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DOE OSTI2025

Designing Future Energy Systems with Generative AI

Energy systems are experiencing various changes that impact the distribution, use, and reliability of energy. Local utilities and municipalities must respond and adapt to these changes, moving towards a future energy system with modernized infrastructure and other targeted investments and policy decisions. However, planning for and enacting these advancements requires significant effort from experts and engineers to develop strategies that ensure a reliable and secure energy future. This includes characterizing the current energy infrastructure, identifying areas for development, and engaging with local community members. Emerging generative artificial intelligence techniques can alleviate pain points and help support the development of the next generation of energy systems. Here, in this article, we highlight on-going generative AI work in the areas of atmospheric modeling, building energy management, and distribution network design, and we propose a vision for the role of generative AI that considers opportunities and identifies challenges inherent to this technology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan details the strategy, mission, scope, and goals—both near-term and long-term—along with the structure and organization of nuclear fuels and materials research, development, and demonstration (RD&D) activities within the Fuel Cycle Technologies (FCT) program. The FCT program, tasked by the U.S. Department of Energy (DOE), employs a science-based approach to advance fuel technologies. This approach integrates theory, experiments, and multi-scale modeling and simulation (M&S) to develop a predictive understanding of fuel fabrication processes and fuel/cladding performance under irradiation, moving beyond traditional empirical methods. The long-term goals of the AFC are guided by the AFC Strategic Plan and align with the DOE Office of Nuclear Energy (NE) Roadmap [1], which outlines a multi-decade vision for demonstrating and qualifying advanced fuel forms to support diverse fuel cycle options. Near-term goals focus on enhancing accident tolerant fuels (ATF) for Light Water Reactors (LWR), a significant challenge that demands balancing immediate objectives with ongoing progress toward advanced reactor missions. Accelerating the traditional fuel qualification process to meet ATF objectives is another critical challenge. A detailed set of 5-year goals, summarized below, has been developed in line with the overarching science-based fuel development approach: • Advanced LWR Fuel Technologies: By 2027, support the development of advanced LWR fuel technologies with improved performance and enhanced accident tolerance. This includes high burnup (HBu), low enriched uranium (LEU)+, coated cladding, and doped fuel, aimed at complementing industry-led significant LWR uprates and plant refurbishments. • Tristructural Isotropic (TRISO) Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Metal Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Molten Salt Fuel: By 2027, deploy a robust program that enables fuel salt qualification technologies needed to support fuel salt research and development (R&D), focusing on emergent needs to derisk fuel salt production and utilization in advanced reactors. • Long-Term ATF: Develop fuel technologies that enable significant power uprates (~50%) in refurbished or new LWRs while optimizing fissile material utilization and waste disposal. The 5-year milestones in the AFC Execution Plan are contingent on an assumed budget. This Execution Plan will be updated annually to reflect actual funding profiles as budget guidance becomes available, ensuring milestones are adjusted accordingly. In summary, the AFC Execution Plan presents a comprehensive strategy to advance nuclear fuel technologies through a science-based approach, addressing both near-term and long-term goals while adapting to funding realities.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Modeling Variable Renewable Energy and Storage in the Power Sector

The emergence of variable renewable energy and battery storage technologies have fundamentally transformed the electric power sector and generated demand for analysis to understand their roles in future energy systems. Although unique characteristics of these resources are well-recognized and require more sophisticated methodologies to capture effectively, guidance is limited on best practices and research gaps. This paper selectively reviews recent literature and draws upon our collective modeling experience to offer recommendations to analysts and consumers of model outputs on approaches for modeling variable renewable energy and storage in long-term electric sector models. We focus on regional- and national-scale models with technological, temporal, and spatial detail given their prevalence in planning and policy analysis, though insights are applicable in other settings. The review highlights how the research frontier has advanced in representing renewables and energy storage over the past decade; however, given the many considerations involved with appropriately capturing salient economic and operational characteristics of renewables, there is a gap between commonly used models and state-of-the-art methods. Model simplifications can materially impact policy analysis associated with power sector decarbonization and high renewables deployment, and improving model representations of variable renewables can enhance insights for policymakers and other stakeholders. This review can point the way for improved methods for established models and designs for emerging ones.

energy and environmental policy↗

DOE OSTI2022

Enabling real-time adaptation of machine learning models at x-ray Free Electron Laser facilities with high-speed training optimized computational hardware

