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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 109 records · Page 6

Reactor transient analyses with KIN3D/PARTISN

Efforts are going on at the Karlsruhe Institute of Technology (KIT) to extend the kinetics capability of the PARTISN code in order to run in parallel two- and three-dimensional transient analyses with the quasistatic method, while taking into account delayed neutrons. In the original code version, time-dependent transport problems are solved by employing a semi-implicit direct kinetics option, the delayed neutrons being not taken into account. The PARTISN 5.97 code has been extended and then coupled with KIN3D, a time-dependent model embedded in the ERANOS code system. In the coupled code, PARTISN 5.97 is used as neutron transport solver to perform transient analyses while employing direct and quasi-static kinetics options of KIN3D. The coupled code can be also applied for first-order and exact perturbation theory calculations. In the paper, the PARTISN 5.97 extensions and coupling procedure are described and the performances of the KIN3D/PARTISN coupled code are investigated by analyzing transients induced by a source-jerk in a three-dimensional ADS model driven by an external source. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗

Finding Horndeski theories with Einstein gravity limits

The Horndeski action is the most general scalar-tensor theory with at most second-order derivatives in the equations of motion, thus evading Ostrogradsky instabilities and making it of interest when modifying gravity at large scales. To pass local tests of gravity, these modifications predominantly rely on nonlinear screening mechanisms that recover Einstein's Theory of General Relativity in regions of high density. We derive a set of conditions on the four free functions of the Horndeski action that examine whether a specific model embedded in the action possesses an Einstein gravity limit or not. For this purpose, we develop a new and surprisingly simple scaling method that identifies dominant terms in the equations of motion by considering formal limits of the couplings that enter through the new terms in the modified action. This enables us to find regimes where nonlinear terms dominate and Einstein's field equations are recovered to leading order. Together with an efficient approximation of the scalar field profile, one can then further evaluate whether these limits can be attributed to a genuine screening effect. For illustration, we apply the analysis to both a cubic galileon and a chameleon model as well as to Brans-Dicke theory. Finally, we emphasise that the scaling method also provides a natural approach for performing post-Newtonian expansions in screened regimes.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectroscopic factors in dripline nuclei

Single-nucleon knockout reaction studies of the proton-dripline nuclei 9 C and 13 O suggest an appreciable suppression of spectroscopic factors. In this work, we calculate the one-neutron and one-proton spectroscopic factors for the mirror pair 9 C – 9 Li and 13 O using two variants of the continuum shell model: the complex-energy Gamow shell model and the real-energy shell model embedded in the continuum. Furthermore, our results indicate that the continuum effects strongly suppress the spectroscopic factors of well-bound orbits in the dripline systems but have less impact on the spectroscopic factors of weakly bound states.

