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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Assessing Energy Infrastructure Devices for Vulnerabilities

Industrial control systems prove to be vital to the health and security of the nation in our critical infrastructure. Critical infrastructure includes the most foundational systems to support modern civilization which includes water and wastewater systems, communications, and the electricity we use to name a few sectors. However, these devices' overall composition remains largely unknown and are untested from a cyber security perspective. As part of the Cyber Testing for Resilient Industrial Control Systems (CyTRICS) program, I analyzed one such energy infrastructure device to better understand how it functions, what hardware and software components are present within it, and assess it for security vulnerabilities. To achieve this, I reverse engineered binary files using Ghidra to understand system functionality and learned more about how to collaborate with other researchers on a shared Ghidra project. I learned more about how web sockets function and how to interact with them through Python to test if they are secure or not. This work led me to assess possible vulnerabilities in this device and provide a better understanding of its composition and function, which are essential to INL's mission of securing our nation's energy infrastructure.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Electric Vehicle Infrastructure Consequence Assessment

With consumers’ growing interest in electric vehicles, extreme fast charging stations are poised to provide high-power charging to rapidly recharge light-duty passenger vehicles. High-power charging requires high-level communication between vehicle and charger to govern the charging process. The coupling of power and communication increases the potential scale of cyberattacks. Using a full Western Electricity Coordinating Council planning model, load manipulation from high-power charging infrastructure is investigated. Two cases of load manipulation are studied: (i) a discrete, widespread system event and (ii) loads modulated near the Western Interconnect’s resonant frequency. In (i) some generation trips and in (ii) oscillations are observed on the California Oregon Intertie. Neither scenario results in significant adverse effects to the grid.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Evolving Multi-hazard Machine Learning Modeling for Advanced Risk-Informed Infrastructure Resilience Assessment

The socioeconomic impacts of pipeline incidents have escalated over the past three decades, revealing the limitation of traditional risk modeling methods when applied to extensive pipeline networks. This research aims to develop machine learning (ML) models that effectively identify, rank, and predict the diverse hazards and socioeconomic consequences associated with pipeline incidents. Utilizing historical data on pipeline incidents alongside weather and oceanographic data from the 1980s onward, the Houston metropolitan area serves as a testbed for the proposed methodologies. The research segments the combined datasets into three consecutive periods, demonstrating the efficacy of the updated model in predicting future events, particularly concerning precipitation rate data. Despite the challenges posed by a relatively limited dataset, local-level ML modeling offers valuable insights into the spatial and temporal dynamics of multiple hazards that contribute to pipeline incidents. These findings hold significant implications for future research, particularly in understanding and mitigating risks in various locations across the Gulf Coast and other coastal regions.

42 ENGINEERING↗
DOE OSTI2024

Sovereign Credit Rating Processes Adapted to Critical Infrastructure Cyber Risk Assessment

United States critical infrastructure entities are increasingly targeted by motivated and capable threat actors and must be prepared to assess and treat a diverse range of cyber risks. Consequently, this necessitates some form of analytical process to evaluate risks and inform cyber security investment decisions. A potential solution for structuring cyber risk evaluation exists within the field of sovereign credit ratings – where agencies employ mature approaches that integrate quantitative and qualitative data to produce a singular value of assessment. Adapting such approaches, we present a novel criterion and methodology for measuring and communicating the likelihood element of cyber risk. The methodology is composed of three sequential phases: a quantitative baseline organized by distinct capability frames, a bounded qualitative adjustment per frame, and a greater-bounded qualitative adjustment spanning the entire process. The process culminates in publication of a cyber capability rating that communicates a critical infrastructure entity’s ability and willingness to mitigate discontinuous function due to cyberattack.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

MASTODON: An Open-Source Software for Seismic Analysis and Risk Assessment of Critical Infrastructure

