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Results for “correlated systems”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

The use of correlation receiving systems for detection of noise sources at short distances

The use of a directional receiving system to detect noise sources masked by isotropic noise field interference at distances comparable with the distance between the two receivers, was discussed. Wide band noise was also examined. Results indicate the following limitations must be considered when using the method: (1) the system is directional only in the plane of the base, (2) directional power of the system is impaired with a decrease in the bandwidth of the noise source spectrum, (3) the system does not permit unambiguous determination of the direction to noise sources, located on both sides of the base line, and (4) the system has a comparatively low output signal-to-noise ratio.

Tarabarin, V. V.↗
NASA NTRS2001

Development of an Early Warning Fire Detection System using Correlation Spectroscopy

Combustion byproducts are numerous. A few examples of the gaseous byproducts include carbon dioxide, carbon monoxide, hydrogen chloride, hydrogen cyanide and ammonia. For detecting these chemical species, classic absorption spectroscopy has been used for many decades, but the sensitivity of steady-state methods is often unsuitable for the detection of trace compounds at the low levels (parts per million to parts per billion) appropriate for scientific purposes. This is particularly so for monitoring equipment, which must be compact and cost-effective, and which is often subjected to shock, vibration, and other environmental effects that can severely degrade the performance of high-sensitivity spectrometers in an aircraft. Steady-state techniques also suffer from a lack of specificity; the deconvolution of the spectra of complex mixtures is a laborious and error prone process. These problems are exacerbated in remote fiber-optic monitoring where, for practical reasons, the fundamental absorbance region of the spectrum (often between 3 and 8 microns) is inaccessible, and the low-strength, closely spaced, near-infrared overtone absorbance bands must be used. We circumvented these challenges by employing correlation spectroscopy, a variation of modulation spectroscopy.

Goswami, K.↗
NASA NTRS1970

Optical probing of supersonic aerodynamic turbulence

Laser quasi-schlieren system and laser shadow-correlation system retrieve flow-related signals sufficient for computing accurate, reproducible correlation peaks. Statistical method for obtaining one-shot measurements of the decay history of turbulent structures in a stationary frame of reference is discussed.

Cikanek, H. A., Jr.↗
DOE OSTI2024

Active learning approach to simulations of strongly correlated matter with the ghost Gutzwiller approximation

Quantum embedding (QE) methods such as the ghost Gutzwiller approximation (gGA) offer a powerful approach to simulating strongly correlated systems, but come with the computational bottleneck of computing the ground state of an auxiliary embedding Hamiltonian (EH) iteratively. In this work, we introduce an active learning (AL) framework integrated within the gGA to address this challenge. The methodology is applied to the single-band Hubbard model and results in a significant reduction in the number of instances where the EH must be solved. Through a principal component analysis (PCA), we find that the EH parameters form a low-dimensional structure that is largely independent of the geometric specifics of the systems, especially in the strongly correlated regime. Our AL strategy enables us to discover this low-dimensionality structure on the fly, while leveraging it for reducing the computational cost of gGA, laying the groundwork for more efficient simulations of complex strongly correlated materials. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
NASA NTRS2011

2014/2219 Tri-Point Crack Analysis

Friction stir welding (FSW) is a solid state welding process with potential advantages for aerospace and automotive industries dealing with light alloys. Self-reacting friction stir welding (SR-FSW) is one variation of the FSW process being developed at the National Aeronautics and Space Administration (NASA) for use in the fabrication of propellant tanks. Friction plug welding is used to seal the exit hole that remains in a circumferential SR-FSW. The objective of this study was to evaluate the deformation response at the tips of cracks located in the heat affected zone of friction plug welds and to study the fracture behavior of welds with defects in the form of fatigue cracks. The study used existing 2014-T6 to 2219-T87 self-reacting friction stir weld panels with 2219-T87 friction plug welds. Electro-discharge machined (EDM) notches were machined into the heat affected zone of the plug at the plug-to-base metal interface. Samples were then cycled to generate a fatigue crack emanating from the notch. After the fatigue crack reached a pre-defined length, a speckle pattern was applied and the ARAMIS system (a three dimensional imaging correlation system) was used to measure the deformations at the crack tip under a sequence of loads. Testing was conducted at ambient laboratory conditions. Fracture data from the testing was analyzed to evaluate residual strength capability of the panel as a function of flaw size. ARAMIS strain data was evaluated to examine strain and deformation patterns that develop around the crack tip and at the plug/weld interfaces. Four samples were used in this study, with three samples in a post-weld heat treated condition. Three samples contained large diameter plugs (M5) and one sample contained a small diameter plug (M3). Two samples were 4 inches in width and two samples were 8.5 inches in width. All samples failed through the precrack with residual strengths ranging from 37 ksi to 42 ksi.

