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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

High-resolution climate model datasets for energy infrastructure planning in a renewable-dependent future

Electrification and renewables deployment efforts are amplifying the interdependence of the climate and energy systems. Increases in climate model resolution, which is now approaching that of reanalysis datasets and operational weather forecast models, present a unique opportunity to use future climate projections for energy infrastructure planning. In this Perspective, we review recent developments in high-resolution climate modeling, which have been driven by increased computing power and advanced software tools. We then look ahead to discuss how high-resolution climate data can be used to plan for a renewable-dependent future, and envision a unified climate-energy model framework that captures the two-way feedbacks between these interdependent systems.

climate change↗

Non-linear MHD modelling of transients in tokamaks: a review of recent advances with the JOREK code

Transient magneto-hydrodynamic (MHD) events like edge localized modes (ELMs) or disruptions are a concern for magnetic confinement fusion power plants. Research with the MHD code JOREK towards understanding control of such instabilities is reviewed here in a concise way to provide a complete overview, while we refer to the original publications for details. Experimental validation for unmitigated vertical displacement events progressed. The mechanism of vertical force mitigation by impurity injection was identified. Two-way eddy current coupling to CARIDDI was completed. Shattered pellet injection was simulated in JET, KSTAR, ASDEX Upgrade (AUG) and ITER. Benign runaway electron beam termination in JET and ITER was studied. Coupling of kinetic REs to the MHD is ongoing and a virtual RE synchrotron radiation diagnostic was developed. Regarding pedestal physics, regimes devoid of large ELMs in AUG were simulated and predictive JT60-SA simulations are ongoing. For ELM suppression by resonant magnetic perturbations (RMPs), AUG, ITER and EAST simulations were performed. A free boundary RMP model was validated against experiments. Evidence for penetrated magnetic islands at the pedestal top based on AUG experiments and simulations was found. Simulations of the naturally ELM-free quiescent H-mode in AUG and HL-3 show external kink mode formation prevents pedestal build-up towards an ELM within windows of the edge safety factor. With kinetic neutral particles, high field side high density formation in ITER was simulated and with kinetic impurities, tungsten transport in AUG RMP plasmas was studied. To capture turbulent transport, electro-static full-f particle in cell models for ion temperature gradient and trapped electron modes were established and benchmarked. Application to RMP plasmas shows enhanced turbulence in comparison to unperturbed states. Energetic particle interactions with MHD were studied. Flux pumping that prevents the safety factor on axis from dropping below unity was simulated. First non-linear stellarator applications include current relaxation in $l$ = 2 stellarators, while verification for advanced stellarators progresses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Saturation of fishbone instability through zonal flows driven by energetic particle transport in tokamak plasmas

Gyrokinetic and kinetic-MHD simulations are performed for the fishbone instability in the DIII-D discharge #178631, chosen for validation of first-principles simulations to predict the energetic particle (EP) transport in an ITER prefusion baseline scenario. Fishbone modes are found to generate zonal flows, which dominate the fishbone saturation. The underlying mechanisms of the two-way fishbone-zonal flows nonlinear interplay are discussed in details. Numerical and analytical analyses identify the fishbone-induced EP redistribution as the dominant generation mechanism for zonal flows. The zonal flows modify the nonlinear dynamics of phase space zonal structures, which reduces the amount of EPs able to resonate with the mode, leading to an early fishbone saturation. Simulation results including zonal flows agree quantitatively with DIII-D experimental measurements of the fishbone saturation amplitude and EP transport, supporting this novel saturation mechanism by self- generated zonal flows. Moreover, the wave-particle mode-locking mechanism is shown to determine quantitatively the fishbone frequency down-chirping, as evident in GTC simulation results in agreement with predictions from analytical theory. Finally, the
fishbone-induced zonal flows are possibly responsible for the formation of an ion-ITB in the DIII-D discharge. Based on the low EP transport and the large zonal flow shearing rates associated with the fishbone instability in gyrokinetic simulations of the ITER scenario, it is conjectured that high performance scenarios could be designed in ITER burning plasmas through fishbone-induced ITBs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Implications of climate change impacts for emission and land use scenario development

