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DOE OSTI2023

A Vision for Coupling Operation of US Fusion Facilities with HPC Systems and the Implications for Workflows and Data Management

The operation of large US Department of Energy (DOE) research facilities, like the DIII-D National Fusion Facility, results in the collection of complex multi-dimensional scientific datasets, both experimental and model-generated. In the future, it is envisioned that integrated data analysis coupled with large-scale high performance computing (HPC) simulations will be used to improve experimental planning and operation. Practically, massive data sets from these simulations provide the physics basis for generation of both reduced semi-analytic and machine-learning-based models. Storage of both HPC simulation datasets (generated from US DOE leadership computing facilities) and experimental datasets presents significant challenges. In this paper, we present a vision for a DOE-wide data management workflow that integrates US DOE fusion facilities with leadership computing facilities. Data persistence and long-term availability beyond the length of allocated projects is essential, particularly for verification and recalibration of artificial intelligence and machine learning (AI/ML) models. Because these data sets are often generated and shared among hundreds of users across multiple leadership computing facility centers, they would benefit from cross-platform accessibility, persistent identifiers (e.g. DOI, or digital object identifier), and provenance tracking. Here, the ability to handle different data access patterns suggests that a combination of low cost, high latency (e.g. for storing ML training sets) and high cost, low latency systems (e.g. for real-time, integrated machine control feedback) may be needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Impact of Biofouling on Point Absorber Wave Energy Converter Performance and Control

Biofouling is a well-documented problem in naval engineering, but little is known about its effect on wave energy converter (WEC) performance. In this study, the software WEC-Sim is used to simulate the performance of a point absorber WEC that has been biofouled by “hard” species (e.g., mussels, barnacles) to varying degrees. Specifically, biofouling is assumed to change the nonlinear drag forces acting on the WEC, which have quantifiable effects on key performance characteristics such as optimal damping conditions, power, peak displacement, and peak velocity. The results of this analysis are then used to discuss strategies for WEC control as it relates to biofouling. Furthermore, the results show that average power production can decrease by as much as 15% with heavy biofouling and require an adjustment of the optimal control law by up to 20%.

Biofouling↗

DOE OSTI2025

Techno-Economic Analysis for the Addition of Thermal Energy Storage to a Campus With Existing Battery Storage

Rising global temperatures and increasing energy demands pose significant challenges for energy management, particularly in institutional and commercial settings. As cooling needs grow, campuses must balance operational efficiency, cost control, and grid stability. Energy storage solutions, such as thermal energy storage (TES) systems, offer a promising approach to shifting energy consumption from peak to off-peak periods, alleviating peak demand, reducing utility costs, and enhancing grid resilience. When integrated with existing battery energy storage systems (BESS), TES can further optimize load management and improve energy savings, especially in buildings with diverse energy needs. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills, which already operates a BESS. We assess three TES sizing strategies—full storage, load leveling, and peak demand limiting—by modeling and simulations based on historical energy loads. Our findings show that we can control TES systems to complement BESS operation, with campus-level load leveling providing the greatest cost savings by reducing peak demands. Furthermore, the study also evaluates the long-term economic viability of TES, considering installation costs, energy savings, and payback periods under varying tariffs. This research offers practical guidance for institutions seeking to enhance energy resilience and reduce operational costs through energy storage solutions.

25 ENERGY STORAGE↗

DOE OSTI2020

Software Requirements for a Consequence Management Sample Data Simulator for Training and Drills

This document describes the requirements for a software tool that will enable FRMAC to simulate large sets of sample result data that is based realistically on simulated radionuclide deposition grids from NARAC. The user of this tool would be scientists involved in exercise and drill planning or part of the simulation cell of an exercise controller team. A key requirement is that this tool must be able to be run with a reasonable amount of training and job aids by any person within the Assessment, Laboratory Analysis, or Monitoring and Sampling divisions of the FRMAC to support any level of exercise from the small IPX to the national level full scale exercise. This tool should be relatively lean and stand-alone so that the user can run it in the field with limited IT resources. This document will describe the desired architecture, design characteristics, order of operations, and algorithms that can be given to a software development team to assist them in project scoping, costing, and eventually, development.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Simulation-trained machine learning models for Lorentz transmission electron microscopy

