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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Socio-Technical Perspective on Interdisciplinary Interactions During the Development of Complex Engineered Systems

This study investigates interdisciplinary interactions that take place during the research, development, and early conceptual design phases in the design of large-scale complex engineered systems (LaCES) such as aerospace vehicles. These interactions, that take place throughout a large engineering development organization, become the initial conditions of the systems engineering process that ultimately leads to the development of a viable system. This paper summarizes some of the challenges and opportunities regarding social and organizational issues that emerged from a qualitative study using ethnographic and survey data. The analysis reveals several socio-technical couplings between the engineered system and the organization that creates it. Survey respondents noted the importance of interdisciplinary interactions and their benefits to the engineered system as well as substantial challenges in interdisciplinary interactions. Noted benefits included enhanced knowledge and problem mitigation and noted obstacles centered on organizational and human dynamics. Findings suggest that addressing the social challenges may be a critical need in enabling interdisciplinary interactions

McGowan, Anna-Maria R.↗
DOE OSTI2022

Social Disparities of Pain and Pain Intensity Among Women Diagnosed With Early Stage Breast Cancer

Background: Breast cancer is one of the most commonly diagnosed cancers among women in the United States and pain is the most common side effect of breast cancer and its treatment. Yet, the relationships between social determinants of pain and pain experience/intensity remain under-investigated. We examined the associations between social determinants of pain both at the individual level and the neighborhood level to understand how social conditions are associated with pain perception among early stage breast cancer patients. Methods: We conducted integrated statistical analysis of 1,191 women with early stage breast cancer treated at a large cancer center in Memphis, Tennessee. Combining electronic health records, patient-reported data and census data regarding residential address at the time of first diagnosis, we evaluated the relationships between social determinants and pain perception. Pain responses were self-reported by a patient as a numerical rating scale score at the patient’s initial diagnosis and follow-up clinical visits. We implemented two sets of statistical analyses of the zero-inflated Poisson model and estimated the associations between neighborhood poverty prevalence and breast cancer pain intensity. After adjustment for demographic characteristics, cancer stage, and chemotherapy, pain perception was significantly associated with poverty and blight level of the neighborhood. Results: Among women living in the highest-poverty areas, the odds of reporting pain were 2.48 times higher than those in the lowest-poverty area. Women living in the highest-blight area had 5.43 times higher odds of reporting pain than those in the lowest-blight area. Neighborhood-level social determinants were significantly associated with pain intensity among women diagnosed with early-stage breast cancer. Conclusions: Distressed neighborhood conditions are significantly associated with higher pain perception. Breast cancer patients living in socio-economically disadvantaged neighborhoods and in poor environmental conditions reported higher pain severity compared to patients from less distressed neighborhoods. Therefore, post-diagnosis pain treatment design needs to be tailored to the social determinants of the breast cancer patients.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2019

Simulated Microgravity Affects Behavior and Cytokine Expression in the Hippocampus of Adult Mice: Influence of Mitochondrial Reactive Oxygen Species

The effects of microgravity, and social isolation on the CNS are poorly understood. We hypothesize that mitochondrial reactive oxygen species (ROS) play an important role in this process. Since mice are social animals, our lab developed a novel social model of hindlimb unloading (HU), enabling us to determine the effects of both social isolation and simulated microgravity. Responses to 30d of HU were compared in wildtype or transgenic MCAT mice who over-express human catalase in mitochondria. Abundance of 4-Hydroxynonenal, Park7 (a redox-sensitive chaperone and sensor of oxidative stress) and corticosterone were measured by ELISA. Cytokines related to inflammation in the hippocampus and in plasma were analyzed by a protein array. Behavioral data was collected over a 24-hour period.Socially housed HU mice were more active and conducted at least two times more exploratory activities, compared to normally loaded mice. Correlation analysis revealed that specific brain and plasma cytokines correspond with specific behaviors. Simulated microgravity and/or social isolation caused changes in cytokine patterns in the hippocampus and in plasma, with significant interaction effects of HU and genotype in expression levels of five cytokines (out of 35). Interestingly, elevation of these generally pro-inflammatory cytokines by HU in WT mice was mitigated in MCAT mice, suggesting a role for mitochondrial ROS signaling in inflammatory CNS responses to microgravity. Interestingly, socially housed mice had also lower level of 4HNE and higher level of Park7 in the hippocampus compared to singly housed animals. The cytokine responses to social isolation were more extensive in brain vs plasma. Further, there was no overlap in the cytokine repertoire regulated in response to microgravity versus, isolation suggesting divergent mechanisms or downstream signaling. These findings implicate a potentially important role for mitochondrial ROS in CNS responses to the challenges posed both by prolonged missions in space and bedrest on Earth

