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DOE OSTI2022

An Improved Method for Coupling Hydrodynamics with Astrophysical Reaction Networks

Reacting astrophysical flows can be challenging to model, because of the difficulty in accurately coupling hydrodynamics and reactions. This can be particularly acute during explosive burning or at high temperatures where nuclear statistical equilibrium is established. We develop a new approach, based on the ideas of spectral deferred corrections (SDC) coupling of explicit hydrodynamics and stiff reaction sources as an alternative to operator splitting, that is simpler than the more comprehensive SDC approach we demonstrated previously. We apply the new method to a double-detonation problem with a moderately sized astrophysical nuclear reaction network and explore the time step size and reaction network tolerances, to show that the simplified-SDC approach provides improved coupling with decreased computational expense compared to traditional Strang operator splitting. This is all done in the framework of the Castro hydrodynamics code, and all algorithm implementations are freely available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗

DOE OSTI2025

Constraining GREA, an alternative theory accounting for the present cosmic acceleration

The origin of the Universe's late-time accelerated expansion remains unknown. The General Relativistic Entropic Acceleration (GREA) theory offers a compelling alternative to $Λ$CDM, attributing cosmic acceleration to entropy growth associated with cosmic and black hole horizons, without invoking a cosmological constant. We test GREA against the latest DESI DR2 Baryon Acoustic Oscillations (BAO), multiple Type Ia supernova compilations (Union3, Pantheon$\texttt{+}$, DES-SN5YR), and cosmic microwave background (CMB) distance measurements. While GREA is not nested within $Λ$CDM, it achieves a comparable goodness-of-fit, highlighting its potential as a theoretically motivated framework that circumvents some of the fine-tuning issues of the standard $Λ$CDM cosmology. We find that the best-fit model features a transient phantom crossing at $z \lesssim 2$, with $w_a\equiv \mathrm{d} w(a=1)/\mathrm{d}a \simeq-0.3$, in good agreement with observations. However, its present-day value $w_0\equiv w(z=0)$ is tightly constrained to be $w_0\simeq-1$. Upcoming low-redshift (i.e. $z < 1$) cosmological probes, from both background and perturbations, will offer promising avenues for further exploring the viability of the GREA theory.

Calderon, R. [Prague, Inst. Phys.] (ORCID:00000002↗

DOE OSTI2024

Solid Sorbent Cost Sensitivity Analysis: A Framework for UNF Reprocessing Sorbent Cost Comparison

Solid sorbents have been the subject of research and development across the U.S. Department of Energy national laboratory complex for many years. They are generally accepted as a safer alternative to cryogenic distillation for noble gas capture, and they present an easier pathway in development of long-term waste forms after iodine capture. As more types of sorbents have been proposed for capture of volatile radionuclides, it has become necessary to compare them based on performance and cost criteria. This report details cost and performance information for three promising sorbents and provides a cost sensitivity analysis. The goal of this analysis is to establish a framework which can be utilized to directly compare future sorbents, with differing properties, to the sorbents discussed in this report. Direct comparison is instrumental to making informed decisions to efficiently guide research and minimize laborious detours. In all cases, sorbent capacity is a major cost driver as it influences the mass of sorbent, operational footprint, and disposal cost requirements., However, sorbent price can greatly increase the cost of a capture technology. For sorbents used in krypton capture, the purity of krypton released to storage is the highest cost driver.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Investigation of the Effect of Framework Flexibility on Adsorption in SIFSIX-3-Cu using a Machine-Learned Force Field

Metal-organic frameworks (MOFs) are a promising class of adsorbents. The performance of MOF sorbents relies on high selectivity and low regeneration energy. This work focuses on the use of machine learned force fields (MLFFs) to model adsorption in a flexible MOF, SIFSIX-3-Cu. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies, forces, and stresses, using an iterative sampling scheme combining sampling based on molecular dynamics, Monte Carlo, and geometry optimization to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included in this model. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations using the MLFF predicted adsorption isotherms in good agreement with experimental data for a range of pressures (40 Pa – 104 Pa) in contrast to rigid models, which overpredict CO2 adsorption at low pressures. The improvement was the result of a description of the variability of fluorine-fluorine diagonal distances at adsorption sites. This detailed description of flexibility afforded by the MLFF resulted in more accurate predictions adsorption isotherms when compared to the experimentally measured values. These results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low pressure applications and provide a robust procedure for training MLFF models for MOFs.

Atomistic Simulation↗

DOE OSTI2020

Framework for Analysis and Quantification of Wide-Area Control Resilience for Power Systems

Wide-area control helps damp the inter-area oscillations in modern power systems. However, compared to traditional local control, it is more vulnerable to cyber attacks due to its dependence on remote real-time-communicated measurements. In this paper, a formal mathematical framework for analyzing resilience of various wide-area controllers under adversarial scenarios is proposed. A novel resilience index based on the $\H_2$ norm of the post-attack closed-loop system is defined. Computation of such an index is, in general, challenging due to the combinatorial nature of the attack profiles and the bilinear nature of the problem. To address these difficulties, a gradient-based path-following-like solution is developed in this paper to solve a relaxed version of the original non-convex problem. Case studies on IEEE 39-bus system are performed to demonstrate the usage of the proposed framework.