Understanding the collective behavior of complex spin textures, such as lattices of magnetic skyrmions, is of fundamental importance for exploring and controlling the emergent ordering of these spin textures and inducing phase transitions. It is also critical to understand the skyrmion–skyrmion interactions for applications such as magnetic skyrmion-enabled reservoir or neuromorphic computing. Magnetic skyrmion lattices can be studied using in situ Lorentz transmission electron microscopy (LTEM), but quantitative and statistically robust analysis of the skyrmion lattices from LTEM images can be difficult. In this work, we show that a convolutional neural network, trained on simulated data, can be applied to perform segmentation of spin textures and to extract quantitative data, such as spin texture size and location, from experimental LTEM images, which cannot be obtained manually. This includes quantitative information about skyrmion size, position, and shape, which can, in turn, be used to calculate skyrmion–skyrmion interactions and lattice ordering. We apply this approach to segmenting images of Néel skyrmion lattices so that we can accurately identify skyrmion size and deformation in both dense and sparse lattices. The model is trained using a large set of micromagnetic simulations as well as simulated LTEM images. This entirely open-source training pipeline can be applied to a wide variety of magnetic features and materials, enabling large-scale statistical studies of spin textures using LTEM.

McCray, Arthur R. C. (ORCID:0000000160774698)↗

DOE OSTI2021

FY2020 Energy Efficient Mobility Systems Annual Progress Report

EEMS Program activities during FY 2020 focused on analytical research and large-scale modeling and simulation to understand the impacts that new mobility technologies and services will have at the vehicle-, traveler-, and overall transportation system-level. This research included the development of a multi-fidelity, end-to-end transportation system models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system. This document presents a brief overview of the EEMS Program and documents progress and results from projects within each of the EEMS activity areas. The Computational Modeling and Simulation key activity area summarizes work within the sub-areas of (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) Artificial Intelligence, High-Performance Computing, and Data Analytics, and (3) Core Simulation and Evaluation Tools. Additionally, the program’s advanced R&D projects are summarized within (4) the Connectivity and Automation Technology key activity area. Each of the individual progress reports provide a project overview and highlights of the technical results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗

DOE OSTI2020

Low-Frequency Stability Analysis of Inverter-Based Islanded Multiple-Bus AC Microgrids Based on Terminal Characteristics

For system planning of three-phase inverter-based islanded ac microgrids, the low frequency instability issue caused by interactions of inverter droop controllers is a major concern. When internal control information of procured commercial inverters is unknown, impedance-based small-signal stability criteria facilitate prediction of resonances in medium and high frequency ranges, but they usually assume the grid fundamental frequency as constant and thus they are incapable of analyzing the low-frequency oscillation of the fundamental frequency in islanded microgrids. Aiming at solving this issue, this paper proposes two stability analysis methods based on terminal characteristics of inverters and passive connection network including the dynamics of the fundamental frequency for analysis of low-frequency stability in islanded multiple-bus microgrids. Based on the Component Connection Method (CCM) to systematically separate inverters from the passive connection network, a general approach is developed to model the microgrid as a multiple-input-multiple-output (MIMO) negative feedback system in the common system d-q reference frame. By applying the generalized Nyquist stability criterion (GNC) to the return-ratio and return-difference matrices of the MIMO system model, the low-frequency stability related to the fundamental frequency can be analyzed using the measured terminal characteristics of inverters. Finally, analysis and simulation of a 37-bus microgrid verify the effectiveness of the proposed stability analysis methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Emergence of Unstable Focused Flow Induced by Variable‐Density Flows in Vertical Fractures

Abstract Fluids with different densities often coexist in subsurface fractures and lead to variable‐density flows that control subsurface processes such as seawater intrusion, contaminant transport, and geologic carbon sequestration. In nature, fractures have dip angles relative to gravity, and density effects are maximized in vertical fractures. However, most studies on flow and transport through fractures are often limited to horizontal fractures. Here, we study the mixing and transport of variable‐density fluids in vertical fractures by combining three‐dimensional (3D) pore‐scale numerical simulations and visual laboratory experiments. Two miscible fluids with different densities are injected through two inlets at the bottom of a fracture and exit from an outlet at the top of the fracture. Laboratory experiments show the emergence of an unstable focused flow path, which we term a “runlet.” We successfully reproduce the unstable runlet using 3D numerical simulations and elucidate the underlying mechanisms triggering the runlet. Dimensionless number analysis shows that the runlet instability arises due to the Rayleigh‐Taylor instability (RTI), and flow topology analysis is applied to identify 3D vortices that are caused by the RTI. Even under laminar flow regimes, fluid inertia is shown to control the runlet instability by affecting the size and movement of vortices. Finally, we confirm the emergence of a runlet in rough‐walled fractures. Since a runlet dramatically affects fluid distribution, residence time, and mixing, the findings in this study have direct implications for the management of groundwater resources and subsurface applications.

