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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Eigenfunction methods in magnetospheric radial-diffusion theory

Complete sets of orthonormal basis functions constructed according to a generalization of the quantum-mechanical WKB approximation can be used to generate a nearly-diagonal matrix representation of the radial-transport operator for ring-current ions in the presence of radial diffusion and charge exchange. The resulting eigenfunctions (constructed by weighting the basis functions in proportion to the respective components of the eigenvectors of the matrix representation) and eigenvalues provide a spatial and temporal description of the evolving phase-space density during and following a magnetospheric disturbance (e.g., a magnetic storm). A linear superposition of the basis functions can also be used to eliminate any discrepancy between the steady-state solution of the transport equation and the appropriate WKB approximation of this steady-state solution.

Schulz, Michael↗
DOE OSTI2023

Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods

Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree–Fock and density functional theory but offer higher accuracy. Accordingly, quantum computers have been predominantly regarded as competitors to only the most accurate and costly classical methods for treating electron correlation. However, here we tighten bounds showing that certain first-quantized quantum algorithms enable exact time evolution of electronic systems with exponentially less space and polynomially fewer operations in basis set size than conventional real-time time-dependent Hartree–Fock and density functional theory. Although the need to sample observables in the quantum algorithm reduces the speedup, we show that one can estimate all elements of the k-particle reduced density matrix with a number of samples scaling only polylogarithmically in basis set size. We also introduce a more efficient quantum algorithm for first-quantized mean-field state preparation that is likely cheaper than the cost of time evolution. We conclude that quantum speedup is most pronounced for finite-temperature simulations and suggest several practically important electron dynamics problems with potential quantum advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

The Grassmann interpolation method for spin-unrestricted open-shell systems

The recently reported Grassmann interpolation (G-Int) method [J. A. Tan and K. U. Lao, J. Chem. Phys. 158, 051101 (2023)] has been extended to spin-unrestricted open-shell systems. In contrast to closed-shell systems, where G-Int has to be performed only once since the α and β density matrices are the same, spin-unrestricted open-shell systems require G-Int to be performed twice—one for the α spin and another for the β spin density matrix. In this work, we tested the performance of G-Int to the carbon monoxide radical cation CO●+ and nickelocene complex, which have the doublet and triple ground states, respectively. We found that the Frobenius norm errors associated with the interpolations for the α and β spin density matrices are comparable for a given molecular geometry. These G-Int density matrices, when used as an initial guess for a self-consistent field (SCF) calculation, outperform the conventional SCF guess schemes, such as the superposition of atomic densities, purified superposition of atomic densities, core Hamiltonian, and generalized Wolfsberg–Helmholtz approximation. Depending on the desired accuracy, these G-Int density matrices can be used to directly evaluate the SCF energy without performing SCF iterations. In addition, the spin-unrestricted G-Int density matrices have been used for the first time to directly calculate the atomic charges using the Mulliken and ChElPG population analysis.

Chemistry↗
NASA NTRS1993

Fluctuations at the blue edge of saturated wind lines in IUE spectra of O-type stars

We examine basic issues involved in synthesizing resonance-line profiles from 1-D, dynamical models of highly structured hot-star winds. Although these models exhibit extensive variations in density as well as velocity, the density scale length is still typically much greater than the Sobolev length. The line transfer is thus treated using a Sobolev approach, as generalized by Rybicki & Hummer (1978) to take proper account of the multiple Sobolev resonances arising from the nonmonotonic velocity field. The resulting reduced-Lambda-matrix equation describing nonlocal coupling of the source function is solved by iteration, and line profiles and then derived from formal solution integration using this source function. The more appropriate methods that instead use either a stationary or a structured, local source function yield qualitatively similar line-profiles, but are found to violate photon conservation by 10 percent or more. The full results suggest that such models may indeed be able to reproduce naturally some of the qualitative properties long noted in observed UV line profiles, such as discrete absorption components in unsaturated lines, or the blue-edge variability in saturated lines. However, these particular models do not yet produce the black absorption troughs commonly observed in saturated lines, and it seems that this and other important discrepancies (e.g., in acceleration time scale of absorption components) may require development of more complete models that include rotation and other 2-D and/or 3-D effects.