6 ≤ A ≤ 19↗

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗

Convergent Manufacturing of Large-Scale Components for Nuclear Applications, via Additive Manufacturing and Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy (PM)–hot isostatic pressing (PM-HIP) has long been recognized as a powerful route for producing fully dense, near net shape metallic components. By consolidating powders under high temperature and pressure, HIP provides isotropic properties, uniform microstructures, and scalability to complex geometries that are vital for sectors such as aerospace, energy, and nuclear power. Yet despite these advantages, the technology has remained constrained by costly trial and error canister fabrication, limitations of conventional forging, and incomplete knowledge about how the canister design influences final part properties. Additive manufacturing (AM), by contrast, thrives on design freedom and geometric flexibility but struggles with speed, scalability, and cost when applied to very large structures. The research presented in this report investigated how a convergent manufacturing approach, combining AM with PM-HIP, can merge the strengths of both technologies, leveraging AM’s flexibility for canister design and HIP’s consolidation capability to deliver reliable, large, and complex parts. The work progressed through three case studies that built on one another in scale and complexity. Small cylindrical canisters fabricated by conventional methods, laser powder bed fusion, and directed energy deposition were filled with stainless steel powders and subjected to HIP. The resulting parts demonstrated near-full density and mechanical properties on par with wrought stainless steel, showing for the first time that AM canisters can be a direct substitute for conventional ones without sacrificing quality. The next step involved a medium-scale, noncentrosymmetric T-valve, which is an enclosed, multibranch geometry that tested the limits of AM + PM-HIP integration. The T-valve achieved predictable shrinkage and uniform densification, confirming feasibility for enclosed designs. However, this study also revealed oxide inclusions and interfacial challenges at the AM + HIP boundary, underscoring the critical importance of controlling interface chemistry and employing robust, in situ strategies, such as melt pool monitoring and thermal monitoring, coupled with nondestructive evaluation techniques such as x-ray computed tomography. Finally, the effort culminated in fabricating a large-scale impeller weighing nearly 2000 lb and spanning 5 ft in diameter. Produced via multirobot wire arc AM and hot isostatic pressed to near-full density, the impeller validated industrial-scale feasibility. Predictive models closely matched experimental shrinkage, tensile properties were spatially uniform across the component, and the AM + PM-HIP interface proved mechanically sound despite the presence of oxide-decorated prior particle boundaries. This large-scale demonstration is a major milestone, showing that hybrid AM + PM‑HIP can reliably deliver components at reactor-relevant scales. Collectively, these studies charted a logical pathway: small-scale work built scientific confidence, medium-scale work highlighted opportunities and challenges, and large-scale work proved industrial impact. The overarching conclusion of this report is that AM + PM-HIP should not be seen as a replacement for forging but as a complementary pathway that provides the US with flexibility, resilience, and new options for manufacturing nuclear-grade components. Looking ahead, several directions emerge as critical to sustaining progress. Predictive modeling must become faster, more accessible, and more accurate, with digital twins and machine learning reducing reliance on trial and error. Powders and alloys must be optimized for HIP, with improved cleanliness, reduced oxides, and tailored chemistries that enhance creep, fatigue, and irradiation resistance. Interfaces between AM and HIP regions must be better engineered through coatings, machining strategies, and surface treatments to mitigate oxide formation and ensure reliable bonding to explore opportunities for HIP of targeted compositional parts, as well as multimaterial HIP cladding applications. Monitoring and nondestructive evaluation need to expand, incorporating multimodal sensors, x-ray computed tomography, and real-time data integration through platforms such as Pelican. At the same time, the pathway to industrial adoption requires techno-economic analysis, machinability studies, and qualification frameworks aligned with industry and regulatory standards. Finally, workforce and academic engagement must be strengthened. Programs that train technicians and engineers for US Navy and US Department of Energy manufacturing challenges should be paired with academic partnerships to support fundamental research, with open sharing of non-export-controlled data to accelerate innovation and build the next generation of experts. In conclusion, this report demonstrates that hybrid AM + PM-HIP is scientifically viable and strategically important. By combining the design agility of AM with the consolidation strength of HIP and embedding modeling, monitoring, and workforce development, this approach provided a transformative new capability for US manufacturing. The path forward is clear: hybrid AM + PM-HIP is not just a promising research direction but is also potentially an industrially relevant pathway that can reshape how nuclear-grade components are designed, qualified, and deployed.

36 MATERIALS SCIENCE↗

Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal components and the brightness temperature principal components of the classes. Because the classes are stratified by the sea surface temperature and the echo-top-height estimator, the number of classes that are considered for retrieval is significantly smaller than the total number of classes, making the algorithm computationally efficient. The radiometer-only algorithm is applied to TMI observations, and precipitation estimates are compared with combined TRMM precipitation radar (PR) TMI reference estimates. The TMI-only algorithm, supported by the empirically derived database, produces estimates that are more consistent with the reference values than the precipitation estimates from the version-6 TRMM facility TMI algorithm. Cloud-resolving model simulations are used to assign a latent heating profile to each precipitation profile in the empirically derived database, making it possible to estimate latent heating using the radiometer-only algorithm. Although the evaluation of latent heating estimates in this study is preliminary, because realistic conditional probability distribution functions are attached to latent heating structures in the algorithm s database, a generally positive impact on latent heating estimation from passive microwave observations is expected.