Guttmann, Linda↗
NASA NTRS2012

An Analysis of Shuttle Crew Scheduling Violations

From the early years of the Space Shuttle program, National Aeronautics and Space Administration (NASA) Shuttle crews have had a timeline of activities to guide them through their time on-orbit. Planners used scheduling constraints to build timelines that ensured the health and safety of the crews. If a constraint could not be met it resulted in a violation. Other agencies of the federal government also have scheduling constraints to ensure the safety of personnel and the public. This project examined the history of Space Shuttle scheduling constraints, constraints from Federal agencies and branches of the military and how these constraints may be used as a guide for future NASA and private spacecraft. This was conducted by reviewing rules and violations with regard to human aerospace scheduling constraints, environmental, political, social and technological factors, operating environment and relevant human factors. This study includes a statistical analysis of Shuttle Extra Vehicular Activity (EVA) related violations to determine if these were a significant producer of constraint violations. It was hypothesized that the number of SCSC violations caused by EVA activities were a significant contributor to the total number of violations for Shuttle/ISS missions. Data was taken from NASA data archives at the Johnson Space Center from Space Shuttle/ISS missions prior to the STS-107 accident. The results of the analysis rejected the null hypothesis and found that EVA violations were a significant contributor to the total number of violations. This analysis could help NASA and commercial space companies understand the main source of constraint violations and allow them to create constraint rules that ensure the safe operation of future human private and exploration missions. Additional studies could be performed to evaluate other variables that could have influenced the scheduling violations that were analyzed.

Bristol, Douglas↗
DOE OSTI2025

Analyzing Trip Chaining Behavior in New York State Using 2009 and 2017 National Household Travel Survey

Trip chaining, defined as the sequential linking of trips by individuals throughout a given day, provides critical insights into daily mobility patterns and activity sequencing. Understanding these patterns has significant implications for transportation demand forecasting, congestion management, and local economic activity. This analysis examines trip chaining behaviors in New York State (NYS) for the years 2009 and 2017 and compares the Middle Atlantic Census Division with other U.S. regions in 2022, utilizing data from the National Household Travel Survey (NHTS). Through demographic, geographic, and temporal analysis, this study characterizes how populations organize travel for work, personal errands, and social activities, providing empirical evidence of evolving trip chaining behaviors to inform transportation planning strategies.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1982

Solar thermal technologies benefits assessment: Objectives, methodologies and results for 1981

The economic and social benefits of developing cost competitive solar thermal technologies (STT) were assessed. The analysis was restricted to STT in electric applications for 16 high insolation/high energy price states. Three fuel price scenarios and three 1990 STT system costs were considered, reflecting uncertainty over fuel prices and STT cost projections. After considering the numerous benefits of introducing STT into the energy market, three primary benefits were identified and evaluated: (1) direct energy cost savings were estimated to range from zero to $50 billion; (2) oil imports may be reduced by up to 9 percent, improving national security; and (3) significant environmental benefits can be realized in air basins where electric power plant emissions create substantial air pollution problems. STT research and development was found to be unacceptably risky for private industry in the absence of federal support. The normal risks associated with investments in research and development are accentuated because the OPEC cartel can artificially manipulate oil prices and undercut the growth of alternative energy sources.

