SEARCH · Engineering Papers

Results for “dynamical correlation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,765 records · Page 98

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Realistic simulations of spin squeezing and cooperative coupling effects in large ensembles of interacting two-level systems

We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which combines the mean-field dynamics of a spin ensemble with a Monte Carlo sampling of discrete initial spin values to account for quantum correlations. Here we show how this approach can be generalized for dissipative spin systems by replacing the deterministic mean-field evolution by a stochastic process, which describes the decay of coherences and populations while preserving the length of each spin. We demonstrate the application of this technique for simulating nonclassical spin-squeezing effects or the dynamics and steady states of cavity QED models with 10 5 interacting two-level systems. This opens up the possibility to perform accurate real-scale simulations of a diverse range of experiments in quantum optics or with solid-state spin ensembles under realistic laboratory conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Halted-pendulum Relaxation: Application to White Dwarf Binary Initial Data

Studying compact-star binaries and their mergers is integral to determining progenitors for observable transients. Today, compact-star mergers are typically studied via state-of-the-art computational fluid dynamics codes. One such numerical technique, smoothed particle hydrodynamics (SPH), is frequently chosen for its excellent mass, energy, and momentum conservation. The natural treatment of vacuum and the ability to represent highly irregular morphologies make SPH an excellent tool for the study of compact-star binaries and mergers. For many scenarios, including binary systems, the outcome of simulations is only as accurate as the initial conditions. For SPH, it is essential to ensure that the particles are distributed regularly, representing the initial density profile but without long-range correlations. Particle noise in the form of high-frequency local motion and low-frequency global dynamics must be damped out. Damping the latter can be as computationally intensive as the actual simulation. We discuss a new and straightforward relaxation method, halted-pendulum relaxation (HPR), to remove global oscillation modes of SPH particle configurations. In combination with effective external potentials representing gravitational and orbital forces, we show that HPR has an excellent performance in efficiently relaxing SPH particles to the desired density distribution and removing global oscillation modes. We compare the method to frequently used relaxation approaches and test it on a white dwarf binary model at its Roche-lobe overflow limit. We highlight the importance of our method in achieving accurate initial conditions and its effect on achieving circular orbits and realistic accretion rates when compared with other general relaxation methods.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. Here, we designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with <0.4 m geolocation accuracy, <0.1 m altitude drift, and <1.5° error of the fiber optic from nadir position during scanning. Weekly seasonal campaigns reveal that SIF outperforms conventional VIs such as the normalized difference vegetation index (NDVI) for distinguishing plots with different crop yield potential, especially after canopy closure when NDVI tends to saturate. The UAS can capture the diurnal dynamics of SIF and PRI for both corn and soybean. At the seasonal scale, SIF acquired from the UAS correlates well with that from a fixed SIF tower system ( R 2 = 0.81), which measured the same target albeit with different footprints, demonstrating the capability of UAS in characterizing the seasonal progression of crop activity. In conclusion, our newly developed UAS provides high-quality SIF and hyperspectral reflectance, facilitating mechanistic understanding of the physiological control on photosynthesis dynamics. Our findings also imply that this UAS could enable extension of fixed tower-based systems to monitor multiple targets from diurnal to seasonal scales and improve monitoring of heterogeneous fields.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Performance of wave function and Green's function methods for non-equilibrium many-body dynamics

Theoretical descriptions of the non-equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on the truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In this work, we select representative cases of each of the methods and address how these complementary approaches capture the dynamics driven by intense field perturbations to non-equilibrium states. Under strong driving, the systems are characterized by strong entanglement of the single-particle density matrix and natural populations approaching those of a strongly interacting equilibrium system. We generate a representative set of results that are numerically exact and form a basis for a critical comparison of the distinct families of methods. We demonstrate that the compressed formulation based on similarity-transformed Hamiltonians (coupled-cluster approach) is practically exact in weak fields and, hence, weakly or moderately correlated systems. Coupled cluster, however, struggles for strong driving fields, under which the system exhibits strongly correlated behavior, as measured by the von Neumann entropy of the single-particle density matrix. The dynamics predicted by Green's functions in the (widely popular) G W approximation are less accurate, but improve significantly upon the mean-field results in the strongly driven regime. Published by the American Physical Society 2025

Reeves, Cian C. (ORCID:0009000642581845)↗

NASA NTRS1987

A dynamic threshold method for obtaining cloud cover from satellite imagery data

Errors in cloud cover derived by using a fixed threshold applied to imagery data depend not only on the fractional cover but also on cloud size. As a result, a fixed threshold applied to two scenes having the same cloud cover will produce different estimates of the cover when the clouds in the two scenes have different sizes. To allow for this influence due to cloud size, a dynamic threshold method is presented. In this method an infrared threshold is adjusted to achieve the highest correlation between the threshold-derived cloud cover and the mean emitted radiance for mesoscale-sized subregions within the scene. For single-layered cloud systems this threshold achieves a cancellation of errors in the cloud cover for the subregions so that the resulting cloud cover for the region and the associated estimates of cloud properties are in fair agreement with estimates obtained using the spatial coherence method. The agreement illustrates the validity of the layered cloud model used in different ways by the two methods. The performance of the dynamic threshold method is contrasted with that of a fixed threshold applied to the same data in order to illustrate the merits of applying a scene-dependent threshold.

