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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Evaluation of convergence behavior of metamodeling techniques for bridging scales in multi-scale multimaterial simulation

The effectiveness of several metamodeling techniques, viz. the Polynomial Stochastic Collocation method, Adaptive Stochastic Collocation method, a Radial Basis Function Neural Network, a Kriging Method and a Dynamic Kriging Method is evaluated. This is done with the express purpose of using metamodels to bridge scales between micro- and macro-scale models in a multi-scale multimaterial simulation. The rate of convergence of the error when used to reconstruct hypersurfaces of known functions is studied. For sufficiently large number of training points, Stochastic Collocation methods generally converge faster than the other metamodeling techniques, while the DKG method converges faster when the number of input points is less than 100 in a two-dimensional parameter space. Because the input points correspond to computationally expensive micro/meso-scale computations, the DKG is favored for bridging scales in a multi-scale solver.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

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

Bion non-perturbative contributions versus infrared renormalons in two-dimensional $\mathbb{C}$P N - 1 models

We derive the semiclassical contributions from the real and complex bions in the two-dimensional $\mathbb{C}$ P N 1 sigma model on $\mathbb{R}$× S 1 with a twisted boundary condition. The bion configurations are saddle points of the complexified Euclidean action, which can be viewed as bound states of a pair of fractional instantons with opposite topological charges. We first derive the bion solutions by solving the equation of motion in the model with a potential which simulates an interaction induced by fermions in the $\mathbb{C}$ P N - 1 quantum mechanics. The bion solutions have quasi-moduli parameters corresponding to the relative distance and phase between the constituent fractional instantons. By summing over the Kaluza-Klein modes of the quantum fluctuations around the bion backgrounds, we find that the effective action for the quasi-moduli parameters is renormalized and becomes a function of the dynamical scale (or the renormalized coupling constant). Based on the renormalized effective action, we obtain the semiclassical bion contribution in a weak coupling limit by making use of the Lefschetz thimble method. We find in the supersymmetric case that the bion contribution vanishes as expected from supersymmetry. In non-supersymmetric cases, the non-perturbative contribution has an imaginary ambiguity which is consistent with the expected infrared renormalon ambiguity. Our results explicitly demonstrate that the complex bion can explain the infrared renormalon.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Dynamics of McMillan mappings III. Symmetric map with mixed nonlinearity

This article extends the study of the dynamical properties of the symmetric McMillan map, emphasizing its utility in understanding and modeling complex nonlinear systems. Although the map features six parameters, we demonstrate that only two are irreducible: the linearized rotation number at the fixed point and a nonlinear parameter representing the ratio of terms in the biquadratic invariant. Through a detailed analysis, we classify regimes of stable motion, provide exact solutions to the mapping equations, and derive a canonical set of action-angle variables, offering analytical expressions for the rotation number and nonlinear tune shift. We further establish connections between general standard-form mappings and the symmetric McMillan map, using the area-preserving Hénon map and accelerator lattices with thin sextupole magnet as representative case studies. Our results show that, despite being a second-order approximation, the symmetric McMillan map provides a highly accurate depiction of dynamics across a wide range of system parameters, demonstrating its practical relevance in both theoretical and applied contexts.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Physics-informed latent neural operator for real-time predictions of time-dependent parametric PDEs

Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between infinite-dimensional function spaces. However, when applied to systems with high-dimensional input-output mappings arising from large numbers of spatial and temporal collocation points, these models often require heavily overparameterized networks, leading to long training times. Latent DeepONet addresses some of these challenges by introducing a two-step approach: first learning a reduced latent space using a separate model, followed by operator learning within this latent space. While efficient, this method is inherently data-driven and lacks mechanisms for incorporating physical laws, limiting its robustness and generalizability in data-scarce settings. Here, in this work, we propose PI-Latent-NO, a physics-informed latent neural operator framework that integrates governing physics directly into the learning process. Our architecture features two coupled DeepONets trained end-to-end: a Latent-DeepONet that learns a low-dimensional representation of the solution, and a Reconstruction-DeepONet that maps this latent representation back to the physical space. By embedding PDE constraints into the training via automatic differentiation, our method eliminates the need for labeled training data and ensures physics-consistent predictions. The proposed framework is both memory and compute-efficient, exhibiting near-constant scaling with problem size and demonstrating significant speedups over traditional physics-informed operator models. We validate our approach on a range of parametric PDEs, showcasing its accuracy, scalability, and suitability for real-time prediction in complex physical systems.

