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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Solution of second-order linear system by matched asymptotic expansions

Matched asymptotic expansions (MAE) are used to obtain a first order approximation to the solution of a singularly perturbed second order system. A special case is considered in which the uniform asymptotic solution obtained by MAE is shown to converge to the exact solution. Ways in which the method can be used to sole higher-order linear systems, including those which are not singularly perturbed, are also discussed.

Ardema, M. D.↗
NASA NTRS1996

Theory and Computation of Optimal Low- and Medium- Thrust Orbit Transfers

This report presents new theoretical results which lead to new algorithms for the computation of fuel-optimal multiple-burn orbit transfers of low and medium thrust. Theoretical results introduced herein show how to add burns to an optimal trajectory and show that the traditional set of necessary conditions may be replaced with a much simpler set of equations. Numerical results are presented to demonstrate the utility of the theoretical results and the new algorithms. Two indirect methods from the literature are shown to be effective for the optimal orbit transfer problem with relatively small numbers of burns. These methods are the Minimizing Boundary Condition Method (MBCM) and BOUNDSCO. Both of these methods make use of the first-order necessary conditions exactly as derived by optimal control theory. Perturbations due to Earth's oblateness and atmospheric drag are considered. These perturbations are of greatest interest for transfers that take place between low Earth orbit altitudes and geosynchronous orbit altitudes. Example extremal solutions including these effects and computed by the aforementioned methods are presented. An investigation is also made into a suboptimal multiple-burn guidance scheme. The FORTRAN code developed for this study has been collected together in a package named ORBPACK. ORBPACK's user manual is provided as an appendix to this report.

Goodson, Troy D.↗
NASA NTRS1993

Structure and thermochemistry of ClO2 radicals

The structure of ClO2 has been calculated for the X 2A-double prime ground state using unrestricted Hartree-Fock (UHF), unrestricted second-order Moller-Plesset perturbation (UMP2), configuration interaction employing single and double excitation (CISD), and quadratic configuration interaction (QCI) ab initio molecular orbital methods. Calculations using UMP2 and CISD wave functions predict a ClO bond length of 1.728 +/- 0.01 A. The single-configuration-based QCI in the singles and doubles space with perturbation inclusion of triple substitutions, denoted QCISD(T), yield a ClO bond length of 2.205 A. The QCI results are consistent with results of Jensen (1990) who showed that the ClO bond length is 2.181 A using annihilated self-consistent methods (AUMP2). The thermochemistry of ClO2 radical has been calculated using MP2 and QCI methods employing an isodesmic scheme. Our scheme predicts the heat of formation for ClO2 at 0 K to be 24.6 +/- 2 kcal/mol.

Francisco, J. S.↗
NASA NTRS2010

Guidance and Control System for a Satellite Constellation

A distributed guidance and control algorithm was developed for a constellation of satellites. The system repositions satellites as required, regulates satellites to desired orbits, and prevents collisions. 1. Optimal methods are used to compute nominal transfers from orbit to orbit. 2. Satellites are regulated to maintain the desired orbits once the transfers are complete. 3. A simulator is used to predict potential collisions or near-misses. 4. Each satellite computes perturbations to its controls so as to increase any unacceptable distances of nearest approach to other objects. a. The avoidance problem is recast in a distributed and locally-linear form to arrive at a tractable solution. b. Plant matrix values are approximated via simulation at each time step. c. The Linear Quadratic Gaussian (LQG) method is used to compute perturbations to the controls that will result in increased miss distances. 5. Once all danger is passed, the satellites return to their original orbits, all the while avoiding each other as above. 6. The delta-Vs are reasonable. The controller begins maneuvers as soon as practical to minimize delta-V. 7. Despite the inclusion of trajectory simulations within the control loop, the algorithm is sufficiently fast for available satellite computer hardware. 8. The required measurement accuracies are within the capabilities of modern inertial measurement devices and modern positioning devices.

