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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamics in Flexible Pillar[ n ]arenes Probed by Solid-State NMR

Pillar[n]arenes are supramolecular assemblies that can perform a range of technologically important molecular separations which are enabled by their molecular flexibility. Here, we probe dynamical behavior by performing a range of variable-temperature solid-state NMR experiments on microcrystalline perethylated pillar[n]arene (n = 5, 6) and the corresponding three pillar[6]arene xylene adducts in the 100–350 K range. This was achieved either by measuring site-selective motional averaged 13 C 1 H heteronuclear dipolar couplings and subsequently accessing order parameters or by determining 1 H and 13 C spin–lattice relaxation times and extracting correlation times based on dipolar and/or chemical shift anisotropy relaxation mechanisms. We demonstrate fast motional regimes at room temperature and highlight a significant difference in dynamics between the core of the pillar[n]arenes, the protruding flexible ethoxy groups, and the adsorbed xylene guest. Additionally, unexpected and sizable 13 C 1 H heteronuclear dipolar couplings for a quaternary carbon were observed for p-xylene adsorbed in pillar[6]arene only, indicating a strong host–guest interaction and establishing the p-xylene location inside the host, confirming structural refinements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine Learning of Key Variables Impacting Extreme Precipitation in Various Regions of the Contiguous United States

Abstract Amplification in extreme precipitation intensity and frequency can cause severe flooding and impose significant social and economic consequences. Variations in extreme precipitation intensity, frequencies, and return periods can be attributed to many physical variables across spatial and temporal scales. Here we employ ensemble machine learning (ML) methods, namely random forest (RF), eXtreme Gradient Boosting (XGB), and artificial neural networks (ANN), to explore key contributing variables to monthly extreme precipitation intensity and frequency in six regions over the United States. We further establish emulators for return periods. Results show that the ML models for intensity perform better in regions with obvious seasonality (i.e., Northern Great Plains, Southern Great Plains, and West Coast) than the other three regions (Northeast, Southwest, and Rocky Mountains), while for frequency the models perform well for most regions. The Shapley additive explanation is used to help explain the relationships between extreme precipitation characteristics and identify top variables for RF and XGB. We find that latent heat flux, relative humidity, soil moisture, and large‐scale subsidence are key common variables across the regions for both monthly intensity and frequency, and their compound effects are non‐negligible. The developed ML models capture the probability and return period of extreme precipitation well for all regions and may be used for decision making (e.g., infrastructure planning and design).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons

The formation of oscillating phase clusters in a network of identical Hodgkin–Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition—through (possibly perturbed) period-doubling and subsequent bifurcations—to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar “fine” states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron’s “identity” (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established “identity-state” correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence

Here, we synthesize available literature, data, and analysis on the degree to which growth in variable renewable energy (VRE) has impacted or might in the future impact bulk power system assets, pricing, and costs in the United States. Most studies of future scenarios indicate that VRE reduces wholesale energy prices and capacity factors of thermal generators. Traditional baseload generators are more exposed to these changing market conditions than low-capital cost and more flexible intermediate and peak-load generators. From analysis of historical data we find that VRE is already influencing the bulk power market through changes in temporal and geographic patterns areas with higher levels of VRE. The most significant observed impacts have concentrated in areas with significant VRE and/or nuclear generation along with limited transmission, with negative pricing also often occurring during periods with lower system-wide load. So far, however, VRE, has had a relatively modest impact on historical average annual wholesale prices across entire market regions, at least in comparison to other drivers. The reduction of natural gas prices is the primary contributor to the decline in wholesale prices since 2008. Similarly, VRE impacts on thermal plant retirements have been limited and there is little relationship between the location of recent retirements and VRE penetration levels. Finally, although impacts on wholesale prices have been modest so far, impacts of VRE on the electricity market will be more significant under higher VRE penetrations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale

A strict throughput requirement has placed a cap on the degree to which we can depend on the execution of single, long, fine spatial grid simulations to explore global atmospheric climate behavior. Alternatively, running an ensemble of short simulations is computationally more efficient. We test the null hypothesis that the climate statistics of a full-complexity atmospheric model derived from an ensemble of independent short simulation is equivalent to that from an equilibrated long simulation. The climate of short simulation ensembles is statistically distinguishable from that of a long simulation in terms of the distribution of global annual means, largely due to the presence of low-frequency atmospheric intrinsic variability in the long simulation. We also find that model climate statistics of the simulation ensemble are sensitive to the choice of compiler optimizations. While some answer-changing optimization choices do not effect the climate state in terms of mean, variability and extremes, aggressive optimizations can result in significantly different climate states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.

