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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Convolution Neural Network for Fault Identification in Distribution Feeder with High Penetration Solar PV

Identification and zonal classification of the faults is a decisive factor in the relay’s decision to trip or not. Different types of fault like three-phase, line-to-line-to-ground and single-line-to-ground can occur at various locations in the feeder. These faults are seen as the variation in the instantaneous values of three-phase voltages and currents, i.e., waveforms, that are measured at the relay location. The objective of this work is to develop a machine learning model that can identify a fault and classify it to various protection zones based on measured waveforms. In this work, a data-driven relay based on Convolutional Neural Network (CNN) is proposed for fault identification in distribution feeders with high penetration solar PV. The proposed CNN model takes local current and voltage waveforms as input and classify it into fault, no-fault or a capacitor switching. Further, the CNN also attempts to identify fault zones based on the images of waveforms. The overall testing accuracy of the trained model exceeds 95%.

Ramesh, Meghana↗
DOE OSTI2025

Development of Innovative Non-Concentrated Alloy (NCA) Fuel Cladding for Advanced Nuclear Reactors

As the nuclear energy sector advances toward next-generation reactors, the need for high-performance fuel cladding materials has become increasingly urgent. Traditional alloys like zirconium and stainless steel are reaching their performance limits under higher temperatures, more corrosive coolants, and extended irradiation. This report presents the development of a new class of fuel cladding materials based on Non-Concentrated Alloys (NCAs) ? multi-element systems designed to deliver enhanced mechanical strength, corrosion resistance, and radiation tolerance. Through a combination of computational modeling (Computer Coupling of Phase Diagrams and Thermochemistry: CALPHAD), simulation-guided alloy selection, and experimental fabrication via arc melting and spark plasma sintering (SPS), three strategic alloy design paths were explored: (1) FeCrAl-based NCAs, (2) refractory-lean neutron-efficient alloys, and (3) equimolar high-entropy compositions. Microstructural analysis confirmed the formation of stable body-centered cubic BCC_A2 phases, while mechanical testing demonstrated hardness values significantly exceeding those of conventional cladding materials. The results highlight the tunability of NCA systems and their potential for balancing strength and ductility ? a critical consideration for in-reactor performance. Looking forward, future work will focus on thermomechanical optimization, CALPHAD refinement, and benchmarking against industry standards to enable scalable deployment. This work not only advances the science of nuclear materials but also supports broader goals in nuclear safety, performance, and nuclear energy innovation.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications.

14 SOLAR ENERGY↗
DOE OSTI2021

Quantifying and Controlling Entanglement in the Quantum Magnet Cs 2 CoCl 4

The lack of methods to experimentally detect and quantify entanglement in quantum matter impedes our ability to identify materials hosting highly entangled phases, such as quantum spin liquids. We thus investigate the feasibility of using inelastic neutron scattering (INS) to implement a model-independent measurement protocol for entanglement based on three entanglement witnesses: one-tangle, two-tangle, and quantum Fisher information (QFI). We perform high-resolution INS measurements on Cs 2 CoCl 4 , a close realization of the S = 1/2 transverse-field XXZ spin chain, where we can control entanglement using the magnetic field, and compare with density-matrix renormalization group calculations for validation. The three witnesses allow us to infer entanglement properties and make deductions about the quantum state in the material. Overall, we find QFI to be a particularly robust experimental probe of entanglement, whereas the one and two-tangles require more careful analysis. Our results lay the foundation for a general entanglement detection protocol for quantum spin systems.

