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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Microstructure–Property Correlation in a Laser Powder Bed Fusion Processed High-Strength AF-9628 Steel

Laser powder bed fusion additive manufacturing (LPBF-AM) of a low-alloy, high-performance AF-9628 steel results in exceptionally high strength and good ductility. The reasons for such mechanical properties are investigated through detailed microscopy performed at several length scales. Thus, the characterization of melt pool, porosity, grain morphology, phases, and dislocations is performed in the as-printed material. The as-printed material consists of only 0.004 vol% of uniformly distributed porosity, single-phase martensitic laths with an average lath size of ≈2.5 μm, the absence of carbides indicating interstitial trapping of C atom, and high dislocation density in the martensitic laths. Experimental data through microscopy are then fed in analytical models for calculating strengthening contributions from various strengthening mechanisms. Calculated yield strength agrees well with experimentally determined value, and therefore, activation of various strengthening mechanisms is established in as-printed AF-9628.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dimensionless parameters for ballistic performance evaluation of ceramic-faced bicomponent targets against sharp-nosed projectiles

Two dimensionless parameters are proposed to give first-order approximations for the ballistic performance of ceramic-faced bicomponent armor plates impacted by conical-nosed steel projectiles. The current work collates expansive experimental data from Wilkins and Mayseless covering a broad range of material and mechanical properties, target construction, and projectile dimensions, the data is collapsed using the Hugoniot elastic limit of the ceramic strike face as a strength metric. We find that within datasets where experimental conditions are kept constant, a singular cubic curve can be generated, but variations in experimental conditions for the ballistic limit test between datasets can result in differences in the predictive curve coefficients.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A continuum damage mechanics (CDM) based Wilshire model for creep deformation, damage, and rupture prediction

In this report, a new constitutive model is derived that combines the Wilshire equations with continuum damage mechanics (CDM) to enable the long-term prediction of creep deformation, damage, and rupture. The Wilshire equations have been demonstrated to accurately extrapolate the stress-rupture, minimum-creep-strain-rate, and time-to-strain of various alloys across decade of life. Recently, the time-to-creep-strain equation has been rearranged to predict creep deformation curves; however, the resulting equation is difficult to calibrate and does not track damage. The CDM-based Sinh constitutive model accurately predicts creep deformation, damage, and stress-rupture for a variety of alloys; however, it lacks an explicit description of stress and temperature co-dependence which limits interpolation and extrapolation ability. In this study, the Wilshire and the CDM-based Sinh equations are combined to create the “WCS” model. The WCS model combines the best features of each model while eliminating their deficiencies. Experimental data for alloy P91 is gathered and the WCS model is calibrated to the data. The WCS model accurately predicts the stress rupture, minimum-creep-strain-rate, creep deformation, and damage of alloy P91 across the experimental stress and temperature range as well as consistency in parametric simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗
DOE OSTI2021

Trimeron-phonon coupling in magnetite

Using density functional theory, we study the lattice dynamical properties of magnetite (Fe 3 O 4 ) in the high-temperature cubic and low-temperature monoclinic phases. The calculated phonon dispersion curves and density of states are compared with the available experimental data obtained by inelastic neutron, inelastic x-ray, and nuclear inelastic scattering. We find a very good agreement between the theoretical and experimental results for the monoclinic Cc structure revealing the strong coupling between the charge-orbital (trimeron) order and specific phonon modes. For the cubic phase, clear discrepancies arise due to fluctuation effects, which are not included in the calculation method. Despite this shortcoming, we argue that the main spectral features can be understood assuming that the strong trimeron-phonon coupling is extended above the Verwey transition, with lattice dynamics influenced by the short-range order instead of the average cubic structure. Our results indicate the validity of trimerons (and trimeron-phonon coupling) to explain the physics of magnetite much beyond their original formulation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Prompt-delayed γ-ray spectroscopy of neutron-rich 119.121 In isotopes

