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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Local and Total Density Measurements in Ice Shapes

Preliminary measurements of local and total densities inside ice shapes were obtained from ice shapes grown in the NASA Glenn Research Tunnel for a range of glaze ice, rime ice, and mixed phase ice conditions on a NACA 0012 airfoil at 0 angle of attack. The ice shapes were removed from the airfoil and a slice of ice 3 mm thick was obtained using a microtome. The resulting samples were then x-rayed to obtain a micro-radiography, the film was digitized, and image processing techniques were used to extract the local and total density values.

Vargas, Mario↗
NASA NTRS2016

Zero Boil-Off Tank (ZBOT) Experiment

The Zero-Boil-Off Tank (ZBOT) experiment has been developed as a small scale ISS experiment aimed at delineating important fluid flow, heat and mass transport, and phase change phenomena that affect cryogenic storage tank pressurization and pressure control in microgravity. The experiments use a simulant transparent low boiling point fluid (PnP) in a sealed transparent Dewar to study and quantify: (a) fluid flow and thermal stratification during pressurization; (b) mixing, thermal destratification, depressurization, and jet-ullage penetration during pressure control by jet mixing. The experiment will provide valuable microgravity empirical two-phase data associated with the above-mentioned physical phenomena through highly accurate local wall and fluid temperature and pressure measurements, full-field phase-distribution and flow visualization. Moreover, the experiments are performed under tightly controlled and definable heat transfer boundary conditions to provide reliable high-fidelity data and precise input as required for validation verification of state-of-the-art two-phase CFD models developed as part of this research and by other groups in the international scientific and cryogenic fluid management communities.

ISS↗
NASA NTRS1992

Weakly nonlinear models for turbulent mixing in a plane mixing layer

New closure models for turbulent free shear flows are presented in this paper. They are based on a weakly nonlinear theory with a description of the dominant large-scale structures as instability waves. Two models are presented that describe the evolution of the free shear flows in terms of the time-averaged mean flow and the dominant large-scale turbulent structure. The local characteristics of the large-scale motions are described using linear theory. Their amplitude is determined from an energy integral analysis. The models have been applied to the study of an incompressible mixing layer. For both models, predictions of the mean flow developed are made. In the second model, predictions of the time-dependent motion of the large-scale structures in the mixing layer are made. The predictions show good agreement with experimental observations.

Liou, William W.↗
NASA NTRS2022

Limitations in Representation of Physical Processes Prevents Successful Simulation of PM2.5 During KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by -64% but overestimates nitrate by +36%. The largest underestimate in sulfate occurs during the pollution event, where models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 25% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Katherine R. Travis↗
DOE OSTI2019

Particle Strain Analysis of Epoxy-Based Composites Following Quasi-Static and Dynamic Compression

We investigate localized strains in polymer-based composites subjected to varying strain-rates and strains. Research on composites is often focused on their bulk mechanical behavior. However, many material phenomena are influenced by their microstructure, such as the mixing and reaction mechanisms of constituents in structural energetic materials. Therefore, the response of composites at the mesoscale is of clear interest; especially as insight into the micro-deformation and damage, and interaction effects between the constituents at the local level will better inform our understanding of the bulk composite constitutive behavior. To more fully understand the composite mechanical behavior at the mesoscale, uniaxial compression experiments were conducted on epoxy reinforced with aluminum (20 or 40 vol%) and nickel (0 or 10 vol%) particles. Additionally, the particle size of aluminum was either 5 or 50 μm in diameter. Experiments were carried out at quasi-static and dynamic strain rates. Resulting microstructures were analyzed to measure the degree of particle strain and compared to the global material strains for different degrees of strain-rate, strain, and particle size and volume fraction. The aluminum particle strain increased with global strain and had a strong dependency on strain rate. Introducing stiffer nickel particles resulted in larger aluminum particle strains. The nickel particle strain was minimal (< 3%) and showed no dependency with strain rate. This research gives insight into the interactions of particle reinforced composite constituents and their deformation at the mesoscale which is important for understanding phenomena such as preignition mechanisms in structural energetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impact of Mixed Sources on the Atmospheric Aerosols of Urbanized Areas in the Philippines

