Almost-periodic behavior of solutions of a nonlinear Volterra system
Almost periodic solutions of two nonlinear Volterra integral equations
Miller, R. K.↗
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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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Single-family-residence solar heating--Carlsbad, New Mexico
Solar-heating and hot-water system includes 408 square feet of flat-plate air collectors, rock storage bin, energy transport system, air-to-water heat exchanger, controls, and hot-water preheat tank. Hot-air oil furnace supplies auxiliary space heating, and electricity powers air-handler blower and hot water preheat pump. For 12 month period, system provided 43 percent of space-heating and 53 percent of hot-water energy; net energy savings were 23.072 million Btu.
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Optimizing Spacecraft Placement for Liaison Constellations
A navigation and communications network is proposed to support an anticipated need for infrastructure in the Earth-Moon system. Periodic orbits will host the constellations while a novel, autonomous navigation strategy will guide the spacecraft along their path strictly based on satellite-to-satellite telemetry. In particular, this paper investigates the second stage of a larger constellation optimization scheme for multi-spacecraft systems. That is, following an initial orbit down-selection process, this analysis provides insights into the ancillary problem of spacecraft placement. Two case studies are presented that consider configurations of up to four spacecraft for a halo orbit and a cycler trajectory.
lunar cycler orbits↗
Long Periodic Terms in the Solar System
The long period variations of the first eight planets in the solar system are studied. First, the Lagrangian solution is calculated and then the long period terms with fourth order eccentricities and inclinations are introduced into the perturbation function. A second approximation was made taking into account the short period terms' contribution, namely the perturbations of first order with respect to the masses. Special attention was paid to the determination of the integration constants. The relative importance of the different contributions is shown. It is useless, for example, to introduce the long period terms of fifth order if no account has been taken of the short period terms. Meanwhile, the terms that have been neglected would not introduce large changes in the integration constants. Even so, the calculation should be repeated with higher order short period terms and fifth order long periods.
Bretagnon, P.↗
Stochasticity in numerical solutions of the nonlinear Schroedinger equation
The cubically nonlinear Schroedinger equation is an important model of nonlinear phenomena in fluids and plasmas. Numerical solutions in a spatially periodic system commonly involve truncation to a finite number of Fourier modes. These solutions are found to be stochastic in the sense that the largest Liapunov exponent is positive. As the number of modes is increased, the size of this exponent appears to converge to zero, in agreement with the recent demonstration of the integrability of the spatially periodic case.
Shen, Mei-Mei↗
Towards Ab-Initio Simulations of Crystalline Defects at the Exascale Using Spectral Quadrature Density Functional Theory
Defects in crystalline solids play a crucial role in determining properties of materials at the nano, meso- and macroscales, such as the coalescence of vacancies at the nanoscale to form voids and prismatic dislocation loops or diffusion and segregation of solutes to nucleate precipitates, phase transitions in magnetic materials via disorder and doping. First principles Density Functional Theory (DFT) simulations can provide a detailed understanding of these phenomena. However, the number of atoms needed to correctly simulate these systems is often beyond the reach of many widely used DFT codes. The aim of this article is to discuss recent advances in first principles modeling of crystal defects using the spectral quadrature method. The spectral quadrature method is linear scaling with respect to the number of atoms, permits spatial coarse-graining, and is capable of simulating non-periodic systems embedded in a bulk environment, which allows the application of appropriate boundary conditions for simulations of crystalline defects. In this article, we discuss the state-of-the-art in ab-initio modeling of large metallic systems of the order of several thousand atoms that are suitable for utilizing exascale computing resourses.
36 MATERIALS SCIENCE↗
Design, development and demonstration of a warm gas distribution system Quarterly report, period ending 31 Mar. 1968
Component tests and system assembly for hydrazine fuel gas distribution system of torque generator for spacecraft attitude control
Boyce, W. D.↗
Probabilistic vibration analysis of nearly periodic structures
A disordered structure with weakly coupled subsystems has localized modes with the vibratory energy concentrated in one part of the mode shape. The localization of modes may significantly affect the forced vibration response, increasing the maximum vibration amplitude dramatically in some cases. It is the scope of this paper to study the forced vibration of nearly periodic systems consisting of almost identical substructures and to analyze their free and forced dynamic responses probabilistically. It is shown that the sensitivity of the forced response to the degree of localization depends on a combination of the symmetry of the mode, which is excited, and the phase difference between the forces acting on each substructure. These results might explain the range of contrasting conclusions of earlier publications on the effects of forced response on mistuned structures. A probabilistic analysis of the free and forced responses of a nearly periodic structure is shown to be useful in the design of structures that are sensitive to the degree of localization. The results of the probabilistic analysis are verified using Monte Carlo simulation.
