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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

STATISTICAL ANALYSIS OF IN-SERVICE ULTRASONIC INSPECTION DATA OF WASTE TANKS AT THE SAVANNAH RIVER Site-25021

CONCLUSIONS AND RECOMMENDATIONS •“There is no evidence of pit depth growth over the last 15-years demonstrating the effectiveness of the corrosion control program. •“Incipient pits” are not growing and are likely pre-service pits. • No need to continue measuring these tiny pits. However, due to the random nature of pit initiation and the potentially accelerated growth of a pit, periodic monitoring for pit growth is prudent. 1. No reportable pits were identified. All identified pits are far less than the reportable depth of 25% of the nominal wall thickness. 2. No cracking was identified. 3. There is no evidence that active, systemic corrosion has occurred in Tank 29 during its 38-year service history as of 2009.

Harris, Stephen P. [Savannah River National Labora↗
DOE OSTI2020

Impact of Tuned Lighting on Skilled Nursing Center Residents' Sleep

The Problem: Sleep disturbance is common among nursing center residents and places them at risk for poor health outcomes. Lighting that changes in color and intensity over the course of the day and night may improve sleep and other outcomes, like dementia behaviors, but has has not been rigorously evaluated under real-world conditions. The Resolution: This single-facility study establishes that facility-level tuned lighting is feasible to implement and evaluate in a nursing center. Researchers randomly-assigned three corridors to one of two lighting conditions, then the other. Residents experienced half as many sleep disturbances while exposed to tuned vs. static lighting. There was no effect on behaviors. Tips for Success: Tuned lighting is a low-risk intervention that could be employed in new construction or when retrofitting fixtures into existing buildings. Key Words: Nursing home, long-term care, lighting, sleep, behaviors

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Influence of Wetting on Viscous Fingering Via 2D Lattice Boltzmann Simulations

We present simulations of two-phase flow using the Rothman and Keller colour gradient Lattice Boltzmann method to study viscous fingering when a “red fluid” invades a porous model initially filled with a “blue” fluid with different viscosity. We conducted eleven suites of 81 numerical experiments totalling 891 simulations, where each suite had a different random realization of the porous model and spanned viscosity ratios in the range $$M\in [0.01,100]$$ M ϵ [ 0.01 , 100 ] and wetting angles in the range $$\theta _w\in [180^\circ ,0^\circ ]$$ θ w ϵ [ 180 ° , 0 ° ] to allow us to study the effect of these parameters on the fluid-displacement morphology and saturation at breakthrough (sweep). Although sweep often increased with wettability, this was not always so and the sweep phase space landscape, defined as the difference in saturation at a given wetting angle relative to saturation for the non-wetting case, had hills, ridges and valleys. At low viscosity ratios, flow at breakthrough is localized through narrow fingers that span the model. After breakthrough, the flow field continues to evolve and the saturation continues to increase albeit at a reduced rate, and eventually exceeds 90% for both non-wetting and wetting cases. The existence of a complicated sweep phase space at breakthrough, and continued post-breakthrough evolution suggests the hydrodynamics and sweep is a complicated function of wetting angle, viscosity ratio and time, which has major potential implications to Enhanced Oil Recovery by water flooding, and hence, on estimates of global oil reserves. Validation of these results via experiments is required to ensure they translate to field studies.

Engineering↗
DOE OSTI2020

Residential electricity conservation in response to auto-generated, multi-featured, personalized eco-feedback designed for large scale applications with utilities

While past research has shown that providing residents with feedback about their electricity usage can reduce demand and its associated environmental burdens, some questions remain regarding what makes such feedback most effective. We followed the electricity usage of 36 residents who each received 14 feedback messages over 2 months. Using approaches borrowed from Natural-Language-Processing, feedbacks were generated automatically, using 10 features in random combinations. Unlike in previous studies, each resident received varying types of messages over time. In 504 observations, the average prompted reduction in electricity usage was 11 ± 3%, compared to a control group of 89 residents who received no messages. Feedback types prompting the largest reductions were self-comparisons with one’s own earlier usage (average reduction 14%) and messages of high variety from one feedback-cycle to the next (average reduction 16%). Comparisons with neighbors did not prompt higher reductions on average. Instead, they prompted reductions only when a resident’s recent usage happened to be higher than the average usage of neighbors, and increases when the reverse was true. Finally, this behavior was exhibited by all residents and is likely explained by a norm-conforming mean reversion of residents to their neighbors’ average usage, rather than an anti-conform “boomerang” behavior previously suggested in similar contexts.