Gates, W. R.↗
DOE OSTI2023

Data from "The Influence of Climate Change on Flooding and Social Inequalities from Remnants of Hurricane Ida"

Previous research has demonstrated that tropical cyclone-related precipitation and flooding have been increased by anthropogenic global warming. Our work aims to quantify the contribution of climate change to the deadly flooding from the remnants of Hurricane Ida (2021) and its impact on human society. We developed an analysis framework that combines lessons from climate change attribution science, two-dimensional hydrodynamic modeling, and flood impact evaluation, including a social inequality index, to estimate remnants of Ida flooding and consequences responding to current (locally 1°C warmer) and future (another 1°C warmer) climate change. We find that an additional quarter to a half million people were exposed to flooding due to current and future climate change. The human influence on flood impacts was larger with deeper flood water depth (≥ 1 m) than with shallow depths. Socially vulnerable populations were found to be disproportionately more affected, and climate change exacerbates this inequality

Climate Change↗
DOE OSTI2021

User Role Identification in Software Vulnerability Discussions over Social Networks

Understanding and early awareness of software vulnerabilities is vital for preventing and mitigating potential impacts from cybersecurity events. One step toward early characterization of software vulnerabilities may involve analyzing discussion and spread of information in online social networks. Prior work has used information from such discussions over multiple online forums to develop dynamic networks among users followed by analysis of structure, spread, and information evolution. In this work, we advance the state-of-the-art by focusing on data-driven learning of types, roles, and transition of roles exhibited by users over time. In social networks, users take on particular roles based on their actions and structure of the network. Identifying “meaningful” roles can help separate potential users of interest from the larger community, and identify patterns in a network. We will identify and compare roles found in online forums (e.g., Twitter) using techniques such as feature-based Non-negative Matrix Factorization coupled with topological and influence-based measures of centrality. Since users’ activities change over time, we also analyze role evolution in dynamic networks.

Jones, Rebecca D.↗
DOE OSTI2023

Exploring temporal community evolution: algorithmic approaches and parallel optimization for dynamic community detection

Abstract Dynamic (temporal) graphs are a convenient mathematical abstraction for many practical complex systems including social contacts, business transactions, and computer communications. Community discovery is an extensively used graph analysis kernel with rich literature for static graphs. However, community discovery in a dynamic setting is challenging for two specific reasons. Firstly, the notion of temporal community lacks a widely accepted formalization, and only limited work exists on understanding how communities emerge over time. Secondly, the added temporal dimension along with the sheer size of modern graph data necessitates new scalable algorithms. In this paper, we investigate how communities evolve over time based on several graph metrics under a temporal formalization. We compare six different algorithmic approaches for dynamic community detection for their quality and runtime. We identify that a vertex-centric (local) optimization method works as efficiently as the classical modularity-based methods. To its advantage, such local computation allows for the efficient design of parallel algorithms without incurring a significant parallel overhead. Based on this insight, we design a shared-memory parallel algorithm DyComPar , which demonstrates between 4 and 18 fold speed-up on a multi-core machine with 20 threads, for several real-world and synthetic graphs from different domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Environmental DNA as a tool for hydropower impact assessments: current status, special considerations, and future integration

Globally there is an urgent need to find sustainable solutions to balance energy production with the protection of vulnerable species and conservation of biodiversity. This is particularly critical for freshwater ecosystems, habitats, and species that may be impacted by hydropower development and operations needed to meet energy grid demands. Reliable and accurate environmental impact assessments (EIAs) that identify the biological, physical, or social impacts of hydropower are key to ensure biodiversity, ecosystem, and societal sustainability. The analysis of environmental DNA (eDNA) has the potential to transform hydropower EIAs, management and mitigation planning, and decision-making procedures. Further, the incorporation of eDNA surveys into EIAs during both hydropower planning and continued operations may streamline regulatory processes by improving our understanding of potentially impacted biota and habitats and evaluating environmental impacts mitigation. Here, we: (i) highlight current understanding and use of eDNA in freshwater environments; (ii) examine critical considerations for eDNA integration into hydropower EIAs and biological monitoring; (iii) identify knowledge gaps in eDNA analysis and applications unique to hydropower-regulated systems; and (iv) discuss future opportunities to bolster the incorporation of eDNA into hydropower research including regulatory acceptance and public engagement. While we acknowledge that there are several factors that may complicate the broad adoption of eDNA as a tool for assessing the impacts of hydropower, we anticipate that growing confidence in eDNA through hydropower-specific protocols, calibrations, and validations will overcome these inherent uncertainties.