The emergence of novel computational hardware is enabling a new paradigm for rapid machine learning model training. For the Department of Energy’s major research facilities, this developing technology will enable a highly adaptive approach to experimental sciences. In this manuscript we present the per-epoch and end-to-end training times for an example of a streaming diagnostic that is planned for the upcoming high-repetition rate x-ray Free Electron Laser, the Linac Coherent Light Source-II. We explore the parameter space of batch size and data parallel training across multiple Graphics Processing Units and Reconfigurable Dataflow Units. We show the landscape of training times with a goal of full model retraining in under 15 min. Although a full from scratch retraining of a model may not be required in all cases, we nevertheless present an example of the application of emerging computational hardware for adapting machine learning models to changing environments in real-time, during streaming data acquisition, at the rates expected for the data fire hoses of accelerator-based user facilities.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Berkeley Lab 2021 Annual Financial Report

Lawrence Berkeley National Laboratory (LBNL) continued to successfully operate during the ongoing COVID pandemic, providing world-class science facilities to both researchers and scientific users in its five national user facilities. The dedication and commitment of the Lab community to continuing the Lab’s mission has been unparalleled during this difficult time. Due to the diligence of the Lab’s Operations teams and each person who came on site, the Lab was able to safely operate these facilities. In December, the Lab received its annual appraisal from the U.S. Department of Energy (DOE). The Lab received “A” grades for each of the performance goals which include mission accomplishment, leadership, health and safety, security and emergency management, business systems, and facilities. The University of California manages the Lab on behalf of the DOE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2016

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

Howell, Lauren R.↗

DOE OSTI2026

Powering Up Secure and Reliable Operations at the Port of Honolulu's Kapalama Container Terminal

The National Laboratory of the Rockies (NLR) is providing resilience planning support to the Pasha Group, the operator of Kapalama Container Terminal (KCT) at the Port of Honolulu, by exploring how distributed clean energy resources could help the terminal sustain a 36-hour outage and continue emergency operations. The Department of Energy's Energy Transitions Initiative (ETI) aims to advance self-reliant island and remote communities by promoting resilient, affordable, and sustainable clean energy resources.

25 ENERGY STORAGE↗

DOE OSTI2021

Oregon Rivers Characterization Tool

DHS’s Regional Resiliency Assessment Program (RRAP) undertook the Oregon State Transportation Systems RRAP project between 2018-2021 to assess the seismic vulnerabilities of the state’s transportation system to a Cascadia Subduction Zone (CSZ) earthquake (CISA 2021). The project primarily focused on the effects of a CSZ earthquake on the mobility of emergency response efforts into the region. In the event that bridges located at crucial river crossings fail during a CSZ earthquake, rivers will become natural barriers affecting the ability to support response and recovery efforts. The characteristics of rivers (e.g., width, depth, and flow) are critical data to inform planning for the recovery of transportation systems across river barriers and determine reopening times following a CSZ earthquake. As part of the transportation system assessment, an Argonne National Laboratory (Argonne) project team developed a River Characterization Tool (RCT) to quantify the physical characteristics of the river system in Oregon, which can be used to inform a system-level analysis of transportation recovery and reopening times. This report mainly discusses approaches, methods, development, and applications of the RCT. The use of the river data generated from this tool for a system-level analysis of transportation recovery is discussed in the Oregon Transportation Systems RRAP Resiliency Assessment report (CISA 2021). The primary goal of the RCT is to generate statewide dataset of widths, depths, and flows for all rivers across Oregon to assess the effects of river barriers on emergency response and recovery efforts following a CSZ earthquake. The RCT leverages remote sensing data that multispectral sensors collect from satellites, employs a deep learning model to characterize river predictions, and computes river channel geometric dimensions with hydraulic relationships and river predictions. The entire process of river characterization is automated and implemented through the RCT.

58 GEOSCIENCES↗

DOE OSTI2021

Hillsborough County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Hillsborough County used the Clear Sky Decision Support Toolkit to analyze solar + storage as an additional resiliency feature at its Brandon Support Operation Complex (BSOC). During normal operations, the BSOC houses water utility administration services and workspaces for water and wastewater engineers, facilities maintenance, and environmental management staff. During emergency management activation, the BSOC serves as an emergency hub for Emergency Support Function 3 (ESF-3), which includes public utilities, public works, and engineering staff support members. The BSOC is designated as a critical facility by the County.

