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DOE OSTI2024

Overview of recent experimental results on the EAST Tokamak

Since the last IAEA-FEC in 2021, significant progress on the development of long pulse steady state scenario and its related key physics and technologies have been achieved, including the reproducible 403 s long-pulse steady-state H-mode plasma with pure radio frequency (RF) power heating. A thousand-second time scale (~1056 s) fully non-inductive plasma with high injected energy up to 1.73 GJ has also been achieved. The EAST operational regime of high β P has been significantly extended (H 98y2 > 1.3, β P ~ 4.0, β N ~ 2.4 and n e /n GW ~ 1.0) using RF and neutral beam injection (NBI). The full edge localized mode suppression using the n = 4 resonant magnetic perturbations has been achieved in ITER-like standard type-I ELMy H-mode plasmas with q 95 ≈ 3.1 on EAST, extrapolating favorably to the ITER baseline scenario. The sustained large ELM control and stable partial detachment have been achieved with Ne seeding. The underlying physics of plasma-beta effect for error field penetration, where toroidal effect dominates, is disclosed by comparing the results in cylindrical theory and MARS-Q simulation in EAST. Breakdown and plasma initiation at low toroidal electric fields (<0.3 V m -1 ) with EC pre-ionization is developed. A beneficial role on the lower hybrid wave injection to control the tungsten concentration in the NBI discharge is observed for the first time in EAST suggesting a potential way toward steady-state H-mode NBI operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗

DOE OSTI2024

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo: Preprint

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. Using GHEDesigner, a lookup table was created to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on agent energy bills. This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of different costing and pricing future scenarios. While the code is still under development and nationwide simulations are ongoing, initial results for two states are provided. Future work includes expanding the module to consider mixed residential and commercial districts and considering multiple costing scenarios.

ambient temperature loop↗

DOE OSTI2024

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint

Geothermal cost and performance evaluation implemented via technoeconomic assessment (TEA) modeling is critical for the Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for the Annual Technology Baseline (ATB). The ATB data are inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL’s reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the US generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on technoeconomic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next generation technologies such as closed loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

Annual Technology Baseline↗

DOE OSTI2025

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop

Geothermal cost and performance evaluation implemented via techno-economic assessment (TEA) modeling is critical for the U.S. Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for NREL's Annual Technology Baseline (ATB), which provides inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL's reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the U.S. generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on techno-economic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next-generation technologies such as closed-loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

annual technology baseline↗

DOE OSTI2026

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗

DOE OSTI2024

Overview of the EUROfusion Tokamak Exploitation programme in support of ITER and DEMO

Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called ‘Tokamak Exploitation’. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

ASDEX upgrade↗

DOE OSTI2025

Adaptive Dynamic Digital Twin for Test Scenario Generation

Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.

Chen, Hanlin [ORNL] (ORCID:0000000165087715)↗

DOE OSTI2026

Analysis of synergies in converting underground storage sites: Natural gas to hydrogen with co-located CO2 storage

This study examines the untapped potential of synergistically converting underground natural gas storage (UGS) into underground hydrogen storage (UHS) with co-located CO2 storage. Current approaches to subsurface storage technology (SST) development often prioritise single-use scenarios, overlooking the benefits of integrating multiple technologies. We investigate converting UGS assets into UHS through gradual cushion-gas injection over multiple years, rather than injecting all cushion gas in the first year, and include on-site CO2 storage to offset site emissions. Mechanistic modelling shows this gradual transition reduces the Levelised Cost of Storage (LCOS) of H2 by 1.2-13.1% while retaining energy output within 3% of the current status quo. We also show that combined UHS and CO2 storage hubs can reduce the LCOS of CO2 by 45-77% for only a 3-10% increase in hydrogen LCOS relative to the status quo. This analysis framework may help future-proof SST sites and support a resilient, economically beneficial energy transition.

Mouli-Castillo, Julien↗

DOE OSTI2025

Weather and climate extremes in a changing Arctic

Weather and climate extremes are increasingly occurring in the Arctic. Here, in this Review, we evaluate historical and projected changes in rare Arctic extremes across the atmosphere, cryosphere and ocean and elucidate their driving mechanisms. Clear shifts occur in mean and extreme distributions after ~2000. For instance, pre-2000 to post-2000 observational probabilities of 1.5 standard deviation events increase by 20% for atmospheric heat waves, 76.7% for Atlantic layer warm events, 83.5% for Arctic sea ice loss and 62.9% for Greenland Ice Sheet melt extent — in many cases, low probability, rare extreme events in the early period become the norm in the latter period. These observed changes can be explained using a ‘pushing and triggering’ concept, representing interplay between external forcing and internal variability: long-term warming destabilizes the climate system and ‘pushes’ it to a new state, allowing subsequent variability associated with large-scale atmosphere–ocean–ice interactions and synoptic systems to ‘trigger’ extreme events over different timescales. Ongoing anthropogenic warming is expected to further increase the frequency and magnitude of extremes, such that simulated probabilities of 1.5 standard deviation events increase by 72.6% for atmospheric heat waves, 68.7% for Atlantic layer warm events and 93.3% for Greenland Ice Sheet melt rate between historic (1984–2014) and future (2069–2099) periods under a very high emission scenario. Future research should prioritize the development of physically based metrics, enhance high-resolution observation and modelling capabilities and improve understanding of multiscale Arctic climate drivers.