Coakley, James A., Jr.↗

DOE OSTI2023

Wavelength-Dependent Excitonic Properties of Covalent Organic Frameworks Explored by Theory and Experiments

Many aspects of the correlation between physical structure, light harvesting, and excitonic properties of covalent organic frameworks (COFs) remain unclear despite being key properties determining their photocatalytic function. One area of COF research that could bring clarity is through using both electronic structure theory and time-resolved spectroscopic analysis over a series of isomeric COFs. Here, we show structure-property relationships between four imine COFs built from a combination of ditopic and tritopic monomers using transient absorption spectroscopy together with time-dependent density functional theory. We find that monomer selection only moderately affects the charge transfer (CT) behavior of the COFs. Instead, we infer that imine chemistry profoundly impacts CT by acting as a CT mediator. Moreover, we discover two distinct valence bands arising from varying degrees of locally excited/CT mixing, which is responsible for energy dependent exciton dynamics. Finally, we use theory to hypothesize that interlayer interactions can modify excitonic properties that we correlate with tail states commonly observed, but rarely investigated in COFs. Furthermore, these results reveal that imine chemistry should be recognized as a very important factor to consider in the development of COF photocatalysts and the correlation of their structural environment with light harvesting and CT properties that should ultimately determine their photocatalytic function.

14 SOLAR ENERGY↗

DOE OSTI2020

Temperature dependence of nuclear quantum effects on liquid water via artificial neural network model based on SCAN meta-GGA functional

We investigate the temperature dependence of nuclear quantum effects (NQEs) on structural and dynamic properties of liquid water by training a neural network force field using first-principles molecular dynamics (FPMD) based on the strongly constrained and appropriately normed meta-generalized gradient approximation exchange-correlation approximation. The FPMD simulation based on density functional theory has become a powerful computational approach for studying a wide range of condensed phase systems. However, its large computational cost makes it difficult to incorporate NQEs in the simulation and investigate temperature dependence of various properties. To circumvent this difficulty, we use an artificial neural network model and employ the thermostatted ring polymer MD approach for studying the temperature dependence of NQEs on various properties. The NQEs generally bring the radial distribution functions closer to the experimental measurements. Translational diffusivity and rotational dynamics of water molecules are both slowed down by the NQEs. The competing inter-molecular and intra-molecular quantum effects on hydrogen bonds, as discussed by Habershon, Markland, and Manolopoulos [J. Chem. Phys. 131(2), 024501 (2019)], can explain the observed temperature dependence of the NQEs on the dynamical properties in our simulation.

Yao, Yi (ORCID:0000000299576979)↗

DOE OSTI2023

River thorium concentrations can record bedrock fracture processes including some triggered by distant seismic events

Fractures are integral to the hydrology and geochemistry of watersheds, but our understanding of fracture dynamics is very limited because of the challenge of monitoring the subsurface. Here we provide evidence that long-term, high-frequency measurements of the river concentration of the ultra-trace element thorium (Th) can provide a signature of bedrock fracture processes spanning neighboring watersheds in Colorado. River Th concentrations show abrupt (subdaily) excursions and biexponential decay with approximately 1-day and 1-week time constants, concentration patterns that are distinct from all other solutes except beryllium and arsenic. The patterns are uncorrelated with daily precipitation records or seasonal trends in atmospheric deposition. Groundwater Th analyses are consistent with bedrock release and dilution upon mixing with river water. Most Th excursions have no seismic signatures that are detectable 50 km from the site, suggesting the Th concentrations can reveal aseismic fracture or fault events. We find, however, a weak statistical correlation between Th and seismic motion caused by distant earthquakes, possibly the first chemical signature of dynamic earthquake triggering, a phenomenon previously identified only through geophysical methods.