42 ENGINEERING↗
DOE OSTI2022

The Supplementation of FloraMax-B11 Did Not Affect the Bile Acid Neosynthesis and the Enterohepatic Circulation in Broiler Chickens

Most probiotics possess bile salt hydrolase enzymes and may increase bile acid excretion and negatively affect fat digestion and absorption. Therefore, the study objective was to determine the time course effects of a commercial probiotic (P) FloraMax-B11 (FM) supplementation on bile acid neosynthesis and enterohepatic circulation in broiler chickens. Fertile Ross 708 eggs were incubated under standard commercial conditions. At hatch, chicks (n = 550) were randomly assigned to 5 treatment groups (n = 5 replicates per treatment group) with 22 birds per pen. The 5 treatment groups consisted of: control group (C, normal water from hatch to 35 days of age without supplements); P3, water supplemented with FM for the first 3 days post-hatch followed by normal water until day 35; P10, water supplemented with FM for the first 10 days post-hatch followed by normal water until day 35; P35, water supplemented with FM from hatch to day 35; and AGP, water supplemented with antibiotic growth promoter (AGP) from hatch until day 35. Ileum, liver, and plasma were collected at hatch, days 3, 10, 21, and 35 post-hatch. The relative mRNA expression of genes involved in bile acid synthesis (CYP7A1, CYP8B1, FXR, FGFR4, and FGF19) and transport (ASBT, I-BABP, OSTα, OSTβ, and BSEP) as well as ileal deoxycholic acid and plasma cholic acid were determined. There was no FM and AGP interaction for any of the response criteria. No FM or AGP effects were observed (p > 0.05) for any genes, except FGF19, which expression was increased (p < 0.0001) in AGP compared to P35. No FM or AGP effects were observed (p > 0.05) for levels of deoxycholic and cholic acids. However, all the genes, deoxycholic acid, and plasma cholic acid were affected by age (p < 0.0001). In general, the data indicate that FM did not negatively impact bile acid metabolism and enterohepatic circulation, which appeared to be age dependent. However, more research should be conducted to confirm these results and investigate the effects of FM on bile acid metabolism, fat digestion, and intestinal microbiota in broiler chickens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Thermal conductivity modeling of monodispersed microspheres using discrete element method

Particle beds are widely used in various systems and processes, such as particle heat exchangers, granular flow reactors, and additive manufacturing. Accurate modeling of the thermal conductivity of particle beds and understanding of their heat transfer mechanisms are important. However, previous models were based on simple cubic packing of particles, which could not accurately represent the actual heat transfer processes under certain conditions. Here, we examine the effect of the packing structure on the thermal conductivity of particle beds. We use monodispersed silica microspheres with average particle sizes ranging from 23 to 330 μm as a model material. We employ a transient hot-wire technique to measure the thermal conductivity of the particle beds with packing density of 43%–57% within a temperature range of room temperature to 500 °C and under N2 gaseous pressures of 20–760 Torr. We then use a discrete element method (DEM) to obtain the realistic packing structure of the particles, which is then fed into a finite-element model (FEM) to calculate the thermal conductivity, with the consideration of solid conduction, gas conduction, and radiation heat transfer. Our results show that the thermal conductivity model based on the more realistic random packing structure derived from the DEM shows better agreement with the experimental data compared to that based on the simple cubic-packing structure. The combined DEM and FEM methodology can serve as a useful tool to predict the effective thermal conductivity of particle beds and to quantify different heat transfer mechanisms under various conditions.

14 SOLAR ENERGY↗
DOE OSTI2020

Stochastic Fault Detection

This entry describes the state-of-the-art and future perspectives on stochastic fault detection, namely, stochastic fault detection and diagnosis (FDD). Both model-based and data-driven FDD methods for stochastic signals and systems have been included, where the use of hypothesis testing, Kalman filtering, system estimation, principal component analysis (PCA), and stochastic distribution control has been discussed for the construction of effective FDD algorithms. Indeed, stochastic FDD constitute an important and integrated part in developing fault-tolerant controls (FTC) for guaranteed safe operation of control systems, of which increased penetration of random factors is inevitable nowadays.

Wang, Aiping↗
DOE OSTI2020

Probability Density Function Control for Stochastic Nonlinear Systems using Monte Carlo Simulation

This paper presents a fast implementation framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

Zhang, Qichun↗
DOE OSTI2023

Direct observation of magnetic ordering induced via systematic lattice disorder in artificial rhombus spin ices

It is critical to understand the effect of lattice geometry on the order parameter of a condensed matter system, as it controls phase transitions in such systems. Artificial spin ices (ASIs) are two-dimensional lattices of Ising-like nanomagnets that provide an opportunity to explore such phenomena by lithographically controlling the lattice geometry to observe its influence on magnetic ordering and frustration effects. Here we report a systematic approach to studying the effects of disorder in rhombus ASIs generated from combinations of five vertex motifs. We investigate four geometries characterized by a geometric order parameter, with symmetries ranging from periodic to quasiperiodic to random. Lorentz transmission electron microscopy data indicates magnetic domain behavior depends on chains of strongly-coupled islands in the periodic and sixfold-twinned lattices, while the behavior of the disordered lattice is dominated by vertex motifs with large configurational degeneracy. Utilizing micromagnetic simulations, a quantitative analysis of the lattice energetics showed that the experimental rotationally-demagnetized state of the disordered ASI was closer in energy to the idealized ground state compared to other periodic and twinned ASIs. Finally, our work provides a unique pathway for using degeneracy, magnetic frustration, and order to control the magnetization behavior of designer disordered systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ultrafast nonequilibrium evolution of excitonic modes in semiconductors