Owocki, Stanley P.↗
NASA NTRS1993

On the synthesis of resonance lines in dynamical models of structured hot-star winds

We examine basic issues involved in synthesizing resonance-line profiles from 1-D, dynamical models of highly structured hot-star winds. Although these models exhibit extensive variations in density as well as velocity, the density scale length is still typically much greater than the Sobolev length. The line transfer is thus treated using a Sobolev approach, as generalized by Rybicki & Hummer (1978) to take proper account of the multiple Sobolev resonances arising from the nonmonotonic velocity field. The resulting reduced-lambda-matrix equation describing nonlocal coupling of the source function is solved by iteration, and line profiles are then derived from formal solution integration using this source function. Two more approximate methods that instead use either a stationary or a structured, local source function yield qualitatively similar line-profiles, but are found to violate photon conservation by 10% or more. The full results suggest that such models may indeed be able to reproduce naturally some of the qualitative properties long noted in observed UV line profiles, such as discrete absorption components in unsaturated lines, or the blue-edge variability in saturated lines. However, these particular models do not yet produce the black absorption troughs commonly observed in saturated lines, and it seems that this and other important discrepancies (e.g., in acceleration time scale of absorption components) may require development of more complete models that include rotation and other 2-D and/or 3-D effects.

Puls, J.↗
DOE OSTI2020

Basis light-front quantization for a chiral nucleon-pion Lagrangian

We present the first application of the basis light-front quantization method to a simple chiral model of the nucleon-pion system as a relativistic bound state for the physical proton. In this work, the light-front mass-squared matrix of the nucleon-pion system is obtained within a truncated basis. The mass and the corresponding light-front wave function (LFWF) of the proton are computed by numerical diagonalization of the resulting mass-squared matrix. With the boost-invariant LFWF, we calculate the probability density distribution of the pion's longitudinal momentum fraction and the Dirac form factor of the proton.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

An unsupervised selection of polarimetric features useful for the segmentation and analysis of polarimetric synthetic aperture radar (SAR) data is presented. The technique is based on multidimensional clustering of the parameters composing the polarimetric covariance matrix of the data. Clustering is performed on the logarithm of these quantities. Once the polarimetric cluster centers have been determined, segmentation of the polarimetric data into regions is performed using a maximum likelihood polarimetric classifier. Segmentation maps are further improved using a Markov random field to describe the statistics of the regions and computing the maximum of the product of the local conditional densities. Examples with real polarimetric SAR imagery are given to illustrate the potential of this method.

Rignot, Eric↗
NASA NTRS2017

Nuclear Rocket Ceramic Metal Fuel Fabrication Using Tungsten Powder Coating and Spark Plasma Sintering

Nuclear thermal propulsion is an enabling technology for crewed Mars missions. An investigation was conducted to evaluate spark plasma sintering (SPS) as a method to produce tungsten-depleted uranium dioxide (W-dUO2) fuel material when employing fuel particles that were tungsten powder coated. Ceramic metal fuel wafers were produced from a blend of W-60vol% dUO2 powder that was sintered via SPS. The maximum sintering temperatures were varied from 1,600 to 1,850 C while applying a 50-MPa axial load. Wafers exhibited high density (>95% of theoretical) and a uniform microstructure (fuel particles uniformly dispersed throughout tungsten matrix).

