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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Tribal Engagement in Transmission Planning

The purpose of this white paper is to provide Tribes with information that (a) helps assess whether transmission access is important for their energy goals, and (b) provides guidance on how to engage in transmission planning, if and when doing so would help the Tribe achieve its energy goals. DOE's Office of Indian Energy notes that "Indian Country contains vast untapped energy resources" (OIE 2023). Individual tribes express a wide array of energy needs and goals, ranging from simple access to basic electricity service and energy efficiency tools, to the development of utility-scale generating plants. Access to transmission is a key part of this multifaceted tribal energy picture. About 2.3 percent of the nation's transmission miles are on tribal lands (OIE 2023). Even within that slice, however, circumstances vary widely. Much of that transmission is for local network delivery (138kV or less). There are some large-capacity 500kV lines, but in many cases the Tribe has limited access to them even when they run across the reservation. Some of the Tribes with the largest land area have little transmission, and some such as Navajo Nation and Hopi Tribe have many homes with no access to electricity. This white paper begins with a high-level summary of transmission issues that can affect a Tribe's energy goals. The discussion includes findings from major transmission-related studies, including the 2023 National Transmission Needs Study (GDO 2023). It then discusses strategies that could help a Tribe safeguard its interests when those interests intersect transmission infrastructure planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Joint modeling of water and energy for resilience and flexibility

This white paper addresses the intersection of energy and water resources for potable water, considering energy-for-water through joint systems modeling. Specifically, we focus on the opportunities to promote joint resilience in water and power systems through coupled modeling to inform decision-makers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Remarks on the thesis of Aitor Bengoechea Fernández: Generalization of Doppler effect processing using S(α,β) thermal diffusion laws

The thesis titled “Generalization of Doppler effect processing using S(α,β) thermal diffusion laws” addresses a critical gap in the modeling of neutron scattering phenomena in nuclear materials, particularly where crystal lattice effects intersect with low-energy resonances. Conducted within the Doctoral School ED 352 at Aix-Marseille Université and hosted at CEA Cadarache, the research presents a theoretical and numerical framework for extending the applicability of Thermal Scattering Laws (TSLs) using higher-order correlation functions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Powered By reV [Slides]

The reV model empowers users to calculate energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades. By automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and energy cost supply curves.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Micro-Hydropower and Aquatic Restoration on Lands of the Eastern Band of Cherokee Indians

Rural and Tribal communities in Southern Appalachia face persistent challenges in energy access owing to rugged terrain, dense forest cover, and limited infrastructure. The Eastern Band of Cherokee Indians (EBCI) is a federally recognized Tribe whose ancestral homelands include much of Southern Appalachia. The Tribe’s present-day homeland, termed the Qualla Boundary, lies in the heart of the region, where the extreme ruggedness of the Blue Ridge Mountains exacerbates challenges to energy access. For the EBCI, these challenges also intersect with a deep cultural commitment to stewardship of land and water. The Tribe has explored multiple energy solutions, with hydropower serving as an existing and realized source of energy for the region’s communities. However, the EBCI’s commitment to protecting aquatic systems has led not only to a historical lack of endorsement of new conventional hydropower on Tribal lands but also to ongoing efforts to remove the area’s only existing hydropower facility at Ela Dam.

13 HYDRO ENERGY↗
DOE OSTI2026

A Comparative Analysis of Infrastructure-Based Perception Sensors for Intelligent Transportation Systems

The rise of privatized and public investment in smart city infrastructure and intelligent transportation systems has generated a heightened demand for perception sensors that effectively track and detect objects while being reliable in diverse weather and lighting conditions. This growing demand for perception sensors has accelerated their development and enhanced their capabilities. With these new capabilities, it is challenging to determine the most suitable sensing unit to use in each situation. Therefore, it is essential to have a comprehensive understanding of the benefits and limitations of each sensing unit to effectively leverage their capabilities. The purpose of this paper is to provide a detailed evaluation of various perception sensors. Additionally, this paper will demonstrate the benefits of combining multiple perception sensors, which complement each other by addressing data gaps inherent to single-sensor systems, to facilitate the creation of a digital twin that models the real world. The Infrastructure, Perception, and Control (IPC) team will conduct data analysis using data collected through field testing at traffic intersections in Colorado Springs, Colorado, to make comparisons between sensors. This research aims to provide clear and concise information about modern perception systems, which will support the development of intelligent transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Hurricane Helene: Energy Systems Impact and Situational Insights in East Tennessee