58 GEOSCIENCES↗

DOE OSTI2021

Solid-state NMR of unlabeled plant cell walls: high-resolution structural analysis without isotopic enrichment

Abstract Background Multidimensional solid-state nuclear magnetic resonance (ssNMR) spectroscopy has emerged as an indispensable technique for resolving polymer structure and intermolecular packing in primary and secondary plant cell walls. Isotope ( 13 C) enrichment provides feasible sensitivity for measuring 2D/3D correlation spectra, but this time-consuming procedure and its associated expenses have restricted the application of ssNMR in lignocellulose analysis. Results Here, we present a method that relies on the sensitivity-enhancing technique Dynamic Nuclear Polarization (DNP) to eliminate the need for 13 C-labeling. With a 26-fold sensitivity enhancement, a series of 2D 13 C– 13 C correlation spectra were successfully collected using the unlabeled stems of wild-type Oryza sativa (rice). The atomic resolution allows us to observe a large number of intramolecular cross peaks for fully revealing the polymorphic structure of cellulose and xylan. NMR relaxation and dipolar order parameters further suggest a sophisticated change of molecular motions in a ctl1 ctl2 double mutant: both cellulose and xylan have become more dynamic on the nanosecond and microsecond timescale, but the motional amplitudes are uniformly small for both polysaccharides. Conclusions By skipping isotopic labeling, the DNP strategy demonstrated here is universally extendable to all lignocellulose materials. This time-efficient method has landed the technical foundation for understanding polysaccharide structure and cell wall assembly in a large variety of plant tissues and species.

09 BIOMASS FUELS↗

DOE OSTI2021

Simple biochemical features underlie transcriptional activation domain diversity and dynamic, fuzzy binding to Mediator

Gene activator proteins comprise distinct DNA-binding and transcriptional activation domains (ADs). Because few ADs have been described, we tested domains tiling all yeast transcription factors for activation in vivo and identified 150 ADs. By mRNA display, we showed that 73% of ADs bound the Med15 subunit of Mediator, and that binding strength was correlated with activation. AD-Mediator interaction in vitro was unaffected by a large excess of free activator protein, pointing to a dynamic mechanism of interaction. Structural modeling showed that ADs interact with Med15 without shape complementarity (‘fuzzy’ binding). ADs shared no sequence motifs, but mutagenesis revealed biochemical and structural constraints. Finally, a neural network trained on AD sequences accurately predicted ADs in human proteins and in other yeast proteins, including chromosomal proteins and chromatin remodeling complexes. These findings solve the longstanding enigma of AD structure and function and provide a rationale for their role in biology.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Estimating the carbon footprint of computational fluid dynamics

In this study, computational resources have grown exponentially in the past few decades. These machines make possible research and design in fields as diverse as medicine, astronomy, and engineering. Despite ever-increasing computational capabilities, direct simulation of complex systems has remained challenging owing to the degrees of freedom involved. At the cusp of exascale computing, high-resolution simulation of practical problems with minimal model assumptions may soon experience a renaissance. However, growing reliance on modern computers comes at the cost of a growing carbon footprint. To illustrate this, we examine historic computations in fluid dynamics where larger computers have afforded the opportunity to simulate flows at increasingly relevant Reynolds numbers. Under a variety of flow configurations, the carbon footprint of such simulations is found to scale roughly with the fourth power of Reynolds number. This is primarily explained by the computation cost in core-hours, which is also described by similar scaling, though regional differences in renewable energy use also play a role. Using the established correlation, we examine a large database of simulations to develop estimates for the carbon footprint of computational fluid dynamics in a given year. Collectively, the analysis provides an additional benchmark for new computations where, in addition to balancing considerations of model fidelity, carbon footprint should also be considered.

42 ENGINEERING↗

DOE OSTI2020

Quantification of Dispersion for Weakly and Strongly Correlated Nanofillers in Polymer Nanocomposites

The dispersion of nanoparticles in viscous polymers is dictated by kinetics, interaction potentials between particles, and interfacial compatibility between the matrix and dispersed phases. It was previously proposed that an analogy can be made between thermally dispersed colloids and kinetically dispersed nanoparticles in viscous media when weak interactions exist between particles allowing for a mean-field description under the Ginzburg criterion such as for carbon black dispersed in polybutadiene elastomer. For these cases, the second virial coefficient can be used to quantify the quality of dispersion; additionally, the nanoscale network mesh size can be calculated, which is related to dynamic properties. However, this approach fails for nanoparticles with surface charges or other specific interactions that lead to correlations. Here, these correlated systems are investigated in the context of the mean-field systems in order to gain a comparative description of dispersion using the network mesh size and a derived virial coefficient. The physical origin of the structural parameters from the proposed model for these correlated systems is investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Fluctuation dynamics near the QCD critical point