The Z = 50 shell closure, near N = 82, is unique in the sense that it is the only shell closure with the spin-orbit partner orbitals, π g 9 / 2 and π g 7 / 2 , enclosing the magic gap. The interaction of the proton hole/particle in the above-mentioned orbitals with neutrons in the νh 11/2 orbital is an important prerequisite to the understanding of the nuclear structure near N = 82 and the νπ interaction. To explore the structural similarity between the high-spin isomeric states in In ( Z = 49), Sn ( Z = 50), and Sb ( Z = 51) isotopes from a microscopic point of view. In addition, to understand the role of a proton hole or particle in the spin-orbit partner orbitals, π g 9 / 2 and π g 7 / 2 , respectively, with neutron holes in the ν h 11 / 2 orbital on these aforementioned isomers. The fusion and transfer induced fission reaction Be 9 ( U 238 , f ) with 6.2 MeV/u beam energy, using a unique setup consisting of AGATA, VAMOS++, and EXOGAM detectors, was used to populate through the fission process and study the neutron-rich In 119 , 121 isotopes. This setup enabled the prompt-delayed γ -ray spectroscopy of isotopes in the time range of 100 ns – 200 μ s . In the odd- A In 119 , 121 isotopes, indications of a short half-life 19/2 - isomeric state, in addition to the previously known 25/2 + isomeric state, were observed from the present data. Further, new prompt transitions above the 25/2 + isomer in In 121 were identified along with reevaluation of its half-life. The experimental data were compared with the theoretical results obtained in the framework of large-scale shell-model calculations in a restricted model space. Furthermore, the ( π g 9 / 2 ν h 11 / 2 ; I | H ^ | π g 9 / 2 ν h 11 / 2 ; I ) two-body matrix elements of residual interaction were modified to explain the excitation energies and the B ( E 2) transition probabilities in the neutron-rich In isotopes. The (i) decreasing trend of E (29/2 + ) - E (25/2 + ) in odd-In (with dominant configuration π g 9 / 2 - 1 ν h 11 / 2 - 2 and maximum aligned spin of 29/2 + ) and (ii) increasing trend of E (27/2 + ) - E (23/2 + ) in odd-Sb (with dominant configuration π g 7 / 2 + 1 ν h 11 / 2 - 2 and maximum aligned spin of 27/2 + ) with increasing neutron number could be understood as a consequence of hole-hole and particle-hole interactions, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Decay studies of the 𝛽-delayed neutron emitters 87 Br and 88 Br measured by means of the Modular Total Absorption Spectrometer at ORNL HRIBF

The β decays of 87 Br, 88 Br, and 87 Kr were measured with the Modular Total Absorption Spectrometer (MTAS) at Oak Ridge National Laboratory’s Holifield Radioactive Ion Beam Facility (HRIBF). Both bromine isotopes are β-delayed neutron emitters that have large cumulative fission yields and were identified as top-priority cases for total absorption study by the Nuclear Energy Agency in 2007. Our investigations corroborate that the decay schemes of 87 Br and 88 Br suffer from the so-called pandemonium effect. Unique MTAS properties enable direct neutron measurements. Here, we present MTAS-derived β-delayed neutron spectra, β-delayed neutron emission probabilities of P n ( 87 Br) = 2.36(24)%, and P n ( 88 Br) = 6.4(6)%, and the β-delayed neutron transitions intensity of 4(2)% to the first excited 87 Kr state, populated in the β-neutron decay of 88Br. Incorporating new data into calculations of the electromagnetic decay heat component emitted during thermal neutron fission of 235 U and 239 Pu improves agreement with experimental data up to approximately 80 s after fission. The estimation of the nuclear reactor $\bar{ν}_e$ flux results in changes of up to 1% in the expected $\bar{ν}_e$ interactions with the detector material for 235 U, 238 U, 239Pu, and 241 Pu.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Experimental testing of hypotheses for temperature‐ and pH ‐based niche specialization of ammonia oxidizing archaea and bacteria

Summary Investigation of niche specialization in microbial communities is important in assessing consequences of environmental change for ecosystem processes. Ammonia oxidizing bacteria (AOB) and archaea (AOA) present a convenient model for studying niche specialization. They coexist in most soils and effects of soil characteristics on their relative abundances have been studied extensively. This study integrated published information on the influence of temperature and pH on AOB and AOA into several hypotheses, generating predictions that were tested in soil microcosms. The influence of perturbations in temperature was determined in pH 4.5, 6 and 7.5 soils and perturbations in pH were investigated at 15°C, 25°C and 35°C. AO activities were determined by analysing changes in amoA gene and transcript abundances, stable isotope probing and nitrate production. Experimental data supported major predictions of the effects of temperature and pH, but with several significant discrepancies, some of which may have resulted from experimental limitations. The study also provided evidence for unpredicted activity of AOB in pH 4.5 soil. Other discrepancies highlighted important deficiencies in current knowledge, particularly lack of consideration of niche overlap and the need to consider combinations of factors when assessing the influence of environmental change on microbial communities and their activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Investigation of Gas Turbine Internal Cooling Using Supercritical CO 2 —Effect of Surface Roughness and Channel Aspect Ratio

