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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A connectivity-based modeling approach for representing hysteresis in macroscopic two-phase flow properties

During CO 2 injection and storage in deep reservoirs, the injected CO 2 enters into an initially brine saturated porous medium, and after the injection stops, natural groundwater flow eventually displaces the injected mobile-phase CO 2 , leaving behind residual non-wetting fluid. Accurate modeling of two-phase flow processes are needed for predicting fate and transport of injected CO 2 , evaluating environmental risks and designing more effective storage schemes. The entrapped non-wetting fluid saturation is typically a function of the spatially varying maximum saturation at the end of injection. At the pore-scale, distribution of void sizes and connectivity of void space play a major role for the macroscopic hysteresis behavior and capillary entrapment of wetting and non-wetting fluids. This paper presents development of an approach based on the connectivity of void space for modeling hysteretic capillary pressure-saturation-relative permeability relationships. The new approach uses void-size distribution and a measure of void space connectivity to compute the hysteretic constitutive functions and to predict entrapped fluid phase saturations. Two functions, the drainage connectivity function and the wetting connectivity function, are introduced to characterize connectivity of fluids in void space during drainage and wetting processes. These functions can be estimated through pore-scale simulations in computer-generated porous media or from traditional experimental measurements of primary drainage and main wetting curves. The hysteresis model for saturation-capillary pressure is tested successfully by comparing the model-predicted residual saturation and scanning curves with actual data sets obtained from column experiments found in the literature. A numerical two-phase model simulator with the new hysteresis functions is tested against laboratory experiments conducted in a quasi-two-dimensional flow cell (91.4cm×5.6cm×61cm), packed with homogeneous and heterogeneous sands. Initial results show that the model can predict spatial and temporal distribution of injected fluid during the experiments reasonably well. However, further analyses are needed for comprehensively testing the ability of the model to predict transient two-phase flow processes and capillary entrapment in geological reservoirs during geological carbon sequestration.

58 GEOSCIENCES↗
DOE OSTI2016

Impact of wettability alteration on 3D nonwetting phase trapping and transport

We investigate capillary trapping and fluid migration via x-ray computed microtomography (x-ray CMT) of nonwetting phase (air) and wetting phase (brine) in Bentheimer sandstone cores which have been treated to exhibit different degrees of uniform wettability. x-Ray CMT scans were acquired at multiple steps during drainage and imbibition processes, as well as at the endpoints; allowing for assessment of the impact of wettability on nonwetting phase saturation and cluster size distribution, connectivity, topology and efficiency of trapping. Compared with untreated (water-wet) Bentheimer sandstone, cores treated with tetramethoxylsilane (TMS) were rendered weakly water-wet, and cores treated with octadecyltrichlorosilane (OTS) demonstrate intermediate-wet characteristics. As apparent contact angle increases, drainage flow patterns deviate from those derived for water-wet systems, total residual trapping and trapping efficiency decrease, and buoyancy plays a larger role during nonwetting phase mobilization; this has significant implications for CO 2 migration and trapping during CO 2 sequestration operations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Structural dynamics of a methionine γ-lyase for calicheamicin biosynthesis: Rotation of the conserved tyrosine stacking with pyridoxal phosphate

CalE6 from Micromonospora echinospora is a (pyridoxal 50 phosphate) PLP-dependent methionine γ-lyase involved in the biosynthesis of calicheamicins. Here, we report the crystal structure of a CalE6 2-(N-morpholino)ethanesulfonic acid complex showing ligand-induced rotation of Tyr100, which stacks with PLP, resembling the corresponding tyrosine rotation of true catalytic intermediates of CalE6 homologs. Elastic network modeling and crystallographic ensemble refinement reveal mobility of the N-terminal loop, which involves both tetrameric assembly and PLP binding. Modeling and comparative structural analysis of PLP-dependent enzymes involved in Cys/Met metabolism shine light on the functional implications of the intrinsic dynamic properties of CalE6 in catalysis and holoenzyme maturation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effects of interaction strength of associating groups on linear and star polymer dynamics

