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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

How deep to dig: effects of web-scraping search depth on hyperlink network analysis of environmental stewardship organizations

Abstract Social network analysis (SNA) tools and concepts are essential for addressing many environmental management and sustainability issues. One method to gather SNA data is to scrape them from environmental organizations’ websites. Web-based research can provide important opportunities to understand environmental governance and policy networks while potentially reducing costs and time when compared to traditional survey and interview methods. A key parameter is ‘search depth,’ i.e., how many connected pages within a website to search for information. Existing research uses a variety of depths and no best practices exist, undermining research quality and case study comparability. We therefore analyze how search depth affects SNA data collection among environmental organizations, if results vary when organizations have different objectives, and how search depth affects social network structure. We find that scraping to a depth of three captures the majority of relevant network data regardless of an organization’s focus. Stakeholder identification (i.e., who is in the network) may require less scraping, but this might under-represent network structure (i.e., who is connected). We also discuss how scraping web-pages of local programs of larger organizations may lead to uncertain results and how our work can combine with mixed methods approaches.

Sayles, Jesse S. (ORCID:0000000218378920)↗
DOE OSTI2024

Virtual texture analysis to understand microstructure effects on deformation twinning and detwinning behavior in BCC metals

Understanding and predicting deformation twinning contributions to plastic deformation in BCC metals has been a long-standing challenge due to the interplay with dislocation slip and non-Schmid effects that render an asymmetry under tension and compression. This paper uses molecular dynamics simulations to understand the effect of unloading and grain orientation on deformation twinning in a nanocrystalline Fe (nc-Fe) system as a model BCC metal. The nc-Fe system is loaded under uniaxial stress tension and compression to understand the effect of grain orientation (Schmid effects) on deformation twinning behavior and the tension/compression asymmetry (non-Schmid effects). A new virtual texture analysis “VirTex” tool is used to understand the role of grain orientation on the nucleation of twins and their contributions to the observed stress–strain response. For certain grain orientations, the twinnability is observed to be different in tension and compression. In addition, the flow stress accommodation from twins in certain grains is observed to be different in tension and compression and different from that for the grains. Subsequent unloading leads to detwinning in the deformed microstructures, where the extent of detwinning depends on the strain from which the system is unloaded and on the morphology of the twin. Lastly, the simulations are carried out to analyze the role of the Schmid factor on the twinnability and asymmetry in tension and compression.

Kannan, Aadhithyan [University of Connecticut, Sto↗
DOE OSTI2023

Computational tools for the simulation and analysis of spin-polarized EPR spectra

The EPR spectra of paramagnetic species induced by photoexcitation typically exhibit enhanced absorptive and emissive features resulting from sublevel populations that differ from thermal equilibrium. The populations and the resulting spin polarization of the spectra are dictated by the selectivity of the photophysical process generating the observed state. Simulation of the spin-polarized EPR spectra is crucial in the characterization of both the dynamics of formation of the photoexcited state as well as its electronic and structural properties. EasySpin, the simulation toolbox for EPR spectroscopy, now includes extended support for the simulation of the EPR spectra of spin-polarized states of arbitrary spin multiplicity and formed by a variety of different mechanisms, including photoexcited triplet states populated by intersystem crossing, charge recombination or spin polarization transfer, spin-correlated radical pairs created by photoinduced electron transfer, triplet pairs formed by singlet fission and multiplet states arising from photoexcitation in systems containing chromophores and stable radicals. In this paper, we highlight EasySpin’s capabilities for the simulation of spin-polarized EPR spectra on the basis of illustrative examples from the literature in a variety of fields ranging across chemistry, biology, material science and quantum information science.