Stander, Nielen↗
DOE OSTI2024

Evaluation of a practical approach for field scale moisture flow modeling in heterogeneous media at a semiarid site

Abstract A practical approach for modeling field‐scale moisture flow in a highly heterogeneous unsaturated medium is described in this study. The validity of this approach is demonstrated through comparison of the numerical simulations with field observations at a semiarid site located in southcentral Washington State. The methodology is based on upscaling the core scale hydraulic properties and combining power‐law and tensorial connectivity‐tortuosity (PA‐TCT) approaches to derive macroscopic anisotropy parameters for each hydrostratigraphic unit (HSU) identified in the field. Each heterogeneous HSU is approximated by an equivalent homogeneous medium (EHM) model for which PA‐TCT parameters are used in the flow simulations. The available field data on moisture content and matric potential are compared with steady‐state flow simulations based on the mean form of Richards' equation. While the homogenization or averaging of heterogeneities, embedded in the EHM modeling approximation, cannot capture all of the field‐scale variability, the simulated steady‐state moisture and matric potential profiles capture well the central tendency of the field data. This approach is deemed practical for assessing the fate and transport of contaminants in highly heterogeneous unsaturated media at the transport scale of hundreds of meters.

Khaleel, Raziuddin↗
DOE OSTI2023

Raccoon spatial ecology in the rural southeastern United States

The movement ecology of raccoons varies widely across habitats with important implications for the management of zoonotic diseases such as rabies. However, the spatial ecology of raccoons remains poorly understood in many regions of the United States, particularly in the southeast. To better understand the spatial ecology of raccoons in the southeastern US, we investigated the role of sex, season, and habitat on monthly raccoon home range and core area sizes in three common rural habitats (bottomland hardwood, upland pine, and riparian forest) in South Carolina, USA. From 2018–2022, we obtained 264 monthly home ranges from 46 raccoons. Mean monthly 95% utilization distribution (UD) sizes ranged from 1.05 ± 0.48 km 2 (breeding bottomland females) to 5.69 ± 3.37 km 2 (fall riparian males) and mean monthly 60% UD sizes ranged from 0.25 ± 0.15 km 2 (breeding bottomland females) to 1.59 ± 1.02 km 2 (summer riparian males). Males maintained home range and core areas ~2–5 times larger than females in upland pine and riparian habitat throughout the year, whereas those of bottomland males were only larger than females during the breeding season. Home ranges and core areas of females did not vary across habitats, whereas male raccoons had home ranges and core areas ~2–3 times larger in upland pine and riparian compared to bottomland hardwood throughout much of the year. The home ranges of males in upland pine and riparian are among the largest recorded for raccoons in the United States. Such large and variable home ranges likely contribute to elevated risk of zoonotic disease spread by males in these habitats. These results can be used to inform disease mitigation strategies in the southeastern United States.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Probing the Accretion Disk and Central Engine Structure of the NGC 4258 with Suzaku and XMM-Newton Observations

