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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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DOE OSTI2025

LandScan Mosaic Rapid Population Update: Jamaica After Hurricane Melissa (V1)

During a natural disaster such as Hurricane Melissa, understanding where people are located is critical for situational awareness, operational planning and humanitarian support and consequence assessment. Traditional population datasets focus on mapping populations based on residential, or "business-as-usual" scenarios. However, natural disasters can create disruptions in daily routines of population in addition to the magnitude of the population displacement, depending on the type, duration, context, and location of the event. The Geospatial Science and Human Security Division at Oak Ridge National Laboratory (ORNL) produced this latest LandScan Mosaic Rapid Population Update for Jamaica following Hurricane Melissa, a category 5 hurricane that made landfall on Jamaica on October 28 2025. This Rapid Population Update captures the immediate population displacement following the hurricane using a combination of open-source building damage assessment data from Microsoft, flood exposure data from the Global Flood Monitoring service, reported population displacement information, and humanitarian shelter locations from the Jamaican Office of Disaster Preparedness and Emergency Management and the underlying LandScan Mosaic Jamaica as a base population.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Participation in and Assessment of the Second DNCSH Public Workshop

The DOE/NRC Criticality Safety for Commercial-Scale HALEU Fuel Cycle and Transportation (DNCSH) project was established through the Inflation Reduction Act of 2022 (H.R. 5376) to support the US Nuclear Regulatory Commission (NRC) and industry in addressing critical experiment validation gaps that impede the licensing basis and regulatory approval of high-assay low-enriched uranium (HALEU) operations. An initial public workshop was held in February 2024 to address HALEU transportation validation gaps. The resulting call for proposals was released in April and resulted in funding for the execution and/or evaluation of 16 critical experiments. A second public workshop was held in August 2025 to address facility and operational validation gaps, precluding a second call for proposals. A list of attendees is provided in APPENDIX A, Table A-1. A total of 319 participants joined the meeting, which was hosted online via Microsoft Teams as well as in person. The slides from the meeting were uploaded online to the NRC’s Agencywide Documents Access and Management System (ADAMS). The meeting agenda is provided in Table 1-1. In preparation for the meeting, a study was performed to examine expected fissile forms for the fuel cycles of various fuel types at different stages of production and the apparent validation gaps. The resulting report, titled “Benchmark Gap Assessment for the Manufacturing of High-Assay Low-Enriched Uranium Fuels,” provided the foundation for the discussions that took place during the workshop. The discussions and the validation gaps in the report were used to develop the second call for proposals. The present report presents the feedback received before, during, and after the second workshop. All the data presented are based on voluntarily self-reported identification, opinions from workshop participants, and survey responses and are assumed to be as accurate as practically reasonable. The discussions during the workshop and the subsequent survey responses were intended to direct attention to industry-specific areas of interest and to collect feedback on the work performed to date by the DNCSH project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Open Energy Data Initiative (OEDI) FY22-24 (Final Technical Report)

Final technical report for the Open Energy Data Initiative (OEDI) project covering fiscal years FY22 through FY24. The DOE Open Energy Data Initiative (OEDI) is a partnership between the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and major cloud providers including Amazon, Microsoft, and Google to provide universal access to big data in the cloud. At the heart of OEDI is a centralized repository of high-value energy research datasets aggregated from the U.S. Department of Energy's Program Offices, National Laboratories and other collaborators. It aggregates smaller, domain-specific repositories, allows direct data submissions, and includes support for big data through its energy data lakes. OEDI's data lakes make high-value data universally accessible and help researchers, collaborators and the general public overcome many of the obstacles to accessing and using big data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Precursor Analysis Report: Industroyer Targeting Ukraine Electric Power Transport Utility (Ukrenergo) 2016