Southeast Asia (SEA) holds approximately 10% of the global population, who are constantly exposed to severe local and transboundary air pollution. Here, we characterized the physiochemical characteristics of atmospheric aerosols in urbanized areas (Valenzuela, Manila, and Boracay) in the Philippines. The variability of coarse and fine aerosols, black carbon (BC), and trace elements of particulate matter (PM) were analyzed between June 2017 and April 2019. The average fine (coarse) aerosols of Valenzuela, Manila, and Boracay were 26.7 (80.4), 27.9 (86.6), and 20.9 (124.6) µg m –3 , respectively, which all exceeded the recent annual limits of the World Health Organization. The average BC level was 6.6 µg m –3 across three sampling sites, ranging between 4 to 83% of the fine PM mass. Vehicular emission predominated at the extreme urban sites as reflected by the high BC levels attributed to transport activities. The conventional receptor modeling procedure was implemented and improved by integrating BC speciation, which distinguished vehicle emission and biomass burning. The new method revealed eight and seven sources influencing the atmospheric conditions of Valenzuela and Boracay. In particular, the elevated zinc and lead highlighted the substantial impact of industrial sources in Valenzuela, attributing more than 9% of PM 2.5 . For Boracay, construction activities evidently enhanced PM based on the mass burden of calcium. Overall, the results uncovered the origin of PM 2.5 in urbanized locations in the Philippines, which will be valuable in reducing the exposure of a significant portion of the global population to harmful pollutants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Application of mixed kernels function (MKF) based support vector regression model (SVR) for CO 2 – Reservoir oil minimum miscibility pressure prediction

Carbon dioxide (CO 2 ) injection into oil reservoirs is considered a mature enhanced oil recovery (EOR) technique for conventional reservoirs. The local displacement efficiency of the CO 2 -EOR process is highly dependent on the minimum miscibility pressure (MMP), estimating this parameter is critical to design of the CO 2 injection process. Traditional empirical methods to test the CO 2 -oil MMP are time consuming and expensive; derived correlations are fast but not accurate. Therefore, an efficient and reliable method to determine MMP is beneficial. Here in this study, a mixed kernels function (MKF) based support vector regression (SVR) model was developed and used to predict the MMP for both pure and impure CO 2 injection cases. Four parameters were chosen as input parameters: (1) reservoir temperature; (2) average critical temperature; (3) molecular weight of pentane plus (C 5+ ) fraction of crude oil, and; (4) the ratio of volatile components to intermediate components in crude oil. MMP was selected as the desired output parameter to train and test this newly developed model. The performance of basic kernels function based SVR model is compared with that of this newly developed MKF-SVR model. The well-trained MFK-SVR was compared with three well-established published correlations, demonstrated the highest correlation coefficient (R of 0.9381), lowest root mean square error (RMSE of 1.9151), smallest average absolute error (AAE of 1.1406) and maximum absolute error (MAE of 4.6291). We believe that the proposed MFK-SVM model is a more reliable and stable regression model to predict MMP. In addition, a sensitivity analysis was conducted to evaluate the physical correctness. It indicates that the predicted results from the newly developed model are in excellent agreement with previous empirical work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A priori analysis of a power-law sub-filter scale mixing model for transported PDF modeling of high Karlovitz turbulent premixed flames