We present an X-ray study of the low-luminosity active galactic nucleus (AGN) in NGC 4258 using data from Suzaku, XMM-Newton, and the Swift/Burst Alert Telescope survey. We find that signatures of X-ray reprocessing by cold gas are very weak in the spectrum of this Seyfert-2 galaxy; a weak, narrow fluorescent K(alpha) emission line of cod iron is robustly detected in both the Suzaku and XMM-Newton spectra but at a level much below that of most other Seyfert-2 galaxies. We conclude that the circumnuclear environment of this AGN is very "clean" and lacks the Compton-thick obscuring torus of unified Seyfert schemes. From the narrowness of the iron line, together with evidence of line flux variability between the Suzaku and XMM-Newton observations, we constrain the line emitting region to be between 3 x 10(exp 3)r(sub g) and 4 x 10(exp 4)r(sub g), from the black hole. We show that the observed properties of the iron line can be explained if the line originates from the surface layers of a warped accretion disk. In particular, we present explicit calculations of the expected iron line from a disk warped by Lens-Thirring precession from a misaligned central black hole. Finally, the Suzaku data reveal clear evidence of large amplitude 2-10 keV variability on timescales of 50 ksec and smaller amplitude flares on timescales as short as 5-10 ksec. If associated with accretion disk processes, such rapid variability requires an origin in the innermost regions of the disk (r approx. equals 10(r(sub g) or less). Analysis of the difference spectrum between a high- and low-flux states suggests that the variable component of the X-ray emission is steeper and more absorbed than the average AGN emission, suggesting that the primary X-ray source and absorbing screen have a spatial structure on comparable scales. We note the remarkable similarity between the circumnuclear environment of NGC 4258 and another well studied low-luminosity AGN, M81*.

Reynolds, Christopher S.↗
DOE OSTI2024

Timeseries Unlabeled and Labeled Photos, Modeled Stream Elevation, and (Meta)Data of Variably Inundated Streams Across The Yakima River Basin, Washington, United States (v2)

This dataset is associated with the “River Monitoring Photos” (RMP) study and subsequent manuscript (Bao et al. 2025. Monitoring river flow status using low-cost wildlife camera and image segmentation artificial intelligence doi: 10.1016/j.envsoft.2025.106715). Game camera timeseries photos were collected to evaluate stream variable inundation via changes in width. A subset of photos was labeled for training the YOLOv8 and Mask2Former models and used to segment water surface fractions from all the game camera photos.This data package was originally published in March 2024. It was updated in October 2025 (v2) to add additional photos and files associated with the manuscript (i.e., processed data, labeled photos, and trained models). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to a readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; and (5) folders containing game camera photos and manuscript-associated files. Each Yakima River Basin site has a folder that contains subfolders for each month photos were collected. There is also a folder for files associated with the manuscript which has subfolders for labeled data, trained models, Yakima River Basin site water surface fractions, and USGS site water surface fractions. All files are .csv, .json, .txt, .yaml, .pth, .pt, or .pdf. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Critical temperature of metallic hydrogen sulfide at 225-GPa pressure

The Eliashberg theory generalized for electron—phonon systems with a nonconstant density of electron states and with allowance made for the frequency behavior of the electron mass and chemical potential renormalizations is used to study T{sub c} in the SH{sub 3} phase of hydrogen sulfide under pressure. The phonon contribution to the anomalous electron Green’s function is considered. The pairing within the total width of the electron band and not only in a narrow layer near the Fermi surface is taken into account. The frequency and temperature dependences of the complex mass renormalization ReZ(ω), the density of states N(ε) renormalized by the electron—phonon interactions, and the electron—phonon spectral function obtained computationally are used to calculate the anomalous electron Green’s function. A generalized Eliashberg equation with a variable density of electron states has been solved. The frequency dependence of the real and imaginary parts of the order parameter in the SH{sub 3} phase has been obtained. The value of T{sub c} ≈ 177 K in the SH{sub 3} phase of hydrogen sulfide at pressure P = 225 GPa has been determined by solving the system of Eliashberg equations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

A Multiwavelength Study of Flaring Activity in the High-energy Peaked BL Lac Object 1ES 1959+650 During 2015–2016