Environmental Sciences & Ecology↗

DOE OSTI2020

Convex Relaxation of Grid-Connected Energy Storage System Models With Complementarity Constraints in DC OPF

Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. Here, we propose a convex relaxation for a common ESS model that has terms for both charging and discharging based on a penalty reformulation for use in a model predictive control (MPC) based optimal power flow (DC OPF) problem. In this approach, the complementarity constraints are omitted and a penalty term is added to the optimization objective function. For the DC OPF problem, we provide analysis for the conditions under which the convex relaxation of the complementarity constraint ensures that a solution with simultaneous ESS charging and discharging operation is suboptimal. Simulation results demonstrating ESS behavior with and without the penalty reformulation are provided for an MPC-based DC OPF problem on multiple IEEE test systems.

25 ENERGY STORAGE↗

DOE OSTI2021

An efficient method to identify uncertainties of WRF-Solar variables in forecasting solar irradiance using a tangent linear sensitivity analysis

Uncertainty in predicting solar energy resources introduces major challenges in power system management and necessitates the development of reliable probabilistic solar forecasts. As the first part of the development of probabilistic forecasts based on the Weather Research and Forecasting model with solar extensions (WRF-Solar), this study presents a tangent linear approach to identify input variables responsible for the largest uncertainties in predicting surface solar irradiance and clouds. A tangent linear analysis is capable of efficiently investigating sensitivities of output variables with respect to various input variables of WRF-Solar because this approach avoids the computational burden of perturbing the initial conditions of individual input variables. We develop tangent linear models (TLMs) for six WRF-Solar physics packages that control the formation and dissipation of clouds and solar radiation, and we evaluate the validity of TLMs using a linearity test. The tangent linear sensitivity analysis is conducted under various scenarios based on satellite observations and model simulations to consider realistic input conditions. A simple method is used to quantify the impact of the uncertainty of input variables on the output variables from the TLMs. The results demonstrate that uncertainties in the output variables that are the focus of this study—including global horizontal irradiance, direct normal irradiance, cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes—are highly sensitive to uncertainties in 14 input variables. This study indicates that the tangent linear method can identify key variables of physics modules in WRF-Solar that can be stochastically perturbed to generate ensemble-based probabilistic forecasts.

14 SOLAR ENERGY↗

DOE OSTI2022

Power Decoupling Method for Voltage Source Inverters Using Grid Voltage Modulated Direct Power Control in Unbalanced System

The grid voltage modulated direct power control (GVM-DPC) is a novel power regulation method for grid-connected voltage source inverters (VSI). However, interactions between real and reactive powers still exist in GVM-DPC under unbalanced grid voltage condition, which may deteriorate its transient performance. Here, this article proposes a power decoupling method for GVM-DPC-based VSI in unbalanced systems based on the dynamic feedforward power compensation strategy, which can reduce the coupling magnitudes of real and reactive powers in the transient stages. First, the power coupling mechanism of positive and negative sequence real and reactive powers of VSI under the unbalanced voltage condition is analyzed. Then, the power coupling magnitudes (PCM) are derived according to relationships among the positive sequence components of real power, reactive power and point of common coupling (PCC) voltages. Next, the PCM are compensated into the GVM-DPC for the better decoupling performance. Furthermore, a stability analysis of the proposed control system is studied based on the impedance model, and a comparison with the traditional power decoupling method based on virtual impedance is conducted to show the superiority of the proposed method. Finally, simulations, hardware-in-loop test and experiment are conducted to validate the effectiveness of the proposed method.

42 ENGINEERING↗

DOE OSTI2023

Investigating Hydrogen Isotope Exchange Reactions on Lithium Aluminate Pellets in TPBAR (FY22 Report)

We developed a novel operando Raman spectroscopy method for investigation of hydrogen (H) isotope exchange reactions in the lithium aluminate (γ-LiAlO 2 ) that allows modeling of tritium behaviors in high temperature and in an irradiated environment. The lithium aluminate pellet is a main component in the Tritium-Producing Burnable Absorber Rod (TPBAR). We used deuterium ( 2 H or D) as a surrogate to simulate tritium ( 3 H or T). We used a surface analysis tools in situ/operando Raman spectroscopy to observe the transformation OH and OD compositional changes. We also used ToF-SIMS to analyze the lithium aluminate pellet control sample to build the base line for future in situ/operando analysis. To conduct operando Raman spectroscopy, we developed a custom reaction cell with a detachable micro heater using microelectromechanical systems (MEMS) and 3D printing techniques. Multiple versions were developed and tested. Using the new reaction cell, we demonstrated operando Raman spectroscopy of water (H 2 O) and deuterated water (D 2 O) with nitrogen (N 2 ) exposure onto the lithium aluminate (LiAlO2) pellet specimen, respectively, using a wet gas injection setup. We also successfully developed a detachable microheater that can heat up to ~250°C for ~90 mins. The Raman spectra did not show clear H 2 O and D 2 O characteristic peaks, which indicates that introducing H 2 O and D 2 O onto the surface of the pellet is challenging due to its dense structure nature. Our efforts suggest that various improvements are needed, such as increasing reaction cell operating gas pressure and thinning pellet sample thickness, to obtain meaningful measurements.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Benchmark Calculation for Turkey Point Unit 3 Cycles 1-3 Using the SCALE 6.3/Polaris–PARCS v3.4.2 Code Package