Latent representations↗
DOE OSTI2018

Organophosphorus esters (OPEs) in PM2.5 in urban and e-waste recycling regions in southern China: concentrations, sources, and emissions

Highlights: • OPE concentrations and compositions displayed great variations among the sources. • High OPE levels were related to the electronic, plastic, and chemical industries. • Correlations between OPEs suggests different emission mechanisms from the sources. • The total air emission of OPEs from the 20 urban industrial sources was 1460 kg/yr. • The total air emission of OPEs from the e-waste recycling facilities was 133 kg/yr. Organophosphate esters (OPEs) are novel ubiquitous contaminants that are attracting growing concern, but their emissions into the environment are still poorly understood. In this study, 12 OPEs were measured in fine particulate matter (PM{sub 2.5}) at 20 industrial sites in an urban region and four e-waste recycling facilities in a rural region in southern China. There was no significant difference in the concentrations of ∑OPEs between the urban region (519–62,747 pg/m{sup 3}, median = 2854 pg/m{sup 3}) and the rural e-waste region (775–13,823 pg/m{sup 3}, 3321 pg/m{sup 3}). High OPE concentrations in urban PM{sub 2.5} were generally associated with the electrical, electronic, plastic, and chemical industries. There were no significant correlations between most OPEs in these two regions, suggesting different emission mechanisms. The average emissions of ∑OPEs estimated using a simplified dispersion model were 73.0 kg/yr from the urban industrial point sources and 33.2 kg/yr from the e-waste recycling facilities. The estimated emission inventory from industrial activities in the whole city (3228–4452 kg/yr) was approximately 30-fold higher than that from the e-waste recycling (133 kg/yr) facilities because urban region has a much larger industrial scale. To the best of our knowledge, this is the first effort to model the emissions of OPEs from industrial and e-waste recycling activities to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Self-induced temperature correction for inter-phase heat transfer in Euler-Lagrange point-particle simulation

In a two-way coupled Euler-Lagrange simulation, particles are approximated as point sources and their momentum and energy exchange with the surrounding flow are modeled through point-particle force and heat transfer models. As the particle size increases and approaches the Eulerian grid, the feedback force and heat transfer become large and strongly affect the local flow at the particle location. The fluid velocity and temperature computed in the EL simulation when interpolated to the particle location will be substantially different from the corresponding undisturbed values. In this work we will follow the approach pursued in Balachandar et al. (2018) [1] for self-induced velocity correction to develop an analogous correction procedure for self-induced temperature. We obtain analytical solutions for the self-induced thermal perturbation for a steady uniform cross flow past a Gaussian filtered heat source under both steady and unsteady conditions. The analytical results are extended to finite Peclet number using numerical simulations. The resulting quasi-steady and unsteady models are tested with a simple problem of exponential thermal evolution against the corresponding EL simulation results. We also provide a simple criterion for when the self-induced temperature correction is needed in an Euler-Lagrange simulation.

42 ENGINEERING↗
DOE OSTI2019

M11plus: A Range-Separated Hybrid Meta Functional with Both Local and Rung-3.5 Correlation Terms and High Across-the-Board Accuracy for Chemical Applications

The way to improve Kohn–Sham density functional theory is to improve the exchange–correlation functionals, and functionals have been successively improved by adding new ingredients, especially local spin density gradients, nonlocal Hartree–Fock exchange, and local meta terms based on kinetic energy density. Here, we present a new kind of functional obtained by adding rung-3.5 terms to a functional including local gradients, local meta terms, and range-separated Hartree–Fock exchange. A rung-3.5 term has short-range nonlocality designed to account for nondynamic correlation; we add two kinds of rung-3.5 terms, one kind modeled on position-dependent Hartree–Fock exchange and another modeled on the spin density at a point interacting with the opposite-spin exchange hole at the same point. Here, optimization of the functional yields broad accuracy for both ground states and excited states with especially significant improvement for systems with strong correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Inferring dark matter substructure with astrometric lensing beyond the power spectrum