We study the time evolution of excitonic states after photoexcitation in the one-dimensional spinless extended Falicov-Kimball model. Several numerical methods are employed and benchmarked against each other: time-dependent mean-field simulations, the second-Born approximation (2BA) within the Kadanoff-Baym formalism, the generalized Kadanoff-Baym ansatz (GKBA) implemented with the 2BA, and the infinite time-evolving block decimation (iTEBD) method. It is found that the GKBA gives the best agreement with iTEBD and captures the relevant physics. Excitations to the particle-hole continuum and resonant excitations of the equilibrium exciton result in a qualitatively different dynamics. In the former case, the exciton binding energy remains positive and the frequency of the corresponding coherent oscillations is smaller than the band gap. On the other hand, resonant excitations trigger a collective mode whose frequency is larger than the band gap. We discuss the origin of these different behaviors by evaluating the nonequilibrium susceptibility using the nonthermal distribution and a random phase approximation. We note the peculiar mode with frequency larger than the band gap is associated with a partial population inversion with a sharp energy cutoff. We also discuss the effects of the cooling by a phonon bath. We demonstrate the real-time development of coherence in the polarization, which indicates excitonic condensation out of equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Tidal Disruption Event Galaxy Binner

This software simulates astronomical survey detections of tidal disruptions of stars by super-massive black holes. It begins with the synthetic galaxy catalogue described in van Velzen 2008 (https://arxiv.org/abs/1707.03458). The stellar disruption rate in each galaxy is estimated based on Stone & Metzger 2016 (https://arxiv.org/abs/1410.7772). Based on these rates, and the present-day stellar mass function in the galaxy, disruptions are randomly sampled, and the properties of the resulting flares are sampled based on empirical distributions. The code also accounts for obscuration by dust in the host galaxy. Finally, the survey selection effects are applied. The detectable simulated flares are stored in a database, allowing histograms of their properties to be created.

Roth, NathanielJ.↗
DOE OSTI2021

Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks

In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems

Strongly-correlated quantum many-body systems are difficult to study and simulate classically. We recently proposed a variational quantum eigensolver (VQE) based on the multiscale entanglement renormalization ansatz (MERA) with tensors constrained to certain Trotter circuits. Here, we determine the scaling of computation costs for various critical spin chains which substantiates a polynomial quantum advantage in comparison to classical MERA simulations based on exact energy gradients or variational Monte Carlo. Algorithmic phase diagrams suggest an even greater separation for higher-dimensional systems. Hence, the Trotterized MERA VQE is a promising route for the efficient investigation of strongly-correlated quantum many-body systems on quantum computers. Furthermore, we show how the convergence can be substantially improved by building up the MERA layer by layer in the initialization stage and by scanning through the phase diagram during optimization. For the Trotter circuits being composed of single-qubit and two-qubit rotations, it is experimentally advantageous to have small rotation angles. We find that the average angle amplitude can be reduced considerably with negligible effect on the energy accuracy. Benchmark simulations suggest that the structure of the Trotter circuits for the TMERA tensors is not decisive; in particular, brick-wall circuits and parallel random-pair circuits yield very similar energy accuracies.

Miao, Qiang [Duke Quantum Center, Duke University,↗
DOE OSTI2021

Interpreting Write Performance of Supercomputer I/O Systems with Regression Models

This work seeks to advance the state of the art in HPC I/O performance analysis and interpretation. In particular, we demonstrate effective techniques to: (1) model output performance in the presence of I/O interference from production loads; (2) build features from write patterns and key parameters of the system architecture and configurations; (3) employ suitable machine learning algorithms to improve model accuracy. We train models with five popular regression algorithms and conduct experiments on two distinct production HPC platforms. We find that the lasso and random forest models predict output performance with high accuracy on both of the target systems. We also explore use of the models to guide adaptation in I/O middleware systems, and show potential for improvements of at least 15% from model-guided adaptation on 70% of samples, and improvements up to 10× on some samples for both of the target systems.