Benchmark calculations were performed for Turkey Point Unit 3 cycles 1–3 to validate the SCALE 6.3/Polaris–PARCS v3.4.2 code with the ENDF/B–VII.1 56–group library by comparing the simulated results with the measured data. The benchmark results will be used in evaluating the SCALE/Polaris–PARCS code package’s uncertainties for pressurized water reactor physics analysis. That future analysis will include key nuclear parameters such as reactivity, control bank worth, temperature coefficients, and pin and assembly power peaking factors. The present document details plant and fuel design specifications and input data for SCALE/Polaris, GenPMAXS, and PARCS. Additional details are provided with respect to the input and output files produced for the benchmark calculations. The benchmark results are summarized such that they can be used in evaluating uncertainties with other benchmark results for key nuclear parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

The LSST DESC DC2 Simulated Sky Survey

Here, we describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep area of approximately 300 deg 2 , as well as a deep drilling field of approximately 1 deg 2 . We simulate 5 yr of the planned 10 yr survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the data set to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic test bed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time domain cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Explicit Dynamic Impact Analysis of the Building 3525 Packages

The safe transport and handling of radioactive material containers is critical to ensure the protection of personnel, facilities, and the environment. Accidental drops during handling pose a significant hazard, necessitating robust design and analysis to mitigate potential consequences. This study presents an explicit dynamic impact analysis of two container designs, the Baby Sugarman and the Core Conduction Cooldown Test Facility (CCCTF) Tall Boy, used in Building 3525 at Oak Ridge National Laboratory. The analysis employed nonlinear finite element modeling in LS-DYNA to simulate free-fall impacts from a height of 16.5 ft across eight critical orientations. The study evaluated deformation, strain failure, and shielding integrity under these extreme conditions. Results demonstrated that both designs maintain structural integrity, with no breaches or loss of shielding under specified administrative controls. Notably, a maximum shielding loss of 10 lbs was observed during a top-corner drop, highlighting the need to limit drop heights to less than 1 ft for certain orientations. These findings underscore the effectiveness of engineering controls and design measures in preventing containment breaches and ensuring compliance with safety requirements. This work provides a comprehensive methodology for impact analysis, contributing valuable insights to the field of radioactive materials packaging and transportation safety.

Martinez, Oscar [ORNL] (ORCID:0000000181814046)↗

DOE OSTI2026

Thermo-hydro-mechanical analysis of subsurface ice-based thermal energy storage

Ice-based thermal energy storage systems are widely utilized for cooling and managing peak electrical demand globally, offering daily or weekly storage capabilities for both individual homes and larger office buildings. However, scaling these systems for district-level cooling or integrating them with renewable energy sources presents challenges, especially in accommodating larger volumes and addressing seasonal storage requirements in densely populated urban areas. This paper proposes a novel solution by evaluating subsurface ice-based thermal energy storage, in which the underground is subjected to seasonal freeze/thaw cycles. However, these cycles may influence ground behavior, affecting pore pressure and inducing ground movement. To systematically investigate these challenges, we enhance the TOUGH-FLAC simulator by integrating water/ice phase change capabilities and updating the effective stress–strain constitutive relation. Both modifications are validated against analytical solutions or experimental data. Through numerical simulations spanning a decade with ten seasonal freeze/thaw cycles, we evaluate the performance and long-term stability of a generic subsurface ice-based thermal energy storage system, considering factors such as ground permeability, freezing pipe spacing, freeze/thaw damage, and glycol solution temperature. The simulations indicate that ice formation induces pore pressure variations that drive seasonal surface heave and settlement, controlled by ground permeability, pipe spacing, and glycol solution temperature, along with tensile and localized shear deformation around freeze pipes. This highlights the need for accurate ground property characterization and geomechanical analysis for subsurface ice-based thermal energy storage.

Ground freezing↗