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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrating Cyber-Informed Engineering into Enterprise Risk Management

This document supports the application of Cyber-Informed Engineering (CIE) within the context of Enterprise Risk Management (ERM) to enhance cyber-resilience. It highlights that many critical infrastructure organizations use ERM to manage business risks and emphasizes the importance of evaluating critical systems and assets. The proposed approach can be adopted independently of formal ERM processes and offers a starting point for integrating CIE alongside existing or new ERM practices. Both CIE and ERM are iterative, and their alignment fosters continuous improvement and supports the engineering and operations cultures of an organization.

42 ENGINEERING↗
DOE OSTI2025

Cybersecurity and Infrastructure Security Agency (CISA) Infrastructure Security Division (ISD) Assessment Prioritization Project

The Cybersecurity and Infrastructure Security Agency’s Infrastructure Security Division (CISA ISD) manages a diverse portfolio of assessments across the nation’s critical infrastructure sectors. These assessments—ranging in type, scope, and complexity—are essential for identifying vulnerabilities and strengthening national security. However, the wide variation in assessment offerings and the increasing demand for limited resources have highlighted the need for a transparent, structured approach to prioritizing assessment activities. To address this challenge, CISA ISD partnered with Lawrence Livermore National Laboratory (LLNL) to review current assessment methodologies, analyze existing prioritization practices, and develop a comprehensive, national-security-focused prioritization framework. This report summarizes the project’s approach, key findings, and actionable recommendations for enhancing ISD’s assessment program.

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

Yesterday’s extremes, today’s new normal: flood risk in the Kathmandu Valley, Nepal

Unplanned urban growth has left many cities increasingly vulnerable to extreme rainfall events, particularly in regions with inadequate drainage infrastructures and development encroaching on natural floodplains. Here, in this perspective paper, we examine the September 2024 floods that struck Central Nepal, triggered by a persistent low-pressure system and enhanced by converging moisture flows from the Arabian Sea and the Bay of Bengal which led to widespread catastrophic damage. In the Kathmandu Valley, floodwaters expanded to more than 2.5 times the bankfull water extent, causing significant damage to housing, transportation network, and critical infrastructure, displacing thousands of residents, and severely disrupting urban services. This event highlights the urgent need for improved flood management strategies that integrate both structural and non-structural measures into the infrastructure development. While early warning systems provided critical lead time, challenges remain in reducing forecasting uncertainties and improving communication across government agencies and with local communities. A forward-looking approach is essential, including probabilistic flood forecasting systems, sustainable floodplain management, risk-sensitive land use planning, climate- and disaster- resilient infrastructure development, and the integration of nature-based solutions like urban green and blue spaces to mitigate flood impacts. By involving local communities in planning and preparedness efforts, particularly through citizen science initiatives, and engagement with underserved and disadvantaged communities, Nepal can better adapt to the growing risks posed by extreme rainfall and urban flooding and enhance long-term disaster resilience in rapidly urbanizing areas like Kathmandu Valley.

Kathmandu Valley↗
NASA NTRS2007

Assessing Hurricane Katrina Vegetation Damage at Stennis Space Center using IKONOS Image Classification Techniques

Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 9:45 a.m. CDT as a category 3 storm with surges up to approx. 9 m and sustained winds of approx. 120 mph. The hurricane's wind, rain, and flooding devastated several coastal towns, from New Orleans through Mobile. The storm also caused significant damage to infrastructure and vegetation of NASA's SSC (Stennis Space Center). Storm recovery at SSC involved not only repairs of critical infrastructure but also forest damage mitigation (via timber harvests and control burns to reduce fire risk). This presentation discusses an effort to use commercially available high spatial resolution multispectral IKONOS data for vegetation damage assessment, based on data collected over SSC on September 2, 2005.

Spruce, Joseph P.↗
NASA NTRS2015

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

MBSE↗
DOE OSTI2026

Revolutionizing thermal Management in Next-Generation AI data centers: Challenges and breakthrough innovations

Data centers (DCs) serve as critical infrastructure for powering the growth and evolution of AI. Next-generation AI DCs present unique challenges in thermal management driven by unprecedented computational demands. This paper provides a comprehensive summary of key stakeholder perspectives on technology gaps, infrastructure requirements, test bed needs, emerging opportunities, and preliminary solutions related to thermal management for AI DCs. It establishes six strategic pillars of thermal management for next generation AI DC: reliability, deployability, efficiency, resilience, measurability, and valorization. The discussion spans a range of critical topics, including advanced cooling technologies, thermal strategies for emerging modular and edge DCs, system-level optimization and control frameworks, infrastructure planning and grid integration designs, benchmarking approaches, and pathways for waste heat recovery and reuse. The proposed research, development, and demonstration efforts are aimed at accelerating the deployment of AI DCs while ensuring energy efficiency, reliability, safety, and regulatory compliance.

Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗
DOE OSTI2024

Developing Data-Driven Synthetic Infrastructure Models for Resilience Analysis

Research on infrastructure resilience has produced promising methods to simulate and optimize complex networks to improve performance. However, restrictions on sharing infrastructure models and the steep cost of developing and maintaining infrastructure models presents a roadblock to adoption. To overcome this limitation, this research focuses on methods to create data-driven infrastructure models that will help improve infrastructure resilience and security. The analysis couples incomplete utility data, geospatial data, machine learning, and synthetic network generation methods to rapidly develop and update infrastructure models. The methods are validated using realistic utility models and site-specific data, with a focus on Puerto Rico due to its unique infrastructure challenges and available data. This research highlights promising opportunities for the use of synthetic network generation and machine learning to create infrastructure models when very little data is available. Results demonstrate that hybrid methods, which combine sparse utility data with synthetic models, can enhance model accuracy, and machine learning can predict model attributes using training data from other models. However, the complexity of infrastructure systems means that even minor changes in network connectivity can significantly impact simulation results. Resilience analysis using synthetic infrastructure models shows that while some system behaviors are preserved, the magnitude of disruptions may not be accurately represented, indicating the need for more research and validation before using synthetic models for critical infrastructure investment decisions. The framework outlined in this report represents a significant advance to infrastructure model development and could be applied to additional domains and sites. Future research will continue to streamline and validate methods to help reduce roadblocks to resilience analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Center of Excellence for Operational Technology

The Center of Excellence for Operational Technology Traditional Presentation Abstract 2025 National Laboratories Information Technology Summit | Denver, CO Traditional Presentation Session Managing cybersecurity risk in Operational Technology (OT) presents a significant challenge across the Department, and critically, at many of the national laboratories. This includes IT-OT convergence, aging OT systems, cost of updating OT systems, and increased Advanced Persistent Threat efforts against OT including the 16 critical infrastructure sectors as listed in Presidential Policy Directive 21. DoE’s Office of Science and NNSA’s Office of the Chief Information Officer are taking the lead in addressing this challenge to include critical systems, by establishing the Center of Excellence (CoE) for Operational Technology. Championed by NNSA Deputy Chief Information Officer Steven McAndrews and the Office of Science Chief Information Officer Shila Cooch, the CoE for OT was chartered in February 2025 to address the challenges of OT cybersecurity and compliance. The CoE for OT will create partnerships and leverage expertise from across the NNSA National Security Enterprise and DOE Labs, Plants and Sites. The CoE will also collaborate with colleagues in other government agencies, industry partners and academia. The CoE for OT discussion at the National Laboratories Information Technology Summit ’25 will include the genesis of the CoE, stated goals, organizational structure, and the effort to attract OT subject matter experts to join the CoE effort to share knowledge and expertise. The discussion will include opportunities to get involved and contribute to this important effort. This session will be led by CoE for OT Co-Chairs Matt Kwiatkowski, Fermi National Laboratory Chief Information Security Officer, and Steven Weldon, Savannah River National Laboratory Cyber Program Director at the Georgia Cyber Center. The session will be of particular interest to CIOs, CTOs, CISOs, as well as IT and OT practitioners.

Kwiatkowski, Matt [Fermilab]↗
DOE OSTI2026

CyTRICS™ Assessment Report: Whole Home Battery Applications

This report examines the software supply chain security posture of mobile applications developed for consumer whole-house battery and energy-management products. While these applications are not currently integrated with critical infrastructure, their growing role in connected energy domain spaces underscores the importance of understanding the external dependencies, permission structures, and runtime behaviors that could introduce systemic risk; particularly, if adoption expands into more critical environments.