Hamade, Karen S.↗
Specialists Meeting on Rotorcraft Dynamics, Moffett Field, Calif., February 13-15, 1974, Proceedings
Analysis of specific problems in rotorcraft dynamics. Topics include hingeless rotor theory, dynamic stall modelling, periodic systems identification, analysis of complex systems with phasing matrices, flapping stability, flap-lag dynamics at high advance ratios, finite element analysis and fuselage free-vibration characteristics, coupled rotor/frame vibration methods, gust response characteristics with unsteady stall effects, antiresonance theory, cyclic feathering motions and dynamic loads, control load envelope shaping, rotor aeroelasticity, use of Floquet theory, theory of proprotors and tilt-rotors, two-bladed teetering rotors, stability of air and ground resonance, vertical-plane pendulum absorbers, multicyclic jet-flap control, engine/frame interface dynamics, and others. The minutes of the question and answer periods following the presentations are presented in the supplement. Individual items are announced in this issue.
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ATS-6 - UCSD auroral particles experiment
The University of California at San Diego Auroral Particles Experiment aboard Applications Technology Satellite-6 (ATS-6) is discussed. The experiment is designed to investigate the time development of geomagnetic substorm particles, the confinement and loss of such particles, and the roles of plasma wave instabilities and characteristic system periodicities in substorm and general magnetospheric processes. The instrumentation includes a complement of five electrostatic charged particle detectors. Two detector assemblies are capable of rotation through 220 deg. The electrostatic curved plate energy/unit charge analyzers are ovoid, requiring particles to be bent only 55 deg to obtain azimuthal focusing. The inside of the plates is serrated to eliminate particles striking the sides. A post-analysis electrostatic lens consisting of two wire grids, one at the potential of the inner plate and one at the potential of ground, focuses particles strongly upon the center of the sensor. A spiraltron particle sensor detects the charged particles. The system has an energy range of five orders of magnitude with a lower extreme of less than 1 eV. Preliminary data are presented to illustrate phenomena which are observed as a result of the novel features described.
Mauk, B. H.↗
Tearing mode instability in a multiple current sheet system
The tearing mode and magnetic reconnection are studied for multiple current sheet systems by two-dimensional magnetohydrodynamic (MHD) simulations. Both the linear and nonlinear evolution of this process are anaylsed for laminar perturbations. The results illustrate the existence of a linear regime with a symmetric and antisymmetric mode and agree with previous analytic results (Otto and Birk, 1992). The nonlinear evolution shows a number of interesting new features and may explain some properties in corresponding studies of turbulent reconnection. For wavelengths larger than twice the current sheet separation the evolution of antisymmetric modes leads to an entire reconfiguration of the magnetic field and converts a major portion of the magnetic energy into kinetic energy. Antisymmetric modes with smaller wavelengths and symmetric modes are found to saturate. The influence of the value of the resistivity on the reconnection rate decreases in the nonlinear evolution, and the ratio of current sheet separation to wavelength seems to be of major importance. A comparion of the dynamics of periodic current sheets with the evolution of only two current sheets indicates that some of the results for the periodic system also apply to the evolution of only two interacting current sheets. The results are discussed with respect to observations of large-scale plasma and magnetic field reconfigurations in the magnetosheath and near the Earth's bow shock.
Yan, M.↗
Predictive Synthesis
Current solid state synthesis intrinsically involves a multidimensional space which is challenging to parametrize and predict. The diversity of extended structures comes from the diversity of basic properties of elements of the Periodic system which may exhibit a variety of bonding modes. The fundamental challenges of prediction of the preparative outcome are further complicated by practical synthetic issues. Current development in computational and experimental methods calls for collaborative efforts to make solid state synthesis more predictable. Overall, this Perspective discusses several steps in this direction, including integration of predictions of synthetic conditions with new structure predictions, widespread in situ studies to obtain a panoramic view of the reaction mechanism, and the creation of a synthetic database to properly document all synthetic efforts, including the unsuccessful ones.