Abstract Astrometry—the precise measurement of positions and motions of celestial objects—has emerged as a promising avenue for characterizing the dark matter population in our Galaxy. By leveraging recent advances in simulation-based inference and neural network architectures, we introduce a novel method to search for global dark matter-induced gravitational lensing signatures in astrometric datasets. Our method based on neural likelihood-ratio estimation shows significantly enhanced sensitivity to a cold dark matter population and more favorable scaling with measurement noise compared to existing approaches based on two-point correlation statistics. We demonstrate the real-world viability of our method by showing it to be robust to non-trivial modeled as well as unmodeled noise features expected in astrometric measurements. This establishes machine learning as a powerful tool for characterizing dark matter using astrometric data.

convolutional neural networks (1938)↗
DOE OSTI2023

Strong-field nonsequential double photoionization using virtual-detector theory with path summation

We present an ab initio study of the nonsequential strong-field ionization dynamics of a model two-electron atom with helium character. Single- and double-ionization events are characterized and displayed using detector signals extracted at different points in the two-electron two-dimensional space. The double photoelectron momentum distribution is calculated via coherent path-summation over virtual-particle trajectories. A comparison is made between the momentum distributions obtained with the virtual-detector method, the Schrödinger wave function, and the time-dependent surface flux method developed by Tao and Scrinzi [New J. Phys. 14, 013021 (2012)]. Insights into different ionization and electron recollision pathways are gained from detailed virtual-particle tracking and energy-time readouts. Furthermore, this study demonstrates the extension of virtual-detector theory to strong-field multielectron quantum dynamics and highlights the importance of the evolving quantum phase in quasiclassical electron propagation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Low-energy excitations in type-II Weyl semimetal T d - MoTe 2 evidenced through optical conductivity

Molybdenum ditelluride, MoTe 2 , is a versatile material where the topological phase can be readily tuned by manipulating the associated structural phase transition. The fine details of the band structure of MoTe 2 , key to understanding its topological properties, have proven difficult to disentangle experientially due to the multiband character of the material. Through experimental optical conductivity spectra, we detect two strong low-energy interband transitions. Both are linked to excitations between spin-orbit split bands. The lowest interband transition shows a strong thermal shift, pointing to a chemical potential that dramatically decreases with temperature. Finally, with the help of ab initio calculations and a simple two-band model, we give qualitative and quantitative explanations of the main features in the temperature-dependent optical spectra up to 400 meV.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Quasilinear dispersion in electronic band structure and high Seebeck coefficient in CuFeS 2 -based thermoelectric materials

The earth-abundant natural mineral chalcopyrite CuFeS 2 is a potential n-type thermoelectric material because of its large Seebeck coefficient at high carrier concentrations. For a long time, the large Seebeck coefficient of CuFeS 2 has been attributed to a large electron effective mass, but the reasons for this and the unusual carrier concentration dependent behavior have rarely been discussed. Here, we systematically investigated the special transport behavior of CuFeS 2 and found the classical parabolic band model to be inadequate in explaining it. Our experimental and theoretical studies indicate that there are two flat electronic pockets at the and Z points of the Brillouin zone near the conduction band edge of CuFeS 2 that dominate the charge transport. These electronic pockets result from nonparabolic quasilinearly dispersing bands that give rise to a linear wave vector dependent energy (E ~ k) and a carrier density dependent effective mass (m* ~ m 0 n 1/3 ). Such a strong carrier concentration dependent carrier effective mass results in the high Seebeck coefficient of CuFeS 2 compound under a large carrier density. Here, the work demonstrates that quasilinearly dispersing bands can give strongly enhanced Seebeck coefficient, and could be useful in optimizing the properties of thermoelectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Onset of Scrambling as a Dynamical Transition in Tunable-Range Quantum Circuits

