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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 37 records · Page 2

Water & Energy Interdependencies Across Economic Sectors of the United States

The motivation of the Integrated Water Power Resilience Project is to identify and develop opportunities for improving resilience in the water and power sectors through coordinated planning, investment, and operations and thereby provide benefits to power and water utilities, consumers, and the environment. Water and power systems are interdependent, subject to many of the same natural and manmade hazards, and are critical for the well-being of communities and society. Because of the interconnectedness of water and power systems, there are substantial economic, social, and environmental benefits to co-managing the market sectors for resilience instead of managing them separately. To support this initiative and future research in this area, a county level water and energy flow dataset was developed to build, calculate, and visualize interconnections in water and energy between various sectors. This report presents county and regional water and energy visualizations across nine economic sectors of the United States: agriculture, commercial, electricity generation, industrial, mining, public water supply, residential, transportation, and wastewater treatment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Atomistic understanding of interdependence of crystal growth of two seeds embedded in glass

Recent results showed that during growth, a crystal seed embedded in glass experiences nonuniform forces from the host matrix. This result raised the possibility that during devitrification of glass, the growth of a crystal can be affected by the presence of neighboring crystals. To investigate the nature of any such interdependence of growth of neighboring crystals, atomic scale morphology of two seeds growing in a glass matrix was simulated as a function of their separation and relative misorientation. The results show a coupled rotation of seeds driven by (1) non-uniform forces from the surrounding glass, and (2) mutual interactions between the seeds. At small separations and low misorientation, each seed rotates toward perfect alignment, ultimately forming a single crystal. The onset and rate of alignment, as well as subsequent crystal growth, are strongly dependent on the growth temperature. In contrast, at larger separations and higher misorientation, the seeds cannot achieve full alignment before coalescing, resulting in polycrystalline structures.

36 MATERIALS SCIENCE↗

Interdependence in active mobility adoption: Joint modeling and motivational spillover in walking, cycling and bike-sharing

Active mobility offers an array of physical, emotional, and social well-being benefits. However, with the proliferation of the sharing economy, new nonmotorized means of transport are entering the fold, complementing some existing mobility options while competing with others. The purpose of this research study is to investigate the adoption of three active travel modes—namely walking, cycling, and bikesharing—in a joint modeling framework. Here, the analysis is based on an adaptation of the stages of change framework, which originates from the health behavior sciences. Multivariate ordered probit modeling drawing on U.S. survey data provides well-needed insights into individuals’ preparedness to adopt multiple active modes as a function of personal, neighborhood, and psychosocial factors. The research suggests three important findings. (1) The joint model structure confirms interdependence among different active mobility choices. The strongest complementarity is found for walking and cycling adoption. (2) Each mode has a distinctive adoption path with either three or four separate stages. We discuss the implications of derived stage-thresholds and plot adoption contours for selected scenarios. (3) Psychological and neighborhood variables generate more coupling among active modes than individual and household factors. Specifically, identifying strongly with active mobility aspirations, experiences with multimodal travel, possessing better navigational skills, along with supportive local community norms are the factors that appear to drive the joint adoption decisions. This study contributes to the understanding of how decisions within the same functional domain are related and help to design policies that promote active mobility by identifying positive spillovers and joint determinants.

42 ENGINEERING↗

Capturing Infrastructure Interdependencies for Power Outages Prediction During Extreme Events

As extreme weather events such as hurricanes, severe thunderstorms, and floods grow in frequency and intensity, the disruption of power grid systems poses significant challenges, including widespread electrical outages, economic losses, and threats to public safety. This paper presents a forward-looking approach that leverages geographical graph-based machine learning models to predict county-level maximum power outages during such events. By capturing the intricate interdependencies within power system networks, our approach aims to provide precise and actionable predictions that can optimize emergency response efforts and enhance grid resilience. Through the integration of real-world data, including hurricane advisories and power outage records, we have trained and benchmarked multiple machine learning models, demonstrating the feasibility and potential of this method. While our initial results are promising, this paper also charts a course for advancing these models, addressing the remaining challenges, and ultimately transforming how we anticipate and respond to the impacts of extreme weather on power systems.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗

Generative Design for Resilience of Interdependent Network Systems

Abstract Interconnected complex systems usually undergo disruptions due to internal uncertainties and external negative impacts such as those caused by harsh operating environments or regional natural disaster events. To maintain the operation of interconnected network systems under both internal and external challenges, design for resilience research has been conducted from both enhancing the reliability of the system through better designs and improving the failure recovery capabilities. As for enhancing the designs, challenges have arisen for designing a robust system due to the increasing scale of modern systems and the complicated underlying physical constraints. To tackle these challenges and design a resilient system efficiently, this study presents a generative design method that utilizes graph learning algorithms. The generative design framework contains a performance estimator and a candidate design generator. The generator can intelligently mine good properties from existing systems and output new designs that meet predefined performance criteria while the estimator can efficiently predict the performance of the generated design for a fast iterative learning process. Case studies results based on synthetic supply chain networks and power systems from the IEEE dataset have illustrated the applicability of the developed method for designing resilient interdependent network systems.