25 ENERGY STORAGE↗
NASA NTRS2022

Landslide Likelihood Prediction using Machine Learning Algorithms

The supply of electricity via power plants is criticalto the operation of many critical infrastructure systems in mod-ern society. Natural hazards can disrupt the power supply, causepower outages that can halt economic growth, and impede emer-gency response until power is restored. The proposed work aimsto predict the landslides likelihood in these critical infrastructurelocations in the Northeastern USA using integrated databases ofexplanatory variables and machine learning algorithms. First,data related to landslides are obtained and merged, includingtopographic, soil moisture, and precipitation-related data. Fiveregression algorithms, namely: Random Forest, Extreme Gradi-ent Boosting (XGBoost), K-Nearest Neighbor regression (KNN),Linear Support Vector Regressor (SVR), and Linear regression,are utilized to predict the landslide probability and evaluatedon the dataset. The accuracy of the models is assessed by usingstatistical metrics such as mean absolute error (MAE), meansquared error (MSE), and root mean squared error (RMSE).The study results show that Random Forest outperformed othermodels with the mutual information feature selection method.It achieved an MSE of 0.0011 with mutual information-basedfeature selection and an MSE of 0.00157 without feature selection.KNN regressor outperformed the other models with an MSEof 0.00139 with correlation-based information selection. Theproposed landslide identification model with Random Forestalgorithm shows outstanding robustness and great potential intackling the landslide likelihood prediction by employing MLalgorithms.

Vasundhara Acharya↗
DOE OSTI2025

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]↗
DOE OSTI2025

Hawaii Threat Brief

The Digital Energy Transformation is redefining how power systems operate, integrating physical infrastructure with digital technologies to enhance efficiency, visibility, and resilience. For islanded and digitally modernizing systems like Hawai‘i’s, this shift presents both new opportunities and evolving challenges in cybersecurity, supply chain assurance, and environmental resilience. This brief provides an overview of critical infrastructure dependencies and systemic risks associated with increasing digital integration. It summarizes recent energy-sector threat activity and case studies that illustrate adversary tactics and supply chain vulnerabilities, and identifies pathways to strengthen resilience.

25 - ENERGY STORAGE↗
DOE OSTI2024

A Visual Analytic Platform for Interactive Validation of Human Mobility Simulations

Human mobility insights guide domain experts in an array of decisions, including critical infrastructure design, disaster response, epidemic modeling, national security, and policy making. Due to the inherent noise and privacy concerns in real-world individual-level mobility data, it is often preferred to leverage simulators that generate synthetic mobility data instead. However, it is critical to inspect and validate the output of such simulators to ensure the synthetic data is aligned with the characteristics of the population and the area of interest known to domain experts. While there exist many quantitative approaches for validating synthetic data, we argue it is also important to also validate such data qualitatively to capture aspects that are known to domain experts but difficult to quantify. In this work, we demonstrate a visual analytic platform that empowers domain experts to interact with their simulation outputs along spatial and temporal dimensions. By augmenting automated techniques and human skills, our visual analytic platform is a step towards interactive capabilities for model steering and quality control of mobility simulators.

Monadjemi, Shayan↗
NASA NTRS2022

Preparing the Mars Relay Network for the Arrival of the Perseverance Rover at Mars

The Perseverance rover represents NASA’s latest achievement in Mars exploration. Landing successfully on 18 Feb 2021, the rover’s transmitted data during its entry, descent, and landing (EDL) were captured by the Mars Reconnaissance Orbiter (MRO) and the Mars Atmosphere and Volatile Evolution (MAVEN) orbiter. This data, broadcast in near-realtime to the world, allowed everyone to share in the excitement (and “terror”) of the day. The images returned thereafter included the first images of the new landing site, video of the landing itself taken from a variety of vantage points, and eventually the historic images of the first powered flight on another planet. Behind the scenes, the return of that data to Earth was accomplished via Mars orbiters operated by NASA and ESA, using three different ground tracking networks. Considered together, this Mars Relay Network (MRN) enabled the successful, timely, and unobtrusive return of the rover’s data. This paper describes the preparations taken by the participants of the MRN in anticipation of the arrival of Perseverance at Mars. These were not only focused on successfully acquiring the rover’s critical event telemetry during its EDL, but also on readying the network to return the rover’s data on an ongoing basis as it pursued its mission objectives. Included is a brief description of the MRN, which represents a highly successful international collaboration and continues as critical infrastructure for NASA’s and ESA’s ongoing Mars exploration. Also summarized are the activities performed prior to EDL, including landing site reconnaissance and mission test and training activities; those activities performed on EDL day, especially the recording, return, and processing of the rover’s critical event telemetry; and those activities that are now being performed on an ongoing basis during the rover’s surface operations, including an outline of the planning processes that enable relay services. Finally, a description of the performance of the network to-date on behalf of the Perseverance rover is given, summarizing the success of the network to provide support to both it and other spacecraft on the surface of Mars.

