in time, STEM educators need to pivot themselves and update educational materials to consistently motivate the next generation of k-12 students to enter into STEM careers. Once they enter undergraduate education, universities need to motivate their undergraduates students to consider graduate studies to ensure qualified human resources can be developed for research, and teaching. We present in this paper, our work on developing STEM materials for k-12 students targeting grid integration of hydrogen assets. This paper also presents our work on leveraging open source distribution system model, digital real time simulation tool to create projects for undergraduate students and motivate their interest in research topics, and enter into graduate level education.

electro-magnetic transients↗
NASA NTRS1997

Psychosocial value of space simulation for extended spaceflight

There have been over 60 studies of Earth-bound activities that can be viewed as simulations of manned spaceflight. These analogs have involved Antarctic and Arctic expeditions, submarines and submersible simulators, land-based simulators, and hypodynamia environments. None of these analogs has accounted for all the variables related to extended spaceflight (e.g., microgravity, long-duration, heterogeneous crews), and some of the stimulation conditions have been found to be more representative of space conditions than others. A number of psychosocial factors have emerged from the simulation literature that correspond to important issues that have been reported from space. Psychological factors include sleep disorders, alterations in time sense, transcendent experiences, demographic issues, career motivation, homesickness, and increased perceptual sensitivities. Psychiatric factors include anxiety, depression, psychosis, psychosomatic symptoms, emotional reactions related to mission stage, asthenia, and postflight personality, and marital problems. Finally, interpersonal factors include tension resulting from crew heterogeneity, decreased cohesion over time, need for privacy, and issues involving leadership roles and lines of authority. Since future space missions will usually involve heterogeneous crews working on complicated objectives over long periods of time, these features require further study. Socio-cultural factors affecting confined crews (e.g., language and dialect, cultural differences, gender biases) should be explored in order to minimize tension and sustain performance. Career motivation also needs to be examined for the purpose of improving crew cohesion and preventing subgrouping, scapegoating, and territorial behavior. Periods of monotony and reduced activity should be addressed in order to maintain morale, provide meaningful use of leisure time, and prevent negative consequences of low stimulation, such as asthenia and crew member withdrawal. Leadership roles and lines of authority need to be studied further to understand the factors leading to status leveling, leadership competition, and role confusion. Finally, the relationship between crews and ground personnel should be characterized in order to minimize the displacement of anger and tension to the outside, to counter the effects of inter-group miscommunications, and to develop support strategies that can help to counter in-group/out-group conflicts. Ground-based space simulations still have a role to play in terms of understanding the impact of these factors and ways of dealing with them. In particular, issues involving language, cultural differences, gender biases, career motivation, monotonous conditions, use of free time, leadership, lines of authority, and the relationship between crews and outside monitoring personnel need to be further characterized and examined under controlled conditions. Until such time as these factors can be studied directly in space, simulations provide an opportunity to learn more about these psychosocial issues and to plan ways of minimizing their negative consequences during actual space missions.

NASA Discipline Number 00-00↗
DOE OSTI2021

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Advanced Permanent Magnet Generator Topologies Using Multimaterial Shape Optimization and 3D Printing: Preprint

A vast majority of utility-scale wind turbine generators in the United States are dependent on foreign- sourced rare-earth permanent magnets that are vulnerable to supply chain uncertainties. Many small wind original equipment manufacturers are motivated to pursue continuous improvements to the generator design to lower the material and production costs and improve performance by lowering cogging torque and increasing the efficiency. Traditional design and manufacturing offer limited opportunities. In this work, we demonstrate advanced design approaches for a 15-kW baseline wind turbine generator by making use of recent progress in three-dimensional (3D) printing of polymer- bonded magnets and, electrical and structural steel. We explore three methods of magnet parametrization using Bezier curves resulting in symmetric, asymmetric and multimaterial magnet designs. We employ a multiphysics approach combining parametric computer-aided design modeling, finite- element analysis and targeted sampling to identify novel designs with more opportunities for reducing rare-earth material, improving efficiency and minimizing cogging torque. The results show that asymmetric-pole design and multimaterial-pole designs offer a greater opportunity to minimize rare-earth magnet materials by up to 35% with similar performance as the baseline generator, suggesting newer opportunities with design freedom beyond traditional limits of symmetry and as allowed by 3D printing.

Bezier curves↗
DOE OSTI2021

Axion dark matter experiment: Run 1B analysis details

Searching for axion dark matter, the ADMX Collaboration acquired data from January to October 2018, over the mass range 2.81–3.31 μeV, corresponding to the frequency range 680–790 MHz. Using an axion haloscope consisting of a microwave cavity in a strong magnetic field, the ADMX experiment excluded Dine-Fischler-Srednicki-Zhitnisky (DFSZ) axions at 90% confidence level and 100% dark matter density over this entire frequency range, except for a few gaps due to mode crossings. This paper explains the full ADMX analysis for run 1B, motivating analysis choices informed by details specific to this run.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