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

Temperature Effects on Interdiffusion of Al and U-Mo under Irradiation

A high-energy Xe ion irradiation experiment was conducted to investigate the temperature dependence of interdiffusion in bilayer Al-UMo samples under irradiation. The amount of interdiffusion achieved at a fixed dose with the increase of temperature showed a clear transition at 175 degrees C (with an estimated error in the range of ± 10 degrees C) from temperature-independent to temperature-dependent behavior. The activation energy derived from the curve of interdiffusion quantity vs. irradiation temperature is 0.77 ± 0.16 eV. This information has been utilized to understand the temperature effect on the interdiffusion process that occurred at the interfaces of U-Mo particles and the Al matrix in U-Mo/Al dispersion fuels, whose magnitude significantly impacts the fuel's performance. Although this temperature effect was deemed important, it cannot be examined directly using in-pile irradiation data, as fuel temperatures cannot be measured in reactor irradiation and are highly correlated with fission rate and thermal conductivity evolution. To connect the knowledge accumulated from ion irradiation with in-pile irradiation data, simulation of a full-sized U-Mo/Al dispersion fuel plate irradiated in the FUTURE test in the BR2 reactor was performed with the Dispersion Analysis Research Tool (DART), a dispersion fuel performance code. DART is equipped with an interaction or interdiffusion layer (IL) growth correlation formulated to describe the temperature dependence of ion mixing results. The agreement between calculated and measured fuel meat constituent volume fractions and swelling data demonstrated that the temperature effect on in-pile Al-UMo interdiffusion is well captured with the correlation. In this case, the fitted activation energy is 0.70 eV. Considering the uncertainties associated with the ion irradiation data, the activation energy obtained from in-pile data fitting is in accord with that from ion irradiation results.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Integrated simulation of U-10Mo monolithic fuel swelling behavior

Here, a separate computational branch has been implemented within the DART (Dispersion Analysis Research Tool) computational code to simulate the swelling behavior of U-10Mo monolithic fuel under the operating conditions of high-power research and test reactors (RTRs). The monolithic branch of the DART code implements a mechanistic rate-theory-based fission-gas-behavior model for the calculation of fission gas swelling, as well as a suite of thermal, physical, and mechanical models to take into account various processes occurring in RTR fuels during irradiation. In order to accurately simulate and eventually predict U-10Mo monolithic fuel irradiation behavior, the code uses materials properties calculated with lower length-scale computational methods, such as gas atom diffusivity and U-Mo surface energy from atomic simulations and grain-morphology-specific recrystallization kinetics (recrystallized fuel volume fractions vs. fission density) predicted using the phase-field method. The remainder of fission gas behavior parameters used in the model were calibrated with measured intergranular bubble size distributions. With this integrated simulation approach, the swelling behavior of U-10Mo monolithic fuel was simulated for various initial grain sizes at different operating conditions and compared with measured data. Furthermore, because limited experimental data exist for parameter calibration detailed sensitivity studies for the important parameters used in the fission gas behavior model were performed in order to examine their impact on both intergranular gas bubble morphology at low fission density, and on total porosity at high fission density.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Verification and validation of the Alternative Nonlinear Two-phase Subchannel (ANTS) code

The Alternative Nonlinear Two-phase Subchannel solver (ANTS) code was written to provide a fast-running, steady-state, pin-resolved modeling and simulation tool for analysis of common boiling water reactor (BWR) geometry and common operating conditions. ANTS has been integrated into the Virtual Environment for Reactor Application (VERA) core simulator software, where it can be used to provide a thermal/hydraulic (T/H) subchannel solution that is then used to provide neutronic feedback as well as perform the fuel depletion and temperature solution. Herein, this paper presents the rigorous analysis performed on the ANTS code, which includes both code and solution verification testing, benchmarking with the existing two-phase subchannel capability in VERA, CTF, and validation testing using popular two-phase experiments such as PWR Sub-channel and Bundle Tests (PSBT), BWR Full-size Fine-mesh Bundle Tests (BFBT), Risø, and FRIGG. This assessment was used to qualify ANTS for its intended applications before its use for core-scale, multiphysics BWR simulations. In general, it was found that agreement with experimental data was good; errors were within the range of experimental data uncertainty. Furthermore, code and solution verification confirmed that the governing equations and the most important closure terms were correctly implemented and behaving as expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence

The evolution of buoyancy-driven homogeneous variable-density turbulence (HVDT) at Atwood numbers up to 0.75 and large Reynolds numbers is studied by using high-resolution direct numerical simulations. To help understand the highly non-equilibrium nature of buoyancy-driven HVDT, the flow evolution is divided into four different regimes based on the behaviour of turbulent kinetic energy derivatives. The results show that each regime has a unique type of dependence on both Atwood and Reynolds numbers. It is found that the local statistics of the flow based on the flow composition are more sensitive to Atwood and Reynolds numbers compared to those based on the entire flow. It is also observed that, at higher Atwood numbers, different flow features reach their asymptotic Reynolds-number behaviour at different times. The energy spectrum defined based on the Favre fluctuations momentum has less large-scale contamination from viscous effects for variable-density flows with constant properties, compared to other forms used previously. The evolution of the energy spectrum highlights distinct dynamical features of the four flow regimes. Thus, the slope of the energy spectrum at intermediate to large scales evolves from -7/3 to -1 , as a function of the production-to-dissipation ratio. The classical Kolmogorov spectrum emerges at intermediate to high scales at the highest Reynolds numbers examined, after the turbulence starts to decay. Finally, the similarities and differences between buoyancy-driven HVDT and the more conventional stationary turbulence are discussed and new strategies and tools for analysis are proposed.

42 ENGINEERING↗
DOE OSTI2025

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗
DOE OSTI2023

One dimensional wormhole corrosion in metals

Corrosion is a ubiquitous failure mode of materials. Often, the progression of localized corrosion is accompanied by the evolution of porosity in materials previously reported to be either three-dimensional or two-dimensional. However, using new tools and analysis techniques, we have realized that a more localized form of corrosion, which we call 1D wormhole corrosion, has previously been miscategorized in some situations. Using electron tomography, we show multiple examples of this 1D and percolating morphology. To understand the origin of this mechanism in a Ni-Cr alloy corroded by molten salt, we combined energy-filtered four-dimensional scanning transmission electron microscopy and ab initio density functional theory calculations to develop a vacancy mapping method with nanometer-resolution, identifying a remarkably high vacancy concentration in the diffusion-induced grain boundary migration zone, up to 100 times the equilibrium value at the melting point. Deciphering the origins of 1D corrosion is an important step towards designing structural materials with enhanced corrosion resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

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

Correction and verification of x-ray imaging crystal spectrometer analysis on Wendelstein 7-X through x-ray ray tracing

X-ray ray tracing is used to develop ion-temperature corrections for the analysis of the X-ray Imaging Crystal Spectrometer (XICS) used at Wendelstein 7-X (W7-X) and perform verification on the analysis methods. The XICS is a powerful diagnostic able to measure ion-temperature, electron-temperature, plasma flow, and impurity charge state densities. While these systems are relatively simple in design, accurate characterization of the instrumental response and validation of analysis techniques are difficult to perform experimentally due to the requirement of extended x-ray sources. For this reason, a ray tracing model has been developed that allows characterization of the spectrometer and verification of the analysis methods while fully considering the real geometry of the XICS system and W7-X plasma. Through the use of ray tracing, several important corrections have been found that must be accounted for in order to accurately reconstruct the ion-temperature profiles. The sources of these corrections are described along with their effect on the analyzed profiles. The implemented corrections stem from three effects: (1) effect of sub-pixel intensity distribution during de-curving and spatial binning, (2) effect of sub-pixel intensity distribution during forward model evaluation and generation of residuals, and (3) effect of defocus and spherical aberrations on the instrumental response. Possible improvements to the forward model and analysis procedures are explored, along with a discussion of trade-offs in terms of computational complexity. Finally, the accuracy of the tomographic inversion technique in stellarator geometry is investigated, providing for the first time a verification exercise for inversion accuracy in stellarator geometry and a complete XICS analysis tool-chain.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Metalloproteins in an Era of Modern Crystallography and Why the Beamline Matters

The Structural Molecular Biology (SMB) macromolecular crystallography (MC) group at the Stanford Synchrotron Radiation Lightsource (SSRL) have developed state-of-the-art capabilities tailored for metalloenzyme structural analysis. Metalloproteins sit at the center of biology’s most audacious chemistry. From multi-electron redox catalysis to radical rearrangements and light-driven transformations, metal sites give proteins access to reaction landscapes that would otherwise be inaccessible under ambient conditions. Yet their study presents a fundamental paradox for MC studies: the very X-rays we use to reveal atomic structure can alter the electronic states we seek to understand. As the field moves beyond static snapshots toward mechanistic insight, success increasingly depends on our ability to maintain metal centers in their native state throughout the experiment. The SSRL SMB-MC beamlines integrate a suite of capabilities specifically designed to address these challenges. By combining in situ spectroscopic verification, intelligent dose management, controlled reaction initiation, optimized anomalous diffraction, and real-time crystallographic diffraction analysis, these tools enable researchers to interrogate metalloproteins with unprecedented rigor. This article explores how these complementary approaches are reshaping our ability to capture metalloprotein chemistry, and what this means for mechanistic studies at synchrotron beamlines.