Scenarios of future emissions and land use produced by integrated assessment models have traditionally been developed without accounting for how climate change impacts could affect the emissions and land use trajectories themselves. This omission risks skewing our assessments of the plausible range of future emission pathways and associated Earth system changes. Beyond the salience for emission scenario development, a better integrated representation of human and Earth system changes and feedbacks would enable better anticipation of the implications of alternative socio-economic development pathways. We use the Global Change Analysis Model to investigate whether endogenizing several impacts when generating its baseline emission scenario is warranted. We do so by comparing the emissions and land use change that result from the baseline scenario with and without impacts, where impacts are implemented as exogenous changes to water availability, crop and labor productivity, and energy demand and supply. Our results indicate that the effect on global emissions leads to less than 0.1 °C increase in warming by 2100 and therefore do not support endogenizing impacts. This conclusion is conditional on our modeling framework and the specific impact channels represented but is consistent with other studies that have addressed the magnitude of feedbacks by implementing a two-way coupling. However, we do find regional impacts indicating that local economies and well-being measures may be affected significantly.

climate impacts↗

Stabilizing Non-Abelian Topological Order Against Heralded Noise via Local Lindbladian Dynamics

An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady states under local quantum dynamics. In this work, we show how robust steady-state phases with both Abelian and non-Abelian mixed-state topological order can be stabilized, in two spatial dimensions, against generic “heralded” noise using active dynamics that incorporate measurement and feedback, modeled as a fully local Lindblad master equation. These topologically ordered steady states are two-way connected to pure topologically ordered ground states using local quantum channels, and preserve quantum information for a time that is exponentially large in the system size. Specifically, we present explicit constructions of families of local Lindbladians for both Abelian (ℤ 2 ) and non-Abelian (𝐷 4 ) topological order whose steady states host mixed-state topological order when the noise is below a threshold strength. As the noise strength is increased, these models exhibit first-order transitions to intermediate mixed-state phases where they encode robust classical memories, followed by (first-order) transitions to a trivial steady state at high noise rates. When the noise is imperfectly heralded, steady-state order disappears but our active dynamics significantly enhances the lifetime of the encoded logical information. To carry out the numerical simulations for the non-Abelian 𝐷 4 case, we introduce a generalized stabilizer tableau formalism that permits efficient simulation of the non-Abelian Lindbladian dynamics.

Monte Carlo methods↗

Error-Free and Current-Driven Synthetic Antiferromagnetic Domain Wall Memory Enabled by Channel Meandering

We propose a new type of energy-efficient multi-bit magnetic memory based on current-driven, field-free, controlled domain wall motion. A meandering domain wall channel with precisely interspersed pinning regions provides the multi-bit capability of a magnetic tunnel junction memory. The magnetic free layer of the memory device has perpendicular magnetic anisotropy (PMA) and interfacial Dzyaloshinskii-Moriya interaction (DMI) so that spin-orbit torques (SOTs) induce efficient domain wall motion. Using micromagnetic simulations, we find two different cell designs: two-way switching and four-way switching. The memory cell design choices and the physics of pinning mechanisms are discussed in detail. Furthermore, we show that switching reliability and speed may be significantly improved by replacing the ferromagnetic free layer with a synthetic antiferromagnetic (SAF) layer. Switching behavior and material choices will be discussed for the two memory implementations.

magnetic domain wall↗

mDNS to support local price server discovery with OpenADR 3 (mDNS for OpenADR 3) v1.0

This software contains a template VEN with local VTN service discovery over mDNS. It provides common starter code for an OpenADR3.0 VEN that advertises itself over mDNS, conducts local VTN service discovery over mDNS, connects to the VTN over HTTP(S), and regularly polls and acts on energy prices and events hosted on the VTN. The software is written to be easily modified to accommodate different VEN appliances, VEN-VTN networking protocols, user interfaces, and default responses, given the wide range of possible use cases for local price server discovery. OpenADR3.0 is an open communications standard from the OpenADR Alliance that is designed to provide two-way information exchange regarding e.g., dynamic price and event signals to utility applications, so that customers can modify their energy usage to save money and reduce their carbon footprint.

