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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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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Programming Function via Soft Materials (PFvSM) (Final Report)

The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication

36 MATERIALS SCIENCE↗
NASA NTRS1990

ISTP Global Geospace Science. Energy transfer in geospace

Solar-terrestrial physics concerns the study of the generation, flow, and dissipation of mass, momentum, and energy between the Sun and the Earth. Mass, momentum, and energy are carried by charged particles that compose the solar wind. When the solar wind reaches the Earth, some solar-wind particles enter the magnetosphere; this coupling between the solar wind and the Earth means that the solar wind can influence the Earth's upper atmosphere. As the first step in addressing the behavior of this solar-terrestrial system, the Global Geospace Science (GGS) Initiative will use the Wind and Polar satellites, provided by NASA, and the Geotail satellite provided by the Japanese Institute of Space and Astronautical Science (ISAS), to perform simultaneous and closely coordinated measurements of the key geospace regions and will add data from equatorial missions. Magnetic field and particle changes that occur when particles are energized during auroral events will be monitored. The intention behind the GGS Initiative is to understand the physical mechanisms and various regions controlling the transport of mass, momentum, and energy in geospace. A summary of the GGS Initiative is presented.

Source record↗
NASA NTRS2004

Harnessing Systems Engineering Methodology in Using Earth Science Research Data for Real Applications

For the last three decades, Earth science remote sensing technologies have been providing an enormous amount of useful data and information serving to broaden our understanding of the home planet as a system. NASA's Earth science program has deployed about 18 complex satellites and is in the process of defining and launching multiple observing systems in this decade. At the same time, the European Community and many other countries such as Russia, France, India, Japan, and China have also significantly contributed to Earth science research. To date, the majority of such efforts have concentrated on expanding our scientific understanding of the multiple nonlinear and chaotic processes of Earth's behavior. In recent years, legislators and stakeholders have put serious pressure on the science community to devote more attention to making use of scientific results for societal benefit. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural efficiency, disaster management, air quality and public health that can directly take advantage of Earth science results to analyze and predict large scale problems and conditions. This is becoming even more important now that we live in a global economy interconnected via the internet and transportation systems; regional environmental conditions can have far reaching impact across continental boundaries. These factors dictate requirements for global data that can help us assess and control the devastating problems of famine, water resources, wildfires, human health and more. To do this requires a serious, organized, and systematic approach that transfers fundamental research products to the applied sciences domain. This paper presents a systems engineering and management process that can effectively make such transfer of data to the user community. Examples are presented on how the above decision making framework can help in solving critical problems such as the spread of vector borne diseases, forecasts of harmful algal blooms as well as forest fires and wildfires, and the intercontinental transport of dust storms and pollution.

Habib, Shahid↗
NASA NTRS1983

Behavioral biology of mammalian reproduction and development for a space station

Space Station research includes two kinds of adaption to space: somatic (the adjustments made by an organism, within its lifetime, in response to local conditions), and transgenerational adaption (continuous exposure across sequential life cycles of genetic descendents). Transgenerational effects are akin to evolutionary process. Areas of a life Sciences Program in a space station address the questions of the behavioral biology of mammalian reproduction and development, using the Norway rat as the focus of experimentation.

Alberts, J. R.↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
DOE OSTI2021

Defect-Driven Oxide Transformations and the Electrochemical Interphase

The redox reaction pathway is crucial to the sustainable production of the fuels and chemicals required for a carbon-neutral society. Our society is becoming increasingly dependent on devices using batteries and electrolyzers, all of which rely on a series of redox reactions. The overall properties of oxide materials make them very well suited for such electrochemical and catalytic applications due to their associated cationic redox properties and the static site-adsorbate interactions. As these technologies have matured, it has become apparent that defect-driven redox reactions, defect-coupled diffusion, and structural transformations that are both time- and rate-dependent are also critical materials processes. This change in focus, considering not only redox properties but also more complex, dynamic behaviors, represents a new research frontier in the molecular sciences as they are strongly linked to device operation and degradation and lie at the heart of various phenomena that take place at electrochemical interfaces. Fundamental studies of the structural, electronic, and chemical transformation mechanisms are key to the advancement of materials and technological innovations that could be implemented in various electrochemical systems. In this Account, we focus on recent studies and advances in characterizing and understanding the dynamic redox evolution and structural transformations that take place in model perovskites and layered oxides under reactive conditions and correlate them with degradation mechanisms and operations in electrolyzers and batteries. We show that the dynamic evolution of oxygen vacancies and cationic migration in the surface or bulk occurs at the solid-liquid interface, using a combination of different synchrotron-based Xray spectroscopies and scattering probes. Detailed redox-structure-reactivity correlation studies show how defects and diffusion processes can be tailored to drive various physical and chemical transformations in electrolyzers and batteries. We also highlight a strong correlation between oxygen redox reactivity and structural reorganization in both model thin films and particles, helping to bridge the gap between fundamental studies of the reaction mechanism and device applications. Finally, on the basis of these findings, we discuss strategies to probe and tune the redox reactivity and structural stability of the redox-active oxide interphase toward devising efficient pathways for energy and chemical harvesting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pseudonymization at Scale: OLCF’s Summit Usage Data Case Study

