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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Domestic Extremism (Executive Summary)

Domestic extremism (DE) has been a growing concern in the U.S. in recent months, as illustrated in multiple bulletins from the Department of Homeland Security (DHS) warning law enforcement partners of the heightened threat. As concerns about these actors grows, it is important that facilities in the U.S. and internationally that protect critical assets, such as sensitive information, hazardous materials, or critical infrastructure, have effective methods in place to secure those assets. DE has challenged security systems through the danger of insider attack and violence, creating a new threat to be countered. In this effort, therefore, we used a literature review and focus group discussions with experts in critical asset security and extremism to understand the nature of the domestic extremist threat, to identify best practices in securing assets, recognize potential gaps in security measures to be corrected, and recommend actions for the Office of Radiological Security (ORS) to address DE with its partners.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Position Papers for Inverse Methods for Complex Systems under Uncertainty Workshop

The ability to solve inverse problems – inferring unknown parameters, structures, or states of a system from observed data – is essential for advancing scientific discovery and innovation capabilities for the DOE mission. Basic research needs and challenges are particularly acute in emerging areas such as the interactive, data-driven, modeling and simulation of digital twins; decision support for experiments at DOE scientific user facilities; and for other complex systems and workflows. Inverse problems are at the heart of understanding and controlling complex systems due to factors such as observational data with varying modalities and fidelities, inherent uncertainties in physical measurements and numerical models, and the computational demands of rapid and high-fidelity simulations. The convergence of recent scientific computing trends – scientific machine learning, artificial intelligence, and computing advances such as exascale computing – is creating unprecedented opportunities. These advancements offer the potential to revolutionize how we approach inverse problems to extract actionable insights with the required level of accuracy and computational efficiency. This workshop and the Call for Position Papers are vital steps in bringing together experts to collectively explore and identify the new computational and mathematical directions needed in inverse methods for complex systems under uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Advances in the Application and Utility of Subseasonal-to-Seasonal Predictions

The subseasonal-to-seasonal (S2S) predictive time scale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this time scale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a “knowledge–value” gap, where a lack of evidence and awareness of the potential socioeconomic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development—demonstrating both skill and utility across sectors—this dialogue can be used to help promote and accelerate the awareness, value, and cogeneration of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable, and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting time scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ILLICIT TRANSIT INTERDICTION GLOBAL ANALYSIS

This study aims to enhance the security of radioactive materials during transport by analyzing commonalities in cargo thefts conducted by non-state groups such as thieves and terrorists. This research focuses on identifying patterns and trends in the methods used to steal high-value cargo, with the goal of applying these insights to improve transport security of radioactive materials. Key questions addressed include the frequency of specific tools, techniques, and insider involvement in thefts, as well as the use of weapons, electronic jamming equipment, and specialized tools. Findings will inform security design improvements and industry practices to mitigate vulnerabilities. The study involves a comprehensive review of literature and case studies, utilizing data sources from 2018 to 2023. Articles will be selected based on their relevance to thefts of valuable cargo in transit, with a focus on incidents involving non-state actors. The methodology will include statistical and inferential analysis to identify trends, with results visualized through pie charts, frequency analyses, and terrain maps. The discussion will highlight the implications of findings and provide actionable recommendations for strengthening security measures. Limitations such as data availability and reporting inconsistencies will be acknowledged. Suggestions for future improvements will be constructed using existing case studies and expert feedback. The study’s outcomes aim to raise awareness within the industry, inform policy decisions, and enhance security protocols for radioactive material transport. Metrics for impact include the potential publication of findings, presentations at conferences to raise awareness, and the subsequent actions taken by stakeholders based on the research. By identifying trends and vulnerabilities and suggesting improvements, this research contributes to preventing the illicit use of nuclear and radiological materials.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗
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 OSTI2024

Community Solar Potential Analysis for Lawrence, Massachusetts

This report was prepared as part of the U.S. Department of Energy's Communities Local Energy Action Program (Communities LEAP) pilot competitive technical assistance for the Lawrence Massachusetts Stakeholder Coalition (LSC). In accordance with Technical Assistance Area 1 (Community Solar Analysis) and in coordination with the LSC, the UMass Clean Energy Extension (CEE) research team conducted a high-level geographic information system (GIS) evaluation of potential community solar (CS) development sites within Lawrence, and its three bordering towns of Andover, North Andover, and Methuen.