aquatic biodiversity↗
NASA NTRS1979

A study of the potential impacts of space utilization

Because the demand for comprehensive impact analysis of space technologies will increase with the use of space shuttles, the academic social sciences/humanities community was surveyed in order to determine their interests in space utilization, to develop a list of current and planned courses, and to generate a preliminary matrix of relevant social sciences. The academic scope/focus of a proposed social science space-related journal was identified including the disciplines which should be represented in the editorial board/reviewer system. The time and funding necessary to develop a self-sustaining journal were assessed. Cost income, general organizational structure, marking/distribution and funding sources were analyzed. Recommendations based on the survey are included.

Cheston, T. S.↗
NASA NTRS2013

Athena in 2013 and Beyond

TRISA, the U.S. Army TRADOC G2 Intelligence Support Activity, received Athena 1 in 2009. They first used Athena 3 to support studies in 2011. This paper describes Athena 4, which they started using in October 2012. A final section discusses issues that are being considered for incorporation into Athena 5 and later. Athena's objective is to help skilled intelligence analysts anticipate the likely consequences of complex courses of action that use our country's entire power base, not just our military capabilities, for operations in troubled regions of the world. Measures of effectiveness emphasize who is in control and the effects of our actions on the attitudes and well being of civilians. The planning horizon encompasses not weeks or months, but years.Athena is a scalable, laptop-based simulation with weekly resolution. Up to three months of simulated time can pass between game turns that require user interaction. Athena's geographic scope is nominally a country, but can be a region within a county. Geographic resolution is "neighborhoods", which are defined by the user and may be actual neighborhoods, provinces, or anything in between. Models encompass phenomena whose effects are expected to be relevant over a medium-term planning horizon--three months to three years.The scope and intrinsic complexity of the problem dictate a spiral development process. That is, the model is used during development and lessons learned are used to improve the model. Even more important is that while every version must consider the "big picture" at some level of detail, development priority is given to those issues that are most relevant to currently anticipated studies. For example, models of the delivery and effectiveness of information operations messaging were among the additions in Athena 4.

Diplomatic, Informational, Military, Economic (DIM↗
DOE OSTI2024

A New Understanding of Decarbonizing Industrial Process Heat

Analysis conducted over the last few years has improved our understanding of how industrial process heat is used in the United States. These improvements are important for characterizing the possibilities for industrial decarbonization. However, this analysis has largely been conducted from technical perspective and has remained disconnected from the social processes that underlie how industrial firms may adopt and implement technologies to decarbonize their process heating operations. This presentation introduces the concept of generic and configurational technology systems, and outlines the how the incorporation of user requirements and local contexts are essential for successful implementation of configurational systems. Insights drawn from semi-structured interviews with representatives of industrial firms are used to support the hypothesis that industrial process heat technologies are configurational. The potential implications for strategies to decarbonize process heat are then discussed.

adoption↗
DOE OSTI2025

Insights Into Thermal Runaway Mechanisms: Fast Tomography Analysis of Metal Agglomerates in Lithium-Ion Batteries

Thermal Runaway (TR) in lithium-ion batteries (LIB) is a critical technological and social concern. Whilst such events are rare, TR is characterized by uncontrollable heating leading to catastrophic failures. To deepen the understanding of the failure process and subsequently develop more accurate TR prediction models and as a result safer battery systems, we present in this work high-speed X-ray tomography for in-depth investigations of the copper current collector melting and agglomeration during TR. The melting process presents valuable real-time internal information about heat evolution during TR, previously challenging to access but crucially important for validating TR models. In this work, controlled failure studies combined with high-speed X-ray tomography were performed on two different commercial LIB models, subjecting them to both external heating and nail penetration to induce TR. Through real-time observation via high-speed tomography, followed by segmentation, rendering, and analysis, the formation of copper agglomerates was qualitatively and quantitatively characterized and visualized for the first time. Agglomerates tended to form either from the battery's outermost layers or centrally, depending on the method of TR initiation, and gives an indirect insight into the internal temperature evolution and distribution. Moreover, an initial comparative analysis between the battery models also revealed differences in agglomerate size, which has been linked to the thicker copper current collectors of one of the cell models. We further discuss the impact of larger copper agglomerates on heat distribution and safety. This study not only sheds light on the intricate dynamics of TR in LIBs but also underscores the pivotal role of 'gold-standard' imaging techniques in advancing battery safety, crucial for the robust modeling of TR and the future design of electric vehicle safety systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit

Software vulnerabilities are flaws in computer systems that leave users open to attack. In many cases, these vulnerabilities go unnoticed and remain unresolved in codebases. Thus, awareness of software vulnerabilities among the public is crucial to ensure effective cybersecurity practices, the development of high quality software, and ultimately national security. This awareness can be better understood by studying the spread and evolution of software vulnerability discussions in online communities. This work is the first to evaluate and contrast how discussions about software vulnerabilities spread on three social platforms -- Twitter, GitHub, and Reddit. To lay the groundwork, we showcase a novel fundamental framework for measuring information spread that identifies the spread mechanisms and observables across platforms, the units of information, and the groups of measurements that can be applied to focus on a specific phenomena e.g., information cascades. We then analyze and contrast social network topologies for three example social networks and measure the scale and speed of the spread of discussion of specific vulnerabilities to understand how far and how widely they spread, how many users participate in discussions, and the duration of their spread. To demonstrate the awareness of more impactful software vulnerabilities, a subset of our analysis focuses on vulnerabilities targeted during recent major cyber attacks as well as vulnerabilities exploited by advanced persistent threat groups. We discover that usually, vulnerability discussions start on GitHub, before occurring on Twitter and Reddit. While studying how some user-level and content-level characteristics influence vulnerability spread, we observe that Twitter discussions started by users predicted to be humans have larger size, breadth, depth, adoption rate, lifetime, and structural virality compared to those started by users predicted to be bots. On Reddit, we contrast the differences in thread structure that originate from posts with positive, negative and neutral polarity. We find that posts that are positive have larger, deeper and wider discussions compared to negative and neutral posts. We anticipate the results of our analysis to not only increase the understanding of software vulnerability awareness but also inform models for simulating information spread across multiple social environments online.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

The application of natural science data to land management decision-making

A natural environmental analysis process which allows the decision maker to know the probable consequences of a decision prior to the act is developed. Emphasis is placed on the fit between the natural environment and the social, economic, and functional attributes of man's communities and the transition from nature in its present state to various forms and intensities of development. Applications of the analysis are examined. It is concluded that the analysis is a workable system for land use management.

Williams, D. L.↗
DOE OSTI2023

The role of social support on midwestern farmers’ willingness to grow perennial bioenergy crops

The lack of farmers' willingness to grow perennial bioenergy crops (PBCs) presents a critical barrier to the emergence of cellulosic biofuel production. The willingness relies on a complex network of economic, environmental, and social drivers, among which the influence of social factors (e.g., the influence of neighborhood, community, and communication) is less understood. This study addresses this knowledge gap via a survey analysis of midwestern farmers. The survey data are analyzed through ordinary least square regression and structural equation model, which together investigate the individual and interactive impacts of multiple factors on farmers' decisions to adopt PBCs. Based on a farm-scale analysis, six statistically significant predictors of farmer willingness to grow PBCs are identified: perception of PBCs' environment benefits, education level, willingness to take risks, familiarity with PBCs, portion of peers already growing PBCs, and support of biorefineries locating in the local community. Among these, the latter three predictors are social support variables. It is found that familiarity with the crops is the most significant predictor of willingness; familiarity is also an important intermediate variable that mediates the influence of many other predictors. In addition, peer adoption can both directly and indirectly affect willingness via its influence on familiarity. Furthermore, these findings suggest that it is a pressing need to improve farmers’ knowledge of PBCs to promote the adoption of such crops.

09 BIOMASS FUELS↗