Marinovici, Laurentiu D.↗

DOE OSTI2024

Polarized 𝐽/𝜓 production in semi-inclusive DIS at large 𝑄 2 : Comparing quark fragmentation and photon-gluon fusion

We compare the relative importance of different mechanisms for polarized 𝐽/𝜓 production in semi-inclusive deep inelastic scattering processes at large 𝑄 2 . The transverse momentum dependent (TMD) factorization framework and nonrelativistic quantum chromodynamics are used to study the leading contributions from light quark fragmentation to polarized 𝐽/𝜓, and compared to direct production via photon-gluon fusion, which can proceed through color-singlet as well as color-octet mechanisms. We identify kinematic regimes where light quark fragmentation dominates, allowing for the extraction of the 3 𝑆$^{[8]}_{1}$ matrix element, as well as regimes where photon gluon fusion dominates, suggesting that the gluon TMD parton distribution function can be probed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Computational capacity in hydrodynamic real-time hybrid simulation applied to simulate the dynamic response of floating offshore wind turbines

Real-time hybrid simulation (RTHS) mitigates similitude distortions in model-scale tests of floating offshore wind turbines (FOWTs) by coupling physical experiments with numerical models in real time. The coupling requires faster-than-real-time numerical computations to satisfy temporal similitude with the physical experiment, presenting a bottleneck for using more complex numerical models in RTHS. This paper presents a hydrodynamic-RTHS (hydro-RTHS) framework for FOWTs that simulates the hydrodynamics physically and the aerodynamics numerically with sensor feedback from the physical testing. The framework adapts the three-loop hardware architecture to leverage greater computational resources and mitigate strict temporal requirements, enabling more computationally demanding numerical analyses in hydro-RTHS. The three-loop hardware architecture integrates multiple machines, each dedicated to either numerical analysis or RTHS controls, with a rate-transition algorithm to synchronize the tasks executed across the different machine processors. Virtual and physical tests verified and validated the hydro-RTHS framework, respectively. The ”virtual” tests, which approximates the physical domain numerically, verified the RTHS framework with respect to a numerical full-scale complete FOWT model simulated in the open-source software, OpenFAST. The virtual tests were able to maintain comparable control signals while enabling greater computational resources for the numerical calculations. Real-world physical tests demonstrated that the hydro-RTHS framework computes aerodynamic forces similar to the complete OpenFAST model, validating the hydro-RTHS framework using the three-loop hardware architecture. Findings show that the hydro-RTHS framework with the three-loop hardware architecture is computationally efficient, with reserve capacity to simulate more complex problems due to the customized software, hardware, and rate-transition algorithm.

17 WIND ENERGY↗

DOE OSTI2021

Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation

—Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today’s synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems.

Zhao, Junbo↗

DOE OSTI2022

Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics

Online transient analysis plays an increasingly important role in dynamic power grids as the renewable generation continues growing. Traditional numerical methods for transient analysis not only are computationally intensive but also require precise contingency information as input, and therefore, are not suitable for online applications. Existing online transient assessment studies focus on the determination of post-contingency system stability or stability margin. Here, this paper develops a novel graph-learning framework, Deep-learning Neural Representation or DNR, for online prediction, of the time-series trajectories of the system states using initial system responses that can be measured by phasor measurement units (PMUs). The proposed DNR framework consists of two sequential modules: a Network Constructor that captures network dependencies among generators, and a Dynamics Predictor that predicts the system trajectories. The key to improved prediction performance is the introduction of the spatio-temporal message-passing operations into graph neural networks with structural knowledge. Its effectiveness and scalability are validated through comparative studies, demonstrating the prediction performance under different contingency scenarios for systems of different sizes. This framework provides a solution to online predicting post-fault system dynamics based on real-time PMU measurements. Additionally, it can also be applied to facilitate the offline transient simulation without simulating the entire trajectories.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants

Digital instrumentation and control (DI&C) systems at nuclear power plants (NPPs) have many advantages over analog systems. They are proven to be more reliable, cheaper, and easier to maintain given obsolescence of analog components. However, they also pose new engineering and technical challenges, such as possibility of common cause failures (CCFs) unique to digital systems. Here this paper proposes a Platform for Risk Assessment of DI&C (PRADIC) that is developed by Idaho National Laboratory (INL). A methodology for evaluation of software CCFs in high safety-significant safety-related DI&C systems of NPPs was developed as part of the framework. The framework integrates three stages of a typical risk assessment—qualitative hazard analysis and quantitative reliability and consequence analyses. The quantified risks compared with respective acceptance criteria provide valuable insights for system architecture alternatives allowing design optimization in terms of risk reduction and cost savings. A comprehensive case study performed to demonstrate the framework's capabilities is documented here in this paper. Results show that the PRADIC is a powerful tool capable to identify potential digital-based CCFs, estimate their probabilities, and evaluate their impacts on system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Role of Zeolite Structural Properties toward Iodine Capture: A Head-to-head Evaluation of Framework Type and Chemical Composition