14 SOLAR ENERGY↗
DOE OSTI2023

Probing supersymmetric black holes with surface defects

It has long been conjectured that the large N deconfinement phase transition of $\mathcal{N}$ = 4 SU(N) super-Yang-Mills corresponds via AdS/CFT to the Hawking-Page transition in which black holes dominate the thermal ensemble, and quantitative evidence of this has come through the recent matching of the superconformal index of $\frac{1}{16}$-BPS states to the supersymmetric black hole entropy. Here we introduce the half-BPS Gukov-Witten surface defect as a probe of the superconformal index, which also serves as an order parameter for the deconfinement transition. This can be studied directly in field theory as a modification of the usual unitary matrix model or in the dual description as a D3-brane probe in the background of a (complex) supersymmetric black hole. Using a saddle point approximation, we determine our defect index in the large N limit as a simple function of the chemical potentials and show independently that it is reproduced by the renormalized action of the brane in the black hole background. Along the way, we also comment on the Cardy limit and the thermodynamics of the D3-brane in the generalized ensemble. The defect index sharply distinguishes between the confining and the deconfining phases of the gauge theory and thus is a supersymmetric non-perturbative order parameter for these large N phase transitions which deserves further investigation. Finally, our work provides an example where the properties of a black hole coupled to an external system can be analyzed precisely.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Enhanced Inertial Support: Modeling Fast Frequency Response Controls for Energy Storage System Inverters

Reduction of power system inertia is a growing concern for grid operators given the transition under way from conventional fossil generators to inverter-based resources. One key concern is the rapid and severe dip in power system frequency following a large disturbance which could trigger remedial actions including operation of under frequency load shedding (UFLS) relays. A potential solution is to utilize battery energy storage systems (BESS) to provide fast frequency response(FFR) to mitigate the system frequency impact of low system inertia. In this work, we investigate different control parameters to achieve modeled FFR response from BESS in the simulated US Western Interconnection. First, a very low inertia model is developed from an existing positive sequence model of the Western Interconnection. Afterwards, we tune the BESS dynamic response parameters to eliminate any risks of reaching UFLS relay thresholds following the loss of large generators. Finally, we investigate the relative impact of having large BESS units in comparison of multiple smaller units in the same area. The results of the analyses indicate that 1 GW of transmission-connected BESS can help mitigate the frequency drop caused by large generators outages in the Western Interconnection, and significantly reduce the risk of under frequency load shedding.

power system dynamic performance, Low Inertia, Fas↗
DOE OSTI2025

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗
DOE OSTI2023

Quantifying co-benefits of water quality policies: An integrated assessment model of land and nitrogen management

Due to the nature of nitrogen cycling, policies designed to address water quality concerns have the potential to provide benefits beyond the targeted water quality improvements. For example, actions to protect water quality by reducing nitrate leaching from agriculture also reduce emissions of nitrous oxide, a potent greenhouse gas. These positive effects, which are incidental to the regulation's intended target, are termed “co-benefits.” To quantify the co-benefits associated with reduced nitrate leaching, we integrate an economic model of farmer decision making with a model of terrestrial nitrogen cycling for the watershed surrounding Lake Mendota, Wisconsin, USA. Our modeling approach provides a framework that links air and water pollutants in an agri-environmental system and offers a direction for future studies. Our model results highlight the finding that the co-benefits from nitrous oxide abatement are substantial, and their inclusion increases the benefit–cost ratio of water quality policies. Consideration of these co-benefits has the potential to reverse the conclusions of benefit–cost analysis in the assessment of current water quality policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Los Alamos National Laboratory Floodplain Assessment for Fire Risk Mitigations at the Lower Slobbovia Testing Site in (TA-36)