Nordman, Bruce [Lawrence Berkeley National Laborat↗

The Strength of Coupling to the Southern Ocean Modulates Tropical Eastern Pacific Variability and Forced Response

Despite rising global-mean temperatures, large parts of the Southern Ocean and tropical eastern Pacific Ocean have cooled during the satellite era. These regions may be linked by teleconnections, with Southern Ocean cooling contributing to tropical eastern Pacific cooling. We demonstrate that, on average, state-of-the-art Earth system models (ESMs) underestimate the magnitude of interaction between the Southern Ocean and tropical eastern Pacific Ocean. The strength of the teleconnection is shown to be mediated by the magnitude of the positive cloud–sea surface temperature (SST) feedback in the subtropical eastern Pacific Ocean and the strength of the wind–evaporation–SST (WES) feedback. We link excessive precipitation in the tropical Pacific south of the equator to the strength of the Southern Ocean–eastern Pacific teleconnection. This model bias, known as the double intertropical convergence zone (ITCZ), is shown to be related to erroneous convection south of the equator, weakened cross-equatorial trade winds, and unfavorable meteorological conditions for marine boundary layer subtropical clouds. We postulate there is a two-way interaction, in which a double-ITCZ occurs with weaker cloud–SST and WES feedbacks, which in turn impact local SSTs and amplify the double-ITCZ. Models with a stronger Southern Ocean to tropical Pacific teleconnection tend to exhibit more multidecadal variability in the Walker circulation, ITCZ, and west–east equatorial SST gradient, as well as greater delayed warming in the tropical eastern Pacific Ocean resulting from delayed Southern Ocean warming under greenhouse gas forcing. These results provide insight into why ESMs struggle to replicate observed tropical Pacific temperature trend patterns and point to ITCZ location as a key target for improvement in future model development.

Climate change↗

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

Planning and Operations in Electricity Markets Under System Transformation

United States electricity markets, planning mechanisms, and operational procedures are currently evolving in concert with three key trends. First, a range of new resources—solar, wind, energy storage, hybrid co-located storage, and distributed energy—are coming online and require new solutions to ensure they are efficiently integrated into existing systems. Second, consumers now face more opportunities to participate in markets by providing demand response and engaging in two-way interactions with the grid. Third, there is an increasing need for enhanced coordination between generation and transmission planning as well as across transmission and distribution systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Characterizing Land-Atmosphere Interactions During the Afternoon-to-Evening Transition Using ARM SGP Observations

The land-atmosphere (LA) system consists of the soil, vegetation, and lowest layer of the atmosphere. The energy and water transport processes in this system contribute to the structure and the daily cycle of the atmospheric boundary layer (ABL), which is the layer between the land surface and the free troposphere that controls the exchange of momentum, energy, and water. The state of the ABL is the result of complex two-way interactions between local processes such as surface fluxes and entrainment at the ABL top as well as large-scale and mesoscale processes such as advection and subsidence.

54 ENVIRONMENTAL SCIENCES↗

Grid Resiliency with a 100% Renewable Microgrid

San Diego Gas & Electric Company (SDG&E) installed America’s first and largest utility-scale microgrid in Borrego Springs in 2013. The first generation Borrego Springs Microgrid utilized diesel generators to form and stabilize the microgrid island, with support from grid-scale batteries and local solar photovoltaic (PV) generation. In this project, SDG&E in partnership with National Renewable Energy Laboratory (NREL) demonstrated through modeling, simulation and utility field testing that blackstart and islanding of the microgrid can be led with 100% renewable, inverter based resources (IBRs), to help reduce community reliance on conventional generation resources. Through equipment upgrades, grid-forming island leader capability was transitioned to a battery IBR instead of the Borrego Springs Microgrid diesel generators. A new microgrid controller was integrated to the microgrid and programmed to control and manage multiple energy storage systems. Synchrophasor and other power quality data verified autonomous, high-speed response of the IBRs through blackstart, islanding, and load step testing. Results of project field evaluations provide distribution systems operators (DSO) with increased confidence that renewable, IBR can replace traditional generators to blackstart and island microgrids and rapidly establish stable island frequency with rapid changes in peak power demand. Importantly, the project validated the integration feasibility of a distributed energy resource management system (DERMS) controller that manages multiple grid-forming and grid-following IBRs, establishing a standard design interface to reduce the complexity of integrating new DERs in the future and supporting replication by the industry. As a result of learnings in this project, SDG&E has implemented the microgrid controller strategy at multiple other microgrid sites, thereby validating the replicability of the solution. Hardware-in-the-loop (HIL) simulations including power and controller HIL hardware — along with electromagnetic transient (EMT) simulations of Borrego Springs Microgrid —informed adjustments to inverter parameters and were important to characterize the performance of the IBRs in relevant operating conditions before deployment. The EMT and HIL simulations of islanding the entire community are important contributions in providing confidence in IBR performance prior to future islanding of the community in the field. High-fidelity EMT and/or HIL simulation of IBRs can de-risk field operations, and its relevance and importance as a tool is increasing as distribution grids and microgrids become more complex and dynamic with an increasing proportion of renewable generation, distributed energy storage, and two-way power and energy flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Replace Human Intelligence with Fast and Smart Geometric Reasoning and Graph Neural Network to Accelerate Next Gen ModSim Workflows