The evolution of nonhydrodynamic slow processes near the QCD critical point is explored with the novel hydro+ framework, which extends the conventional hydrodynamic description by coupling it to additional explicitly evolving slow modes describing long wavelength fluctuations. Here, their slow relaxation is controlled by critical behavior of the correlation length and is independent from gradients of matter density and pressure that control the evolution of the hydrodynamic quantities. In this exploratory study, we follow the evolution of the slow modes on top of a simplified QCD matter background, allowing us to clearly distinguish and study, both separately and in combination, the main effects controlling the dynamics of critical slow modes. In particular, we show how the evolution of the slow modes depends on their wave number, the expansion of and advection by the fluid background, and the behavior of the correlation length. Nonequilibrium contributions from the slow modes to bulk matter properties that affect the bulk dynamics (entropy, pressure, temperature, and chemical potential) are discussed and found to be small.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2005

Space Shuttle Partial Stack Rollout Test Analytical Correlation In Support Of Fatigue Load Development

A rollout test with only the Solid Rocket Boosters was conducted in November 2003 to gather structural dynamic response data of the transportation environment from the Vehicle Assembly Building to the Launch Pad. The data was acquired to develop and validate analytical methods used to predict rollout Orbiter fatigue load spectra. Earlier predictions computed by a base drive approach with only 5 input drive degrees-of-freedom raised questions that commissioned the partial stack test. Not only was there a concern because of the input degree-of-freedom omission due to measurement limitations, but there was also a concern with the implementation of the "large mass" itself. Three methods were evaluated with the partial stack test data. The analytical correlations to measured strain derived SRB base loads and acceleration5 showed the earlier 5 degree-of-freedom base drive approach to yield the most conservative results for all quantities monitored except the SRB base moment about the axis in which the input drive was missing. This non-conservative shortcoming led to a recommendation to use either the 6 degree-of-freedom base drive or the 12 degree-of-freedom Craig-Bampton boundary drive methods whose results did not substantially differ.

DelBasso, Steve↗

DOE OSTI2023

Magnetic Fluctuations in Niobium Pentoxide

Using a spin-polarized muon beam we were able to capture magnetic dynamics in an amorphous niobium pentoxide thin film. Muons are used to probe internal magnetic fields produced by defects. Magnetic fluctuations could be described by the dynamical Kubo-Toyabe model considering a time-dependent local magnetic field. We state that observed fluctuations result from the correlated motion of electron spins. We expect that oxygen vacancies play a significant role in these films and lead to a complex magnetic field distribution which is non-stationary. The characteristic average rate of magnetic field change is on the order of 100~MHz. The observed dynamics may provide insight into potential noise sources in Nb-based superconducting devices, while also highlighting the limitations imposed by amorphous oxides.

Krasnikova, Y.↗

DOE OSTI2022

Ligand-Structure-Dependent Coherent Vibrational Wavepacket Dynamics in Pyrazolate-Bridged Pt(II) Dimers

Bimetallic transition metal complexes have gained increasing attention because of their versatile functions in solar energy conversion and photonics applications arising from inter-metal electronic coupling. In bimetallic platinum (Pt) complexes, electronic communication between the Pt-centered and ligand-centered moieties have been shown to be critical for defining their excited-state dynamic trajectories undergoing either localized ligand centered (LC)/metal-to-ligand-charge-transfer (MLCT) transitions or delocalized metal-metal-to-ligand-charge-transfer (MMLCT) transitions. The branching of the excited-state intersystem crossing (ISC) trajectories are modulated through structural factors that alter the relative energies of the different states. In this study, we investigated the correlation of the structural factors influencing the excited state trajectories. Using femtosecond broadband transient absorption (fs-BBTA) spectroscopy, ultrafast dynamics in the excited state of two select Pt(II) dimers have been mapped out using their coherent vibrational wavepacket signatures in corresponding transient absorption spectra. To examine how the ligand moieties of the Pt(II) dimers influence excited-state dynamics and the coherent vibrational wavepacket behavior, here we carried out comparative studies on two pyrazolate-bridged Pt(II) dimers of the general formula [Pt( t Bu 2 Pz)(N^C)] 2 ( t Bu 2 Pz = 3,5-di-tert-butylpyrazole); N^C = 7,8-benzoquinoline (bzq, 1) or 1-phenylisoquinoline (piq, 2)). We found that photoexcitation into the low energy absorption bands of 1 and 2 respectively induce the formation of 1 MMLCT states from which ultrafast ISC proceeds, resulting in stimulated emission quenching and decoherence of the vibrational wavepacket motions. The results obtained in this study suggest that both energetics and the structural rigidity of the aromatic cyclometalating ligands in 1 and 2 can significantly influence dynamics along the excited state trajectory characterized by dephasing of the coherent oscillations. The collective results provide direct evidence of how ligand structure alters electronic dynamics along excited state trajectories associated with ISC processes, providing insight into using ligand design to steer photochemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