Barnes, M. W.↗
DOE OSTI2021

Fault isolation and fault-tolerant control for Takagi-Sugeno fuzzy time-varying delay stochastic distribution systems

A fault isolation, estimation, and fault-tolerant control (FTC) scheme for nonlinear time-varying delay stochastic distribution control systems was presented in this paper. The Takagi-Sugeno fuzzy model was adopted to approach the nonlinear dynamics of time-varying delay systems. According to the output equivalence principle and Laplace transformation, an augmented state vector was given to solve the time-varying delay problem. When multiple actuator faults and interference occur simultaneously, fault detection, isolation and fault estimation was designed to obtained the fault information. To decouple faults and obtain the value and location information of the fault, the system was separated into two parts through the designed multiple conversion matrices, in which one subsystem was only affected by one actuator fault. This has simplified the design of fault isolation and estimation. A adaptive observer for fault estimation was given. Then, fault information such as the time, location, and size was determined. The observer gain matrices were calculated using linear matrix inequality (LMI). When a fault was detected and diagnosed, a FTC algorithm was devised using the proportional-integral control scheme to compensate the fault as much as possible. It has been shown that even if multiple faults actuator occurred simultaneously, the FTC controller still ensured the output probability density function of the system traced the desired probability density function when a fault occurred. Finally, the expected results were obtained through the simulation example, which confirmed the effectiveness of the method.

42 ENGINEERING↗
DOE OSTI2023

Noise-specific beating in the higher-level Ramsey curves of a transmon qubit

We report: in the higher levels of superconducting transmon devices and more generally charge sensitive devices, T 2 * measurements made in the presence of low-frequency time-correlated 1/f charge noise and quasiparticle-induced parity flips can give an underestimation of the total dephasing time. The charge variations manifest as beating patterns observed in the overlay of several Ramsey fringe curves and are reproduced with a phenomenological Ramsey curve model, which accounts for the charge variations. T 2 * dephasing times, which more accurately represent the total dephasing time, are obtained. The phenomenological model is compared with a Lindblad master equation model. Both models are found to be in agreement with one another and the experimental data. Finally, the phenomenological formulation enables a simple method in which the power spectral density for the low-frequency noise can be inferred from the overlay of several Ramsey curves.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Scalable learning of potentials to predict time-dependent Hartree–Fock dynamics

We propose a framework to learn the time-dependent Hartree–Fock (TDHF) inter-electronic potential of a molecule from its electron density dynamics. Although the entire TDHF Hamiltonian, including the inter-electronic potential, can be computed from first principles, we use this problem as a testbed to develop strategies that can be applied to learn a priori unknown terms that arise in other methods/approaches to quantum dynamics, e.g., emerging problems such as learning exchange–correlation potentials for time-dependent density functional theory. We develop, train, and test three models of the TDHF inter-electronic potential, each parameterized by a four-index tensor of size up to 60 × 60 × 60 × 60. Two of the models preserve Hermitian symmetry, while one model preserves an eight-fold permutation symmetry that implies Hermitian symmetry. Across seven different molecular systems, we find that accounting for the deeper eight-fold symmetry leads to the best-performing model across three metrics: training efficiency, test set predictive power, and direct comparison of true and learned inter-electronic potentials. All three models, when trained on ensembles of field-free trajectories, generate accurate electron dynamics predictions even in a field-on regime that lies outside the training set. To enable our models to scale to large molecular systems, we derive expressions for Jacobian-vector products that enable iterative, matrix-free training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Ab initio calculation of atomic solid hydrogen phases based on Gutzwiller many-body wave functions

We apply two ab initio many-body methods based on Gutzwiller wave functions, i.e., correlation matrix renormalization theory (CMRT) and Gutzwiller conjugate gradient minimization (GCGM), to the study of crystalline phases of atomic hydrogen. Both methods avoid empirical Hubbard U parameters and are free from double-counting issues. CMRT employs a Gutzwiller-type approximation that enables efficient calculations, while GCGM goes beyond this approximation to achieve higher accuracy at higher computational cost. By benchmarking against available quantum Monte Carlo (QMC) results, we demonstrate that while both methods are more accurate than the widely used density-functional theory, GCGM systematically captures additional correlation energy missing in CMRT, leading to significantly improved total energy predictions. We also show that by including the correlation energy Ec from local density approximation in the CMRT calculation, CMRT + E c produces energy in better agreement with the QMC results in these hydrogen lattice systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

