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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Theory of terahertz pulse transmission through ferroelectric nanomembranes

An analytical model is developed to predict the temporal evolution of the lattice polarization in ferroelectric nanomembranes upon the excitation by a terahertz (THz) electromagnetic pulse of an arbitrary waveform and the concurrent transmission of the THz pulse in both linear and nonlinear regimes. It involves the use of the perturbation method to solve the equation of motion for the lattice polarization in both unclamped and strained ferroelectric nanomembranes within the framework of Landau-Ginzburg-Devonshire theory. The model is applicable to perovskite oxides such as BaTiO 3 and SrTiO 3 , wurtzite Al 1−𝑥 ⁢Sc 𝑥 ⁢N, and trigonal LiNbO 3 . Our analytical model provides a theoretical basis for determining the thermodynamic and kinetic parameters of ferroelectric materials through a THz transmission experiment. The calculation results also suggest an approach to reversing the chirality of a circularly polarized THz pulse by harnessing the resonant polarization-photon coupling in ferroelectrics. This capability of chirality reversal, along with the high tunability from a strain applied along any arbitrarily oriented in-plane axis, provides new opportunities for THz wave modulation without relying on complex metasurface designs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory

The availability of global high-resolution land cover maps provides promising a priori knowledge for characterizing subpixel heterogeneity and improving predictions of directional reflectance of coarse-resolution pixels. Due to mutual shadowing and sheltering effects between the adjacent forest and cropland patches, the spectral nonlinear mixing of patchy ecotones is significant, especially when the sun illuminates the ecotone from the forest side with high solar zenith angle. The spectral linear mixture (SLM) approach leads to overestimation of the bidirectional reflectance factor (BRF) in the red band in the principal plane (PP), with a maximum absolute error (MAE) of 0.0063 and a maximum relative error (MRE) of 52.5%, and to underestimation in the near-infrared band in PP with an MAE of 0.0940 and an MRE of 14.5%. In a scenario with randomly distributed boundary orientations, the overestimation of SLM increases with the degree of fragmentation and the view zenith angle. We propose a Radiative Transfer model for patchy ECotones (RTEC). which improves R² from 0.61 to 0.94 in the red band of Landsat-8 directional reflectance at the validation site. The RTEC model provides an efficient and analytical approach for directional reflectance predictions over heterogeneous patchy landscapes at coarse resolution and will be used for biophysical parameter retrievals [e.g., the leaf area index (LAI)] in future applications.

Zeng, Yelu↗
DOE OSTI2023

Accelerated Materials Design for Molten Salt Technologies Using Innovative High-Throughput Methods

The focus of the project is on building an innovative accelerated materials design platform for molten salt technologies using novel high-throughput methods coupled to data analytics. The main objectives is to predict a FeCrMnNi alloy compositional space with better corrosion resistance than stainless steel 316 and identify new molten salt corrosion mechanisms. The project demonstrates the feasibility to use high-throughput methods coupled to data analytics to accelerate alloy design for extreme environments applications. Using a trained and tested machine learning (ML) model, 2000 FeCrMnNi alloy corrosion rate in molten chloride salts were predicted and a compositional field with corrosion rate lower than 316 stainless steel was identified. The ML model interpretability unveiled multiple features of importance in the model prediction. Some features were expected to be of relative significance, such as work function, surface energy and alloy electronegativity, and the ML model interpretability analysis confirmed those. On the other hand, the most important feature is the diffusion coefficient of Ni in the bulk alloy which indicates that a surface diffusion mechanism plays an important role in the overall corrosion mechanism in molten salts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A lattice study of ππ scattering at large N c

We present the first lattice study of pion-pion scattering with varying number of colors, N c . We use lattice simulations with four degenerate quark flavors, N f = 4, and N c = 3 – 6. We focus on two scattering channels that do not involve vacuum diagrams. These correspond to two irreducible representations of the SU(4) flavor group: the fully symmetric one, SS, and the fully antisymmetric one, AA. The former is a repulsive channel equivalent to the isospin-2 channel of SU(2). By contrast, the latter is attractive and only exists for N f ≥ 4. A representative state is (|D$^{+}_{s}$π + > – | D + K + >)/√2. Using Lüscher’s formalism, we extract the near-threshold scattering amplitude and we match our results to Chiral Perturbation Theory (ChPT) at large N c . For this, we compute the analytical U(N f ) ChPT prediction for two-pion scattering, and use the lattice results to constrain the N c scaling of the relevant low-energy couplings.