In this paper, an experimental and numerical investigation of internal cooling channels with rib turbulators is presented with sCO 2 as the working fluid at process conditions (pressure-20.7 MPa and temperature up to 150 °C). The effect of channel aspect ratio up to 2:1 on thermal-hydraulic performance is explored in additively manufactured rectangular channels and square channels, both with and without 60 deg ribs on the top and bottom sides. The Wilson-plot method is employed to experimentally measure channel-averaged Nusselt number over a Reynolds number range up to 370,000. The friction factor is calculated from pressure drop and mass flow rate and additionally, the overall thermal performance factor (TPF) is reported. A companion computational fluid dynamics (CFD) simulation is performed for the rib turbulated cooling configurations reported in the experiments using the Reynolds average Navier–Stokes-based turbulence model. The objective of the numerical study is to gain insight into the local heat transfer augmentation in the ribbed channels as a result of varying the aspect ratio, channel configuration (square versus rectangular), operating conditions (Reynolds number) and the surface roughness, an inherent outcome of the additive manufacturing process. Surface roughness is simulated using sand grain roughness height (K S ) calculated from the experimental data, and a comparison is presented with the corresponding channel configuration with varying surface roughness heights starting from smooth surfaces (K S = 0). Experimental results indicate that the heat transfer augmentation is negligible in the rectangular channels with ribs on the long side compared to the square channel. However, it is enhanced by 60% in comparison to placing ribs on the shorter side. The TPF remains constant at around 1 for the entire range of Reynolds numbers consistent with prior work at the National Energy Technology Laboratory (NETL). Here, the simulation results highlight that increased surface roughness can have a favorable considerable influence on Nusselt number and overall thermal performance enhancement.

42 ENGINEERING↗
DOE OSTI2020

Curation of Ground-Truth Validated Benchmarking Datasets for Fault Detection & Diagnostics Tools

Fault detection and diagnostics (FDD) analytical tools for heating, ventilation and air conditioning (HVAC) systems represent one of the most active areas of smart building technology development. A diversity of techniques is used for FDD analytics, spanning physical models, black box, and rule-based approaches, and researchers continuously strive to develop improved algorithms. With FDD algorithm numbers now in the hundreds, there is a need for performance evaluation of these algorithms in order to assess improvements, improve costeffectiveness, and to prioritize investment in the further development of these technologies. A persistent challenge of FDD advance has been the lack of common datasets to benchmark the performance accuracy of FDD algorithms. This paper summarizes the successful curation of HVAC operational data, paired with validated ground-truth information regarding the presence and absence of faults. The current dataset, consisting of both simulation and experimental data, will evolve to include a larger set of HVAC systems with the objective of creating the largest publicly available dataset to be used by FDD developers, users, and researchers to compare and contrast performance accuracy across FDD algorithms, helping to drive improvements that will spur greater market adoption of FDD tools. Furthermore, in order to avoid previously observed issues with contributed datasets and ensure high quality and consistency of future submissions, the development of data validation and ground-truth assessment protocol is detailed in this study.

Casillas, Armando↗
DOE OSTI2020

Model Development for Multi-Component Fuel Vaporization and Flash Boiling

The objectives of this project are to improve the multi-component fuel droplet and film vaporization models used in internal combustion engine simulation, and to develop a comprehensive model to predict the characteristics of multi-component flash boiling spray. This work explores two approaches to fuel composition treatment for modeling multi-component fuel vaporization: one based on discretization and surrogates, and the other based on continuous thermodynamic distribution of fuel properties. The experimental data collected for model validation are done under three fuel form factors: droplet, spray, and thin film. The study on sprays also include experimentation under non-flash and flash boiling conditions, a phenomenon that enhances fuel vaporization. The main goals of this work are: Design and develop a multi-component fuel droplet and wall film vaporization model using both discrete and continuous thermodynamics methods. Design and develop an analytical model for multi-component flash boiling. Integrate the multi-component droplet and film model into multi-dimensional engine calculations to predict the fuel vaporization process under engine operation condition. Conduct multi-component droplet and fuel film vaporization experiments in a non-combusting chamber to verify the proposed vaporization models. Characterize flash boiling phenomena of multi-component fuel sprays by optical and laser diagnostic techniques. This report will detail the experimental setup and the numerical basis for developing a model to achieve the main goals listed above. Key features of observed multi-component fuel vaporization will be summarized at the end of each experimental sections, and corresponding model performance evaluation will be presented at the end of each model development section.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Nuclear Data Sheets for A=245