Grecu, Mircea↗

Quantifying the effects of urbanization on floods in a changing environment to promote water security — A case study of two adjacent basins in Texas

The increased occurrence of flood events resulting from urbanization and global climate change is a great threat to water security. To systematically evaluate the impacts of urbanization on floods, here we applied a paired catchments approach to two adjacent river basins in south-central Texas — the San Antonio River Basin (SARB), with fast urbanization; and the Guadalupe River Basin (GRB), with little land cover change. A physics-based distributed hydrological model — the Distributed Hydrology Soil Vegetation Model, embedded with a multi-purpose reservoir module (DHSVM-Res) — was used to simulate streamflow and reservoir storage. The simulations were conducted under different land cover scenarios, including a newly developed continuous land cover series (CLCS). Holistic analyses were then conducted for the paired basins using three methods: analyzing the selected flood events, detecting change points (CP) of monthly floods, and testing the elasticity of long-term flood regimes. The results suggest that: (1) urbanization may reduce lag time and elevate flood peaks significantly by 3–30% in our study area; (2) when there is little land cover change, changing climate is the major driver of variations in the monthly maximum streamflow (MMS); (3) fast urbanization can amplify streamflow variability, increase MMS significantly, and thus alter the timing of CP; and (4) the mean MMS of observed streamflow in the SARB has increased by as much as 75.7% from the pre-CP to post-CP periods. This comprehensive study fills in a gap in our current understanding of the isolated impacts of urbanization on flooding and is expected to support future explorations of anthropogenic influences on floods.

54 ENVIRONMENTAL SCIENCES↗

Frictionless knowledge injection for few-shot learning

Cutting-edge machine learning methods often require large volumes of curated training data, precluding their use in national security problems with rare events in massive datasets. We present a method for incorporating abstract knowledge into models tailored for sparse data. A subject matter expert defines salient concepts using data examples, which are encoded in the model’s embedding space. Models are then trained to respect these concepts. This method enables knowledge injection, yielding effective models with limited labeled data and the ability to assess model sensitivity for subject matter expertise across the nonproliferation mission space, as demonstrated with Raman spectra analysis.

Stomps, Jordan [ORNL] (ORCID:0000000178114479)↗

A physics-based crystallographic modeling framework for describing the thermal creep behavior of Fe-Cr alloys

In this work, a physics-based thermal creep model is developed based on the understanding of the microstructure in Fe-Cr alloys. This model is associated with a transition state theory based framework that considers the distribution of internal stresses at sub-material point level. The thermally activated dislocation glide and climb mechanisms are coupled in the obstacle-bypass processes for both dislocation and precipitate-type barriers. A kinetic law is proposed to track the dislocation densities evolution in the subgrain interior and in the cell wall. The predicted results show that this model, embedded in the visco-plastic self-consistent (VPSC) framework, captures well the creep behaviors for primary and steady-state stages under various loading conditions. We also discuss the roles of the mechanisms involved.

36 MATERIALS SCIENCE↗

Q-Band Electron-Nuclear Double Resonance Reveals Out-of-Plane Hydrogen Bonds Stabilize an Anionic Ubisemiquinone in Cytochrome bo 3 from Escherichia coli [Q-Band ENDOR Reveals Out-of-Plane Hydrogen Bonds Stabilize an Anionic Ubisemiquinone in Cytochrome bo 3 from Escherichia coli ]

The respiratory cytochrome bo 3 ubiquinol oxidase from E. coli has a high affinity ubiquinone binding site that stabilizes the one-electron reduced ubisemiquinone (SQ H ), which is a transient intermediate during the electron mediated reduction of O 2 to water. It is known that SQ H is stabilized by two strong hydrogen bonds from R71 and D75 to the ubiquinone carbonyl oxygen O1, and weak hydrogen bonds from H98 and Q101 to O4. In the current work, SQ H was investigated with orientation selective Q-band (~34 GHz) pulsed 1 H ENDOR spectroscopy on fully deuterated cyt bo 3 in an H 2 O solvent so that only exchangeable protons contribute to the observed ENDOR spectra. Simulations of the experimental ENDOR spectra provided the principal values and directions of the hyperfine (hfi) tensors for the two strongly coupled H-bond protons (H1 and H2). For H1, the largest principal component of the proton anisotropic hfi tensor T z' = 11.8 MHz, whereas for H2 T z' = 8.6 MHz. Remarkably, the data show that the direction of the H1 H-bond is nearly perpendicular to the quinone plane (~70° out of plane). The orientation of the second strong hydrogen bond, H2, is out of plane by about 25°. Equilibrium molecular dynamics (MD) simulations on a membrane-embedded model of the cyt bo 3 Q H site show that these H-bond orientations are plausible but do not distinguish which H-bond, from R71 or D75, is nearly perpendicular to the quinone ring. Here, density functional theory (DFT) calculations support that the distances and geometries of the H-bonds to the ubiquinone carbonyl oxygens, along with the measured proton anisotropic hfi couplings, are most compatible with an anionic (deprotonated) ubisemiquinone