In a fast-scrambling many-body quantum system, information is spread and entanglement is built up on a time scale that grows logarithmically with the system size. This is of fundamental interest in understanding the dynamics of many-body systems, as well as in efficiently producing entangled resource states and error-correcting codes. In this work, we identify a dynamical transition marking the onset of scrambling in quantum circuits with different levels of long-range connectivity. In particular, we show that as a function of the interaction range for circuits of different structures, the tripartite mutual information exhibits a scaling collapse around a critical point between two clearly defined regimes of different dynamical behavior. We study this transition analytically in a related long-range Brownian-circuit model and show how the transition can be mapped onto the statistical mechanics of a long-range Ising model in a particular region of parameter space. This mapping predicts mean-field critical exponents v=–1/(1 + s c ), which are consistent with the critical exponents extracted from Clifford-circuit numerics. In addition to systems with conventional power-law interactions, we identify the same phenomenon in deterministic sparse circuits that can be realized in experiments with neutral-atom arrays.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1974

Shuttle user analysis (study 2.2). Volume 4: Standardized subsystem modules analysis

The capability to analyze payloads constructed of standardized modules was provided for the planning of future mission models. An inventory of standardized module designs previously obtained was used as a starting point. Some of the conclusions and recommendations are: (1) the two growth factor synthesis methods provide logical configurations for satellite type selection; (2) the recommended method is the one that determines the growth factor as a function of the baseline subsystem weight, since it provides a larger growth factor for small subsystem weights and results in a greater overkill due to standardization; (3) the method that is not recommended is the one that depends upon a subsystem similarity selection, since care must be used in the subsystem similarity selection; (4) it is recommended that the application of standardized subsystem factors be limited to satellites with baseline dry weights between about 700 and 6,500 lbs; and (5) the standardized satellite design approach applies to satellites maintainable in orbit or retrieved for ground maintenance.

Source record↗
NASA NTRS1979

Study of reactor Brayton power systems for nuclear electric spacecraft

The feasibility of using Brayton power systems for nuclear electric spacecraft was investigated. The primary performance parameters of systems mass and radiator area were determined for systems from 100 to 1000 kW sub e. Mathematical models of all system components were used to determine masses and volumes. Two completely independent systems provide propulsion power so that no single-point failure can jeopardize a mission. The waste heat radiators utilize armored heat pipes to limit meteorite puncture. The armor thickness was statistically determined to achieve the required probability of survival. A 400 kW sub e reference system received primary attention as required by the contract. The components of this system were defined and a conceptual layout was developed with encouraging results. An arrangement with redundant Brayton power systems having a 1500 K (2240 F) turbine inlet temperature was shown to be compatible with the dimensions of the space shuttle orbiter payload bay.

Source record↗
NASA NTRS1983

Numerical methods for stiff systems of two-point boundary value problems

Numerical procedures are developed for constructing asymptotic solutions of certain nonlinear singularly perturbed vector two-point boundary value problems having boundary layers at one or both endpoints. The asymptotic approximations are generated numerically and can either be used as is or to furnish a general purpose two-point boundary value code with an initial approximation and the nonuniform computational mesh needed for such problems. The procedures are applied to a model problem that has multiple solutions and to problems describing the deformation of thin nonlinear elastic beam that is resting on an elastic foundation.

Flaherty, J. E.↗
NASA NTRS1983

The spatial correlation function of rich clusters of galaxies

A series of objective statistical estimators is applied to directly study the three-dimensional distribution of rich clusters, using a recently completed redshift sample of 104 Abell clusters out to distance class four and galactic latitude of 30 deg or more. The sample and the relevant positional and redshift selection effects are discussed, and the two-point angular correlation function and nearest-neighbor distribution of clusters in the sample are determined, as well as in the larger D = 5+6 sample and in several subsamples of different richness classes and latitude zones. The redshift correlation function of clusters for various angular separations on the sky is examined as a test for the reality of the observed angular correlations. The two-point spatial correlation function of clusters in the sample is determined, and the consistency among the three observed correlation functions is tested. A model that describes all the observed correlations is presented.

Bahcall, N. A.↗