Accurate modeling of mixing in large-eddy simulation (LES) / transported probability density function (PDF) modeling of turbulent combustion remains an outstanding issue. The issue is particularly salient in turbulent premixed combustion under extreme conditions such as high-Karlovitz number Ka. Here, the present study addresses this issue by conducting an a priori analysis of a power-law scaling based mixing timescale model for the transported PDF model. A recently produced DNS dataset of a high-Ka turbulent jet flame is used for the analysis. A power-law scaling is observed for a scaling factor used to model the sub-filter scale mixing timescale in this high-Ka turbulent premixed DNS flame when the LES filter size is much greater than the characteristic thermal thickness of a laminar premixed flame. The sensitivity of the observed power-law scaling to the different viewpoints (local or global) and to the different scalars for the data analysis is examined and the dependence of the model parameters on the dimensionless numbers Ka and Re (the Reynolds number) is investigated. Different model formulations for the mixing timescale are then constructed and assessed in the DNS flame. The proposed model is found to be able to reproduce the mixing timescale informed by the high-Ka DNS flame significantly better than a previous model.

42 ENGINEERING↗
DOE OSTI2025

Effects of iron carbide crystal phases and dopants on the conversions of CO 2 into ethylene

The density functional theory method was used to investigate the conversions of CO 2 to ethylene formation on two common iron carbide surfaces: Fe 3 C(0 1 0) and Fe 5 C 2 (1 1 1). Based on the structure relaxation of reaction intermediates and the elementary reaction transition states. We deduced the most competitive reaction pathways for ethylene production. The main CO 2 -to-ethylene routes and the competition of side products, CO and CH 4 , are discussed. Our analyses showed that CO 2 conversion is surface structure sensitive, whereas CH 4 and C2+ hydrocarbon formations depend on the reactivity of native C atoms in the carbides. To modify the intrinsic catalyst performance, mixing dopants in Fe catalysts is an effective strategy. Furthermore, we demonstrate that doping Zn and Zr can alter the local electronic structure and enhance CO 2 adsorption on the catalyst surface.

CO2 hydrogenation↗
DOE OSTI2016

Impact of mineral precipitation on flow and mixing in porous media determined by microcomputed tomography and MRI

Here, precipitation reactions in porous media influence transport properties of the environment and can control advective and dispersive transport. In subsurface environments, mixing of saline groundwater or injected solutions for remediation with fresh groundwater can induce supersaturation of constituents and drive precipitation reactions. Magnetic resonance imaging (MRI) and micro-computed tomography (µ-CT) were employed as complimentary techniques to evaluate advection, dispersion and formation of precipitate in a 3D porous media flow cell. Two parallel fluids were flowed concentrically through the porous media under two flow rate conditions with Na 2 CO 3 and CaCl 2 in the inner and outer fluids, respectively. Upon mixing, calcium carbonate became supersaturated and formed a precipitate at the interface of the two fluids. Spatial maps of changing local velocity fields and dispersion in the flow cell were generated from MRI, while high resolution imaging of the precipitate formed in the porous media was achieved via µ-CT imaging. Formation of a precipitate layer minimized dispersive and advective transport between the two fluids and the shape of the precipitation was influenced by the flow rate condition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Seasonal enhancement of the viral shunt catalyzes a subsurface oxygen maximum in the Sargasso Sea

Subsurface oxygen maxima (SOMs) occur directly beneath the mixed layer of stratified water columns across oligotrophic open ocean basins and have been associated with physical transport processes and localized increases in phytoplankton net primary productivity (NPP). We explore the hypothesis that viral lysis (i.e., the ‘viral shunt’) increases nutrient recycling and enhances NPP, supporting SOM formation in stratified water columns, focusing on a recurring SOM at the Bermuda Atlantic Time Series (BATS) in the Sargasso Sea. Reanalysis of historical BATS data showed enhanced Prochlorococcus and virus-like particle abundances associated with SOMs. Instances of high rates of primary and secondary production observed with oxygen supersaturation further implicate a biological mechanism for SOM formation. Leveraging metatranscriptomes, metaviromes, and polony-based data collected during a Lagrangian cruise (October 2019), we link the viral shunt to SOMs, including evidence of elevated cyanophage abundance and infection of Prochlorococcus, and transcriptomic evidence of increased organic matter uptake (i.e., catabolic activity) by copiotrophic bacteria. Cruise data also showed Prochlorococcus nitrogen metabolism transcripts consistent with increased responsiveness to bacterial remineralization. These findings illustrate the biogeochemical impacts of enhanced viral lysis in marine systems, including the potential role of the viral shunt in facilitating SOM formation in the oligotrophic oceans.