The Industroyer Targeting Ukraine Electric Power Transport Utility (Ukrenergo) 2016 Precursor Analysis Report leverages publicly available information about the December 2016 cyber attack against the Ukrainian Ukrenergo electric transmission utility and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. Industroyer is a modular malware framework designed to deploy several Industrial Control System (ICS) protocol-specific attack payloads to disrupt electricity distribution. Adversaries deployed Industroyer within the target network on a Microsoft Windows endpoint capable of directly manipulating or communicating with ICS. Industroyer abuses the functionality of a targeted ICS’s legitimate control system to achieve its intended impact. Adversaries likely first gained access to Ukrenergo enterprise networks in early 2016 after a successful spearphishing campaign against organizations in the electric power sector. Adversaries then began capturing credentials beginning on 1 December 2016. This allowed access to the ICS environment at the Pivnichna electric transmission substation outside Kyiv through a device dual-homed on the Information Technology (IT) and ICS networks. Adversaries conducted discovery, targeting, and access to this device using information and previously captured credentials from compromised enterprise IT machines. Finally, the adversaries deployed and launched the Industroyer malware just before midnight on 17 December. By midnight, Ukrenergo had lost control of a targeted substation, resulting in electric power outages for over an hour in the city of Kyiv and the Kyiv region. Researchers and analysts identified 31 unique techniques (used in a sequence of 33 steps) utilized during the attack with a total of 846 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-nine of the identified techniques used during the Industroyer cyber attack were precursors to the triggering event. Analysis identified 548 observables associated with these precursor techniques, 353 of which were assessed to have an increased likelihood of being perceived in the 300 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

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

Idaho National Laboratory CY 2024 National Emission Standards for Hazardous Air Pollutants Analysis, Methodology, and Results for Radionuclides

This report documents the methodology and results for calculating the effective dose equivalent (EDE) to the maximally exposed individual (MEI) from atmospheric radionuclide emissions from Idaho National Laboratory (INL) sources in Calendar Year (CY) 2024. The calculations were performed in accordance with requirements in Code of Federal Regulations (CFR), Title 40, “Protection of the Environment,” Part 61, “National Emission Standards for Hazardous Air Pollutants (NESHAPs),” Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” (40 CFR 61, Subpart H). UDFs were calculated using the computer model CAP88-PC for unit (1 Ci/yr) emission rates at INL Site facilities and INL in-town (Idaho Falls) facilities and stored in Microsoft Access databases. The UDFs—in this case, mrem/Ci—were then combined with radionuclide-specific release (emission) rates for each facility-specific source to compute doses at predetermined public receptor locations, including the MEI locations. This report contains the dose results and a description of the methodology and tools used to compute the doses.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2025

Gas-Gap Calorimeter Sizing and Rating Tools for Heat Pipe Experimentation

Effective gas-gap calorimeter sizing and rating tools are required to design calorimeters that enable well-defined operating conditions, high cooling powers, and accurate calorimetry. The present report describes two tools utilizing Microsoft Excel and MathWorks MATLAB that enable the sizing and rating of gas-gap calorimeters with a He-Ar binary gas mixture in the gap. The Excel tools are two easy-to-use spreadsheets for calculating heat pipe operating temperature or He-Ar mole fractions given the required inputs. The MATLAB tool includes similar models with more robust solution algorithms along with sub-options for full-vacuum, static gas-gap, and forced circulation in the gas-gap. The accuracy of the developed tools were demonstrated by comparing with existing work in literature. The MATLAB tool was used for a parametric study to determine the gas-gap thickness, coolant gap thickness, coolant flow rate, and coolant inlet temperatures for the testing of a 3/4 in outer diameter heat pipe up to powers of 10 kW and temperatures of 1,000°C. The effects of heat pipe and calorimeter inner shell surface emissivities were investigated, considering the inability to control or accurately measure surface emissivities in most applications. It was found that controlling the He-Ar mole fractions provides a wide operating range for gas-gap thicknesses around ~ 0.042--0.090 in (~ 1.07--2.29 mm) for a surface emissivity range of 0.4--0.8, since conduction heat transfer is a significant fraction of the heat transfer across the gas-gap. In addition, it was found that turbulent flow in the coolant gap is needed at high input powers to prevent shell temperatures from approaching the boiling temperature of the water coolant. The parametric study resulted in choosing stainless steel tubes with an outer diameter and thickness of 1 x 0.065 in as the inner shell, and a 1-1/2 x 0.156 in as the outer shell of the calorimeter. Overall, this report presents the necessary information for the sizing and rating of gas-gap calorimeters with He-Ar mixtures for the testing of high-temperature heat pipes (~ 500--1,000°C).