1/N Expansion↗
DOE OSTI2021

Dark matter absorption via electronic excitations

We revisit the calculation of bosonic dark matter absorption via electronic excitations. Working in an effective field theory framework and consistently taking into account in-medium effects, we clarify the relation between dark matter and photon absorption. As is well-known, for vector (dark photon) and pseudoscalar (axion-like particle) dark matter, the absorption rates can be simply related to the target material’s optical properties. However, this is not the case for scalar dark matter, where the dominant contribution comes from a different operator than the one contributing to photon absorption, which is formally next-to-leading-order and does not suffer from in-medium screening. It is therefore imperative to have reliable first-principles numerical calculations and/or semi-analytic modeling in order to predict the detection rate. We present updated sensitivity projections for semiconductor crystal and superconductor targets for ongoing and proposed direct detection experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Novel nonwetting solid-infused surfaces for superior fouling mitigation

Fouling is a ubiquitous issue in several environmental and energy applications. Here we introduce novel nonwetting solid-infused surfaces (SIS) with superior anti-fouling characteristics that are durable than conventional nonwetting surfaces in a dynamic flow environment. A systematic study is presented to elucidate the fouling mitigation performance of SIS in comparison to lubricant-infused surface (LIS) and conventional smooth surface. Copper tubes with SIS, LIS or smooth inner walls are fabricated and subjected to accelerated calcium sulfate fouling in a flow fouling experimental setup. Fouling on the various surface types is quantified in terms of asymptotic fouling resistance, and the fundamental morphological differences in the interactions of the foulant and the various surface types are analyzed. Based on a systematic sweep of the parameter combinations using design of experiments and Taguchi analysis, an analytical dependence of asymptotic fouling resistance on the governing parameters namely, Reynolds number, foulant concentration and temperature is derived. The analytical model is shown to predict the asymptotic fouling resistance to within 20% accuracy with a 95% confidence. In addition, for the first time, the effects of shear durability on the fouling mitigation performance of LIS vis-à-vis SIS are studied. It is shown that the novel nonwetting SIS offers a robust option for superior fouling mitigation over LIS in the long run.

42 ENGINEERING↗
DOE OSTI2024

Anomalous temperature dependence of elastic limit in metallic glasses

Abstract Understanding the atomistic mechanisms of inelastic deformation in metallic glasses (MGs) remains challenging due to their amorphous structure, where local carriers of plasticity cannot be easily defined. Using molecular dynamics (MD) simulations, we analyzed the onset of inelastic deformation in CuZr MGs, specifically the temperature dependence of the elastic limit, in terms of localized shear transformation (ST) events. We find that although the ST events initiate at lower strain with increasing temperature, the elastic limit increases with temperature in certain temperature ranges. We explain this anomalous behavior through the framework of an energy-strain landscape (ESL) constructed from high-throughput strain-dependent energy barrier calculations for the ST events identified in the MD simulations. The ESL reveals that the anomalous behavior is caused by the transition of ST events from irreversible to reversible with increasing temperature. An analytical formulation is developed to predict this transition and the temperature dependence of the elastic limit.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Assessment of dynamic-screw-pinch-driven, current-scaled MagLIF target implosion performance using 3D magnetohydrodynamic simulations

Analytic studies and two-dimensional “clean” radiation-magnetohydrodynamic (rad-MHD) simulations employing dynamical similarity driver-target scaling prescriptions [Ruiz et al., Phys. Plasmas 30, 032708 (2023)] suggest that Magnetized Liner Inertial Fusion (MagLIF) target implosions can scale to > 10 MJ DT fusion yields when peak drive current is increased beyond 60 MA. We present results from three-dimensional (3D) rad-MHD simulations of similarity-scaled MagLIF target implosions at peak drive currents ranging from 15 to 40 MA. Simulations in this study suggest that magneto-Rayleigh–Taylor instability (MRTI) growth and feedthrough to the fuel region are more severe at higher drive current scales, which reduces the fusion yield compared to prior analytic and 2D clean simulation predictions. In contrast to standard MagLIF, simulations of current-scaled MagLIF target implosions driven by a dynamic screw pinch (DSP) demonstrate reduced MRTI feedthrough and greater fuel magnetization, resulting in improved thermonuclear performance and enhanced performance scaling with peak drive current. DSP drive enables additional scaling of the liner mass to increase liner radius but maintain implosion time, resulting in higher implosion velocities at the expense of increased susceptibility to MRTI. We present a current- and mass-scaled simulated DSP-MagLIF target implosion at the ∼ 40 MA peak current level that produces ignition scale performance, demonstrating a burn-averaged Lawson ignition parameter above unity and DT fusion yield above 1 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Regression Analysis with the Directed Infusion of Data