Seismic analysis and risk assessment of safety-critical infrastructure like hospitals, nuclear power plants, dams, and facilities handling radioactive materials involve computationally intensive numerical models and coupled multiphysics scenarios. They are also performed in a strict regulatory environment that requires high software quality assurance standards, and in the case of safety-related nuclear facilities, a conformance to the American Society of Mechanical Engineers Nuclear Quality Assurance (NQA-1) standard. This paper introduces the open-source finite-element software, MASTODON (Multi-hazard Analysis of Stochastic Time-Domain Phenomena), which implements state-of-the-art seismic analysis and risk assessment tools in a quality-controlled environment. MASTODON is built on MOOSE (Multi-physics Object-Oriented Simulation Environment), which is a highly parallelizable, NQA-1 conforming, coupled multiphysics, finite-element framework developed at Idaho National Laboratory. MASTODON is capable of fault rupture and source-to-site wave propagation using the domain reduction method, nonlinear site response, and soil-structure interaction analysis, implicit and explicit time integration, automated stochastic simulations, and seismic probabilistic risk assessment. When coupled with other MOOSE applications, MASTODON can also solve strongly and weakly coupled multiphysics problems. This paper presents a summary of the capabilities of MASTODON and some demonstrative examples.

42 ENGINEERING↗
DOE OSTI2026

Impact of hydropower availability on resource adequacy of the United States western interconnection

Hydropower is a key energy source in the western interconnection of the United States, comprising about 25% of the annual installed nameplate capacity in 2020. However, its generation is increasingly impacted by changing hydrological conditions, operational constraints, environmental factors, water availability, and aging dam infrastructure. Assessing hydropower availability and resource adequacy is valuable for shaping energy policies and infrastructure requirements. In this study we evaluate the sensitivity of resource adequacy in the Western Interconnection to the unavailability of hydropower plants, under a wide-ranging set of 16,384 hydropower loss scenarios derived from a combination of 14 major hydrologic regions. Although a complete loss of hydropower capacity in any region is unlikely, studying such scenarios helps in identifying hydrologic regions most critical for maintaining resource adequacy. So, we identify key hydrologic regions with disproportionately large adequacy impacts relative to their installed hydropower capacity and study compounding effects between regions using classification and regression trees. Even after controlling for total installed capacity, we find that hydropower resources in the Pacific Northwest contribute the most to interconnection-wide adequacy outcomes, with resources in Northern California and the Desert Southwest providing more moderate incremental contributions.

13 HYDRO ENERGY↗
DOE OSTI2025

MRCI Task 4: Evaluating Regional Infrastructure Technical Summary Report

The infrastructure required to enable carbon capture and sequestration (CCS) goes beyond the equipment and materials needed to capture, transport, and store carbon dioxide (CO2) but includes people and policy that make CCS feasible. The Infrastructure Assessment task of the Midwest Regional Carbon Initiative (MRCI) seeks to determine the infrastructure requirements for the MRCI study area through four activities: • Infrastructure Readiness: Strategizing the buildout of capture, transport, and storage infrastructure in the Midwest, Northeast, and Mid-Atlantic Offshore. • Site Readiness: Determining the CCS readiness of each state in the MRCI region in the categories of subsurface readiness; infrastructure readiness; regulations, permitting, and incentives; and social dynamics. • Jobs, Economics, and Social Characteristics: Quantifying the economic potential, job opportunities, and training opportunities for CCS as well as the social characteristics of the region with a focus on energy and environmental justice (EJ) issues. • Policy and Regulations: Providing an updated accounting of the CCS-relevant policy and regulations in the MRCI region.

CCUS,Carbon storage,Midwest,Midwest Regional Carbo↗
DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗
DOE OSTI2026

RTN-124: Photometric Redshifts for the Vera C. Rubin Observatory Data Preview

We present the photometric redshifts (photo-z) inferred using algorithms implemented in the Redshift Assessment Infrastructure Layers (RAIL) for the NSF-DOE Vera C. Rubin Observatory Data Preview 2 (DP2). We produce a compilation of reference redshift catalog using spectroscopic, grism and many band photometric redshift dataset hosted on the LIneA Photo-z Server. We curate training and testing set for assessing the scientific and technical performance of Rubin photo-z. The algorithm applied to the object catalog are FlexZBoost, BPZ, kNN, GPz, DNF and TPz; with a combination of 6-band and 4-band photo-z depending on availability of u and y photometry. The redshift point estimates and uncertainty estimation in tabular format through the Large Survey DataBase (LSDB).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Electric Vehicle Infrastructure Projection Tool (EVI-Pro)