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating Mesoscale Convective Systems Over the US in Conventional and Multiscale Modeling Framework Configurations of E3SMv1

Organized mesoscale convective systems (MCSs) contribute a significant amount of precipitation in the Central and Eastern US during spring and summer, which impacts the availability of freshwater and flooding events. However, current global Earth system models cannot capture MCSs well and misrepresent the statistics of precipitation in the region. In this study, we investigate the representation of MCSs in three configurations of the Energy Exascale Earth System Model (E3SMv1) by tracking individual storms based on outgoing longwave radiation using a new application of TempestExtremes. Our results indicate that conventional parameterizations of convection, implemented in both low (LR; ~150 km) and high (HR; ~25 km) resolution configurations, fail to capture almost all MCS-like events, in-part because they underestimate high-level cloud ice associated with deep convection. On the other hand, the multiscale modeling framework (MMF; cloud-resolving models embedded in each grid-column of ~150 km resolution E3SMv1) configuration represents MCSs and their annual cycle better. Nevertheless, relative to observations, the E3SMv1-MMF spatial distribution of MCSs and associated precipitation is shifted eastward, and the diurnal timing is lagged. A comparison between the large-scale environment in E3SMv1-MMF and ERA5 reanalysis suggests that the biases during the summer in E3SMv1-MMF are associated with biases in low-level humidity and meridional moisture transport within the low-level jet. The fact that conventional parameterizations of convection, even with high-resolution, cannot capture MCSs over the US suggests that methods with explicit representation of kilometer-scale convective organization, such as the MMF, may be necessary for improving the simulation of these convective systems.

54 ENVIRONMENTAL SCIENCES↗

Probing multi-dimensional composition spaces in search of strong metallic alloys

Refractory complex concentrated alloys (RCCA) offer exceptionally high-temperature strength compared to pure metals and dilute alloys, but predictive theory for RCCA design is lacking. We present large-scale molecular Dynamics (MD) simulations of crystal plasticity to explore alloy compositions for maximum mechanical strength, focusing on Fe-Ta-W and Nb-Ta-Mo-W alloy families modeled with Embedded Atom Model (EAM) and Spectral Neighbor Analysis Potentials (SNAP). To efficiently guide the search for strong alloy compositions, we employ iterative optimization using Gaussian process regression. Many simulated RCCA compositions exhibit pronounced cocktail strengthening, with strengths surpassing their strongest constituent metal, tungsten. Contrary to expectations, the highest strength is found on binary edges of the RCCA composition space. Detailed analyses of atomistic simulations reveal that, similar to pure BCC metals, plastic response in RCCA is primarily governed by screw dislocations. However, at large strains, dislocation multiplication and interactions (Taylor hardening) become the dominant mechanisms contributing to RCCA strength.

Materials science↗

Non destructive technique for cracks detection by an eddy current in differential mode for steel frames

In this paper, a nondestructive technique is used as a tool to control cracks and microcracks in materials. A simulation by a numerical approach such as the finite element method is employed to detect cracks and eventually; to study their propagation using a crucial parameter such as the stress intensity factor. This approach has been used in the aircraft industry to control cracks. Besides, it makes it possible to highlight the defects of parts while preserving the integrity of the controlled products. On the other side, it is proven that the reliability of the control of defects gives convincing results for the improvement of the quality and the safety of the material. Eddy current testing (ECT) is a standard technique in industry for the detection of surface breaking flaws in magnetic materials such as steels. In this context, simulation tools can be used to improve the understanding of experimental signals, optimize the design of sensors or evaluate the performance of ECT procedures. CEA-LIST has developed for many years semi-analytical models embedded into the simulation platform CIVA dedicated to non-destructive testing. The developments presented herein address the case of flaws located inside a planar and magnetic medium. Simulation results are obtained through the application of the Volume Integral Method (VIM). When considering the ECT of a single flaw, a system of two differential equations is derived from Maxwell equations. The numerical resolution of the system is carried out using the classical Galerkin variant of the Method of Moments. Besides, a probe response is calculated by application of the Lorentz reciprocity theorem. Finally, the approach itself as well as comparisons between simulation results and measured data are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impact of cross-linking of polymers on transport of salt and water in polyelectrolyte membranes: A mesoscopic simulation study