atmospheric dynamics↗

DOE OSTI2024

Experimental Study for Validation of Resilient Response of Controls - Thrust 2 Controls Assessment

The focus of this project is to design, execute, and analyze experiments around resilience response. As part of the Resilience through Data-Driven, Intelligently Designed Control (RD2C) initiative, this project builds upon the previously designed control algorithms and experiments. It designs detailed uses cases to test RD2C-developed mitigation schemes in specific realistic scenarios, analyze and save the measurement data sets. Having a high-confidence and consistent data set is crucial for identifying relevant metrics to describe the system resilience in specific real-life-like scenarios of power grid operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Efficient ECCD non-inductive plasma current start-up, ramp-up, and sustainment for an ST fusion reactor

The elimination of the need for an Ohmic heating solenoid may be the most impactful design driver for the realization of economical compact fusion tokamak reactor systems. However, this would require fully non-inductive start-up and current ramp-up from zero plasma current and low electron temperature of sub-keV to the full plasma current of ~10–15 MA at 20–30 keV electron temperature. To address this challenge, an efficient solenoid-free start-up and ramp-up scenario utilizing a low-field-side-launched extraordinary mode at the fundamental electron cyclotron harmonic frequency (X–I) is proposed, which has more than two orders of magnitude higher electron cyclotron current drive (ECCD) efficiency than the conventional ECCD for the sub-keV start-up regime. A time dependent model was developed to simulate the start-up scenarios. For the Spherical Tokamak Advanced Reactor (STAR) (Menard et al 2023 Next-Step Low-Aspect-Ratio Tokamak Design Studies (IAEA)), it was found that to fully non-inductively ramp-up to 15 MA, it would take about 25 MW of EC power at 170 GHz. Because of the relatively large plasma volume of STAR, radiation losses must be considered. It is important to make sure that high Z impurities are kept sufficiently low during the early current start-up phase where the temperature is sub-keV range. Since the initial current ramp up takes place at a factor of ten lower density compared to the sustained regimes, it is important to transition into a higher bootstrap fraction discharge at lower density to minimize the ECCD power requirement during the densification. For the sustainment phase an array of eight gyrotron launchers with a total of about 60 MW of fundamental O-mode was found to be sufficient to provide the required axis-peaked external current drive. High efficiencies between 19–57 kA MW –1 were found with optimal aiming, and these were resilient to small changes in aiming angles and density and temperature profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Indications for Freeze-Out of Charge Fluctuations in the Quark-Gluon Plasma at the LHC

The D-measure of net-charge fluctuations quantifies the variance of net charge in strongly interacting matter. It was introduced over 20 years ago as a potential signal of quark-gluon plasma (QGP) in heavy-ion collisions, where it is expected to be suppressed due to the fractional electric charges of quarks. Measurements have been performed at RHIC and LHC, but the conclusion has been elusive in the absence of quantitative calculations for both scenarios. We address this issue by employing a recently developed formalism of density correlations and incorporate resonance decays, local charge conservation, and experimental kinematic cuts. We find that the hadron gas scenario is in fair agreement with the ALICE data for $\sqrt{{𝑠}_{\textrm{NN}}}$ = 2.76 TeV Pb–Pb collisions only when a very short rapidity range of local charge conservation is enforced, while the QGP scenario is in excellent agreement with experimental data and largely insensitive to the range of local charge conservation. A Bayesian analysis of the data utilizing different priors yields moderate evidence for the freeze-out of charge fluctuations in the QGP phase relative to hadron gas. The upcoming high-fidelity measurements from LHC Run 2 will serve as a precision test of the two scenarios.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Progress and innovations in the TCV tokamak research programme

Research on the Tokamak à Configuration Variable addresses a wide range of key questions relevant to ITER and future fusion power plants. Over the past two years, highly productive experimental campaigns have led to major advances across several areas: the ITER baseline scenario; pedestal properties in low-collisionality, peeling-limited conditions; and the development of high- β N , non-inductive regimes. Alternative high-confinement scenarios have likewise received significant attention, with remarkable progress in quasi-continuous exhaust operation, X-point radiator plasmas, and negative triangularity configurations. Substantial achievements were also made in the mitigation or benign termination of runaway electron beams, in elucidating fast-ion loss mechanisms, and in improving exhaust behaviour in both conventional and alternative divertor geometries. These experimental results have been strongly supported by advances in modelling and their direct application to the experiment, ranging from gyrokinetic simulations of core and pedestal turbulence to fluid-based studies of scrape-off layer and divertor physics in diverse geometries. Plasma control has taken on an increasingly important role, with model-based and data-driven approaches now closely intertwined with physics studies. This article provides a overview of these recent activities, together with a brief outlook on forthcoming upgrades and next steps.