14 SOLAR ENERGY↗

NASA NTRS2010

Remaining Technical Challenges and Future Plans for Oil-Free Turbomachinery

The application of Oil-Free technologies (foil gas bearings, solid lubricants and advanced analysis and predictive modeling tools) to advanced turbomachinery has been underway for several decades. During that time, full commercialization has occurred in aircraft air cycle machines, turbocompressors and cryocoolers and ever-larger microturbines. Emerging products in the automotive sector (turbochargers and superchargers) indicate that high volume serial production of foil bearings is imminent. Demonstration of foil bearings in APU s and select locations in propulsion gas turbines illustrates that such technology also has a place in these future systems. Foil bearing designs, predictive tools and advanced solid lubricants have been reported that can satisfy anticipated requirements but a major question remains regarding the scalability of foil bearings to ever larger sizes to support heavier rotors. In this paper, the technological history, primary physics, engineering practicalities and existing experimental and experiential database for scaling foil bearings are reviewed and the major remaining technical challenges are identified.

DellaCorte, Christopher↗

DOE OSTI2021

Preparing Distribution Utilities for the Future - Unlocking Demand-Side Management Potential: A Novel Analytical Framework

The balance of supply and demand in the power systems has traditionally been served solely through generation and network capacity planning and operations. However, with increased requirements for flexibility due to the uptake in variable renewable generation sources such as wind and solar there is a need to increased demand-side flexibility. In addition, there are increased communications and flexibility capabilities emerging on the demand-side from the adoption of advanced metering infrastructures and smart meter deployment and intelligent loads such as smart thermostats and schedulable white goods (e.g. dishwashers and washing machines). Unlocking demand-side flexibility can bring system benefits from peak load reduction bringing about generation capacity and network upgrade deferral, to reducing demand and more efficient utilization of generation and network capacity. Unlocking demand-side flexibility is an evolving process for utilities and solutions must be tailored to each specific customer group. Demand-side management (DSM) is a broad set of tools that can include demand response (both dispatchable and non-dispatchable), energy efficiency and distributed energy resources and demand-side technologies. The National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL) and Deloitte, examined the potential of DSM in BRPL’s service territory, developing detailed information on customer classes and willingness to participate in DSM. The study developed modeling frameworks for load analysis and the analysis tools to assess the potential of time-of-use tariffs in motivating customers to reduce their peak period energy consumption. The study shows that BRPL customers, specifically their domestic customers, are willing to participate in DSM programs and that time-of-use pricing can help BRPL reduce their peak demand and help unlock demand-side flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Identification of pressure points in modern power systems using transfer entropy

Power shortages disrupt daily life, economic activity, and essential services. In modern power systems, weather is an increasingly important driver of reliability: high temperatures raise demand and limit transmission capacity, and calm or cloudy periods reduce wind and solar supply. Using a data-driven analysis, this study identifies grid infrastructure whose operating patterns help predict power shortages. The results show that reliability risks often emerge from interacting stresses across generation, transmission, and demand, rather than from single bottlenecks. By clarifying how system stress propagates through the grid, this diagnostic perspective helps explain why shortages occur under specific conditions and can complement traditional planning and operational tools to support adaptive reliability strategies, targeted monitoring, and coordinated infrastructure investments.

power systems↗

DOE OSTI2025

Hantavirus is Associated With Open Developed Areas and Arid Climates, Highlighting Increased Risk in the Western United States

In the United States, hantaviruses can cause hantavirus pulmonary syndrome (HPS) in humans, an acute respiratory illness with a high mortality rate. Most people contract HPS from exposure to infected rodent excrement. The interannual dynamics of hantavirus transmission are tied to both environmental and human-related factors, including changes in annual climate conditions, rodent populations, and the built environment in which humans are more likely to be exposed. Similar environmental conditions and socioeconomic factors also likely determine the long-term risk of hantavirus exposure. Here, we use ecological niche models and human cases of HPS in the U.S. from 1993 to 2022 to assess hantavirus risk using four socioeconomic variables, 17 land use variables, one variable of rodent richness, and seven climate variables to determine both the geographical locations of highest exposure risk and leading environmental predictors. We found that areas with higher relative risk tend to be where it is drier, higher social vulnerability, increased rodent richness, and more open to low levels of development—this largely mapped to the western U.S. We found evidence that fringe ecosystems may be important areas of hantavirus transmission, similar to other emerging diseases. Increased rodent richness was associated with increased hantavirus risk, warranting further investigation into how the abundance and community composition of rodents could impact long-term risk. These risk maps can help public health officials develop plans for mitigating hantavirus, especially for the most susceptible populations. They can also be used to further investigate regions estimated to be at high risk for hantavirus where disease cases have not been as common but may be underreported.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A population data-driven workflow for COVID-19 modeling and learning