36 MATERIALS SCIENCE↗
High Accuracy Transition Metal Effective Cores for the Many-Body Diffusion Monte Carlo Method
Practical applications of the real-space diffusion Monte Carlo (DMC) method require the removal of core electrons, where currently localization approximations of semilocal potentials are generally used in the projector. Accurate calculations of complex solids and large molecules demand minimizing the impact of approximated atomic cores. Prior works have shown that the errors from such approximations can be sizable in both finite and periodic systems. In this work, we show that a class of differential pseudopotentials, known as pseudo-Hamiltonians, can be constructed for the 3d transition metal atoms, entirely removing the need for any localization scheme in the DMC projector. As a proof of principle, we demonstrate the approach for the case of Co. In order to minimize errors in the pseudo-Hamiltonian at the many-body level, we generalize the recently proposed correlation-consistent pseudopotential generation scheme to successively close semilocal representations of the differential potentials. Our generation scheme successfully produces potentials tailored specifically for real space projector quantum Monte Carlo methods with low error at the many-body level, i.e., with many-body scattering properties very close to relativistic all-electron results. In particular, we show that the agreement with respect to atomic and molecular quantities reach chemical accuracy in many cases-on par with the most accurate semilocal pseudopotentials available. Further, our pseudo-Hamiltonian generation scheme utilizes standard quantum chemistry codes designed only to work with semilocal pseudopotentials, enabling straightforward generation of pseudo-Hamiltonians for additional elements in future works.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optimized Auxiliary Functions for Robust Mitigation of Finite-Size Errors in Periodic Hybrid Density Functional Theory
When calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a slowly converging quadrature error when approximating an integral in the reciprocal space by a finite sum. The singularity subtraction (SS) method offers a systematic approach for reducing this quadrature error and thus the FSE. Here, in this work, we first investigate the performance of the SS method in the simplest setting, aiming at reducing the FSE in exact exchange calculations by subtracting the Coulomb contribution with a single, adjustable Gaussian auxiliary function. We demonstrate that a simple fitting method can robustly estimate the optimal Gaussian width and leads to rapid convergence toward the TDL. Furthermore, we suggest new forms of the auxiliary function, whose optimal parameters could also be determined through least-squares fitting. For a range of semiconductors and insulators, the proposed auxiliary functions achieve robust, millihartree-level accuracy in hybrid density functional theory calculations, including cases with sparse k-meshes and large basis sets.
Quiton, Stephen Jon [University of California, Ber↗
DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn–Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. Further, this scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Quantum algorithm for electronic band structures with local tight-binding orbitals
While the main thrust of quantum computing research in materials science is to accurately measure the classically intractable electron correlation effects due to Coulomb repulsion, designing optimal quantum algorithms for simpler problems with well-understood solutions is a useful tactic to advance our quantum “toolbox”. With this in mind, we consider the quantum calculation of a periodic system’s single-electron band structure over a path through reciprocal space. Previous efforts have used the Variational Quantum Eigensolver algorithm to solve the energy of each band, which involves numerically optimizing the parameters of a variational quantum circuit to minimize a cost function, constructed as the expectation value of a Hamiltonian operator. Traditionally, a unique Hamiltonian operator is constructed for each k-point, so that many cost functions, each with their own parameter space, must be optimized to generate a single band. Similarly, calculating higher bands than the first has traditionally involved modifying the cost function with additional overlap terms to ensure higher-energy eigenstates are orthogonal to those of lower bands. In this paper, we adopt a direct space approach, using a novel hybrid first/second-quantized qubit mapping which allows us to construct a single Hamiltonian, and a single cost-function, suitable for solving the entire electronic band structure. In contrast to previous approaches, the k-point and the band index are selected by additional parameters in our quantum circuit, rather than through modifications to the cost function. The result is a technically and conceptually simpler approach to band structure calculations on a quantum computer. Moreover, we expect that the tools developed herein will motivate new strategies for tackling highly-correlated materials beyond the grasp of classical computing.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
MOFUN: a Python package for molecular find and replace
MOFUN is an open-source Python package that can find and replace molecular substructures in a larger, potentially periodic, system.
Boone, Paul↗
Exact constraints and appropriate norms in machine-learned exchange-correlation functionals
Machine learning techniques have received growing attention as an alternative strategy for developing general-purpose density functional approximations, augmenting the historically successful approach of human-designed functionals derived to obey mathematical constraints known for the exact exchange-correlation functional. More recently, efforts have been made to reconcile the two techniques, integrating machine learning and exact-constraint satisfaction. We continue this integrated approach, designing a deep neural network that exploits the exact constraint and appropriate norm philosophy to de-orbitalize the strongly constrained and appropriately normed (SCAN) functional. The deep neural network is trained to replicate the SCAN functional from only electron density and local derivative information, avoiding the use of the orbital-dependent kinetic energy density. The performance and transferability of the machine-learned functional are demonstrated for molecular and periodic systems.
Artificial neural networks↗