This presentation includes results from the second California installment of EVI-Pro. Pursuant to California Assembly Bill 2127, evolving market and technology conditions warrant updating this statewide infrastructure assessment at least every two years. EVI-Pro has been updated to consider California's 2030 goal to have 5 million zero emission vehicles (ZEVs) on the road by 2030. CEC and NREL with the support of UC Davis and other state agencies, have set out to refine EVI-Pro to reflect increasing PEV market share, evolving vehicle and charging technology, and observed charging behavior.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗
DOE OSTI2020

Integrated Model of Models for Global Flood Alerting

A dramatic increase in frequency of minor to major flooding since 2000 has caused significant economic losses across the world. To mitigate and recover from these losses, actions have been taken to build resilient communities and infrastructures, specifically, by providing situational awareness in near real-time about flood impacts to enhance response and recovery efforts. Several hydrologic and hydraulic flood models are available at various spatial and temporal resolutions to forecast flood events at regional to global scale. Given the global coverage of two operational flood models – GloFAS (Global Flood Awareness System) and GFMS (Global Flood Monitoring System), the purpose of this project is to implement a Model of Models (MoM) approach to integrate the outputs from these two models to classify flood severity at watershed level worldwide, and send alerts based on severity similar to the USGS PAGER (used for severity alerting and impact analysis for earthquakes) to flood impacted communities. The alerts containing flood impacts and severity information will be disseminated through the DisasterAWARE platform, operated by the Pacific Disaster Center (PDC), that provides global multi-hazard alerting and Situational Awareness information to the emergency management community and public. The current version of the MoM approach was implemented for a case study flood event that occurred during January and February of 2020 in South and Central Africa. The findings of the case study event reveal that the approach is effective in identifying potential flood impact areas and the spatio-temporal variation of flood severity, flood depth and extent at watershed level, which will be used to assess infrastructure and societal impacts using earth-observation data and for alerting.

Kar, Bandana↗
DOE OSTI2025

Electric Vehicle Supply Equipment (EVSE) Site Assessment Report for the U.S. Army Corps of Engineers Chena Site Near Fairbanks, Alaska

This report presents an analysis of the requirements for charging station installation and electric vehicle operation at the US Army Corps of Engineers - Chena Site, located in a cold weather climate in the Fairbanks North Star Borough, AK. The report includes findings from a site visit, and a detailed electric vehicle (EV) charging site plan with cost estimates. Cost for three 50-ampere pedestal chargers located on the edge of the existing parking lot is estimated at $\$$53,100, and the cost of three 80-ampere chargers is estimated at $\$$89,400. The authors did not assess the cost of a heated garage. The USACE Chena site reaches extreme cold temperatures of -40 Degrees Celsius (-40 Degrees Fahrenheit) and below in a typical winter, often for days on end. Considerations of operating EVs as well as electrical vehicle supply equipment (EVSE) at this site can be applicable to other cold or extremely cold locations. Interviews with EV users in cold climates and a literature review indicated that EVs operate well but have significantly decreased range compared to 21 Degrees Celsius (70 Degrees Fahrenheit) operations. Some strategies such as prewarming the vehicle while it is plugged in and using heated seats and steering wheel instead of cabin heat, can improve cold weather performance. Storing the EV in a garage would mean the battery and cabin are automatically preheated, the battery would not age as rapidly as when the vehicle is stored outside, and problems with charging the vehicle are less likely. Lowest temperate-rated Electric Vehicle Supply Equipment (EVSE), as electric vehicle chargers are known as, are rated to -40 Degrees Celsius (-40 Degrees Fahrenheit), and sometimes malfunction. No EVSE is rated to the temperatures that USACE Chena site experienced for more than a week in winter 2023-4, of -50 Degrees Celsius (-45 Degrees Fahrenheit) and which are typical for the area. If reliability is a must, entities may want to consider a heated garage to minimize potential problems with charging equipment. There is a companion technical report to this titled "Electric Vehicle and Charging Infrastructure Assessment in Cold-Weather Climates: A Case Study of Fairbanks, Alaska" that examines the data on EV and EVSE cold-weather functionality in more detail. (Esparza, Truffer Moudra, and Hodge 2024).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