Bryson, Jonathan Lamar↗
DOE OSTI2025

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

Modeling complex materials using high-fidelity, ab initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies using the same physics in a many-body perturbative approach that can be more accurate than generalized-gradient density functional theory (DFT) methods. However, GW/RPA implementations have historically been limited to either specific materials classes or application toward small chemical systems. Here, the static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has previously been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts. We benchmarked RPA total energy calculations using the subspace approximation across a diverse test suite of materials for a variety of computational parameters. The benchmarking quantifies the impact of different extrapolation procedures for representing the static polarizability at infinite screened cutoff, and shows that using screened cutoffs above 20-25 Ryd result in diminishing accuracy returns for predicting RPA total energies. Additionally, for moderately sized electrocatalytic models, 2-3 times fewer computational resources are used to compute RPA total energies by representing the static polarizability with 20-30% of the static subspace basis, with an error of approximately 0.01 eV or better in RPA adsorption energy calculations. Finally, we show that for these electrochemical models RPA can shift DFT adsorption energy shifts by up to 0.5 eV and that GW can frequently shift DFT eigenvalues of surface and adsorbate states by approximately 0.5-1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Big Data and AI at DoE's Legacy Sites - 20546

More than 30 years have passed since DOE started the decommissioning of nuclear weapon complexes and the clean-up of soil and groundwater. All the sites have been collecting and archiving soil and groundwater monitoring datasets; particularly contaminant concentration time-series. These datasets provide unparalleled opportunities to understand the system behavior (including more fundamental hydrological and geochemical processes, the response to various perturbations, the long-term trend and environmental decay rate towards the regulatory limit). This understanding is critical for providing multiple lines of evidences that can support site closure. In this study, we explore the machine learning (ML) and artificial intelligence (AI) applications to the long-term soil and groundwater management at DoE's legacy sites. ML can improve our understanding of the subsurface systems, which is critical for long-term monitoring and management of the sites, while AI can automate or support some of decision-making processes (e.g., anomaly detection, monitoring well placements). The particular focuses are to develop general algorithms to: (1) to identify distinct spatiotemporal patterns and to identify several groups that have similar temporal behaviors, using unsupervised clustering methods, (2) identify the different temporal scales of hydrological responses to climate perturbations by time-series analysis, and (3) reduce the number of monitoring wells by identifying the minimum sufficient number of wells to capture the heterogeneity of the groundwater contaminant plume and concentration distribution, using the Gaussian Process model. We demonstrate our methodology at the Savannah River Site F-Area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Constrained Extrapolation Problem and Order-Dependent Mappings

In this work, we consider the problem of extrapolating the perturbation series for the dilute Fermi gas in three dimensions to the unitary limit of infinite scattering length and into the BEC region, using the available strong-coupling information to constrain the extrapolation problem. In this constrained extrapolation problem (CEP) the goal is to find classes of approximants that give well converged results already for low perturbative truncation orders. First, we show that standard Padé and Borel methods are too restrictive to give satisfactory results for this CEP. A generalization of Borel extrapolation is given by the so-called Maximum Entropy extrapolation method (MaxEnt). However, we show that MaxEnt requires extensive elaborations to be applicable to the dilute Fermi gas and is thus not practical for the CEP in this case. Instead, we propose order-dependent-mapping extrapolation (ODME) as a simple, practical, and general method for the CEP. Here, we find that the ODME approximants for the ground-state energy of the dilute Fermi gas are robust with respect to changes of the mapping choice and agree with results from quantum Monte Carlo simulations within uncertainties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Algorithm advances and applications of time‐dependent first‐principles simulations for ultrafast dynamics

Abstract Far from equilibrium phenomenon is a central theme of contemporary material research. Such phenomenon can exhibit itself in atomic structure and dynamics, but very often it also happens as non‐equilibrium phenomenon in the electronic structure. In ab initio material simulation, density functional theory (DFT) has played an essential role in studying electronic ground state problems. For excited states, besides many‐body perturbation theory, another powerful tool is the time dependent DFT (TDDFT) method. In particular, the real‐time TDDFT (rt‐TDDFT) method can be used to simulate many non‐equilibrium phenomena directly. Here we introduce our works on some algorithm advances based on our recently rt‐TDDFT method. This method uses the plane‐wave basis set, and significantly accelerates its efficiency by increasing the time step from 0.1–1 as in traditional methods to 0.2–0.5 fs. The noncollinear magnetic moments and spin–orbit coupling have also been included in our rt‐TDDFT method. Furthermore, a Boltzmann‐TDDFT algorithm has been developed to solve the hot carrier overheating problem in Ehrenfest dynamics, and a natural orbital branching algorithm has been developed to overcome the mean‐field approximation in Ehrenfest dynamics nuclear trajectory, thus allows stochastic multiple paths in chemical reactions. Utilizing these methods, we have studied the photoinduced ultrafast demagnetization, ultrafast phase transition, energy transfer between plasmon and hot carriers, as well as the high‐energy ion implantation and low‐energy atomic diffusion in semiconductors. We believe the tools as the ones introduced here can enable us to study a wide range of phenomena which are of great interest in modern day material research. This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Ab Initio Electronic Structure Methods Electronic Structure Theory > Density Functional Theory