A small number of associating groups incorporated onto a polymer backbone have dramatic effects on the mobility and viscoelastic response of the macromolecules in melts. These associating groups assemble, driving the formation of clusters, whose lifetime affects the properties of the polymers. In this study, we probe the effects of the interaction strength on the structure and dynamics of two topologies, linear and star polymer melts, and further investigate blends of associative and non-associating polymers using molecular dynamics simulations. Polymer chains of approximately one entanglement length are described by a bead–spring model, and the associating groups are incorporated in the form of interacting beads with an interaction strength between them that is varied from 1 to 20 k B T. We find that, for all melts and blends, interaction of a few k B T between the associating groups drives cluster formation, where the size of the clusters increases with increasing interaction strength. These clusters act as physical crosslinkers, which slow the chain mobility. Blends of chains with and without associating groups macroscopically phase separate for interaction strength between the associating groups of a few k B T and above. For weakly interacting associating groups, the static structure function S(q) is well fit by functional form predicted by the random phase approximation where a clear deviation occurs as phase segregation takes place, providing a quantitative assessment of phase segregation.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Shear stress- and line length-dependent screw dislocation cross-slip in FCC Ni

Screw dislocation cross-slip is important in dynamic recovery of deformed metals. A mobile screw dislocation segment can cross slip to annihilate an immobile screw dislocation segment with opposite Burgers vector, leaving excess dislocations of one kind in a crystal. Previous studies have found that the cross-slip process depends on both the local stress state and dislocation line length, yet a quantitative study of the combined effects of these two factors has not been conducted. In this work, we employ both dynamic concurrent atomistic-continuum (CAC) [L. Xiong, G. Tucker, D.L. McDowell, Y. Chen, J. Mech. Phys. Solids 59 (2011) 160–177] and molecular dynamics simulations to explore the shear stress- and line length-dependent screw dislocation cross-slip in face-centered cubic Ni. It is demonstrated that the CAC approach can accurately describe the 3-D cross-slip process at a significantly reduced computational cost, as a complement to other numerical methods. In particular, we show that the Fleischer (FL) [R.L. Fleischer, Acta Metall. 7 (1959) 134–135] type cross-slip, in which a stair-rod dislocation is involved, can be simulated in the coarse-grained domain. Our simulations show that as the applied shear stress increases, the cross-slip mechanism changes from the Friedel-Escaig (FE) [B. Escaig, J. Phys. 29 (1968) 225–239] type to the FL type. In addition, the critical shear stress for both cross-slip mechanisms depends on the dislocation line length. Moreover, the cross-slip of a screw dislocation with a length of 6.47 nm analyzed using periodic boundary conditions occurs via only the FL mechanism, whereas a longer dislocation with length of 12.94 nm can cross-slip via either the FE or FL process in Ni subject to different shear stresses.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Defect energetics of concentrated solid-solution alloys from ab initio calculations: Ni 0.5 Co 0.5 , Ni 0.5 Fe 0.5 , Ni 0.8 Fe 0.2 and Ni 0.8 Cr 0.2

It has been shown that concentrated solid solution alloys possess unusual electronic, magnetic, transport, mechanical and radiation-resistant properties that are directly related to underlying chemical complexity. Because every atom experiences a different local atomic environment, the formation and migration energies of vacancies and interstitials in these alloys exhibit a distribution, rather than a single value as in a pure metal or dilute alloy. In this study, using ab initio calculations based on density functional theory and special quasirandom structure, we have characterized the distribution of defect formation energy and migration barrier in four Ni-based solid-solution alloys: Ni 0.5 Co 0.5 , Ni 0.5 Fe 0.5 , Ni 0.8 Fe 0.2 and Ni 0.8 Cr 0.2 . As defect formation energies in finite-size models depend sensitively on the elemental chemical potential, we have developed a computationally efficient method for determining it which takes into account the global composition and the local short-range order. In addition we have compared the results of our ab initio calculations to those obtained from available embedded atom method (EAM) potentials. Our results indicate that the defect formation and migration energies are closely related to the specific atomic size in the structure, which further determines the elemental diffusion properties. In conclusion, different EAM potentials yield different features of defect energetics in concentrated alloys, pointing to the need for additional potential development efforts in order to allow spatial and temporal scale-up of defect and simulations, beyond those accessible to ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Protonic solid-state electrochemical synapse for physical neural networks