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

97 MATHEMATICS AND COMPUTING↗

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

42 ENGINEERING↗

Interactions of a Microdischarge with a Premixed Flame (Final Technical Report)

In this project we introduced an experimental platform that facilitates the study of the two-way interaction of plasma and flame, and the exploration of the impact of the spatial location of the discharge on its kinetics, in a controlled environment. The experimental platform is a mesoscale CH4/air premixed flame burner that also acts as a dielectric barrier discharge (DBD) operated by nanosecond pulsed voltage. A unique feature of this setup is that the DBD utilizes transparent electrodes, made of Indium Tin Oxide (ITO), to unlock optical access along the line-of-sight parallel to the dominant electric field. This platform is suitable to study both the forward problem (impact of plasma-on-flame), which manifests itself as a modified flame speed as well as flame wrinkling; and the backward problem (impact of flame-on-plasma), which includes plasma regime transitions, between microdischarges and uniform modes, driven by the flame passage. Prior work at MIT has focused on electrical measurements and direct imaging studies of the plasma-flame interaction through the ITO electrode. This project, which was awarded experimental runtime at the Low-temperature Plasma Research Facility (PRF) at Sandia National Laboratories, quantifies the flame-plasma interaction through temporally resolved measurement of key radicals (oxygen atom, O) produced by the nanosecond repetitively pused discharge (NRPD) in an individual microdischarge, using two-photon absorption laser-induced fluorescence (TALIF).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Integration of Online Cross-Section Generation Capability with Depletion and Transient Solvers in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE)-based reactor multiphysics analysis application jointly developed by Argonne and Idaho National Laboratories under the DOENE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In FY25, an online crosssection generation capability based on the Self-Shielding Application Programming Interface (SSAPI) was demonstrated for TRISO-fueled reactor problems under steady-state conditions. This fiscal year, that capability was extended to support depletion and transient multiphysics calculations, enabling high-fidelity analyses that generate self-shielded cross sections on the fly from the actual evolving composition and temperature states rather than from pre-tabulated libraries. For depletion, a two-way coupling was established in which SSAPI computes compact-averaged self-shielded cross sections that the depletion solver then uses to advance the Bateman equations, with the updated compositions returned to SSAPI at each step; the depletion module was refactored to support both library-based and SSAPI-based cross sections, and additional logic was added to track daughter isotopes and to exclude minor isotopes for efficiency. For transient analysis, the SSAPI multigroup library was extended with the kinetics data required for time-dependent calculations, the Improved Quasi-Static (IQS) scheme was coupled with SSAPI, and several supporting capabilities were implemented, including a self-shielding treatment that lets control rods and drums move within a self-shielded model, which had previously been impossible and had ruled out rod- and drum-movement transients with on-the-fly cross sections altogether, a new mixing scheme for delayed-neutron precursor decay constants, a checkpoint-based restart workflow, and performance improvements such as pointwise cross-section interpolation and the bypassing of unnecessary Dancoff factor calculations. The implemented capabilities were verified against Serpent Monte Carlo solutions. For depletion, a prismatic pin-cell problem based on a Next Generation Nuclear Plant (NGNP) Very High Temperature Reactor benchmark showed excellent agreement, with eigenvalue differences within 200 pcm over the entire burnup range (up to 140 MWD/kgU) and fission-product and actinide inventories agreeing to within 0.8% and 2.5%, respectively; a heat-pipe microreactor assembly problem with a much higher fuel loading confirmed the same behavior and quantified the bias introduced when the multigroup equivalence effect is neglected. For transient analysis, a pin-cell problem with a step reactivity insertion and temperature feedback reproduced the analytically expected asymptotic power and showed close agreement between the direct and IQS solutions, and a two-dimensional microreactor core problem with control-drum rotation exercised the new moving-drum self-shielding treatment and demonstrated successful coupling of the online crosssection generation with both the direct and IQS transient methods. The capability was further exercised on a full-core pebble-bed problem, in which Griffin was coupled with the System Analysis Module (SAM) to simulate load-following operation of the gPBR with the Doppler feedback resolved at the TRISO fuel kernel temperature. These developments in Griffin provide a convenient, high-fidelity approach to cross-section generation for advanced thermal reactors with geometrically complex and highly heterogeneous configurations, including TRISO-fueled prismatic and pebble-bed systems, and support steady-state, depletion, and transient multiphysics calculations. They also enable self-shielded cross sections to be evaluated directly at the actual coupled state of the system, thereby establishing a foundation for high-fidelity, fully coupled multiphysics analysis of advanced reactors