Liu, Wen‐Hao↗
DOE OSTI2025

The three-point form factor of Tr ϕ 3 to six loops

We study the three-point form factor of the length-three half-BPS operator (Tr ϕ 3 ) in planar $\mathcal{N}$ = 4 Super-Yang-Mills theory, using analyticity and integrability methods. We find that the functions describing the form factor in perturbation theory live in the same restrictive space of multiple polylogarithms as the one describing the form factor of the stress-tensor operator (Tr ϕ 2 ). Furthermore, we find that the leading-order data in the collinear limit provided by the form factor operator product expansion (FFOPE) is enough to fix the form factor uniquely, at least through six loops. We perform various tests of our results using the subleading FFOPE corrections. We also analyze the form factor in the Regge limit where two Mandelstam invariants are large; we obtain a compact representation for the form factor in this limit which is valid to all orders in the coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Rotating spokes, potential hump and modulated ionization in radio frequency magnetron discharges

Here, in this work, the transition from the gradient drift instability (GDI) into an m = 1 rotating spoke in the radio frequency magnetron discharge was studied by means of the two-dimensional axial-azimuthal (z–y) particle-in-cell/Monte Carlo collision method. The kinetic model combined with the linear analysis of the perturbation revealed that the cathode sheath (axial) electric field E z triggers the GDI, deforming the local potential until the instability condition is not fulfilled and the fluctuation growth stops in which moment the instability becomes saturated. The potential deformation consequently leads to the formation of the potential hump, surrounding which the azimuthal electric field E y is present. The saturation level of E y was found to be synchronized with and proportional to the time-changing voltage applied at the cathode, resulting in the RF-modulation of the electron heating in the E y due to $\nabla B$ drift. In the saturated stage of the instability, it was shown that the rotation velocity and direction of the spoke present in the simulations agree well with the experimental observation (Panjan 2019 J. Appl. Phys.125 203303). In the instability linear stage, the instability mode wavelength and the growth rate were also found to be in good agreement with the prediction of the GDI linear fluid theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Quantum Kerr learning

Quantum machine learning is a rapidly evolving field of research that could facilitate important applications for quantum computing and also significantly impact data-driven sciences. In our work, based on various arguments from complexity theory and physics, we demonstrate that a single Kerr mode can provide some 'quantum enhancements' when dealing with kernel-based methods. Using kernel properties, neural tangent kernel theory, first-order perturbation theory of the Kerr non-linearity, and non-perturbative numerical simulations, we show that quantum enhancements could happen in terms of convergence time and generalization error. Furthermore, we make explicit indications on how higher-dimensional input data could be considered. Finally, we propose an experimental protocol, that we call quantum Kerr learning, based on circuit QED.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Effects of Compounded Model Size Reductions on Adversarial Robustness

Recent advances in Edge AI and Tiny Machine Learning (TinyML) have enabled the deployment of machine learning models on resource-constrained environments. However, deploying these models on edge devices, such as micro-controllers, requires significant model footprint reduction through a variety of techniques such as quantization, pruning, and clustering. While these optimization methods offer considerable advantages, they potentially introduce AI-related security vulnerabilities, particularly concerning model robustness with respect to adversarial AI attacks. Prior research has extensively examined the impact of quantization on adversarial robustness; however, the effects of alternative reduction techniques and their combinations remain understudied. This paper investigates the impact of model size reduction techniques on adversarial robustness, when applied individually and combined. We utilized Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks to generate adversarial perturbations for both training and testing data, and then evaluated the models' accuracy under adversarial training conditions. Our findings revealed that reduction techniques generally diminished robustness; although, combining techniques was not found to make robustness any worse than when applied individually. Moreover, specific techniques can potentially enhance resistance to small size perturbations. This research provides insights into the trade-offs between model size reduction and security, establishing a foundation for future investigations into improving adversarial training techniques and methodologies for maintaining robustness while preserving memory footprint benefits.