Physical neural networks made of analog resistive switching processors are promising platforms for analog computing. State-of-the-art resistive switches rely on either conductive filament formation or phase change. These processes suffer from poor reproducibility or high energy consumption, respectively. Herein, we demonstrate the behavior of an alternative synapse design that relies on a deterministic charge-controlled mechanism, modulated electrochemically in solid-state. The device operates by shuffling the smallest cation, the proton, in a three-terminal configuration. It has a channel of active material, WO 3 . A solid proton reservoir layer, PdH x , also serves as the gate terminal. A proton conducting solid electrolyte separates the channel and the reservoir. By protonation/deprotonation, we modulate the electronic conductivity of the channel over seven orders of magnitude, obtaining a continuum of resistance states. Proton intercalation increases the electronic conductivity of WO 3 by increasing both the carrier density and mobility. This switching mechanism offers low energy dissipation, good reversibility, and high symmetry in programming.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Biased diffusion in tubes of alternating diameter: Numerical study over a wide range of biasing force

This paper is devoted to particle transport in a tube formed by alternating wide and narrow sections, in the presence of an external biasing force. The focus is on the effective transport coefficients—mobility and diffusivity, as functions of the biasing force and the geometric parameters of the tube. Dependences of the effective mobility and diffusivity on the tube geometric parameters are known in the limiting cases of no bias and strong bias. The approximations used to obtain these results are inapplicable at intermediate values of the biasing force. To bridge the two limits Brownian dynamics simulations were run to determine the transport coefficients at intermediate values of the force. The simulations were performed for a representative set of tube geometries over a wide range of the biasing force. They revealed that there is a range of the narrow section length, where the force dependence of the mobility has a maximum. In contrast, the diffusivity is a monotonically increasing function of the force. A simple formula is proposed, which reduces to the known dependences of the diffusivity on the tube geometric parameters in both limits of zero and strong bias. At intermediate values of the biasing force, the formula catches the diffusivity dependence on the narrow section length, if the radius of these sections is not too small.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Machine Learning in Environmental Chemistry: Application to Surface Complexation Modeling

Environmental chemistry – or biogeochemistry – is the scientific discipline typically invoked when examining and quantifying groundwater or surface water contamination, and nutrient cycling in the environment. Over the last three decades, there have been significant advances in mechanistic model development to describe and predict these complex biogeochemical processes. In particular, surface complexation models (SCMs) have been developed to describe the rock/soil surface reactions of metals and radionuclides, and their partitioning between various mobile species in the aqueous phase or immobile species sorbed on solid surfaces. Often represented by a simplified linear isotherm constant – Kd – in reactive transport models, these reactions play a critical role in many environmental science applications; particularly in contamination risk assessments and nuclear waste disposal performance assessments. In the past several decades, efforts by various institutions across the world have focused on developing SCMs based on datasets from laboratory measurements, including the identification of key parameters such as equilibrium constants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Vehicle Exhaust Monitoring Applications using loT platform

Vehicle emission is a major source of air pollution. A significant number of deaths is associated with air pollution. The existing vehicle emission monitoring system is unable to mitigate the pollution properly. Real-time pollution measurement is necessary to address the problem more precisely. The purpose of this project is to develop novel Vehicle Emission Monitoring Applications (VEMA) using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. As a part of the project, 2 technologies have been used for exhaust gas monitoring. First, an off-the-shelf exhaust gas monitoring prototype has been acquired. Second, a brand new platform was developed using off-the-shelf components. The project focused on predictive application for smart mobility and for large large fleet companies and enterprises. A data collection methodology was developed and tested by collecting close to 20 hours of data within Washington State under varying speeds, altitudes, road conditions etc. An approach for data curation was also used and finally, a simple Machine Learning was used for recognizing patterns between inputs such as vehicle speed and altitude and output such as NOx emission from vehicle exhaust pipe.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Summertime Aerosol across the North Slope of Alaska Field Campaign Report