This situational report focuses specifically on energy system performance and interdependencies associated with Hurricane Helene’s impacts across East Tennessee. It does not attempt to identify root causes, evaluate broader emergency response structures, or assess agency effectiveness. Rather, it aims to illuminate how energy disruptions intersected with other lifeline services, particularly water, transportation, and communications, and identify the infrastructural and logistical conditions that shaped those outcomes. Where possible, this report seeks to highlight both constraints and successful practices that emerged during the event.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Cybersecurity Workforce Training for SMR Integration into Distribution Grids: A Competency Framework and Containerized Hands-On Lab for the SMR/DER/Microgrid Boundary

Small modular reactors (SMRs) and microreactors are entering the U.S. distribution grid as synchronous generation on feeders designed for loads and inverter-based distributed energy resources (DERs). No existing cybersecurity training program addresses this intersection of nuclear operations, DER management, and operational technology security. As subcontractor to Iowa State University on the CyDERMS Center, Argonne analyzed the relevant standards and training landscape, translated the resulting gaps into a twelve-objective competency framework across distribution-operator and graduate-analyst role tracks, and built a containerized training lab using a ∼400-bus composite grid model behind a realistically simulated Modbus TCP SCADA stack. The analysis isolates the balance-of-plant / energy-management-system (BOP/EMS) boundary as the critical jurisdictional seam where, as of March 2026, neither NRC nor NERC CIP cleanly claims cybersecurity responsibility for distribution-connected SMRs. The framework maps each objective across NIST CSF 2.0, ISA/IEC 62443, NIST NICE Task–Knowledge–Skill statements, and NRC RG 5.71 awareness-and-training controls. The training lab implements operator-recognition assessment scenarios spanning grid-side disturbances and telemetry-layer anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Integrated Simulation of Weld Residual Stress Evolution and Crack Propagation Using XFEM

Nuclear power plant components operate in environments that promote multiple degradation mecha- nisms, several of which involve crack initiation and growth. An ongoing effort in the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is developing a general capability within the Multiphysics Object Oriented Simulation Environment (MOOSE) framework for simulating three-dimensional crack growth under a range of driving conditions, including fatigue, stress corrosion cracking (SCC), brittle fracture, and stress-relaxation cracking. This report demonstrates an end-to-end workflow that uses this capability to model weld-residual-stress-driven SCC in the J-groove weld of a pressurized-water reactor control rod drive mechanism penetration in the vessel head. The workflow consists of a thermomechanical welding simulation with temperature-dependent plasticity, followed by cooldown to ambient conditions, and a restart of the simulation using the MOOSE extended finite element method (XFEM) module to propagate a three-dimensional crack through the residual stress field. New welding capabilities were developed to properly initialize newly activated elements in the weld region, and robustness improvements were made to the mesh-based algorithm for defining cutting planes in the 3D XFEM algorithm, allowing it to handle complex crack fronts and stress fields. Together these advances allowed the simulated SCC crack to grow from an initial elliptical flaw in the weld, across the weld, through the tube wall, and almost to the triple point (where the weld, tube, and reactor pressure vessel head intersect) over roughly 36 years of simulated service. These results demonstrate a workflow that can be extended to fully three-dimensional welding simulations and more complex crack interaction problems.

42 - ENGINEERING↗
DOE OSTI2025

TetCrust WILD: Weighted Delaunay meshing in the wild

We introduce the first conforming Voronoi mesher capable of handling unclean input geometries encountered 'in the wild'. Our algorithm handles non-watertight, non-manifold, and self-intersecting inputs without requiring any manual cleanup, providing a standalone, end-to-end meshing framework. The framework enables simultaneous Voronoi and weighted Delaunay meshing, allowing users to generate polyhedral or tetrahedral elements based on application requirements, and produces high-quality elements

Ebeida, Mohamed Salah [Sandia National Laboratorie↗
DOE OSTI2026

SIMBER: the Simula Berkeley Education and Research Collaboration (CRADA Final Report)

The SIMBER project is centered around advancing the state-of-the-art in the science of modelling of the human heart and leveraging the collaborations between leading research groups at the University of California Berkeley (UC Berkeley), the Lawrence Berkeley National Laboratory (Berkeley Lab), and Simula Research Laboratory (Simula). In particular, the following areas of expertise are shared and expanded through this project: “heart-on-chip” experimental systems from UC Berkeley, mathematical modelling of the heart from Simula, and supercomputing software from Simula and Berkeley Lab. This intersection of expertise is already enabling the development of novel tools and knowledge that produce more accurate models of the human heart in both health and disease, which in turn are leading to drug screening technologies that make cardiac drug development faster, cheaper and more humane.