Srnka, Evan↗
DOE OSTI2026

PopGNN: Graph Neural Network-Based Flexible Future Population Forecasting Model

Accurate population forecasts is important to plan critical infrastructure and services, from housing and education to healthcare and transport. However, traditional population prediction studies have only employed traditional machine learning models limited to capture complex spatial interdependencies and patterns. Althogh recently computer vision-based framework was introduced with with promising accuracy, it has critical limitations for real-world planning applications: it function only at fixed spatial resolutions, restricting their use in diverse boundaries such as census tracts, neighborhoods, or administrative zones. Therefore, this study suggests a Graph Neural Network (GNN)-based population prediction framework, called PopGNN. This model recorded remarkable performance compared with state-of-the-art models and traditional baseline models in the grid and administrative boundaries. Furthermore, our framework achieved comparable predictive accuracy to a computer vision-based model in both the South Korea and Tennessee case studies. Consequently, this study is valuable in that a single model can provide accurate population forecasts that address diverse planning demands, ranging from granular grid-level estimates for precise service allocation and facility location planning to aggregate administrative-level forecasts for macro-scale regional policy and resource distribution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

TASTI-GRID: a holistic view of Florida's grid resilience opportunities

In December of 2025, the American Society of Civil Engineers updated Florida’s infrastructure grade to a ”C+” – reflecting overall investments in recent years. With the recommendation to further strengthen the electric grid and establish consistent building standards, extreme weather, aging infrastructure, and population in-migration are still compounding Florida’s grid vulnerabilities. Key challenges related to hurricane and other tropical & marine weather events are not unique to Florida. However, the state’s topography, location, demographics, and variation among rural and urban centers for tourism and industry, demonstrate the need for unique approaches to advancing critical infrastructure resilience, particularly for large concentrations of elderly residents or in areas of historic underinvestment. Florida’s grid asset advancements are credited with a reduction in average power outage durations. Yet, improvements since 2021 have set the stage for future resilience activities – as modernization efforts have greatly improved data collection – enabling better understanding of vulnerabilities and trends across counties and localities (particularly in Central Florida).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future

This paper examines the intersection of security and accessibility within energy systems amidst the rise of grid modernization and digitization, especially considering the regulatory changes and the imperatives of inclusive energy strategies. It addresses the dual need for secure, resilient infrastructure and a commitment to mitigate energy poverty while maintaining equitable access to energy. Amid escalating cybersecurity and physical threats, the paper advocates for sustainable energy delivery systems that ensure robust defenses without compromising the goals of reducing energy poverty and ensuring energy security. This paper identifies the pressing need for Cyber-Informed Engineering (CIE) and Secure-by-Design (SbD) principles, highlighting how these strategies can protect critical infrastructure and democratize access to secure energy, particularly for disadvantaged communities. The analysis underscores the challenges presented by the expansion of attack surfaces, interoperability requirements, and grid-edge analytics, offering innovative solutions that leverage advanced technologies and data-driven insights. Furthermore, this paper addresses the workforce development gap, emphasizing the necessity for public-private partnerships and vendor engagement in creating a skilled cybersecurity workforce. This paper has a dual focus on both the technological aspect of cybersecurity and the social dimension of equity within the context of sustainable energy development. It suggests a comprehensive examination of how these two critical elements interact and support the overarching goal of a sustainable energy future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Evaluating Hydropower Plants for Wildfire Resilient Microgrids

The increasing occurrence and severity of wildfires in recent years is severely impacting critical infrastructures, including the power grid, compromising the quality of life and provision of essential services, including electricity. The western parts of the United States, more specifically Washington, Oregon, and California, which are prone to large wildfires, are also rich in hydropower resources. Hydropower resources located close to communities vulnerable to wildfire can be utilized to develop wildfire-resilient microgrids to support critical needs of those communities. Therefore, this paper develops a framework to characterize hydropower plants and evaluate their feasibility to operate in microgrids during wildfire-related outages. In the proposed framework, hydropower plants are characterized using various plant and site attributes and evaluated in terms of capability and performance indicative metrics. A case study is carried out evaluating the Hills Creek hydropower plant located in a wildfire-prone region of Oregon for wildfire-resilient microgrid. The results of steady-state and dynamic simulations show that the hydropower plant is capable of providing the essential microgrid services and powering nearby communities during extended wildfire-related outages.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