Horton, Karla Renee↗
DOE OSTI2024

Theoretical Studies in Very Strongly Correlated Matter

In this Final Technical Report, a summary of research carried out by the PI and his group from 9/1/2006 to 8/31/2023, on developing new approaches to understand very strongly correlated systems is provided. Novel materials where interactions dominate the kinetic energy (due to hopping motion) of electrons, pose a major puzzle in condensed matter systems. These are located in regimes of parameters where traditional theoretical approaches fail, and new concepts and formalisms are called for. In the area of thermal or thermoelectrical transport the PI has found two new formulas for the Seebeck coefficient. These are easier to apply than the general Kubo formulas, and give interesting insights that lead to new directions in the search for better materials for energy harvesting.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

One-Step Relativistic Driven Similarity Renormalization Group Multireference Perturbation Theory

We present an efficient implementation of a one-step relativistic second-order multireference perturbation theory based on the multireference driven similarity renormalization group (MR-DSRG) using the exact two-component (X2C) Hamiltonian, which we denote X2C-DSRG-MRPT2. We show that the X2C-DSRG-MRPT2 method can accurately capture spin–orbit coupling (SOC) effects in the electronic structure of strongly correlated systems containing elements across the periodic table. We further demonstrate that the X2C-DSRG-MRPT2 method, through its variational treatment of SOC effects, can yield spin–orbit splittings with mean absolute percentage errors consistently below 7% with respect to experimental values for systems containing up to sixth row elements. With its modest computational scaling (fourth power in system size for the perturbative step) and high accuracy, X2C-DSRG-MRPT2 provides a promising avenue for the routine treatment of relativistic effects in strongly correlated molecular systems.

Hamiltonians↗
DOE OSTI2020

Automation of Active Space Selection for Multireference Methods via Machine Learning on Chemical Bond Dissociation

Predicting and understanding the chemical bond is one of the major challenges of computational quantum chemistry. Kohn–Sham density functional theory (KS-DFT) is the most common method, but approximate density functionals may not be able to describe systems where multiple electronic configurations are equally important. Multiconfigurational wave functions, on the other hand, can provide a detailed understanding of the electronic structures and chemical bonds of such systems. In the complete active space self-consistent field (CASSCF) method, one performs a full configuration interaction calculation in an active space consisting of active electrons and active orbitals. However, CASSCF and its variants require the selection of these active spaces. This choice is not black box; it requires significant experience and testing by the user, and thus active space methods are not considered particularly user-friendly and are employed only by a minority of quantum chemists. Our goal is to popularize these methods by making it easier to make good active space choices. Here, we present a machine learning protocol that performs an automated selection of active spaces for chemical bond dissociation calculations of main group diatomic molecules. The protocol shows high prediction performance for a given target system as long as a properly correlated system is chosen for training. Good active spaces are correctly predicted with a considerably better success rate than random guess (larger than 80% precision for most systems studied). Our automated machine learning protocol shows that a “black-box” mode is possible for facilitating and accelerating the large-scale calculations on multireference systems where single-reference methods such as KS-DFT cannot be applied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Object enhanced optical correlation

A major drawback of optical correlator systems is the poor quality of correlation signals. Background noise is one of the many sources of false correlation peaks. However, by reconstructing an input scene with the object's amplitude function, an object-enhanced scene - used as input to the optical correlators - (with respect to background) can be obtained. Thus, the optical correlation of this enhanced image improves the signal-to-noise ratio in the correlation image. Furthermore, construction of a filter plane mask that permits simultaneous scene enhancement and cross-correlation operations is described. Experimental results demonstrate the practicality of this approach.

Scholl, Marija S.↗
DOE OSTI2025

Lattice distortions and metal-insulator transition in hexagonal FeS

Using total x-ray scattering and density functional theory calculations based on experimental data, we study the metal-insulator transition (MIT) in the strongly correlated system FeS with hexagonal symmetry. We find that it arises from the combined effect of static lattice distortions and antiferromagnetic ordering, while electron-electron correlations appear to play a minor role. The presence of local lattice distortions above the MIT explains well the evolution of transport and magnetic properties with changing temperature or pressure. Intrinsically, lattice distortions in hexagonal FeS act as lattice degrees of freedom that bridge competing electronic phases, thus facilitating transitions between them. The mechanism of MIT operating in h-FeS appears to be common to strongly correlated binary systems involving 3d transition metals, warranting further investigations on the lattice distortions-property relationship in this broad class of materials using the approach adopted here.

36 MATERIALS SCIENCE↗