Park, H.↗

Numerical simulations of liquid jetting with solid inclusions

The dynamics of finite-sized particles in fluids, and their influence on the overall flow, are of great interest across several industrial, environmental, and medical fields. In the context of inkjet printing, the presence of solid inclusions can be either intentional, as in additive manufacturing, or unintentional, as in standard printing processes. These inclusions can strongly impact the jetting process, causing effects such as jet asymmetry, bubble entrapment, and the formation of satellite droplets. Understanding and controlling particle behavior is therefore essential, particularly to predict how and when particles are ejected over multiple jetting cycles. It is therefore critical to develop reliable models that allow for a deeper understanding of the complex interplay between particle and fluid during the whole printing process. To address this, we present a tailored implementation of the Color-Gradient multicomponent Lattice Boltzmann Method for fully resolved three-dimensional (3D) simulations of multicycle liquid jetting with particles. Our method supports realistic parameter settings aligned with industrial inkjet systems, and we provide both qualitative and quantitative validation against experimental data. Additionally, we introduce a simplified model based on the Stokes drag law, in which solid particles are represented as point particles and do not influence the fluid flow. Despite this limitation, the model offers a computationally efficient means to explore the vast parameter space typically encountered in industrial applications, allowing, e.g., identifying critical ejection regions and estimating the number of cycles required for particle release. These qualitative insights are valuable for guiding and complement fully two-way coupled simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Leveraging Optimal Sparse Sensor Placement to Aggregate a Network of Digital Twins for Nuclear Subsystems

Nuclear power plants (NPPs) require continuous monitoring of various systems, structures, and components to ensure safe and efficient operations. The critical safety testing of new fuel compositions and the analysis of the effects of power transients on core temperatures can be achieved through modeling and simulations. They capture the dynamics of the physical phenomenon associated with failure modes and facilitate the creation of digital twins (DTs). Accurate reconstruction of fields of interest (e.g., temperature, pressure, velocity) from sensor measurements is crucial to establish a two-way communication between physical experiments and models. Sensor placement is highly constrained in most nuclear subsystems due to challenging operating conditions and inherent spatial limitations. This study develops optimized data-driven sensor placements for full-field reconstruction within reactor and steam generator subsystems of NPPs. Optimized constrained sensors reconstruct field of interest within a tri-structural isotropic (TRISO) fuel irradiation experiment, a lumped parameter model of a nuclear fuel test rod and a steam generator. The optimization procedure leverages reduced-order models of flow physics to provide a highly accurate full-field reconstruction of responses of interest, noise-induced uncertainty quantification and physically feasible sensor locations. Accurate sensor-based reconstructions establish a foundation for the digital twinning of subsystems, culminating in a comprehensive DT aggregate of an NPP.

42 ENGINEERING↗