Our recent atomistic simulation studies demonstrated that the transport properties of salt ions and water in non-crosslinked polymer electrolyte membrane exhibit an intriguing dependence on salt concentration that is opposite to that seen in electrolyte solutions. Here in this paper, we extend our study to probe the influence of the degree of cross-linking of the polymer on the transport properties of salt and water in polymer electrolyte membranes. Towards this objective, we use a coarse-grained model embedded within dissipative particle dynamics (DPD) mesoscale simulations, which allows us to access time scales necessary for studying crosslinked polymer systems. Our DPD simulations on non-crosslinked membranes reproduce results that are in qualitative agreement with our atomistic simulations. For the case of crosslinked membranes, our results demonstrate that the diffusion of salt ions and water is reduced significantly relative to crosslinked systems. However, the trends exhibited by the salt concentration dependence of diffusivities and the coordination of the cations with anions and with the polymer backbone remain qualitatively similar to those observed in non-crosslinked membranes.

36 MATERIALS SCIENCE↗

Near-threshold resonances in C 11 and the B 10 ( p , α ) Be 7 aneutronic reaction

The nucleus 11 C plays an important role in the boron-proton fusion reactor environment as a catalyzer of the 10 B(p,α) 7 Be reaction which, by producing a long-lived isotope of 7 Be, poisons the aneutronic fusion process 11 B(p,2α) 4 He. The low-energy cross section of 10 B(p,α) 7 Be depends on the near-threshold states 7/2$^{+}_{1}$, 5/2$^{+}_{2}$, 5/2$^{+}_{3}$ in 11 C whose properties are primarily known from the indirect measurements. Here we investigate the continuum-coupling induced collectivization of these resonances in the shell model embedded in the continuum. We predict a significant enhancement of the 10 B(p,α) 7 Be cross section at energies accessible to the laser-driven hot plasma facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Deviations from the Isobaric Multiplet Mass Equation due to Threshold States

Recent studies have completed the A=16 isospin quintets for states with J π =0 + and 2 + . The dependence of their masses as a function of isospin projection shows evidence for deviations from quadratic behavior indicating isospin violation beyond the expectation from two-body forces. The deviation is most pronounced for the 2 + states. Predictions from the shell model embedded in the continuum (SMEC) allow us to explain that this isospin violation is associated with a modification of the nuclear structure due to the open-quantum-system nature of the proton-rich members of the quintet. In particular, the 0 + and 2 + states in 16 Ne and the 2 + state in 16 F are threshold resonances located just above a proton-decay threshold where s-wave coupling to the continuum is expected. The measured deviations of these threshold states from the quadratic behavior of the remaining members of the multiplets makes it possible to obtain information on the magnitude and the energy dependence of the continuum-coupling energy correction. Finally, continuum coupling is also indicated for the ground state of 8 C, but this time through p-wave coupling

coulomb energies & analogue states↗

Probabilistic Physics-Informed Graph Convolutional Network for Active Distribution System Voltage Prediction

Here this letter proposes a novel data-driven probabilistic physics-informed graph convolutional network (GCN) for active distribution system voltage prediction with PVs and EVs. It leverages both measurements and network topology to accurately and efficiently predict node voltages without the need for an accurate distribution system power flow model. The dropout-enabled Bayesian inference is developed to achieve uncertainty quantification of the voltage prediction. Thanks to the network model embedding, it also has robustness against topology changes, a key difference with existing machine learning-based approaches. Comparison results with other state-of-the-art machine learning methods on a realistic 759-node distribution system demonstrate that the proposed method can achieve better accuracy and robustness under different scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