Austria, Phillipe [ORNL] (ORCID:0000000236223973)↗
DOE OSTI2021

Machine learning to generate gridded extreme precipitation data sets for global land areas with limited in situ measurements

There is a strong need for gridded observational data sets that describe the climatology of extreme precipitation across the globe; such data sets are critical for quantifying precipitation extremes and their corresponding influence on large perturbations on surface and groundwater systems and flooding. Machine learning (ML) methods can be used to generate pseudo in situ measurements of the climatology of extreme precipitation for land regions with poor sampling by matching relevant geographic (e.g., orography) and atmospheric (e.g., surface temperature, precipitation, and pressure) variables for densely sampled regions and those with limited geographic sampling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nuclear Theory from First Principles to Forefront Experiments (Final Report for DE-SC0018638)

The Lee research group is a part of the Nuclear Lattice Effective Field Theory Collaboration, which has developed and performed ab initio lattice simulations of nuclear structure, scattering, reactions, and many-body systems. The other senior members of the collaboration include Ulf-G. Meißner at Bonn/Julich, Evgeny Epelbaum and Hermann Krebs at Bochum, Timo Lahde and Thomas Luu at Julich, and Gautam Rupak at Mississippi State. Our letter “Ab initio alpha-alpha scattering” was featured in a Nature News and Views article. Another letter “Nuclear binding near a quantum phase transition” was highlighted in a Viewpoint article in the online APS journal Physics as well as a news article in the IOP publication Physics World (September 21, 2016). Our letter “Eigenvector continuation with subspace learning” was also highlighted a Synopsis article in Physics. There are many promising ab initio approaches being used to calculate the properties of few-and many-nucleon systems. This includes the no-core shell model, symmetry-adapted no-core shell model quantum Monte Carlo, auxiliary-field diffusion Monte Carlo, self-consistent Green’s functions, many-body perturbation theory, in-medium similarity renormalization group, and coupled cluster methods. Lattice effective field theory is another ab initio approach which combines the framework of effective field theory with lattice Monte Carlo methods to allow favorable scaling from few- to many-body systems. Perhaps the most important aspect of lattice effective field theory is that its strengths and weaknesses are orthogonal to that of other ab initio methods. For example, lattice effective field theory has little difficulty in probing cluster structures and collectivity, while such features are much more difficult using other methods. Furthermore it can be used to compute superfluid condensate fractions as well as the phase diagram of strongly matter and the density and temperature dependence of clustering. Lattice effective field theory was first used in simulations of infinite nuclear matter and infinite neutron matter with pions and without pions. In addition to the efforts by our collaboration, there have been recent efforts by other groups as well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Bounds on Velocity-dependent Dark Matter–Proton Scattering from Milky Way Satellite Abundance

We use the latest measurements of the Milky Way satellite population from the Dark Energy Survey and Pan-STARRS1 to infer the most stringent astrophysical bound to date on velocity-dependent interactions between dark matter particles and protons. We model the momentum-transfer cross section as a power law of the relative particle velocity v with a free normalizing amplitude, σ MT = σ 0 v n , to broadly capture the interactions arising within the nonrelativistic effective theory of dark matter–proton scattering. The scattering leads to a momentum and heat transfer between the baryon and dark matter fluids in the early universe, ultimately erasing structure on small physical scales and reducing the abundance of low-mass halos that host dwarf galaxies today. From the consistency of observations with the cold collisionless dark matter paradigm, using a new method that relies on the most robust predictions of the linear perturbation theory, we infer an upper limit on σ0 of 1.4 × 10 -23 , 2.1 × 10 -19 , and 1.0 × 10 -12 cm 2 , for interaction models with n = 2, 4, and 6, respectively, for a dark matter particle mass of 10 MeV. These results improve observational limits on dark matter–proton scattering by orders of magnitude and thus provide an important guide for viable sub-GeV dark matter candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Asymptotic theory of a slender rotating beam with end masses.

The method of matched asymptotic expansions is employed to solve the singular perturbation problem of the vibrations of a rotating beam of small flexural rigidity with concentrated end masses. The problem is complicated by the appearance of the eigenvalue in the boundary conditions. Eigenfunctions and eigenvalues are developed as power series in the perturbation parameter beta to the 1/2 power, and results are given for mode shapes and eigenvalues through terms of the order of beta.

Whitman, A. M.↗