1-dimensional spin chains↗
DOE OSTI2022

Time-series forecasting using manifold learning, radial basis function interpolation, and geometric harmonics

We address a three-tier numerical framework based on nonlinear manifold learning for the forecasting of high-dimensional time series, relaxing the “curse of dimensionality” related to the training phase of surrogate/machine learning models. At the first step, we embed the high-dimensional time series into a reduced low-dimensional space using nonlinear manifold learning (local linear embedding and parsimonious diffusion maps). Then, we construct reduced-order surrogate models on the manifold (here, for our illustrations, we used multivariate autoregressive and Gaussian process regression models) to forecast the embedded dynamics. Finally, we solve the pre-image problem, thus lifting the embedded time series back to the original high-dimensional space using radial basis function interpolation and geometric harmonics. The proposed numerical data-driven scheme can also be applied as a reduced-order model procedure for the numerical solution/propagation of the (transient) dynamics of partial differential equations (PDEs). In conclusion, we assess the performance of the proposed scheme via three different families of problems: (a) the forecasting of synthetic time series generated by three simplistic linear and weakly nonlinear stochastic models resembling electroencephalography signals, (b) the prediction/propagation of the solution profiles of a linear parabolic PDE and the Brusselator model (a set of two nonlinear parabolic PDEs), and (c) the forecasting of a real-world data set containing daily time series of ten key foreign exchange rates spanning the time period 3 September 2001–29 October 2020.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Flavor as an Incomplete Structure: Conceptual Questions and the Role of DUNE

Flavor remains one of the most successful yet least understood structures of the Standard Model. The discovery of the Higgs boson completed the electroweak account of mass generation, but did not explain the origin of fermion families, mass hierarchies, or mixing patterns. In this sense, flavor can be regarded as an empirically successful but conceptually incomplete structure. Neutrinos occupy a particularly sensitive place within this problem: their masses are tiny, their mixing is large, and their mass-generation mechanism may differ from that of charged fermions. In this article, we discuss flavor as an open conceptual problem and argue that DUNE, as a phased program spanning precision oscillation measurements and sensitivity to BSM and dark-sector phenomena, provides a powerful framework for testing the self-consistency and possible limits of the present three-flavor description. In particular, the complementarity between the long-baseline program and the Phase I near-detector complex, together with the DUNE-PRISM strategy for controlling interaction-model systematics and enabling data-driven near-to-far predictions, makes DUNE especially well-suited to search for small, correlated departures from the minimal flavor framework.

Montanari, Claudio S. [Fermilab; INFN, Pavia] (ORC↗
DOE OSTI2022

Line Faults Classification Using Machine Learning on Three Phase Voltages Extracted from Large Dataset of PMU Measurements

An end-to-end supervised learning method is developed to classify transmission line faults in a twoyear field-recorded dataset that includes synchronized measurements of three-phase voltages recorded by 38 Phasor Measurement Units (PMU) sparsely located in in the US Western Grid interconnection. Statistical analysis is performed to extract features from this large dataset to train Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) classifiers initially. The training further leverages a simulated dataset from a synthetic grid with 12 PMUs to increase the number of faults of types infrequently seen in the field-recorded dataset. Training the classification models with the combined dataset resulted in a classification accuracy of 97.7%. This is a significant improvement over 89.7% to 92.5% accuracy obtained by relying on the field-recorded dataset alone.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Melting and solidification dynamics during laser melting of reaction-based metal matrix composites uncovered by in-situ synchrotron X-ray diffraction

Laser additive manufacturing (AM) of reaction-based metal matrix composites (MMCs) involves highly complex and non-equilibrium material transformation behavior, including melting, dissolution, precipitation, and solidification. Yet, the dynamics and interplay of these phase transformation processes remain poorly understood, posing substantial challenges in identifying the microstructure formation mechanism, and predicting and controlling the microstructure in the printed parts. Here, in this study, we performed the in-situ X-ray diffraction experiment to characterize the phase evolution dynamics of the 316L + 10 vol.%TiC system during laser melting, which provides direct and quantitative insights of the complex phase reaction and evolution dynamics under rapid heating and cooling conditions relevant to additive manufacturing of reaction-based MMCs. Further in-depth thermodynamic and kinetic calculations revealed that most of the phase evolution behavior observed in the in-situ X-ray diffraction experiment cannot be solely explained by widely used equilibrium thermodynamic models, and diffusion-controlled nonequilibrium dissolution and precipitation kinetics must be considered to elucidate the complex phase evolution behavior, including incomplete TiC dissolution, and three-step TiC precipitation. The three distinct types of precipitates generate unique hierarchical TiC micro- and nanostructures, which enhances the yield strength from 513 MPa to 877 MPa by 71 %, tensile strength from 628 MPa to 1054 MPa by 68 %, and Young's modulus from 193 GPa to 221 GPa by 14 %. The findings of our research provide the knowledge foundation for the design of unique microstructures and advanced MMC materials through laser AM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ice and Supercooled Liquid Water Distributions over the Southern Ocean based on In Situ Observations and Climate Model Simulations