NASMDR: a framework for miRNA-drug resistance prediction using efficient neural architecture search and graph isomorphism networks

Abstract As a frontier field of individualized therapy, microRNA (miRNA) pharmacogenomics facilitates the understanding of different individual responses to certain drugs and provides a reasonable reference for clinical treatment. However, the known drug resistance-associated miRNAs are not yet sufficient to support precision medicine. Although existing methods are effective, they all focus on modelling miRNA-drug resistance interaction graphs, making their performance bounded by the interaction density. In this study, we propose a framework for miRNA-drug resistance prediction through efficient neural architecture search and graph isomorphism networks (NASMDR). NASMDR uses attribute information instead of the commonly used interactive graph information. In the cross-validation experiment, the proposed framework can achieve an AUC of 0.9468 on the ncDR dataset, which is 2.29% higher than the state-of-the-art method. In addition, we propose a novel sequence characterization approach, k-mer Sparse Nonnegative Matrix Factorization (KSNMF). The results show that NASMDR provides novel insights for integrating efficient neural architecture search and graph isomorphic networks into a unified framework to predict drug resistance-related miRNAs. The codes for NASMDR are available at https://github.com/kaizheng-academic/NASMDR.

Zheng, Kai↗
DOE OSTI2021

Bound Constrained Partial DifferentialEquation Inverse Problem Solution by theSemi-Smooth Newton Method

We present the mathematical derivation, software implementation details, and computational results for a semi-smooth Newton method applied to two inverse problems governed by partial differential equations with bound constraints. The two problems share mathematical structural similarities to density-based topology optimization problems. The semi-smooth Newton method provides a mesh independent solution computation for the two test problems. A key step is that the complementarity part of the necessary optimality conditions are reformulated with the use of a complementarity functionφsuch that the complementarity conditions are satisfied if and only if a zero of a nonsmooth function has been obtained. The modular finite element package MFEM is utilized for the software implementation. In addition we constructed a matrix-free Operator to enable the use of efficient Krylov subspace IterativeSolver of MFEM for the solution of our two target problems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Single-Transducer, Ultrasonic Imaging Method for High-Temperature Structural Materials Eliminates the Effect of Thickness Variation in the Image

NASA Lewis Research Center's Life Prediction Branch, in partnership with Sonix, Inc., and Cleveland State University, recently advanced the development of, refined, and commercialized an advanced nondestructive evaluation (NDE) inspection method entitled the Single Transducer Thickness-Independent Ultrasonic Imaging Method. Selected by R&D Magazine as one of the 100 most technologically significant new products of 1996, the method uses a single transducer to eliminate the superimposing effects of thickness variation in the ultrasonic images of materials. As a result, any variation seen in the image is due solely to microstructural variation. This nondestructive method precisely and accurately characterizes material gradients (pore fraction, density, or chemical) that affect the uniformity of a material's physical performance (mechanical, thermal, or electrical). Advantages of the method over conventional ultrasonic imaging include (1) elimination of machining costs (for precision thickness control) during the quality control stages of material processing and development and (2) elimination of labor costs and subjectivity involved in further image processing and image interpretation. At NASA Lewis, the method has been used primarily for accurate inspections of high temperature structural materials including monolithic ceramics, metal matrix composites, and polymer matrix composites. Data were published this year for platelike samples, and current research is focusing on applying the method to tubular components. The initial publicity regarding the development of the method generated 150 requests for further information from a wide variety of institutions and individuals including the Federal Bureau of Investigation (FBI), Lockheed Martin Corporation, Rockwell International, Hewlett Packard Company, and Procter & Gamble Company. In addition, NASA has been solicited by the 3M Company and Allison Abrasives to use this method to inspect composite materials that are manufactured by these companies.