The Summertime Aerosol across the North Slope of Alaska U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility field campaign, a collaborative effort between the University of Michigan and Baylor University, was focused on chemically characterizing sources of summertime aerosol impacting the Utqiagvik (Barrow, NSA) and the Oliktok Point (AMF3) ARM sites. This campaign was co-funded by a grant from the National Oceanic and Atmospheric Administration (NOAA, PI: Kerri Pratt, Co-I: Rebecca Sheesley) titled “Assessment of Atmospheric Aerosols Resulting from Oil and Gas Extraction Activities near the North Slope of Alaska”. The ARM field campaign took place on the North Slope of Alaska (NSA) from August 21 to September 30, 2015 and August 12 to September 20, 2016, with filter sampling occurring both years at both the NSA Barrow and AMF3 Oliktok Point sites. Online intensive measurements occurred at Barrow in 2015 and at Oliktok Point in 2016, coordinated with the arrival of the ARM Aerosol Observing System (AOS) in August 2016 at Oliktok Point. During 2015, the University of Michigan deployed the newly constructed aerosol time-of-flight mass spectrometer (ATOFMS), as well as a microanalysis particle sampler (MPS) to collect particles for offline analysis by computer-controlled scanning electron microscopy with energy-dispersive x-ray spectroscopy (CCSEM-EDX). Unfortunately, an issue with the time-of-flight mass spectrometer on the ATOFMS limited the number of particles that produced mass spectra during the 2015 study. This issue was subsequently fixed for the 2016 deployment. During 2016, the ATOFMS was deployed to the AMF3 at the Oliktok Point field site, in addition to a micro-orifice uniform deposition impactor (MOUDI) to collect particles for offline analysis by CCSEM-EDX. Notably, these measurements, to our knowledge, represent the first real-time, single-particle chemical characterization (aerosol mixing state) measurements at Utqiagvik and Oliktok Point. Online aerosol measurements also included: PM2.5 (particulate matter <2.5 μm) black carbon mass concentrations (aethalometer; Baylor) and size-resolved (0.013-20 μm) number concentrations (scanning mobility particle sizer, SMPS, and aerodynamic particle sizer, APS; Michigan). Baylor conducted filter sampling at both the Utqiagvik and Oliktok Point locations during both intensive operational periods (IOPs). Baylor deployed a total suspended particulate matter (TSP) sampler to Oliktok Point, and continuous one-week samples were collected in 2015 for a total of seven samples; during 2016, continuous 3-7 day samples were collected, for a total of 13 filters. Baylor deployed a TSP sampler and a PM1.0 sampler at Utqiagvik, Alaska; continuous 4-7 day filter samples were collected in 2015 for a total of eight samples. To supplement this campaign, PI Sheesley had a simultaneous DOE ARM field campaign at Utqiagvik and Oliktok Point (https://www.arm.gov/research/ campaigns/amf2016bbc), the goal of which was to collected continuous one-week TSP samples at both sites from June 2016 to September 2017. These results provide better context in terms of annual trends and for year-to-year variability and a final report with data was already submitted by PI Sheesley for that project. Analysis by Baylor focuses on TSP samples because of the extremely low PM loading on the PM1.0 sampler. Michigan deployed a three-stage impactor (0.07-5 μm PM collection) at Utqiagvik and a 10-stage impactor (0.056-10 μm PM collection) at Oliktok Point, during the 2015 and 2016 campaigns, respectively.

Arctic processes, North Slope of Alaska, Barrow, O↗
DOE OSTI2016

Helium segregation on surfaces of plasma-exposed tungsten

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Spectra of clinical CT scanners using a portable Compton spectrometer

Purpose: Spectral information of the output of x-ray tubes in (dual source) computer tomography (CT) scanners can be used to improve the conversion of CT numbers to proton stopping power and can be used to advantage in CT scanner quality assurance. The purpose of this study is to design, validate, and apply a compact portable Compton spectrometer that was constructed to accurately measure x-ray spectra of CT scanners. Methods: In the design of the Compton spectrometer, the shielding materials were carefully chosen and positioned to reduce background by x-ray fluorescence from the materials used. The spectrum of Compton scattered x-rays alters from the original source spectrum due to various physical processes. Reconstruction of the original x-ray spectrum from the Compton scattered spectrum is based on Monte Carlo simulations of the processes involved. This reconstruction is validated by comparing directly and indirectly measured spectra of a mobile x-ray tube. The Compton spectrometer is assessed in a clinical setting by measuring x-ray spectra at various tube voltages of three different medical CT scanner x-ray tubes. Results: The directly and indirectly measured spectra are in good agreement (their ratio being 0.99) thereby validating the reconstruction method. The measured spectra of the medical CT scanners are consistent with theoretical spectra and spectra obtained from the x-ray tube manufacturer. Conclusions: A Compton spectrometer has been successfully designed, constructed, validated, and applied in the measurement of x-ray spectra of CT scanners. These measurements show that our compact Compton spectrometer can be rapidly set-up using the alignment lasers of the CT scanner, thereby enabling its use in commissioning, troubleshooting, and, e.g., annual performance check-ups of CT scanners.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Differentiable Channels Are All You Need