We present the results from a multiwavelength study of the flaring activity in the high-energy peaked BL Lac object 1ES 1959+650 during 2015 January–2016 June. The source underwent two major outbursts, during 2015 March and 2015 October, across the whole electromagnetic spectrum (EMS). We used data from Fermi -LAT and Swift -XRT/UVOT, and optical data from Mt. Abu InfraRed Observatory and Steward Observatory to look for possible correlations between the emissions at different energies and the nature of the variability during the flaring state. During the 2015 October outburst, the nightly averaged V -band brightest magnitude, 14.45(0.03), and faintest magnitude, 14.45(0.03), were recorded. Apart from long-term flares, rapid and short-term variabilities were noticed at all energies. Our study suggests that the flaring activities at all frequencies, with diverse flare durations and time lags, are correlated. The magnetic field strength is estimated to be 4 G using the synchrotron-cooling timescale (2.3 hr), and the upper limits on the sizes of both emission regions, γ -ray and optical, are estimated to be of the order of 10{sup 16} cm. The quasi-simultaneous flux enhancements in 15 GHz and VHE γ -ray emissions indicate a fresh injection of plasma into the jet, which interacts with a standing submillimeter core, resulting in co-spatial emissions across the EMS. The synchrotron peak shifts to higher frequency in the spectral energy distribution while the γ -ray spectra softens during the flaring. The shape of the inverse-Compton spectra indicates a change in the particle energy distribution pre- and post-flare.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Characterization of Electronic Stress-Induced Changes in Multilayer MoS 2

Transition metal dichalcogenides like molybdenum disulfide (MoS 2 ) are compelling for next-generation electronic devices. In this work, we investigate the impact of electronic stress on MoS 2 to illustrate that observational and phenomenological information on multiple devices can be useful to describe changes in the device, and caution against the rationalization of paltry results as representative or correlative to device behavior. Here, we stress MoS 2 by applying a sustained 20 V DC bias to study the material’s response. Post-stress electronic characterization revealed nonuniform shifts in current–voltage (I–V) behavior alongside microscale changes. Complementary mechanical, spectroscopic, and scanning microwave impedance measurements showed that stress-induced features locally modulate stiffness, surface potential, Raman intensity, and charge carrier density. We correlated I–V behavior with morphological features (wrinkles, tears, folds, height) and device-level geometry (MoS 2 overlap with electrodes, channel area, contact length) on 50 test structures across five chips to move beyond anecdotal conclusions. We found no universal correlations before DC stress. However, device-level geometry was correlated with I–V behavior after DC stress, suggesting that electrode contacts play a more dominant role than morphology in determining performance. Delamination and thinning induced by DC stress led to localized reductions in charge carrier density within the affected regions. Further, delamination and thinning appear to map to I–V device performance in a few samples, but the correlation is lost when a larger sample size is considered. This suggests significant sample-to-sample variability in surface electronic states of the test structures. We also discuss how environmental factors introduced during fabrication may contribute to the observed heterogeneous device response. Progress will require high-resolution, multimodal analysis across many samples constructed under controlled, clean conditions. By building data sets that capture variability, we can better identify the true drivers of performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theoretical Kinetics Predictions for Reactions on the NH 2 O Potential Energy Surface

Recent modeling studies of ammonia oxidation, which are motivated by the prospective role of ammonia as a zero-carbon fuel, have indicated significant discrepancies among the existing literature mechanisms. In this study, high-level theoretical kinetics predictions have been obtained for reactions on the NH 2 O potential energy surface, including the NH 2 + O, HNO + H, and NH + OH reactions. These reactions have previously been highlighted as important reactions in NH 3 oxidation with high sensitivity and high uncertainty. The potential energy surface is explored with coupled cluster calculations, including large basis sets and high-level corrections to yield high-accuracy (~0.2 kcal/mol 2σ uncertainty) estimates of the stationary point energies. Variational transition state theory is used to predict the microcanonical rate constants, which are then incorporated in master equation treatments of the temperature- and pressure-dependent kinetics. For radical–radical channels, the microcanonical rates are obtained from variable reaction coordinate transition state theory implementing directly evaluated multireference electronic energies. The analysis yields predictions for the total rate constants as well as the branching ratios. We find that the NO + H 2 channel contributes 10% of the total NH 2 + O flux at combustion temperatures, although this channel is not included in modern NH 3 oxidation mechanisms. Modeling is used to illustrate the ramifications of these rate predictions on the kinetics of NH 3 oxidation and NO x formation. Finally, the present results for NH 2 + O are important for predicting the chain branching and formation of NO in the oxidation of NH 3 and thermal DeNO x .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Excited State Specific Multi-Slater Jastrow Wave Functions