The analysis of vast amounts of data and the processing of complex computational jobs have traditionally relied upon high performance computing (HPC) systems, which offer reliable and efficient management of large-scale computational and data resources. Understanding these analyses’ needs is paramount for designing solutions that can lead to better science, and similarly, understanding the characteristics of the user behavior on those systems is important for improving user experiences on HPC systems. A common approach to gathering data about user behavior is to extract workload characteristics from system log data available only to system administrators. Recently at Oak Ridge Leadership Computing Facility (OLCF), however, we unveiled user behavior about the Summit supercomputer by collecting data from a user’s point of view with ordinary Unix commands.In this paper, we discuss the process, challenges, and lessons learned while preparing this dataset for publication and submission to an open data challenge. The original dataset contains personal identifiable information (PII) about the users of OLCF which needed be masked prior to publication, and we determined that anonymization, which scrubs PII completely, destroyed too much of the structure of the data to be interesting for the data challenge. We instead chose to pseudonymize the dataset, which reduced the linkability of the dataset to the users’ identities. Pseudonymization is significantly more computationally expensive than anonymization, and the size of our dataset, which is approximately 175 million lines of raw text, necessitated the development of a parallelized workflow that could be reused on different HPC machines. We demonstrate the scaling behavior of the workflow on two leadership class HPC systems at OLCF, and we show that we were able to bring the overall makespan time from an impractical 20+ hours on a single node down to around 2 hours. As a result of this work, we release the entire pseudonymized dataset and make the workflows and source code publicly available.

Maheshwari, Ketan↗
DOE OSTI2021

Exploring PV Circularity by Modeling Socio-Technical Dynamics of Modules’ End-of-Life Management

The circular economy (CE) tackles environmental and resource scarcity issues by maximizing value retention in the economy. The concept implies design strategies such as reducing the use of materials or improving products’ durability and end-of-life (EOL) strategies, for example, reusing products and components and recycling materials. With an estimated 80 million tons of global cumulative EOL photovoltaic (PV) modules, applying CE principles to the PV industry could alleviate resource scarcity issues while also providing economic benefits. However, transitioning to a CE may imply changes in organizations and consumer behaviors. In this context, assessment of CE strategies may require accounting for behavioral change, a requirement that methods from complex system science such as agent-based modeling meet. Thus, this paper uses an agent-based modeling (ABM) approach to study circularity in the photovoltaics supply chain. Four types of agents are represented in the ABM: PV owners, installers, recyclers, and manufacturers. Moreover, five possible EOL options – including three CE strategies – are modeled. Departing from traditional techno-economic analysis, the model includes techno-economic factors as well as social factors to model EOL management decisions. Results show that each dollar decrease in the recycling fees improves the recycling rate by roughly 1.1%. However, excluding social factors underestimates the effect that lower recycling prices have on material circularity.

agent-based modeling↗
DOE OSTI2023

Dynamic Subgrid Turbulence Modeling for Shallow Cumulus Convection Simulations beyond LES Resolutions

A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC Cloud (MONC) model using two averaging flavors, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky–Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-gray-zone and gray-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale- and stability-dependent profile of the subfilter turbulence length scale across the chosen resolution range. At gray-zone resolutions the adaptive length scales can better represent the early precloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result, the initialization and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary layer, which fails to ventilate moisture from the boundary layer, resulting in the delayed spinup of the cloud layer. Moreover, strong downgradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for nonlocal transports, leading to overenergetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behavior.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Predicting Compliance in an Epidemiological Model: Constructs from Psychological Theory and Research

Vaccination and the alternative behavior, vaccine refusal, are a classic example of manifesting behaviors driven by social norms and norm violations. Establishing how norms emerge, and under what circumstances people choose to violate them are key issues to understand in modeling epidemics. Interactions between individuals can lead to large-scale patterning of behavior (emergent phenomena). As norm violations are revealed through human behavior, drawing on psychological theory and principles to predict those violations is a viable approach for more human-constrained epidemiological models. As an example of the implications at scale, vaccine refusal is correlated with the spread of mis/disinformation about vaccine side-effects. Considering the complexities of network dynamics, the downstream effects means that if even a small group within a population are persuaded against vaccination, there is a reservoir from which disease and disease outbreaks can propagate. This work will attempt to identify those psychological indicators, to define circumstances that predict health behaviors, and identify potentially modifiable antecedents of health behavior, and factors that influence changes toward health protective behaviors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cyber Physical Subsystems under Adverse Conditions