Three climate models are evaluated using in situ airborne observations from the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) campaign. The evaluation targets cloud phases, microphysical properties, thermodynamic conditions, and aerosol indirect effects from –40°C to 0°C. Compared with 580-s averaged observations (i.e., 100 km horizontal scale), the Community Atmosphere Model version 6 (CAM6) shows the most similar result for cloud phase frequency distribution and allows more liquid-containing clouds below –10°C compared with its predecessor—CAM5. The Energy Exascale Earth System Model (E3SM) underestimates (overestimates) ice phase frequencies below (above) –20°C. CAM6 and E3SM show liquid and ice water contents (i.e., LWC and IWC) similar to observations from –25°C to 0°C, but higher LWC and lower IWC than observations at lower temperatures. Simulated in-cloud RH shows higher minimum values than observations, possibly restricting ice growth during sedimentation. As number concentrations of aerosols larger than 500 nm (Na 500 ) increase, observations show increases of LWC, IWC, liquid, and ice number concentrations (N liq , N ice ). Number concentrations of aerosols larger than 100 nm (Na 100 ) only show positive correlations with LWC and N liq . From –20°C to 0°C, higher aerosol number concentrations are correlated with lower glaciation ratio and higher cloud fraction. From –40°C to –20°C, large aerosols show positive correlations with glaciation ratio. CAM6 shows small increases of LWC and N liq with Na 500 and Na 100 . E3SM shows small increases of N ice with Na 500 . Altogether, CAM6 and E3SM underestimate aerosol indirect effects on ice crystals and supercooled liquid droplets over the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fathoming the anisotropic magnetoelasticity and magnetocaloric effect in GdNi

Intermetallic GdNi adopts a CrB type of crystal structure (space group Cmcm), and it orders ferromagnetically via a second-order phase transition at 70 K, exhibiting unusually strong spontaneous striction along the three independent crystallographic axes in the ferromagnetically ordered state. Here we introduce a microscopic model to describe anisotropic changes of lattice parameters and elastic contribution to magnetocaloric effect of GdNi. In the model, results of density functional theory (DFT) calculations are used as inputs into a Hamiltonian that includes elastic energy of an anisotropic crystal lattice, exchange interactions, and Zeeman effect. The magnetic and elastic Hamiltonians are coupled through an anisotropic Bean-Rodbell model of magnetoelastic interactions. This coupling gives rise to anisotropic changes in the lattice parameters observed experimentally, and the model reveals good to reasonable agreements between the current theoretical results and earlier experimental data, thus validating the model within the limits of assumptions made. We also show that DFT calculations with 4f electrons of Gd treated as core electrons lead to a more adequate estimate of elastic constants of GdNi in comparison with the LDA + U method where 4f electrons are treated as valence electrons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Improbability of Post-Closure Criticality in Array of Transuranic Waste Containers after Compaction by Salt Creep at Waste Isolation Pilot Plant