Available information pertaining to the nuclear structure of ground and excited states for all known nuclei with mass numbers A=245 have been compiled and evaluated. In this work, the adopted level and decay schemes, as well as the detailed nuclear properties and configuration assignments based on experimental data, are presented for these nuclides. When there are insufficient data, expected values from systematics of nuclear properties and/or theoretical calculations are utilized. Unexpected or discrepant experimental results are also noted. Since the last evaluation, new rotational bands in 245 Pu have been observed to high spin from transfer reaction 244 Pu( 209 Bi, 208 Biγ) by 2014Ho16. While in 245 Am, the 249 Bk α decay measurements by 2013Ah03 added a new rotational band based on π3/2[521] configuration. The 245 Pu β - decay scheme is basically what was proposed in the late 60's and 47 γ rays have still not been placed. In 245 Cm, precise alpha energies and intensities were measured by 2015Ah03 in 249Cf α decay. Their reported alpha energies of the main α group were about 2 keV lower than in the previous evaluation. The spin and parity of the g.s. of 245 Es is still ambiguous as more detailed information on the decay is needed. With the production of 249 No via fusion evaporation reaction by groups in Dubna and GSI, it's alpha decay was studied and some properties of the daughter 245 Fm were published and included in this evalaution. Information on the other nuclides is scarce and not much has been investigated since the last evaluation. A summary and compilation of the discovery of the various nuclides in this mass region is given in: 2013Fr02 ( 245 Pu, 245 Am, 245 Cm, 245 Bk, 245 Cf), 2011Me01 ( 245 Es), and 2013Th02 ( 245 Md, 245 Fm).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Digital image correlation and infrared thermography data for seven unique geometries of 304L stainless steel

Material Testing 2.0 (MT2.0) is a paradigm that advocates for the use of rich, full-field data, such as from digital image correlation and infrared thermography, for material identification. By employing heterogeneous, multi-axial data in conjunction with sophisticated inverse calibration techniques such as finite element model updating and the virtual fields method, MT2.0 aims to reduce the number of specimens needed for material identification and to increase confidence in the calibration results. To support continued development, improvement, and validation of such inverse methods—specifically for rate-dependent, temperature-dependent, and anisotropic metal plasticity models—we provide here a thorough experimental data set for 304L stainless steel sheet metal. The data set includes full-field displacement, strain, and temperature data for seven unique specimen geometries tested at different strain rates and in different material orientations. Commensurate extensometer strain data from tensile dog bones is provided as well for comparison. We believe this complete data set will be a valuable contribution to the experimental and computational mechanics communities, supporting continued advances in material identification methods.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A crystal plasticity finite element model embedding strain-rate sensitivities inherent to deformation mechanisms: Application to alloy AZ31

We report the fundamental power-law relationship representing the flow rule in crystal visco-plasticity ensures uniqueness in the selection of slip systems accommodating imposed plastic strain-rates. The power-law relationship also introduces an artificially high strain-rate sensitivity in crystal plasticity simulations, unless a high value of the power-law exponent is used. However, the use of high values for the exponent is limited by numerical tractability. This paper presents a numerical method implemented in a crystal plasticity finite element (CPFE) model for embedding any value of the power-law exponent reflecting the true material strain-rate sensitivity. Importantly, the method does not increase computation time involved in the simulations. The enhanced CPFE model is used to interpret and predict a complex strain-rate sensitive response and microstructural evolution of AZ31 Mg alloy. Measured values of strain-rate sensitivity for slip and twinning modes are used in the simulations. Calculations show that the model successfully captures the phenomena pertaining to the effect of changing applied strain-rate on the mechanical response including flow stress and evolution of texture and twinning for a broad range of strain-rates ranging from 10 -3 s -1 to 10 3 s -1 and loading orientations in tension and compression. It is shown that such predictions are a consequence of not only relative amounts of slip and twinning activities driven by a set of accurately characterized hardening law parameters but also values of the strain-rate sensitivities inherent to individual deformation mechanisms. Besides, the model validates the measured strain-rate dependency of deformation mechanisms while accurately reproducing the mechanical data. Hence, the model can be used to verify and further refine or infer measured strain-rate sensitivity per deformation mechanism by reproducing experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Highly selective ion separations based on counter-flow electromigration in nanoporous membranes

Highly selective ion separations are vital for recovering important salts, and membrane-based techniques may enable environmentally friendly ion separations that operate continuously. This study demonstrates that simply opposing convective flow with electromigration in track-etched membranes leads to remarkable selectivities among monovalent ions. Because the membrane-pore diameters are orders of magnitude larger than the ion diameters, advection moves all ions at the same velocity, whereas electrophoretic velocities are proportional to ion mobilities. Thus during counter-flow cation electromigration, less mobile cations have lower electromigration velocity components and pass through porous membranes more rapidly than more mobile cations. Using membranes with 400 nm pores, counter-flow electromigration gives Li + /K + selectivities of 100 and Li + /Na + selectivities around 30 in mixed-salt studies. In this work, numerical simulations based on the extended Nernst-Planck equation agree with trends in experimental data and highlight the importance of high Péclet numbers, high current-to-flow ratios, and uniform current distributions for achieving high selectivities. Importantly, experimental separations give high selectivities at 0.3 M ionic strength and low Li + /K + ratios, which suggest these methods may also work in brine solutions. Nevertheless, energy costs for such separations are high.

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

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