CityCOVID is a detailed agent-based model that represents the behaviors and social interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 million distinct places, including households, schools, workplaces, and hospitals, as determined by individual hourly activity schedules and dynamic behaviors such as isolating because of symptom onset. Disease progression dynamics incorporated within each agent track transitions between possible COVID-19 disease states, based on heterogeneous agent attributes, exposure through colocation, and effects of protective behaviors of individuals on viral transmissibility. Throughout the COVID-19 epidemic, CityCOVID model outputs have been provided to city, county, and state stakeholders in response to evolving decision-making priorities, while incorporating emerging information on SARS-CoV-2 epidemiology. Here we demonstrate our efforts in integrating our high-performance epidemiological simulation model with large-scale machine learning to develop a generalizable, flexible, and performant analytical platform for planning and crisis response.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Microgrid Hardening Design Toolkit: Puerto Rico Use Case

This document provides a comprehensive example of the microgrid hardening framework and the Sandia developed Microgrid Hardening Design Toolkit v0.27 using a census tract in a coastal area of southern Puerto Rico as a case study. The census tract (72123953100) is located in the municipality of Salinas. Currently, the La Margarita neighborhood within this census tract is part of the Department of Energy’s Cohort 5 of the Energy Technology Innovation and Partnership Program (ETIPP). The neighborhood’s local energy cooperative, Abeyno Coop, has been operating several residential solar photovoltaic (PV) and battery energy storage system (BESS) installations (with around 30 rooftop solar systems as of 2026). As part of the ETIPP project, Abeyno Coop is planning to integrate a larger microgrid into the existing distribution feeder in the area, including solar PV and BESS to supply energy for homes and critical loads such as the medical facilities and the community center that provides emergency shelter and backup power during outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1988

Analysis of the Space Shuttle Orbiter skin panels under simulated hydrodynamic loads

The Space Shuttle orbiter skin panels were analyzed under pressure loads simulating hydrodynamic loads to determine their capability to sustain a potential ditching and to determine pressures that typically would produce failures. Two Dynamic Crash Analysis of Structures (DYCAST) finite element models were used. One model was used to represent skin panels (bays) in the center body, while a second model was used to analyze a fuselage bay in the wing region of the orbiter. From an assessment of the DYCAST nonlinear computer results, it is concluded that the probability is extremely high that most, if not all, of the lower skin panels would rupture under ditching conditions. Extremely high pressure loads which are produced under hydrodynamic planning conditions far exceed the very low predicted failure pressures for the skin panels. Consequently, a ditching of the orbiter is not considered to have a high probability of success and should not be considered a means of emergency landing unless no other option exists.

Carden, Huey D.↗

NASA NTRS1993

Micro-precision control/structure interaction technology for large optical space systems

The CSI program at JPL is chartered to develop the structures and control technology needed for sub-micron level stabilization of future optical space systems. The extreme dimensional stability required for such systems derives from the need to maintain the alignment and figure of critical optical elements to a small fraction (typically 1/20th to 1/50th) of the wavelength of detected radiation. The wavelength is about 0.5 micron for visible light and 0.1 micron for ultra-violet light. This lambda/50 requirement is common to a broad class of optical systems including filled aperture telescopes (with monolithic or segmented primary mirrors), sparse aperture telescopes, and optical interferometers. The challenge for CSI arises when such systems become large, with spatially distributed optical elements mounted on a lightweight, flexible structure. In order to better understand the requirements for micro-precision CSI technology, a representative future optical system was identified and developed as an analytical testbed for CSI concepts and approaches. An optical interferometer was selected as a stressing example of the relevant mission class. The system that emerged was termed the Focus Mission Interferometer (FMI). This paper will describe the multi-layer control architecture used to address the FMI's nanometer level stabilization requirements. In addition the paper will discuss on-going and planned experimental work aimed at demonstrating that multi-layer CSI can work in practice in the relevant performance regime.

Sirlin, Samuel W.↗

NASA NTRS2011

The Soil Moisture Active Passive (SMAP) Applications Activity

The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP measurements will allow global and high-resolution mapping of soil moisture and its freeze/thaw state at resolutions from 3-40 km. These measurements will have high value for a wide range of environmental applications that underpin many weather-related decisions including drought and flood guidance, agricultural productivity estimation, weather forecasting, climate predictions, and human health risk. In 2007, NASA was tasked by The National Academies to ensure that emerging scientific knowledge is actively applied to obtain societal benefits by broadening community participation and improving means for use of information. SMAP is one of the first missions to come out of this new charge, and its Applications Plan forms the basis for ensuring its commitment to its users. The purpose of this paper is to outline the methods and approaches of the SMAP applications activity, which is designed to increase and sustain the interaction between users and scientists involved in mission development.

Brown, Molly E.↗