Engineering↗

Analyzing Infrastructure Interdependencies Using Network-Of-Networks Modeling

Infrastructure networks play a crucial role in our day-to-day lives, and modeling these infrastructure networks can help decisionmakers prepare for and respond to disruptions such as natural disasters or cyberattacks. Because these infrastructure networks depend on each other, it is not sufficient to model a single network in isolation. We build on previous single-network-modeling techniques to develop a methodology for modeling infrastructure interdependencies as a Network-of-Networks. Using distributionlevel data from a real U.S. city on the power grid, road geometry, and hospital locations, we show how to apply this methodology to modeling three of the U.S. Department of Homeland Security's Critical Infrastructure Sectors: Healthcare, Transportation, and Energy. We also analyze three primary metrics before and after a simulated disaster: 1) impact on hospital access; 2) road network impact with the change in betweenness centrality; 3) electric customer outage. We simulate three different disruptions: 1) road flooding from nearby rivers; 2) a malicious actor targeting the road networks; 3) a malicious actor targeting the electric grid. Finally, we discuss how our methodology can be applied to additional infrastructure networks and types of disruption, and how Artificial Intelligence (AI) techniques may be incorporated into this methodology for further research.

Scherrer, Evan [Drake University, Iowa]↗

A Multi-Model, Multi-Scale Research Program in Stressors, Responses, and Coupled Systems Dynamics at the Energy-Water-Land Nexus and for Concentrated, Interdependent Infrastructures: Toward Next Generation Capabilities in Integrated Impacts, Adaptation, and Vulnerability (I-IAV) Modeling and a Community of Practice

The goal of this research program was to build a next generation integrated suite of science-driven modeling and analytic capabilities, and a more expanded and connected community of practice, for analyses of the stressors, impacts, adaptations and vulnerabilities of global and regional change. The emphasis was on understanding energy-water-land interactions and feedbacks and interdependent infrastructures at appropriate regional and temporal scales. Although the scope spans many complex facets of data, modeling, and analysis, as well as scales appropriate for integrated impacts and adaptation research, the focus of this effort was the development of multi-model, multi-scale capabilities spanning the domains of Multi-Sector Dynamics (MSD) models; Impact, Adaptation, and Vulnerability (IAV) models; and Earth System Models (ESMs).

54 ENVIRONMENTAL SCIENCES↗

Correlating Power Outage Spread with Infrastructure Interdependencies During Hurricanes

Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events.

Bose, Avishek↗

Interdependent figure-of-merit software development

This program was undertaken in order to understand the complex nature of interdependent performance in space missions. At the first step in a planned sequence of progress, a spread sheet program was developed to evaluate different fuel/oxidizer combinations for a specific Martian mission. This program is to be linked with output attained using sophisticated software produced by Gordon and McBride. The programming to date makes use of 11 independent parameters. Optimization is essential when faced with the incredible magnitude of costs, risks, and benefits involved with space exploration. A system of weights needs to be devised on which to measure the options. It was the goal to devise a Figure of Merit (FoM) on which different choices can be presented and made. The plan was to model typical missions to Mars, identify the parameters, and vary them until the best one is found. Initially, most of the focus was placed on propellant selection.

Ramohalli, K.↗

Technology Interdependency Roadmaps for Space Operations

The requirements for Space Technology are outlined in terms of NASA Strategic Plan. The national emphasis on economic revitalization is described along with the environmental changes needed for the new direction. Space Technology Interdependency (STI) is elaborated in terms of its impact on national priority on science, education, and economy. Some suggested approaches to strengthening STI are outlined. Finally, examples of Technology Roadmaps for Space Operations area are included to illustrate the value of STI for national cohesiveness and economic revitalization.