Roth, Don J.↗
DOE OSTI2020

Microstructures and mechanical properties of a modified 9Cr ferritic-martensitic steel in the as-built condition after additive manufacturing

A newly developed nano-structured high-Mn 9Cr ferritic-martensitic (FM) steel designed for additive manufacturing (Additive-manufactured Nanostructured Alloy, ANA) was fabricated via the direct energy deposition method. The as-printed ANA2 showed tensile properties (strength and elongation) and Charpy impact toughness (upper-shelf energy and ductile-brittle transition temperature) comparable to oxide-dispersion-strengthened (ODS) Eurofer and PM2000. Compared with wrought P91, the as-built ANA2 showed significantly higher yield strength but inferior Charpy impact toughness and ductility. Microstructural characterization revealed uniformly distributed sub-micron pores, an extremely high dislocation density, and a high density of ultrafine nano-structured precipitates in the matrix. The microstructures indicated the dislocations as the dominant strengthening element and the ultrafine precipitates as the primary contribution to estimated irradiation sink density. This work demonstrates the ability to exploit the unique consolidation properties of additive manufacturing to fabricate steels which marry the benefits of both ODS alloys and conventionally processed FM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Statistical properties of filaments in the cosmic web

ABSTRACT In the context of the cosmological and constrained Exploring the Local Universe with the reConstructed Initial Density field (ELUCID) simulation, this study explores the statistical characteristics of filaments within the cosmic web, focussing on aspects such as the distribution of filament lengths and their radial density profiles. Using the classification of the cosmic web environment through the Hessian matrix of the density field, our primary focus is on how cosmic structures react to the two variables $R_{\rm s}$ and $\lambda _{\rm th}$. The findings show that the volume fractions of knots, filaments, sheets, and voids are highly influenced by the threshold parameter $\lambda _{\rm th}$, with only a slight influence from the smoothing length $R_{\rm s}$. The central axis of the cylindrical filament is pinpointed using the medial-axis thinning algorithm of the COsmic Web Skeleton (COWS) method. It is observed that median filament lengths tend to increase as the smoothing lengths increase. Analysis of filament length functions at different values of $R_{\rm s}$ indicates a reduction in shorter filaments and an increase in longer filaments as $R_{\rm s}$ increases, peaking around $2.5R_{\rm s}$. The study also shows that the radial density profiles of filaments are markedly affected by the parameters $R_{\rm s}$ and $\lambda _{\rm th}$, showing a valley at approximately $2R_{\rm s}$, with increases in the threshold leading to higher amplitudes of the density profile. Moreover, shorter filaments tend to have denser profiles than their longer counterparts.

Zhang, Youcai (ORCID:0000000319674091)↗
DOE OSTI2025

Gauge-fixing quantum density operators at scale

We provide a theory, algorithms, and simulations of nonequilibrium quantum systems using a one-dimensional (1D) completely positive (CP), matrix-product (MP) density-operator (𝜌) representation. By generalizing the matrix product state's orthogonality center, to additionally store positive classical mixture correlations, the MP⁢𝜌 factorization naturally emerges. In this setting, we analytically and numerically examine the virtual gauge freedoms associated with the representation of quantum density operators. Based on this perspective, we simplify algorithms in certain limits to speed up the integration of the canonical-form master-equation dynamics. This enables us to quickly evolve under the dynamics of two-body quantum channels without resorting to optimization-based methods. In addition to this technical advance, we also scale up numerical examples and discuss implications for accurately modeling hardware architectures and predicting their performance in the near term. This includes an example of the quantum to classical transition of informationally leaky, i.e., decohering, qubits. In this setting, because of loss from environmental interactions, nonlocal complex coherence correlations are converted into global incoherent classical statistical mixture correlations. Lastly, the representation of both global and local correlations is discussed. We expect this work to have applications in additional nonequilibrium settings, beyond qubit engineering.

Gangapuram, Amit Jamadagni [Oak Ridge National Lab↗