This study evaluated zeolite-based sorbents for iodine gas [I2(g)] capture. Based on the framework structures and porosities, five zeolites, including two faujasite (FAU), one ZSM-5 (MFI), one mesoMFI, one ZSM-22 (TON), as well as two mesoporous materials, were evaluated for I2(g) capture at room temperature and 150 °C in an iodine-saturated environment. From these preliminary studies, the three best-performing zeolites were ion-exchanged with Ag+ and evaluated for I2(g) capture under similar conditions. Energy-dispersive X-ray spectroscopy data suggest that Ag-FAU frameworks were the materials with the highest capacity for I2(g) in this study, showing ~3× higher adsorption compared to Ag-mordenite (Ag-MOR) at room temperature, but X-ray diffraction measurements show that the faujasite structure collapsed during the adsorption studies because of dealumination. The Ag-MFI zeolites are decent sorbents in real-life applications, showing both good sorption capacities and higher stability. In-depth analyses and characterizations, including synchrotron X-ray absorption spectroscopy, revealed the influence of structural and chemical properties of zeolites on the performance for iodine adsorption from the gas phase.

aluminosilicate zeolites, iodine, porosity, acidit↗

DOE OSTI2020

Using OpenMP for HEP framework algorithm scheduling

The OpenMP standard is the primary mechanism used at high performance computing facilities to allow intra-process parallelization. In contrast, many HEP specific software packages (such as CMSSW, GaudiHive, and ROOT) make use of Intel’s Threading Building Blocks (TBB) library to accomplish the same goal. In these proceedings we will discuss our work to compare TBB and OpenMP when used for scheduling algorithms to be run by a HEP style data processing framework. This includes both scheduling of different interdependent algorithms to be run concurrently as well as scheduling concurrent work within one algorithm. As part of the discussion we present an overview of the OpenMP threading model. We also explain how we used OpenMP when creating a simplified HEP-like processing framework. Using that simplified framework, and a similar one written using TBB, we will present performance comparisons between TBB and different compiler versions of OpenMP.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Collisionless zonal-flow dynamics in quasisymmetric stellarators

The linear collisionless plasma response to a zonal-density perturbation in quasisymmetric stellarators is studied, including the geodesic-acoustic-mode oscillations and the Rosenbluth–Hinton residual flow. While the geodesic-acoustic-mode oscillations in quasiaxisymmetric configurations are similar to tokamaks, they become non-existent in quasi-helically symmetric configurations when the effective safety factor in helical-angle coordinates is small. Compared with concentric-circular tokamaks, the Rosenbluth–Hinton residual is also found to be multiplied by a geometric factor $\mathcal {C}$ that arises from the flux-surface-averaged classical polarization. Using the near-axis-expansion framework, we derive an analytic expression for $\mathcal {C}$ , which varies significantly among different configurations. These analytic results are compared with numerical simulation results from the global gyrokinetic particle-in-cell code GTC, and good agreement with the theoretical Rosenbluth–Hinton residual level is achieved when the quasisymmetry error is small enough.

Zhu, Hongxuan (ORCID:0000000198446972)↗

DOE OSTI2021

Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking

As distributed energy resources (DERs) play an increasing role in generation and grid services, control and market paradigms will need to be tested with models that incorporate transmission and distribution systems. The test systems will need to be realistic and accessible for researchers to form conclusions about realistic behaviors and maintain comparability and repeatability of results. These test systems also must have high resolution models of sufficient size for realistic distribution and transmission interaction. This paper demonstrates the tightly coupled HELICS-based co-simulation of realistic synthetic distribution and transmission models for the Austin metropolitan area and how this framework can be used to analyze resultant behaviors from distributed resources and their controls. These results are compared to the same distribution system run without co-simulation using a fixed feed-in voltage. Results show that even without advanced voltage controls, the feed-in voltage response when coupled to the transmission system results a lower level of voltage excursions, suggesting the importance of using this type of realistic, tightly coupled, transmission and distribution cosimulation when assessing DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2021

Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2026

Autoencoder-Based Sensor Drift Detection and Mitigation for Resilient Charging Systems

This work presents an autoencoder-based approach for sensor signal reconstruction and drift detection for charging systems. The proposed strategy is implemented within a Simulink-based system framework and evaluated under multiple operating conditions. An autoencoder with 8 neurons in the bottleneck layer is adopted, achieving accurate reconstruction across 10 variables and strong agreement with the physical sensor readings under normal conditions. In the case of a sensor fault, the autoencoder reconstruction remains closer to the expected true value compared to the corrupted measurement. Furthermore, feeding the autoencoder-reconstructed signal value back into the control framework in place of the faulty sensor signal leads to improved power monitoring. These results highlight the potential of autoencoder-based virtual sensing to extend the concept of resiliency to all components of the charging system, including sensors.

Rezende Da Costa Reis Kimpara, Renata [ORNL] (ORCI↗