Based on the rationale presented, post-closure nuclear criticality is improbable when room closure compacts containers disposing transuranic (TRU) waste emplaced at the Waste Isolation Pilot Plant (WIPP), an operating repository in bedded salt in southeastern New Mexico. As described in the original WIPP certification, a qualitative estimate of the probability of post-closure criticality in TRU waste produced from atomic energy defense activities has been low either because remote-handled TRU waste canisters are neutronically isolated by the bedded salt or because the low fissile mass in an array of contact-handled TRU waste drums cannot be compacted sufficiently by room closure from salt creep. These situations are still valid for the majority of TRU waste that is disposed at WIPP without any disposal constraints, as updated herein. This report also qualitatively evaluates the probability of criticality after disposal of TRU waste in pipe overpack containers (POC) where every POC in a shipment may have the maximum 200 fissile gram equivalent of 239Pu content. The probability of criticality for a disposal room filled with POCs is estimated during four representative phases of repository evolution: (1) a large salt block falls onto POCs in the first 20 years, (2) salt creep closes a disposal room in the first 1000 years without brine seepage and subsequent gas generation, which permits maximum compaction, (3) some brine seepage occurs into the closed room, which initiates consumption of the fiberboard (cellulose) impact absorber in the POC in the second 1000 years, and (4) full brine inundation of a room and consumption of all fiberboard thereafter. Salt-block fall in the first phase does not greatly disrupt three tiers of POCs. The compacted spacing of POCs in the later three repository conditions is calculated through high-fidelity, geomechanical modeling. Criticality evaluation of compacted 200-g 239 Pu spheres at the compacted spacing shows that neither 12-inch nor 6-inch POCs are critical after the first 1000 years, the second 1000 years, or thereafter as the sea of reflector material changes to represent the three repository conditions. Specifically, fiberboard and iron isolates 239 Pu while dry, and brine reduces the reactivity when a room is partially and fully inundated. Because POC behavior bounds behavior of other standard TRU waste containers, post-closure criticality caused by room closure compacting containers is omitted in the performance assessments for the 2019 and 2026 WIPP compliance re-certification applications to the US Environmental Protection Agency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Properties of Hot Nuclear Matter

A fully quantitative description of the equilibrium and dynamical properties of hot nuclear matter will be needed for the interpretation of the available and forthcoming astrophysical data, providing information on the post-merger phase of a neutron star coalescence. We discuss the results of a recently developed theoretical model, based on a phenomenological nuclear Hamiltonian including two- and three-nucleon potentials, to study the temperature dependence of average and single-particle properties of nuclear matter relevant to astrophysical applications. The potential of the proposed approach for describing dissipative processes leading to the appearance of bulk viscosity in neutron star matter is also outlined.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Integrated three-dimensional characterization of reactive phase formation and coarsening during isothermal annealing of metastable Zn–3Mg–4Al eutectic

Microstructural instabilities associated with a metastable lamellar eutectic when exposed to an elevated temperature were analyzed in a Zn-3Mg-4Al alloy as a model system. X-ray diffraction and scanning electron microscopy showed that annealing at a temperature 43 K below the equilibrium eutectic temperature converted the metastable ternary MgZn 2 /η-Zn/β-ZnAl eutectic to a stable mixture of Mg 2 Zn 11 /η-Zn/α-Al. 3D EBSD suggested that supersaturation of η-Zn with Mg and Al eased difficulties in nucleation of Mg 2 Zn 11 and α-Al at the MgZn 2 /η-Zn phase interfaces. Quasi-in-situ X-ray nanotomography revealed that a reactive diffusion process prevailed in an early stage of annealing leading to rapid consumption of MgZn 2 for growth of Mg 2 Zn 11 and concomitant thinning and pinch-off of η-Zn lamellae. The reactive diffusion process also brought about significant and quantifiable changes in the topological characteristics of the η-Zn phase at remarkably shorter time scales compared to Rayleigh instability and Ostwald ripening mechanisms. Overall, the present results provide fresh insights on the short-term annealing effects on metastable eutectics, with relevance to structural evolution in additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Measurement of directed flow in Au + Au collisions at $\sqrt{s{NN}}$ = 19.6 and 27 GeV with the STAR event plane detector