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Evidence-based Graph Adversary Mapping (EGRAM) [Poster]

Cybersecurity companies such as CrowdStrike, Dragos, Microsoft and Unit 42 categorize Advanced Persistent Threats (APTs) using their own naming schemes. As a result, these APTs are mapped to different malware sources and campaigns, all from differing sources, leading to inconsistent mapping. Inconsistent mapping causes confusion and adds further obscurity around these groups, making it difficult to track and mitigate APT cyberattacks. The Evidence-based Graph Adversary Mapping (EGRAM) tool remediates the mapping challenge by collecting, updating and converting adversary data and their sources into a valid, codified STIX v2.1 bundle which is then stored in a Neo4j graph database. It utilizes graph traversal methods and centrality analysis to generate actionable information as a Structured Threat Intelligence Graph (STIG), based on user queries. EGRAM exists as Python code and a Jupyter Notebook that acts as a searchable, evidence-based, source of intelligence for APT groups’ artifacts and cyber campaigns.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

SPRUCE Photosynthesis and Respiration of Picea mariana and Larix laricina in SPRUCE Experimental Plots, 2016-2017

This dataset contains empirical physiological, morphological, and chemical data collected on two dominant conifer species, Picea mariana and Larix laricina, between May 2016 and August 2017 at the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Analyses assessed the response of conifers to whole-ecosystem warming and elevated atmospheric carbon dioxide (CO2) concentrations. Measurements include light-saturated net photosynthesis and dark respiration at ambient atmospheric carbon dioxide (CO2) concentration (2016), CO2 response curves of light-saturated net photosynthesis (2017), leaf morphology (leaf mass per unit leaf area) and nitrogen content (on both mass and area basis). Leaf photosynthesis and respiration were measured with portable photosynthesis systems (LI6400XT, LI6800, LI-COR Biosciences, USA). In 2016, photosynthesis and respiration were measured at a common temperature of 25 ˚C to assess thermal acclimation, and at growth temperatures (for each of the five treatment temperatures) to assess field performance. In 2017, CO2 response curves of net photosynthesis (so-called A-Ci curves) were conducted at different leaf temperatures (15, 25, 32.5, 40 and 45 ˚C) for assessment of biochemical parameters and their temperature sensitivity. In addition, dark respiration measurements at different leaf temperatures (10, 15, 20, 25, 30, 35, 40, and 45 ºC) were also taken. This dataset contains one data file in comma-separate values (*.csv) and Microsoft Excel (*.xlsx) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Early Investigation of the HHL Quantum Linear Solver for Scientific Applications

In this paper, we explore using the Harrow–Hassidim–Lloyd (HHL) algorithm to address scientific and engineering problems through quantum computing, utilizing the NWQSim simulation package on a high-performance computing platform. Focusing on domains such as power-grid management and climate projection, we demonstrate the correlations of the accuracy of quantum phase estimation, along with various properties of coefficient matrices, on the final solution and quantum resource cost in iterative and non-iterative numerical methods such as the Newton–Raphson method and finite difference method, as well as their impacts on quantum error correction costs using the Microsoft Azure Quantum resource estimator. We summarize the exponential resource cost from quantum phase estimation before and after quantum error correction and illustrate a potential way to reduce the demands on physical qubits. This work lays down a preliminary step for future investigations, urging a closer examination of quantum algorithms’ scalability and efficiency in domain applications.

hybrid software for QC-HPC↗
DOE OSTI2025

Novel Tools for Analyzing Life Cycle Energy Use, Carbon Emissions, and Cost of Additive Manufacturing

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from solid stock as with conventional techniques. This reduces material inputs and generates less waste, which can substantially lower life cycle energy consumption and greenhouse gas emissions. However, AM adoption in the manufacturing sector has been slow, partly due to challenges in making a strong business case compared with more traditional and widely available techniques. This paper highlights the need for the development of simple screening analysis tools to speed the adoption of AM in the manufacturing sector by providing decision-makers easy access to important production life cycle emissions, and cost information. Details on the development of two Microsoft Excel software tools are provided: upgrades to an existing tool on the energy and carbon impacts of AM and a new tool for analyzing the major cost components of AM. A case study applies these two tools to the production of a lightweight aerospace bracket, showing how the tools can be used to estimate the environmental benefits and production costs of AM.