Mobile wireless communication systems must adapt to and compensate for time-varying propagation paths. The process of performing compensation in the receiver for said effects is known as equalization. We seek an improved method for optimizing the reliability of said wireless links to minimize outage probability. A method based on machine learning, specifically deep learning, has the potential to allow for greater flexibility and robustness against unforeseen channel conditions. In this report we investigate the performance of a prior method in the literature with minor modifications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Characterizing Integrase-Attachment Site Pairs: A Machine Learning Approach

Genomic islands (GIs) are mobile genetic elements that integrate into host genomes via self-encoded integrases at specific DNA sequences known as attachment (att) sites. The ability to predict the target att site from an integrase's protein sequence is a central challenge in genomics due to the sequence diversity of integrases and the subtlety of their DNA recognition motifs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Elucidating the Role of Hydrogen at c‐In 2 O 3 /a‐In 2 O 3− x Interface

Ab initio molecular dynamics simulations and hybrid functional electronic structure calculations are employed to determine the formation, the structural and electronic properties, and the dynamics of covalent (In—OH) and ionic (In—H—In) hydrogen defects at crystalline-In 2 O 3 /amorphous-In 2 O 3−x interface. This comprehensive computational study considers (i) various interstitial and substitutional hydrogen site locations within the crystalline, amorphous, and interfacial regions; (ii) several oxygen-to-hydrogen ratios; and (iii) possible defect charged states. The results reveal hydrogen's inability to fully passivate the undercoordinated under-shared in atoms in amorphous highly substoichiometric oxide, giving rise to the formation of deep electron traps even in net-charge neutral structures. These trap defects are found to be sensitive to photoexcitation, in contrast to In—OH with H's electronic states located below the valence band and to In—H—In, where H is found to maintain its charge state upon illumination. Nevertheless, H plays a critical role in photoinduced conductivity and its relaxation by promoting In—O coordination transformations at the interfacial region, including deterioration of the crystalline layer. Finally, the results help identify mobile H species and metastable H defect complexes (such as In—H—H—In, In—OH–H—In, and In—OH–O—In) that are responsible for long relaxation times of the conductivity decay.

H defects↗
DOE OSTI2021

Stochastic pre-event preparation for enhancing resilience of distribution systems

Extreme weather events are the common causes for power supply interruptions and power outages in electrical distribution systems. Improving the distribution system and enhancing its resilience is becoming crucial due to the increased frequency of extreme weather events. Preparation and allocation of multiple flexible resources, such as mobile resources, fuel resources, and labor resources before extreme weather events can mitigate the effects of extreme weather events and enhance the resilience of power distribution systems. Here, in this paper, a two-stage stochastic mixed-integer linear programming (SMILP) is proposed to optimize the preparation and resource allocation process for upcoming extreme weather events, which leads to faster and more efficient post-event restoration. The objective of the proposed two-stage SMILP is to maximize the served load and minimize the operating cost of flexible resources. The first stage in the optimization problem selects the amounts and locations of different resources. The second stage considers the operational constraints of the distribution system and repair crew scheduling constraints. The proposed stochastic pre-event preparation model is solved by a scenario decomposition method, Progressive Hedging (PH), to ease the computational complexity introduced by a large number of scenarios. Furthermore, to show the impact of solar photovoltaic (PV) generation on system resilience, three types of PV systems are considered during a power outage and the resilience improvements with different PV penetration levels are compared. Numerical results from simulations on a large-scale (more than 10,000 nodes) distribution feeder have been used to validate the effectiveness and scalability of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