EPFL↗

DOE OSTI2024

Long duration battery sizing, siting, and operation under wildfire risk using progressive hedging

Battery sizing and siting problems are computationally challenging due to the need to make long-term planning decisions that are cognizant of short-term operational decisions. This paper considers sizing, siting, and operating batteries in a power grid to maximize their benefits, including price arbitrage and load shed mitigation, during both normal operations and periods with high wildfire ignition risk. Here we formulate a multi-scenario optimization problem for long duration battery storage while considering the possibility of load shedding during Public Safety Power Shutoff (PSPS) events that de-energize lines to mitigate severe wildfire ignition risk. To enable a computationally scalable solution of this problem with many scenarios of wildfire risk and power injection variability, we develop a customized temporal decomposition method based on a progressive hedging framework. Extending traditional progressive hedging techniques, we consider coupling in both placement variables across all scenarios and state-of-charge variables at temporal boundaries. This enforces consistency across scenarios while enabling parallel computations despite both spatial and temporal coupling. The proposed decomposition facilitates efficient and scalable modeling of a full year of hourly operational decisions to inform the sizing and siting of batteries. With this decomposition, we model a year of hourly operational decisions to inform optimal battery placement for a 240-bus WECC model in under 70 min of wall-clock time.

25 ENERGY STORAGE↗

DOE OSTI2025

A More La Niña–Like Response to Radiative Forcing after Flux Adjustment in CESM2

Abstract In response to greenhouse gas forcing, most coupled global climate models project the tropical Pacific SST trend toward an “El Niño–like” state, with a reduced zonal SST gradient and a weakened Walker circulation. However, observations over the last five decades reveal a trend toward a more “La Niña–like” state with a strengthening zonal SST gradient. Recent research indicates that the identified trend differences are unlikely to be entirely due to internal variability and probably result, at least in part, from systematic model biases. In this study, Community Earth System Model, version 2 (CESM2), is used to explore how mean-state biases within the model may influence its forced response to radiative forcing in the tropical Pacific. The results show that using flux adjustment to reduce the mean-state bias in CESM2 over the tropical regions results in a more La Niña–like trend pattern in the tropical Pacific, with a strengthening of the tropical Pacific zonal SST gradient and a relatively enhanced Walker circulation, as hypothesized to occur if the ocean thermostat mechanism is stronger than the atmospheric mechanisms which by themselves would weaken the Walker circulation. We also find that the historical strengthening of the tropical Pacific zonal gradient is transient but persists into the near term in a high-emissions future warming scenario. These results suggest the potential of flux adjustment as a method for developing alternative projections that represent a wider range of possible future tropical Pacific warming scenarios, especially for a better understanding of regional patterns of climate risk in the near term.

Zhuo, Jing-Yi [Lamont-Doherty Earth Observatory, C↗

DOE OSTI2026

SPAROW: Stochastic Programming and Related Optimization Workflows

SAND2026-16703O SPAROW: Stochastic Programming and Related Optimization Workflows is a Python library tool that facilitates the development and solution of stochastic programming problems. It provides a user-friendly class structure for defining stochastic programs through scenario-based representations of uncertainties. SPAROW incorporates multiple optimization strategies, including integer programming with all scenarios, progressive hedging, Benders decomposition, and Snoglode, a novel technique developed by Carnegie Mellon University. It also features interfaces to external solvers and functions that are commonly used in analysis workflows, making it applicable to a wide range of scientific and engineering design challenges, particularly in power grid planning. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, William [Sandia National Lab. (SNL-NM), Albu↗

DOE OSTI2025

Radiation Accidents and Malicious Events – Scenarios and Scope of the Work of ICRP Task Group 120

The International Commission on Radiological Protection (ICRP) Task Group 120 (TG120) is developing ICRP recommendations for radiological protection for a wide range of radiation accidents and malicious events, complementing those given in ICRP Publication 146 (2020) for large nuclear accidents. The scope includes accidents involving criticalities, operating faults, and fires and explosions in nuclear facilities, inadvertent damage to sealed radiation sources, as well as malicious events, such as sabotage of nuclear facilities or materials, use of radiological dispersal devices, the contamination of food and drinking water supplies, and the deployment of nuclear weapons. A template has been designed to collate relevant information on a wide range of case studies and hypothetical malicious scenarios to ensure that the recommendations developed are broadly applicable and comprehensive. For all scenarios, a graded approach to protection is being taken, accepting that specific guidance may be required for some distinctive aspects, for example, protection during times of armed conflict. This paper provides an overview of the scenarios and scope of the work of TG120, including some of the radiological and non-radiological impacts of radiation emergencies, along the response and recovery timeline.

ICRP↗