Krishen, Kumar↗

Cooperation of German Airports in Europe: Comparison of Different Types by Means of an Interdependence-Profile-Model

The limited growth possibilities in the home markets - not the least of which, based on capacity and expansion problems - force the large airport operators to enter into, via partnerships, cooperations and alliances. The German airports already cooperate among one another in different forms. The purpose of the paper is to examine the structures and possibilities of cooperation among airports in Europe (e.g. Airport Systems, Airport Networks). The experience of German airports with different cooperations and alliances will be also considered. Finally the forms of cooperations among airports are analysed by means of interdependence-profile-models with different features (mutual dependence, coordination volume, complexity, cooperation profit, value, degree of formalization and temporal frame), in order to find out how high the cooperative attachment of cooperation is to be evaluated.

Meincke, Peter A.↗

Natural Gas-Electric Interdependency Through 2030

Presentation to IEEE Power and Engineering Society 2022 General Meeting on natural-gas electric interdependency results from Grid Modernization Initiative Near-Term Reliability and Resilience project.

Brewer, John↗

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Interdependence of Support Wettability ‐ Electrodeposition Rate‐ Sodium Metal Anode and SEI Microstructure

Abstract This study examines how current collector support chemistry (sodiophilic intermetallic Na 2 Te vs. sodiophobic baseline Cu) and electrodeposition rate affect microstructure of sodium metal and its solid electrolyte interphase (SEI). Capacity and current (6 mAh cm −2 , 0.5–3 mA cm −2 ) representative of commercially relevant mass loading in anode‐free sodium metal battery (AF‐SMBs) are analyzed. Synchrotron X‐ray nanotomography and grazing‐incidence wide‐angle X‐ray scattering (GIWAXS) are combined with cryogenic ion beam (cryo‐FIB) microscopy. Highlighted are major differences in film morphology, internal porosity, and crystallographic preferred orientation e.g. (110) vs. (100) and (211) with support and deposition rate. Within the SEI, sodium fluoride (NaF) is more prevalent with Te−Cu versus sodium hydride (NaH) and sodium hydroxide (NaOH) with baseline Cu. Due to competitive grain growth the preferred orientation of sodium crystallites depends on film thickness. Mesoscale modeling delineates the role of SEI (ionic conductivity, morphology) on electrodeposit growth and onset of electrochemical instability.

Lo, Chang‐An↗

Interdependence of Support Wettability - Electrodeposition Rate- Sodium Metal Anode and SEI Microstructure

Here, this study examines how current collector support chemistry (sodiophilic intermetallic Na 2 Te vs. sodiophobic baseline Cu) and electrodeposition rate affect microstructure of sodium metal and its solid electrolyte interphase (SEI). Capacity and current (6 mAh cm -2 , 0.5–3 mA cm -2 ) representative of commercially relevant mass loading in anode-free sodium metal battery (AF-SMBs) are analyzed. Synchrotron X-ray nanotomography and grazing-incidence wide-angle X-ray scattering (GIWAXS) are combined with cryogenic ion beam (cryo-FIB) microscopy. Highlighted are major differences in film morphology, internal porosity, and crystallographic preferred orientation e.g. (110) vs. (100) and (211) with support and deposition rate. Within the SEI, sodium fluoride (NaF) is more prevalent with Te-Cu versus sodium hydride (NaH) and sodium hydroxide (NaOH) with baseline Cu. Due to competitive grain growth the preferred orientation of sodium crystallites depends on film thickness. Mesoscale modeling delineates the role of SEI (ionic conductivity, morphology) on electrodeposit growth and onset of electrochemical instability.

36 MATERIALS SCIENCE↗

Impact of new experimental data on the C2HDM: the strong interdependence between LHC Higgs data and the electron EDM

The complex two-Higgs doublet model (C2HDM) is one of the simplest extensions of the Standard Model with a source of CP-violation in the scalar sector. It has a $\mathbb{Z}$ 2 symmetry, softly broken by a complex coefficient. There are four ways to implement this symmetry in the fermion sector, leading to models known as Type-I, Type-II, Lepton Specific and Flipped. In the latter three models, there is a priori the surprising possibility that the 125 GeV Higgs boson couples mostly as a scalar to top quarks, while it couples mostly as a pseudoscalar to bottom quarks. This “maximal” scenario was still possible with the data available in 2017. Since then, there have been more data on the 125 GeV Higgs boson, direct searches for CP-violation in angular correlations of $τ$-leptons produced in Higgs boson decays, new results on the electron electric dipole moment, new constraints from LHC searches for additional Higgs bosons and new results on $b$ → $sγ$ transitions. Highlighting the crucial importance of the physics results of LHC’s Run 2, we combine all these experiments and show that the “maximal” scenario is now excluded in all models. Still, one can have a pseudoscalar component in $hτ\overline{τ}$ couplings in the Lepton-Specific case as large as 87% of the scalar component for all mass orderings of the neutral scalar bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