Integrating artificial intelligence and machine learning tools into industry necessitates large-scale collaborative efforts that ensure the robust and accurate execution of downstream analytics such as time series prediction, uncertainty quantification, grid optimization, and condition monitoring. However, concerns related to data privacy pervade the nuclear industry due to the proprietary nature of its data and the possibility of data leakage. Legacy techniques such as encryption often require the explicit transmission of data to trustworthy parties, thereby inviting data leakage concerns. The ideal collaboration scenario avoids the explicit dissemination of data/code while maintaining experimental fidelity, which is currently accomplished using various techniques such as trusted execution environments, homomorphic encryption, differential privacy, and multimatrix masking. These techniques, however, often necessitate a trade-off between trust, efficiency, and utility. This article extends a previously proposed technique called the directed infusion of data (DIOD) that ensures data privacy, allows for scalable obfuscation, and combats the risk of data leakage without compromising utility. The experiments discussed in this article examine a regression-type scenario using DIOD with the goal of preserving the inferential link between two variables. Using the point-kinetics equations, regression experiments compare the performance of a model trained using the original data to that of a model trained using the obfuscated data, which produced identical results. Our claim is further strengthened by an information theoretic proof and experiment, which showed that the inferential content between variables remains the same after obfuscation, thereby avoiding the required communication of the proprietary data.

47 - OTHER INSTRUMENTATION↗
DOE OSTI2022

Enhanced critical axial tensile strain limit of CORC ® wires: FEM and analytical modeling

Abstract Conductor on Round Core (CORC ® ) cables and wires are composed of spiraled high-temperature superconducting (HTS) rare-earth barium copper oxide (REBCO) tapes, wound in multiple layers, and can carry very high currents in background magnetic fields of more than 20 T. They combine isotropic flexibility and high resilience to electromagnetic and thermal loads. The brittle nature of HTS tapes limits the maximum allowable axial tensile strain in superconducting cables. An intrinsic tensile strain above about 0.45% will introduce cracks in the REBCO layer of straight HTS tapes resulting in irreversible damage. The helical fashion at which the REBCO tapes are wound around the central core allows tapes to experience only a fraction of the total axial tensile strain applied to the CORC ® wire. As a result, the critical strain limit of CORC ® wires can be increased by a factor of more than 10 that of REBCO tapes. Finite element (FE) and analytical models are developed to predict the performance of CORC ® wires under axial tensile strain. A parametric analysis is carried out by varying the winding angle, the Poisson’s ratio of the CORC ® wire core, the core diameter, and the tape width. The results show that a small variation in winding angle can have a significant impact on the cable’s axial tensile strain tolerance. While the radial contraction of the helically wound tapes in a CORC ® wire under axial tensile strain depends on its winding angle, it is mostly driven by the Poisson’s ratio of the central core, affecting the tape strain state and thus its performance. Contact pressure from multiple layers within the CORC ® wire also affects the CORC ® wire performance. The FE model can be used to optimize the cable design for specific application conditions, resulting in an irreversible strain limit of CORC ® cables and wires as high as 7%.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Theory of nonlinear terahertz susceptibility in ferroelectrics

An analytical theory is developed for predicting the nonlinear susceptibility of ionic polarization to continuous electromagnetic waves in both bulk and strained thin film ferroelectrics. Using a perturbation method for solving the nonlinear equation of motion for ionic polarization within the framework of Landau-Ginzburg-Devonshire theory, the full second-order nonlinear susceptibility tensor is derived as a function of frequency, temperature, and strain. Here, the theory predicts the coexistence of a significantly enhanced second-order dielectric susceptibility and a relatively low dielectric loss in BaTiO 3 films with a strain-stabilized monoclinic ferroelectric phase and in a strained SrTiO 3 film near its temperature-driven second-order ferroelectric-to-paraelectric phase transition. In this paper, we establish a theoretical framework for predicting and exploiting nonlinear interactions between terahertz waves and ferroelectric materials and, more generally, suggest exciting opportunities to strain-engineer nonlinear dynamical properties of ferroelectrics beyond the static and quasistatic limits.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

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

Attack Surface Analysis of the Digital Twins interface with Advanced Sensor and Instrumentation Interfaces: Cyber Threat Assessment and Attack Demonstration for Digital Twins in Advanced Reactor Architectures

A digital twin is a virtual representation of a physical system or object using real-time data that can predict and analyze how the system or object performs. This relatively new technology can be applied to the field of nuclear power generation, to aid in the design and development of new nuclear power plants and reduce operation costs using predictive maintenance and other data analytical methods. While there are already companies utilizing simulation software to train operators and technicians in the nuclear industry, some are now transitioning to utilizing their existing technology, software, and methods to develop digital twin solutions for the next generation of nuclear power plants, offering their services to utilities and government organizations around the world.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5