The United States power grid is built upon complex cyber-physical systems (CPS), including many distributed energy resources (DERs) and microgrid structures. Due to cross-disciplinary domains that govern the interplay between cyber and physical technologies that sustain DERs, it is difficult to confidently predict how these systems will react under adverse conditions such as faults and cyberattacks. This project utilized power hardware in the loop (PHiL) to gain system behavior knowledge and robust understanding through experimentation and observational science. It also produced a large volume of datasets to feed into other efforts to advance high-fidelity model simulations and to support the design of novel control approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

On the Onset of Plasticity: Determination of Strength and Ductility

The analysis of the work hardening variation with stress reveals insight to operative stress-strain mechanisms in material systems. The onset of plasticity can be assessed and related to ensuing plastic deformation up to the structural instability using one constitutive relationship that incorporates both behaviors of rapid work hardening (Stage 3) and the asymptotic leveling of stress (Stage 4). Results are presented for the mechanical behavior analysis of Ti-6Al-4V wherein the work hardening variation of Stages 3 and 4 are found to: be dependent through a constitutive relationship; be useful in a Hall-Petch formulation of yield strength; and provide the basis for a two point-slope fit method to model the experimental work hardening and stress-strain behavior.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Fuzzy Versions of Epistemic and Deontic Logic

Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.

Ramasamy S Gounder↗
NASA NTRS1999

Human Exploration Ethnography of the Haughton-Mars Project, 1998-1999

During the past two field seasons, July 1988 and 1999, we have conducted research about the field practices of scientists and engineers at Haughton Crater on Devon Island in the Canadian Arctic, with the objective of determining how people will live and work on Mars. This broad investigation of field life and work practice, part of the Haughton-Mars Project lead by Pascal Lee, spans social and cognitive anthropology, psychology, and computer science. Our approach involves systematic observation and description of activities, places, and concepts, constituting an ethnography of field science at Haughton. Our focus is on human behaviors-what people do, where, when, with whom, and why. By locating behavior in time and place-in contrast with a purely functional or "task oriented" description of work-we find patterns constituting the choreography of interaction between people, their habitat, and their tools. As such, we view the exploration process in terms of a total system comprising a social organization, facilities, terrain/climate, personal identities, artifacts, and computer tools. Because we are computer scientists seeking to develop new kinds of tools for living and working on Mars, we focus on the existing representational tools (such as documents and measuring devices), learning and improvization (such as use of the internet or informal assistance), and prototype computational systems brought to the field. Our research is based on partnership, by which field scientists and engineers actively contribute to our findings, just as we participate in their work and life.

Clancey, William J.↗
NASA NTRSDate not supplied

Upping the Ante: The TESS Mission Shortens Full Frame Images to 10 Minutes and Introduces a Twenty-Second Data Collection Mode

The Transiting Exoplanet Survey Satellite (TESS) recently completed its initial two-year, near all-sky survey, identifying over 79 exoplanets and over 2000 exoplanet candidates. The mission is well on its way to find at least 50 small, nearby exoplanets for which masses can be ascertained and whose atmospheres can be characterized by ground- and space-based follow-on observations. TESS has unveiled a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. In the extended mission, TESS is collecting full frame images (FFIs) at 10-minute intervals rather than at 30-minute intervals, as was the case for the two-year primary mission. TESS is also collecting and providing photometry for up to 1000 20-sec targets in addition to the 20,000 target star postage stamps collected at 2-min intervals. The extended mission will also feature a five-month interval in which the 24°x96° field of view (FOV) will be rotated by 90°from its normal North-South orientation to observe a swath of the ecliptic plane. The FOVs for the remainder of the extended mission will be offset in latitude from those of the prime mission to help fill in the gaps in the full sky coverage. We discuss the performance and behavior of the data products generated by the TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center and highlight the new 20-sec data mode and the 10-min FFIs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

TESS↗
NASA NTRSDate not supplied

Gravity Offloading and Analysis of Long Imperfection-Sensitive Elements (GOALIE)

Use of large-scale deployable structures (e.g., iROSA) can enable space exploration and science missions (e.g., ACS3, Solar Cruiser). Numerical models predicting behavior of deployable structures in microgravity are difficult to validate because ground testing of long, slender, and flexible booms is challenging due to the influence of Earth’s gravity. The GOALIE team is collecting data for model validation through experimental testing to increase confidence in numerical models. Redwire, Inc. provided a subscale (7 m) and a full-scale (30 m) Triangular, Rollable, and Collapsible (TRAC) boom to use for test development. Other boom designs may be tested in the future.

Composites↗