The National Nuclear Security Administration (NNSA), a semi-autonomous agency within the U.S. Department of Energy (DOE), is proposing to take fire pre-suppression actions at Los Alamos National Laboratory (LANL) Technical Area (TA) 36. Constructing a fire break and a fuel break surrounding the Lower Slobbovia explosives testing site in addition to the current vegetation mowing practices would establish a safety perimeter to help prevent fires from spreading away from the firing point. NNSA has prepared this floodplain assessment in accordance with 10 Code of Federal Regulations (CFR) Part 1022 Compliance with Floodplain and Wetland Environmental Review Requirements (10 CFR 1022), which was promulgated to implement DOE requirements under Executive Order 11988 Floodplain Management (EO 1977). A floodplain is defined in 10 CFR 1022 as “the lowlands adjoining inland and coastal waters and relatively flat areas and flood prone areas of offshore islands,” and a base floodplain as “the 100-year floodplain, that is, a floodplain with a 1.0 percent chance of flooding in any given year (CFR 2003).” This floodplain assessment evaluates potential impacts to floodplain values and functions from implementation of the proposed action, identifies alternatives to the Proposed Action, and allows for meaningful public comment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Los Alamos National Laboratory Wetland Assessment for the Replacement Water Lines from Technical Area 48 to Technical Area 55 Project

The National Nuclear Security Administration (NNSA), a semi-autonomous agency within the U.S. Department of Energy (DOE), is proposing to take action at Los Alamos National Laboratory (LANL) near a wetland at Technical Area (TA) 48 and under a wetland at TA-55. The project proposes to install two 12-inch water lines along an alignment from TA-48 to Pecos Road on the east side of TA-55 (Figure 1). The proposed water lines will replace aging cast iron pipes that provide water for fire suppression to buildings within TA-55, and potable water to other areas in the Pajarito Corridor. NNSA has prepared this wetland assessment in accordance with 10 Code of Federal Regulations (CFR) Part 1022 Compliance with Wetland and Wetland Environmental Review Requirements (10 CFR Part 1022) (CFR 2003) which was promulgated to implement DOE requirements under Executive Order 11988 Wetland Management (EO 1977). A wetland is defined in 10 CFR 1022 as “the lowlands adjoining inland and coastal waters and relatively flat areas and flood prone areas of offshore islands,” and a base wetland as “the 100-year wetland, that is, a wetland with a 1.0 percent chance of flooding in any given year (CFR 2003).” This wetland assessment evaluates potential impacts to wetland values and functions from implementation of the proposed action, identifies alternatives to the Proposed Action, and allows for meaningful public comment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

BETO 2021 Peer Review - WBS 4.1.2.32: Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis project uses systems thinking and analysis to assess current and/or prospective techno-economics, research and development, deployment strategies, policy, and market conditions and their impact on the potential development trajectories of the bioenergy industry over time. Results from this project include identification of opportunities and constraints to industrial development, quantification of multiple metrics (energy, economic, environmental) and informing researchers, decision makers, and industry of the steps needed for a sustainable, nationwide biofuels industry. Analyses from this project enable the creation of a bioenergy industry by (1) inciting policy-makers to explore scenarios for nationwide biofuels production, identifying policy actions consistent with pathways for growth; (2) improving industry’s understanding of industry growth potential under different technology and investment conditions, better targeting their development efforts; and (3) providing universities and other interested stakeholders with tools and analyses that can be adapted to meet research and teaching objectives, connecting students with careers that build the industry. One of the many modeling tools used in this project, the Biomass Scenario Model (BSM) is a publicly-available, unique, validated, state-of-the-art, award-winning, fourth-generation model of the domestic biofuels supply chain which explicitly focuses on how and under what conditions biofuel technologies might be deployed to contribute to the U.S. transportation energy sector. We use models like the BSM to examine the implications of policies and incentives as well as their potential side-effects. The BSM uses a system-dynamics simulation to model dynamic interactions and transitions across the supply chain; it tracks the deployment of biofuels given industrial learning and the reaction of the investment community in the context of land availability, projected oil markets, consumer demand for biofuels, and government policies over time. Under expected market conditions, analyses using the BSM suggest that the biofuels industry may require significant external actions in the early years to thrive. Interventions that accelerate the industrial learning process (e.g. operation of pre-commercial and commercial facilities) have been identified as having strong influence in starting the growth of a commercial biofuel industry. Policies which are coordinated across the whole supply chain in BSM foster the growth of the biofuels industry and production of tens of billions of gallons of biofuels may occur under sufficiently favorable conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Sustainable Aviation Fuel (SAF) State-of-Industry Report: State of SAF Production Process