GHG emissions↗
DOE OSTI2021

Open Data and Deep Semantic Segmentation for Automated Extraction of Building Footprints

Advances in machine learning and computer vision, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics, cost-effectively, and at scale. These characteristics are relevant to a variety of urban and energy applications, yet are time consuming and costly to acquire with today’s manual methods. Several recent research studies have shown that in comparison to more traditional methods that are based on features engineering approach, an end-to-end learning approach based on deep learning algorithms significantly improved the accuracy of automatic building footprint extraction from remote sensing images. However, these studies used limited benchmark datasets that have been carefully curated and labeled. How the accuracy of these deep learning-based approach holds when using less curated training data has not received enough attention. The aim of this work is to leverage the openly available data to automatically generate a larger training dataset with more variability in term of regions and type of cities, which can be used to build more accurate deep learning models. In contrast to most benchmark datasets, the gathered data have not been manually curated. Thus, the training dataset is not perfectly clean in terms of remote sensing images exactly matching the ground truth building’s foot-print. A workflow that includes data pre-processing, deep learning semantic segmentation modeling, and results post-processing is introduced and applied to a dataset that include remote sensing images from 15 cities and five counties from various region of the USA, which include 8,607,677 buildings. The accuracy of the proposed approach was measured on an out of sample testing dataset corresponding to 364,000 buildings from three USA cities. The results favorably compared to those obtained from Microsoft’s recently released US building footprint dataset.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Improving Building Footprint Extraction Using NAIP and 3DEP Lidar Derived Features with Deep Learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Liu, Jung Kuan [United States Geological Survey (U↗
NASA NTRS1986

Program for Generating Graphs and Charts

Office Automation Pilot (OAP) Graphics Database system offers IBM personal computer user assistance in producing wide variety of graphs and charts and convenient data-base system, called chart base, for creating and maintaining data associated with graphs and charts. Thirteen different graphics packages available. Access graphics capabilities obtained in similar manner. User chooses creation, revision, or chartbase-maintenance options from initial menu; Enters or modifies data displayed on graphic chart. OAP graphics data-base system written in Microsoft PASCAL.

Ackerson, C. T.↗
NASA NTRS1986

The SIMRAND 1 computer program: Simulation of research and development projects

The SIMRAND I Computer Program (Version 5.0 x 0.3) written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles is described. The SIMRAND I Computer Program comprises eleven modules-a main routine and ten subroutines. Two additional files are used at compile time; one inserts the system or task equations into the source code, while the other inserts the dimension statements and common blocks. The SIMRAND I Computer Program can be run on most microcomputers or mainframe computers with only minor modifications to the computer code.

Miles, R. F., Jr.↗
NASA NTRS1986

The RANDOM computer program: A linear congruential random number generator

The RANDOM Computer Program is a FORTRAN program for generating random number sequences and testing linear congruential random number generators (LCGs). The linear congruential form of random number generator is discussed, and the selection of parameters of an LCG for a microcomputer described. This document describes the following: (1) The RANDOM Computer Program; (2) RANDOM.MOD, the computer code needed to implement an LCG in a FORTRAN program; and (3) The RANCYCLE and the ARITH Computer Programs that provide computational assistance in the selection of parameters for an LCG. The RANDOM, RANCYCLE, and ARITH Computer Programs are written in Microsoft FORTRAN for the IBM PC microcomputer and its compatibles. With only minor modifications, the RANDOM Computer Program and its LCG can be run on most micromputers or mainframe computers.

Miles, R. F., Jr.↗
NASA NTRS1987

Designing Echelle Spectrographs

Performance numbers and output maps computed from inputs supplied by user. Echelle Spectrograph Design Aid program (EGRAM) aids in design of spectrographic systems that utilize echelle/first-order crossdisperser combinations. Optical combination causes two-dimensional echellogram to fall on detector. Describes echellogram with enough detail to enable user to judge effectively feasibility of spectrograph design. By iteratively altering system parameters, desired echellogram achieved without making physical model. Calculates system parameters accurately to first order and compare favorably to results from raytracing techniques. EGRAM written in two versions. FORTRAN 77, and Microsoft BASIC A.

Dantzler, A.↗
NASA NTRS1987

Calculating Electromagnetic Fields Of A Loop Antenna

Approximate field values computed rapidly. MODEL computer program developed to calculate electromagnetic field values of large loop antenna at all distances to observation point. Antenna assumed to be in x-y plane with center at origin of coordinate system. Calculates field values in both rectangular and spherical components. Also solves for wave impedance. Written in MicroSoft FORTRAN 77.

Schieffer, Mitchell B.↗
NASA NTRS1987

Simulation Of Research And Development Projects

Measures of preference for alternative project plans calculated. Simulation of Research and Development Projects (SIMRAND) program aids in optimal allocation of research and development resources needed to achieve project goals. Models system subsets or project tasks as various network paths to final goal. Each path described in terms of such task variables as cost per hour, cost per unit, and availability of resources. Uncertainty incorporated by treating task variables as probabilistic random variables. Written in Microsoft FORTRAN 77.

Miles, Ralph F.↗