Xie, Bing↗
DOE OSTI2020

Unraveling the dislocation–precipitate interactions in high-entropy alloys

The precipitates play a significant role in not only enhancing the strength, but also maintaining the high toughness in alloys. However, the interactions of the nanoscale precipitates with dislocations in the high entropy alloys (HEAs) are difficult to observe directly by in-situ TEM experiments due to the limits of the resolution and time. Here, using atomic simulations we report the synergistic strengthening of the coherent precipitate and atomic-scale lattice distortion in the HEAs at cryogenic/elevated temperatures. The effects of temperature, chemical disorder, precipitate spacing, precipitate size, elemental segregation, and dislocation-cutting number on the critical stress for the dislocation to overcome a row of precipitates are studied. A random stacking fault energy landscape along the slip plane, the lattice distortion at different temperatures, and the interface/surface energy at various crystallographic orientations are obtained. Compared with the traditional metals and alloys, HEAs have the severe atomic-scale lattice distortions to generate the local high tensile/compressive stress fields. This complex stress causes the dislocation line to bend, and thus improves the dislocation slip resistance, resulting in the strong solid-solution strengthening. The stacking fault strengthening induced by the obvious difference of the stacking fault energies between the HEA matrix and precipitate (within the inner of the HEA matrix), and the formation of the antiphase domain boundary contribute to the high strength. The precipitate embedded by the solute atoms produces the strong lattice distortion to enhance the dislocation slip resistance at high temperatures. Hence, the current results provide the mechanistic insight into the phenomenon that the coherent precipitate combined with the severe atomic-scale lattice distortion can enhance the strength at cryogenic/elevated temperatures to further broaden the scope of applications of advanced HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Importance of an Ensemble Approach for Modeling Aerosol‐Convection Interactions

Aerosol-convection interactions modulate cloud microphysics, thermodynamics, and updraft intensity, contributing to climate-scale aerosol-radiative forcing. However, quantifying aerosol indirect effects in mixed-phase deep convection remains challenging due to uncertainties in parameterized physics and initial conditions driving nonlinear evolution of convective processes. This study investigates the convective updraft sensitivity to random initial temperature perturbations using an idealized ensemble modeling framework informed by in situ thermodynamic and aerosol observations from the DOE TRACER field campaign. We analyze the impact of small-scale initial perturbations on updraft velocity and supersaturation, and determine the ensemble size required to minimize stochastic internal variability. Results show that minor thermodynamic perturbations can produce updraft variability comparable to aerosol-induced changes reported in prior work. An ensemble of 10 members sufficiently reduces variability, enabling robust investigation of aerosol-related updraft invigoration and informing the design of future ensemble-based aerosol-convection interaction studies in environments with significant spatiotemporal mesoscale thermodynamic and aerosol heterogeneity.

aerosol-convection interactions↗
DOE OSTI2020

Record thermopower found in an IrMn-based spintronic stack

The Seebeck effect converts thermal gradients into electricity. As an approach to power technologies in the current Internet-of-Things era, on-chip energy harvesting is highly attractive, and to be effective, demands thin film materials with large Seebeck coefficients. In spintronics, the antiferromagnetic metal IrMn has been used as the pinning layer in magnetic tunnel junctions that form building blocks for magnetic random access memories and magnetic sensors. Spin pumping experiments revealed that IrMn Néel temperature is thickness-dependent and approaches room temperature when the layer is thin. Here, we report that the Seebeck coefficient is maximum at the Néel temperature of IrMn of 0.6 to 4.0 nm in thickness in IrMn-based half magnetic tunnel junctions. We obtain a record Seebeck coefficient 390 (±10) μV K -1 at room temperature. Our results demonstrate that IrMn-based magnetic devices could harvest the heat dissipation for magnetic sensors, thus contributing to the Power-of-Things paradigm.

42 ENGINEERING↗
DOE OSTI2022

A measurement of stellar surface gravity hidden in radial velocity differences of comoving stars

The gravitational redshift induced by stellar surface gravity is notoriously difficult to measure for non-degenerate stars, since its amplitude is small in comparison with the typical Doppler shift induced by stellar radial velocity. In this study, we make use of the large observational data set of the Gaia mission to achieve a significant reduction of noise caused by these random stellar motions. By measuring the differences in velocities between the components of the pairs of comoving stars and wide binaries, in this work we are able to statistically measure the combined effects of gravitational redshift and convective blueshifting of spectral lines, and nullify the effect of the peculiar motions of the stars. For the subset of stars considered in this study, we find a positive correlation between the observed differences in Gaia radial velocities and the differences in surface gravity and convective blueshift inferred from effective temperature and luminosity measurements. The results rule out a null signal at the 5σ level for our full data set. Additionally, we study the subdominant effects of binary motion, and possible systematic errors in radial velocity measurements within Gaia. Results from the technique presented in this study are expected to improve significantly with data from the next Gaia data release. Such improvements could be used to constrain the mass–luminosity relation and stellar models that predict the magnitude of convective blueshift.

(stars:) binaries: general↗