Abstract. This article presents the C-grid implementation of the CICE sea ice model, including the C-grid discretization of the momentum equation, the boundary conditions (BCs), and the modifications to the code required to use the incremental remapping transport scheme. To validate the new C-grid implementation, many numerical experiments were conducted and compared to the B-grid solutions. In idealized experiments, the standard advection method (incremental remapping with C-grid velocities interpolated to the cell corners) leads to a checkerboard pattern. A modal analysis demonstrates that this computational noise originates from the spatial averaging of C-grid velocities at corners. The checkerboard pattern can be eliminated by adjusting the departure regions to match the divergence obtained from the solution of the momentum equation. We refer to this novel approach as the edge flux adjustment (EFA) method. The C-grid discretization with edge flux adjustment allows for transport in channels that are one grid cell wide – a capability that is not possible with the B-grid discretization nor with the C-grid and standard remapping advection. Simulation results match the predicted values of a novel analytical solution for one-grid-cell-wide channels.

Lemieux, Jean-François (ORCID:0000000320845759)↗
DOE OSTI2021

Quantifying High Temperature Corrosion

Alloys designed for high temperature service can form a variety of surface oxides or scales based on the alloy composition, service temperature, gas environment, surface deposits, etc. The most severe environments, including molten salts and liquid metals can result in significant metal loss, void formation and/or pitting. Standard and evolving practices are discussed for measuring these types of degradationincluding measuring oxide scale thickness, internal oxidation and/or metal loss, correlating them to mass change and reporting the results. Manual and automated methodologies to measure oxide thickness and metal loss are reviewed and compared in order to provide a summary of techniques and identify the best practices for quantifying a variety of materials and damage mechanisms and producing statistically meaningful results. Such techniques create datasets useful for improved understanding of corrosion degradation mechanisms, potentially better predictive models and enhanced data analytics.

Su, Yi Feng↗
DOE OSTI2025

SASHIMI-SIDM: semi-analytical subhalo modelling for self-interacting dark matter at sub-galactic scales

We combine the semi-analytical structure formation model, SASHIMI, which predicts subhalo populations in collisionless, cold dark matter (CDM), with a parametric model that maps CDM halos to self-interacting dark matter (SIDM) halos. The resulting model, SASHIMI-SIDM, generates SIDM subhalo populations down to sub-galactic mass scales, for an arbitrary input cross section, in minutes. We show that SASHIMI-SIDM agrees with SIDM subhalo populations from high-resolution cosmological zoom-in simulations in resolved regimes. Crucially, we predict that the fraction of core-collapsed subhalos peaks at a mass scale determined by the input SIDM cross section and decreases toward higher halo masses, consistent with the predictions of gravothermal models and cosmological simulations. For the first time, we also show that the core-collapsed fraction decreases toward lower halo masses. While the dependence of the collapse time on mass and concentration implies such behaviour, our semi-analytical approach allows us to quantify and illustrate this trend clearly across the full mass spectrum of subhalos, including for subhalo masses below the resolution limit of any current cosmological SIDM simulation. As a proof of principle, we apply SASHIMI-SIDM to predict the boost to the local dark matter density and annihilation rate from core-collapsed SIDM subhalos, which can be enhanced relative to CDM by an order of magnitude for viable SIDM models. Thus, SASHIMI-SIDM provides an efficient and reliable tool for scanning SIDM parameter space and testing it with astrophysical observations. The code is publicly available at https://github.com/shinichiroando/sashimi-si.

cosmological simulations↗
DOE OSTI2020

Centroidal Voronoi tessellation based methods for optimal rain gauge location prediction

With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. Herein we propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting density map that serves as an input to centroidal Voronoi tessellation construction that optimizes placement of precipitation gauges. We provide results of numerical experiments based on the data from the Alto-Adige region in Northern Italy and Oklahoma and compare them against actual gauge locations. This method provides an automated way for choosing new gauge locations and can be generalized to include physical constraints and to tackle other types of resource allocation problems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

PARIS: Predicting application resilience using machine learning

The traditional method to study application resilience to errors in HPC applications uses fault injection (FI), a time-consuming approach. Furthermore, while analytical models have been built to overcome the inefficiencies of FI, they lack accuracy. In this paper, we present PARIS, a machine-learning method to predict application resilience that avoids the time-consuming process of random FI and provides higher prediction accuracy than analytical models. PARIS captures the implicit relationship between application characteristics and application resilience, which is difficult to capture using most analytical models. We overcome many technical challenges for feature construction, extraction, and selection to use machine learning in our prediction approach. Our evaluation on 16 HPC benchmarks shows that PARIS achieves high prediction accuracy. PARIS is up to 450x faster than random FI (49x on average). Compared to the state-of-the-art analytical model, PARIS is at least 63% better in terms of accuracy and has comparable execution time on average.

97 MATHEMATICS AND COMPUTING↗