We combine recent advances in excited state variational principles, fast multi-Slater Jastrow methods and selective configuration interaction, to create multi-Slater Jastrow wave function approximations that are optimized for individual excited states. In addition to the Jastrow variables and linear expansion coefficients, this optimization includes state-specific orbital relaxations in order to avoid the compromises necessary in state-averaged approaches. Here, we demonstrate that, when combined with variance matching to help balance the quality of the approximation across different states, this approach delivers accurate excitation energies even when very modest multi-Slater expansions are used. Intriguingly, this accuracy is maintained even when we study a difficult chlorine-anion-to-π* charge transfer in which traditional state-averaged multireference methods must contend with different states that require drastically different orbital relaxations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Comment on “Five Decades of Observed Daily Precipitation Reveal Longer and More Variable Drought Events Across Much of the Western United States”

Abstract Changes in precipitation patterns with climate change could have important impacts on human and natural systems. Zhang et al. (2021, https://doi.org/10.1029/2020gl092293 ) report trends in daily precipitation patterns over the last five decades in the western United States, focusing on meteorological drought. They report that dry intervals (calculated at the annual or seasonal level) have increased across much of the southwestern U.S., with statistical assessment suggesting the results are statistically robust. However, Zhang et al. (2021, https://doi.org/10.1029/2020gl092293 ) preprocess their annual (or seasonal) averages to compute 5‐year moving window averages before using established statistical techniques for trend analysis that assume independence about some fixed trend. Here we show that the moving window preprocessing violates that independence assumption and inflates the statistical significance of their trend estimates. This raises questions about the robustness of their results. We conclude by discussing the difficulty of adjusting for spatial structure when assessing time trends in a regional context.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Disc tearing leads to low and high frequency quasi-periodic oscillations in a GRMHD simulation of a thin accretion disc

Black hole X-ray binaries (BHXRBs) display a wide range of variability phenomena, from long duration spectral state changes to short-term broad-band variability and quasi-periodic oscillations (QPOs). A particularly puzzling aspect is the production of QPOs, which – if properly understood – could be used as a powerful diagnostic tool of black hole accretion and evolution. In this work, we analyse a high-resolution 3D general relativistic magnetohydrodynamic simulation of a geometrically thin accretion disc, which is tilted by 65° with respect to the black hole spin axis. We find that the Lense–Thirring torque from the rapidly spinning 10 M ⊙ black hole causes several sub-discs to tear off within ~10–20 gravitational radii. Tearing occurs in cycles on time-scales of seconds. During each tearing cycle, the inner sub-disc precesses for 1–5 periods before it falls into the black hole. We find a precession frequency of ~3 Hz, consistent with observed low-frequency QPOs. In addition, we find a high frequency QPO (HFQPO) with centroid frequency of ~55 Hz in the power spectra of the mass-weighted radius of the inner disc and the radial mass flux. This signal is caused by radial epicyclic oscillations of a dense ring of gas at the tearing radius, which suggests a corresponding modulation of the X-ray light curve and may thus explain some of the observed HFQPOs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Meta-Learning Enhanced Physics-Informed Graph Attention Convolutional Network for Distribution Power System State Estimation

Promptly perceiving distribution system states is challenged by frequent topology changes and uncertain power injections. To address these issues, a Meta-learning enhanced physics-informed graph attention convolutional network (Meta-PIGACN) model is proposed to handle topological variability in distribution system state estimation (DSSE). Specifically, physics information is integrated into the graph convolutional network, enabling a physics-informed edge-weighting process that incorporates physical information to control the aggregation of neighboring nodes. Besides, the graph attention mechanism automatically adjusts the importance of different neighboring nodes, allowing the capture and preservation of inherent system features across varying topologies, thereby improving state estimation accuracy. Furthermore, meta-learning is proposed to acquire empirical knowledge across multiple topologies so that the model can rapidly adapt to new configurations through iterative gradient descent updates even in large-scale systems. In conclusion, the simulation results based on the 33/118/1746-node distribution systems show the high accuracy and efficiency of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