Maggiolo, Ailiena O. [SLAC National Accelerator La↗
DOE OSTI2021

SCOPe: improvements to the structural classification of proteins – extended database to facilitate variant interpretation and machine learning

Abstract The Structural Classification of Proteins—extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Measurement of ambient radon progeny decay rates and energy spectra in liquid argon using the MicroBooNE detector

We report measurements of radon progeny in liquid argon within the MicroBooNE time projection chamber (LArTPC). The presence of specific radon daughters in MicroBooNE’s 85 metric tons of active liquid argon bulk is probed with newly developed charge-based low-energy reconstruction tools and analysis techniques to detect correlated Bi 214 − Po 214 radioactive decays. Special datasets taken during periods of active radon doping enable new demonstrations of the calorimetric capabilities of single-phase neutrino LArTPCs for β and α particles with electron-equivalent energies ranging from 0.1 to 3.0 MeV. By applying Bi 214 − Po 214 detection algorithms to data recorded over a 46-day period, no statistically significant presence of radioactive Bi 214 is detected, and a limit on the activity is placed at < 0.35 mBq / kg at the 95% confidence level. This bulk Bi 214 radiopurity limit—the first ever reported for a liquid argon detector incorporating liquid-phase purification—is then further discussed in relation to the targeted upper limit of 1 mBq / kg on bulk Rn 222 activity for the DUNE neutrino detector. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Reconstructing the reflectivity of liquid surfaces from grazing incidence X-ray off-specular scattering data

The capillary wave model of a liquid surface predicts both the X-ray specular reflection and the diffuse scattering around it. A quantitative method is presented to obtain the X-ray reflectivity (XRR) from a liquid surface through the diffuse scattering data around the specular reflection measured using a grazing incidence X-ray off-specular scattering (GIXOS) geometry at a fixed horizontal offset angle with respect to the plane of incidence. With this approach the entire Q z -dependent reflectivity profile can be obtained at a single, fixed incident angle. This permits a much faster acquisition of the profile than with conventional reflectometry, where the incident angle must be scanned point by point to obtain a Q z -dependent profile. The XRR derived from the GIXOS-measured diffuse scattering, referred to in this paper as pseudo-reflectivity, provides a larger Q z range compared with the reflectivity measured by conventional reflectometry. Transforming the GIXOS-measured diffuse scattering profile to pseudo-XRR opens up the GIXOS method to widely available specular XRR analysis software tools. Here the GIXOS-derived pseudo-XRR is compared with the XRR measured by specular reflectometry from two simple vapor–liquid interfaces at different surface tension, and from a hexadecyltrimethylammonium bromide monolayer on a water surface. For the simple liquids, excellent agreement (beyond 11 orders of magnitude in signal) is found between the two methods, supporting the approach of using GIXOS-measured diffuse scattering to derive reflectivities. Pseudo-XRR obtained at different horizontal offset angles with respect to the plane of incidence yields indistinguishable results, and this supports the robustness of the GIXOS-XRR approach. The pseudo-XRR method can be extended to soft thin films on a liquid surface, and criteria are established for the applicability of the approach.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes

Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.

Tabassum, Anika↗
DOE OSTI2021

Modeling Data Movement Performance on Heterogeneous Architectures

The cost of data movement on parallel systems varies greatly with machine architecture, job partition, and nearby jobs. Performance models that accurately capture the cost of data movement provide a tool for analysis, allowing for communication bottlenecks to be pinpointed. Modern heterogeneous architectures yield increased variance in data movement as there are a number of viable paths for inter-GPU communication. In this paper, we present performance models for the various paths of inter-node communication on modern heterogeneous architectures, including the trade-off between GPUDirect communication and copying to CPUs. Furthermore, we present a novel optimization for inter-node communication based on these models, utilizing all available CPU cores per node. Finally, we show associated performance improvements for MPI collective operations.

97 MATHEMATICS AND COMPUTING↗