In heavy-ion collision experiments, the global collectivity of final-state particles can be quantified by anisotropic flow coefficients (𝑣 𝑛 ) . The first-order flow coefficient, also referred to as the directed flow (𝑣 1 ), describes the collective sideward motion of produced particles and nuclear fragments in heavy-ion collisions. It carries information on the very early stage of the collision, especially at large pseudorapidity (𝜂), where it is believed to be generated during the nuclear passage time. Directed flow therefore probes the onset of bulk collective dynamics during thermalization, providing valuable experimental guidance to models of the pre-equilibrium stage. In 2018, the Event Plane Detector (EPD) was installed in STAR and used for the Beam Energy Scan phase-II (BES-II) data taking. The combination of EPD (2.1 < |𝜂| < 5.1) and high-statistics BES-II data enables us to extend the 𝑣 1 measurement to the forward and backward 𝜂 regions. In this paper, we present the measurement of 𝑣 1 over a wide 𝜂 range in Au + Au collisions at $\sqrt{s_{NN}}$ = 19.6 and 27 GeV using the STAR EPD. The results of the analysis at $\sqrt{s_{NN}}$ = 19.6 GeV exhibit excellent consistency with the previous PHOBOS measurement, while elevating the precision of the overall measurement. The increased precision of the measurement also revealed finer structures in heavy-ion collisions, including a potential observation of the first-order event-plane decorrelation. Multiple physics models were compared to the experimental results. Only a transport model and a three-fluid hybrid model can reproduce a sizable 𝑣 1 at large 𝜂 as was observed experimentally. The model comparison also indicates 𝑣 1 at large 𝜂 might be sensitive to the QGP phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Growth modeling to evaluate alternative cultivation strategies to enhance national microalgal biomass production

In this paper, we present a model-based assessment of alternative cultivation strategies on algal biomass production within the conterminous United States. Our assessment focuses on two basic cultivation strategies: 1) seasonal rotation of three representative freshwater algal strains that are well suited for warm weather, cold weather, and all-season diverse weather conditions, respectively; and 2) variation between three open pond water depths (15cm, 20cm, and 25cm). The enhanced Biomass Assessment Tool (BAT) is applied on a site-specific, hourly basis at 5,832 North American Land Data Assimilation System Phase 2 1/8° meteorological model grid cells over a 30-year period (1980-2009) to evaluate the operational strategies. Recognizing that resource management decisions may also consider scales beyond the individual site, we also conduct a regional assessment of focused on 7 representative climate zones in the conterminous United States. Results demonstrate that the spatial variability of algal productivity is largely affected by the strain-specific growth response to light and temperature that vary significantly by climate zone and latitude. Therefore, with a limited set of alternative cultivation strategies, the BAT identified the best performing combination of cultivation strategies on a site-specific basis that considerably enhances national annual biomass productivity. Specifically, the appropriate choice of seasonal strain rotation is able to significantly dampen climate-driven seasonal and spatial variability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Critical fluid dynamics in two and three dimensions

We describe a numerical method for simulating stochastic fluid dynamics near a critical point in the Ising universality class. This theory is known as model H, and is expected to govern the nonequilibrium dynamics of quantum chromodynamics (QCD) near a possible critical endpoint of the phase transition between a hadron liquid and the quark-gluon plasma. The numerical algorithm is based on a Metropolis scheme, and automatically ensures that the distribution function of the hydrodynamic variables in equilibrium is independent of the transport coefficients and only governed by the microscopic free energy. We verify dynamic scaling near the critical point of a two and three-dimensional fluid and extract the associated critical exponent z. Here, we find z≃3 in three dimensions, and z≃2 for a two-dimensional fluid. In a finite system, we observe a crossover between the mean field value z=4 and the true critical exponent z≃3 (z≃2 in d=2). This crossover is governed by the values of the correlation length and the renormalized shear viscosity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

On the role of symmetry in quenching OH tunneling in 2,6-dimethylphenol

Here, we model the spectroscopy of the two methyl torsional degrees of freedom coupled to the OH torsional motion in 2,6-dimethylphenol. Recent gas-phase rotational transitions [Welsh et al ., J. Phys. Chem. Lett. 17 , 3749–3758 (2026)] have been interpreted to be the result of certain symmetry states of the methyl groups leading to the quenching of the OH torsional motion. Both a three-dimensional model and an adiabatic model, in which the OH torsion is treated as the slow mode, are developed to test these conjectures. Good agreement is found between the exact and approximate adiabatic models. The adiabatic model is developed to interpret and elucidate the key couplings leading to the quenching of the tunneling splitting.

Sibert, III, Edwin L. [Univ. of Wisconsin, Madison↗