Gilbert, Naomi E. [Univ. of Tennessee, Knoxville, ↗
DOE OSTI2015

Orbitals from local RDMFT: Are they Kohn-Sham or natural orbitals?

Recently, an approximate theoretical framework was introduced, called local reduced density matrix functional theory (local-RDMFT), where functionals of the one-body reduced density matrix (1-RDM) are minimized under the additional condition that the optimal orbitals satisfy a single electron Schrödinger equation with a local potential. In the present work, we focus on the character of these optimal orbitals. In particular, we compare orbitals obtained by local-RDMFT with those obtained with the full minimization (without the extra condition) by contrasting them against the exact NOs and orbitals from a density functional calculation using the local density approximation (LDA). We find that the orbitals from local-RMDFT are very close to LDA orbitals, contrary to those of the full minimization that resemble the exact NOs. Since local RDMFT preserves the good quality of the description of strong static correlation, this finding opens the way to a mixed density/density matrix scheme, where Kohn-Sham orbitals obtain fractional occupations from a minimization of the occupation numbers using 1-RDM functionals. This will allow for a description of strong correlation at a cost only minimally higher than a density functional calculation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Validation of a Hybrid Domain Overlapping Coupling Between SAM and CFD Against the TALL-3D Transients

The System Thermal Hydraulics (STH) code SAM has been coupled to the Computational Fluid Dynamics (CFD) code Simcenter STAR-CCM+ utilizing a hybrid domain overlapping method with an explicit coupling in time. The coupling aims to extend the STH code’s applicability to scenarios where local momentum and energy transfers are important yet difficult for STH codes to capture, such as three-dimensional (3D) mixing. The coupling method’s numerical stability was verified in the past against two closed-loop configurations, and it was validated against a double T-junction experiment with 3D scalar mixing. In the present work, the coupling method is validated against the TALL-3D STH/CFD coupling benchmark facility. TALL-3D is a three-legged, liquid-metal facility with a large, pool-type enclosure (test section) that exhibits 3D flow effects to be modeled by a CFD code. The rest of the system exhibits approximately 1D behavior well-predicted by an STH code. First, the present STAR-CCM+ CFD model of the 3D test section is validated against experimental data. Then, the SAM-STARCCM+ coupled model is validated against six different TALL-3D steady states, including SAM standalone model results for comparison. Lastly, the SAM-STARCCM+ coupled model is validated against two TALL-3D transients, one exhibiting flow reversal in the test section and one exhibiting nonlinear, Limit Cycle Oscillations (LCO). For the first transient, the SAM-STARCCM+ coupled model properly predicts an increase in the test section’s inlet temperature during flow reversal, and this is not predicted by the SAM standalone model. Following flow reversal, the SAM-STARCCM+ coupled model better-predicts the initial flow recovery and following oscillations as the system approaches a final natural circulation state. For the second transient, no true final steady state is observed due to LCO. Neither the SAM-STARCCM+ coupled model nor the SAM standalone model can perfectly capture the experiment’s changing oscillation frequency during the transient. However, the SAM-STARCCM+ coupled model does reproduce the oscillatory feedback observed in the system. This is a significant achievement as the SAM-STARCCM+ coupled model only uses an explicit coupling in time, as opposed to a semi-implicit coupling. In comparison, previous STH/CFD coupling efforts of the TALL-3D facility required semi-implicit coupling to obtain similar results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Spin and charge excitations in the correlated multiband metal Ca 3 Ru 2 O 7