Li, Xiaoye Sherry [Lawrence Berkeley National Labo↗
DOE OSTI2024

Lightning Climatology Derived from World Wide Lightning Location Network (WWLLN) for US East Coast and European North Sea

This dataset contains gridded (1x1 km) data of lightning stroke observations during 2020, 2021, and 2022 over the US East Coast and European North Sea. Data processing involved intersecting each of the ~26 million lightning strokes over the US East Coast and ~365 thousand strokes over the North Sea within a corresponding 1x1 km grid, resulting in each grid reporting a 'strokes per square kilometer' and 'energy per square kilometer'. For the US, these results are presented as annual averages for 2020, 2021, and 2022, while for the North Sea results are presented as a 3-year annual average.

17 WIND ENERGY↗
DOE OSTI2024

Lightning Climatology Derived from World Wide Lightning Location Network (WWLLN) for US East Coast and European North Sea

This dataset contains gridded (1x1 km) data of lightning stroke observations during 2020, 2021, and 2022 over the US East Coast and European North Sea. Data processing involved intersecting each of the ~26 million lightning strokes over the US East Coast and ~365 thousand strokes over the North Sea within a corresponding 1x1 km grid, resulting in each grid reporting a 'strokes per square kilometer' and 'energy per square kilometer'. For the US, these results are presented as annual averages for 2020, 2021, and 2022, while for the North Sea results are presented as a 3-year annual average.

17 WIND ENERGY↗
DOE OSTI2018

A Very Forward Hadron Spectrometer for the LHC and Cosmic Ray Physics

Charged hadron production in hadron-hadron collisions with longitudinal momentum fraction Feynman-x, x_F, between 0.1 and 0.9 has not been measured above square root s = 63 GeV at the CERN Intersecting Storage Rings. I discuss a way to measure this at the Large Hadron Collider at square root s = 13 TeV, which is 40,000 times higher in equivalent fixed target energy, and important for understanding cosmic ray showers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Altered ß-cell Prohormone Processing and Secretion in Type 1 Diabetes

Analysis of data from clinical cohorts and more recently from human pancreatic tissue, indicate that defects in prohormone processing are an early and persistent component of type 1 diabetes pathogenesis. In this Perspectives article, we review the current state of knowledge of alterations in islet prohormone expression and processing in type 1 diabetes, and consider the clinical impact of these findings. Lingering questions, including pathologic etiologies and consequences of altered prohormone expression and secretion in type 1 diabetes, and the natural history of circulating prohormone production in health and disease are considered. Finally, key steps required to move forward in this area are outlined, including longitudinal testing of relevant clinical populations, studies that probe the genetics of altered prohormone processing, the need for combined functional and histologic testing of human pancreatic tissues, continued interrogation of the intersection between prohormone processing and autoimmunity, and optimal assays or approaches for analysis. Successful resolution of these questions may offer the potential to use altered prohormone processing as a pathogenic anchor that can be used to cluster different endotypes enveloping a large set of variables, and inform therapeutic strategies aimed at personalized intervention in the natural history of type 1 diabetes.

Islets, Insulin, Proinsulin, Islet Amyloid Polypep↗
DOE OSTI2020

Estimating vehicle fuel economy from overhead camera imagery and application for traffic control

In this work, we explore the ability to estimate vehicle fuel consumption using imagery from overhead fisheye lens cameras deployed as traffic sensors. We utilize this information to simulate vision-based control of a traffic intersection, with a goal of improving fuel economy with minimal impact to mobility. We introduce the ORNL Overhead Vehicle Dataset (OOVD), consisting of a data set of paired, labeled vehicle images from a ground-based camera and an overhead fisheye lens traffic camera. The data set includes segmentation masks based on Gaussian mixture models for vehicle detection. We show the dataset utility through three applications: the estimate of fuel consumption based on segmentation bounding boxes, vehicle discrimination for those vehicles with largest bounding boxes, and a fine-grained classification on a limited number of vehicle makes and models using a pre-trained set of convolutional neural network models. We compare these results with estimates based on a large open-source data set based on web-scraped imagery. Finally, we show the utility of the approach using reinforcement learning in a traffic simulator using the open source Simulation of Urban Mobility (SUMO) package. Our results show the feasibility of the approach for controlling traffic lights for better fuel efficiency based solely on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