GHG emissions related to commercial air travel were already significant, at 10% of the domestic transportation emissions and 3% of the global greenhouse gas emissions prior to the pandemic, and are expected to double by 2050, even with modest projected growth in air travel. Since Sustainable Aviation Fuel (SAF) is the only way that medium to long haul commercial aviation can be decarbonized, a US government wide "SAF Grand Challenge" was issued to encourage industry to develop capabilities to produce SAF, to reduce cost, improve sustainability, build value chains, and to scale production capabilities (1). The targets are to expand current domestic SAF 2022 production by 200X to 3 billion gallons per year by 2030, and then further by 12X to 35 billion gallons by 2050, while achieving life cycle GHG reduction of 50% relative to fossil Jet A. Following the SAF Grand Challenge, the DOE, USDA, EPA and FAA collaboratively developed a comprehensive strategy, outlined in the "SAF Grand Challenge Roadmap" (2), to inform stakeholders of the actions necessary to achieve the above volumetric targets. The purpose of this study is to provide an assessment of the current state of the SAF production industry and identify challenges and hurdles that industry may face in delivering the 2030 goals. This assessment is for the potential feedstocks and conversion pathways expected to contribute to 2030 goals and will generally follow action areas in the SAF Grand Challenge: feedstocks, conversion technology, supply chain, and policy & valuation.

09 BIOMASS FUELS↗
DOE OSTI2023

Trust based attachment

In social systems subject to indirect reciprocity, a positive reputation is key for increasing one’s likelihood of future positive interactions. The flow of gossip can amplify the impact of a person’s actions on their reputation depending on how widely it spreads across the social network, which leads to a percolation problem. To quantify this notion, we calculate the expected number of individuals, the “audience”, who find out about a particular interaction. For a potential donor, a larger audience constitutes higher reputational stakes, and thus a higher incentive, to perform “good” actions in line with current social norms. For a receiver, a larger audience therefore increases the trust that the partner will be cooperative. This idea can be used for an algorithm that generates social networks, which we call trust based attachment (TBA). TBA produces graphs that share crucial quantitative properties with real-world networks, such as high clustering, small-world behavior, and powerlaw degree distributions. We also show that TBA can be approximated by simple friend-of-friend routines based on triadic closure, which are known to be highly effective at generating realistic social network structures. Therefore, our work provides a new justification for triadic closure in social contexts based on notions of trust, gossip, and social information spread. These factors are thus identified as potential significant influences on how humans form social ties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Generalising G 2 geometry: involutivity, moment maps and moduli

We analyse the geometry of generic Minkowski N = 1, D = 4 flux compactifications in string theory, the default backgrounds for string model building. In M-theory they are the natural string theoretic extensions of G2 holonomy manifolds. In type II theories, they extend the notion of Calabi-Yau geometry and include the class of flux backgrounds based on generalised complex structures first considered by Graña et al. (GMPT). Using E 7(7) × $\mathbb{R}$ + generalised geometry we show that these compactifications are characterised by an SU(7) ⊂ E 7(7) structure defining an involutive subbundle of the generalised tangent space, and with a vanishing moment map, corresponding to the action of the diffeomorphism and gauge symmetries of the theory. The Kähler potential on the space of structures defines a natural extension of Hitchin’s G 2 functional. Using this framework we are able to count, for the first time, the massless scalar moduli of GMPT solutions in terms of generalised geometry cohomology groups. It also provides an intriguing new perspective on the existence of G 2 manifolds, suggesting possible connections to Geometrical Invariant Theory and stability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Dynamic Interconversion of Metal Active Site Ensembles in Zeolite Catalysis