We use Ru $L_3$-edge resonant inelastic x-ray scattering to study the full range of excitations in Ca 3 Ru 2 O 7 from meV-scale magnetic dynamics through to the eV-scale interband transitions. This bilayer 4d-electron correlated metal expresses a rich phase diagram, displaying long-range magnetic order below 56 K followed by a concomitant structural, magnetic, and electronic transition at 48 K. In the low-temperature phase, we observe a magnetic excitation with a bandwidth of ~30 meV and a gap of ~8 meV at the zone center, in excellent agreement with inelastic neutron scattering data. The dispersion can be modeled using a Heisenberg Hamiltonian for a bilayer S = 1 system with single-ion anisotropy terms. At a higher energy loss, dd-type excitations show heavy damping in the presence of itinerant electrons, giving rise to a fluorescencelike signal appearing between the $t_{2g}$ and $e_g$ bands. At the same time, we observe a resonance originating from localized $t_{2g}$ excitations, in analogy to the structurally related Mott insulator Ca 2 RuO 4 . But whereas Ca 2 RuO 4 shows sharp separate spin-orbit excitations and Hund’s-rule driven spin-state transitions, here we identify only a single broad asymmetric feature. These results indicate that local intraionic interactions underlie the correlated physics in Ca 3 Ru 2 O 7 , even as the excitations become strongly mixed in the presence of itinerant electrons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Distributed Maneuver Planning With Connected and Automated Vehicles for Boosting Traffic Efficiency

Connected and automated vehicles (CAVs) have the potential to improve traffic throughput and achieve a more efficient utilization of the available roadway infrastructure. They also have the potential to reduce energy consumption through traffic motion harmonization, even when operating in mixed traffic with other human-driven vehicles. The key to realizing these potentials are coordinated control schemes that can be implemented in a distributed manner with the CAVs. In this paper, we propose a distributed predictive control framework that features a two-dimensional maneuver planner incorporating explicit coordination constraints between connected vehicles operating in mixed traffic at various penetration levels. Here, the framework includes a distributed implementation of a reference speed assigner that estimates local traffic speed from on-board measurements and communicated information. We present an extensive evaluation of the proposed framework in traffic micro-simulations at various CAV penetrations from traffic flow, energy use, and lane utilization points of view. Results are compared to a baseline scenario with no CAVs, as well as, a benchmark one-dimensional planner.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Laboratory-Based X-ray Absorption Spectroscopy on a Working Pouch Cell Battery at Industrially-Relevant Charging Rates

Li-ion battery (LIB) research has continuing importance for the entire range of applications from consumer products to vehicle electrification and grid stabilization. In many cases, standard electrochemical methods only provide an overall voltage or specific capacity, giving an inadequate description of parallel redox processes or chemical gradients at the particle and pack level. X-ray absorption fine structure (XAFS) is frequently used to augment bulk electrochemical data, as it provides element-specific changes in oxidation state and local atomic structure. Such microscopic descriptors are crucial for elucidating charge transfer and structural changes associated with bonding or site mixing, two key factors in evaluating state of charge and modes of cell failure. However, the impact of XAFS on LIB research has been significantly constrained by a logistical barrier: contemporary XAFS work is performed almost exclusively at synchrotron X-ray light sources, where beamtime is infrequent and experiment time-frames are limited. In this report we show that modern laboratory-based XAFS cannot only be applied to, e.g., characterization of ex situ LIB electrode materials, but can also be used for operando studies at industrially-relevant charging rates in a standard pouch cell preparation. Such capability enables accelerated discovery of new materials and improved operation modes for LIBs.

25 ENERGY STORAGE↗
DOE OSTI2015

Exposing hidden alternative backbone conformations in X-ray crystallography using qFit

Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechain conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Furthermore, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.

59 BASIC BIOLOGICAL SCIENCES↗