Catalysis science is founded on understanding the structure, number, and reactivity of active sites. Kinetic models that consider active sites to be static and noninteracting entities are routinely successful in describing the behavior of heterogeneous catalysts. Yet, active site ensembles often restructure in response to their external environment and even during steady-state catalytic turnover, sometimes requiring non-mean-field kinetic treatments to describe distance-dependent interactions among sites. Such behavior is being recognized more frequently in modern catalysis research, with the advent of experimental methods to quantify turnover rates with increasing precision, an expanding arsenal of operando characterization tools, and computational descriptions of atomic structure and motion at chemical potentials and timescales increasingly relevant to reaction conditions. This review focuses on dynamic changes to metal active site ensembles on zeolite supports, which are silica-based crystalline materials substituted with Al that generate binding sites for isolated and low-nuclearity metal site ensembles. Metal sites can become solvated and mobilized during reaction, facilitating interactions among sites that change their nuclearity and function. Such intersite communication can be regulated by the zeolite support, resulting in non-single-site and potentially non-mean-field kinetic behavior arising from mechanisms of catalytic action that combine elements of those canonically associated with homogeneous and heterogeneous catalysis. Here, we discuss recent literature examples that document dynamic active site behavior in metal-zeolites and outline methodologies to identify and interpret such behavior. We conclude with our outlook on future research directions to develop this evolving branch of catalysis science and harness it for practical applications.

operando characterization↗
DOE OSTI2020

Antibacterial activity of iron oxide, iron nitride, and tobramycin conjugated nanoparticles against Pseudomonas aeruginosa biofilms

Novel methods are necessary to reduce morbidity and mortality of patients suffering from infections with Pseudomonas aeruginosa. Being the most common infectious species of the Pseudomonas genus, P. aeruginosa is the primary Gram-negative etiology responsible for nosocomial infections. Due to the ubiquity and high adaptability of this species, an effective universal treatment method for P. aeruginosa infection still eludes investigators, despite the extensive research in this area. Results We report bacterial inhibition by iron-oxide (nominally magnetite) nanoparticles (NPs) alone, having a mean hydrodynamic diameter of ~ 16 nm, as well as alginate-capped iron-oxide NPs. Alginate capping increased the average hydrodynamic diameter to ~ 230 nm. We also investigated alginate-capped iron-oxide NP-drug conjugates, with a practically unchanged hydrodynamic diameter of ~ 232 nm. Susceptibility and minimum inhibitory concentration (MIC) of the NPs, NP-tobramycin conjugates, and tobramycin alone were determined in the PAO1 bacterial colonies. Investigations into susceptibility using the disk diffusion method were done after 3 days of biofilm growth and after 60 days of growth. MIC of all compounds of interest was determined after 60-days of growth, to ensure thorough establishment of biofilm colonies. Conclusions Positive inhibition is reported for uncapped and alginate-capped iron-oxide NPs, and the corresponding MICs are presented. We report zero susceptibility to iron-oxide NPs capped with polyethylene glycol, suggesting that the capping agent plays a major role in enabling bactericidal ability in of the nanocomposite. Our findings suggest that the alginate-coated nanocomposites investigated in this study have the potential to overcome the bacterial biofilm barrier. Magnetic field application increases the action, likely via enhanced diffusion of the iron-oxide NPs and NP-drug conjugates through mucin and alginate barriers, which are characteristic of cystic-fibrosis respiratory infections. We demonstrate that iron-oxide NPs coated with alginate, as well as alginate-coated magnetite–tobramycin conjugates inhibit P. aeruginosa growth and biofilm formation in established colonies. We have also determined that susceptibility to tobramycin decreases for longer culture times. However, susceptibility to the iron-oxide NP compounds did not demonstrate any comparable decrease with increasing culture time. These findings imply that iron-oxide NPs are promising lower-cost alternatives to silver NPs in antibacterial coatings, solutions, and drugs, as well as other applications in which microbial abolition or infestation prevention is sought.

Biotechnology & Applied Microbiology↗