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Results for “strain gradient modeling”

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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103 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterization of electromigration-induced short-range stress development in Al(0.25 at. % Cu) conductor line

Scanning x-ray microbeam topography and fluorescence experiments were conducted in situ to study the electromigration behavior of a 0.5 μm thick, 10 μm wide, and 200 μm long Al(0.25 at. % Cu) conductor line with 1.5 μm-thick SiO2 passivation on a single crystal Si substrate. The strain sensitivity of x-ray topography measurement allowed detailed examination of the electromigration-induced stress distribution and evolution in the conductor line in response to the depletion of Cu solute early in the electromigration process. Upon electromigration at 0.4 MA/cm2 and 303 °C, a short-range stress gradient was quickly induced by Al migration in the Cu-depleted cathode region to counteract further Al flow. The stress gradient was fully developed during the 5.3 h incubation time, extending over the critical Blech length of about 66 μm from the cathode end. Plastic deformation then occurred at the downstream end of the Cu-depleted region. The preferential electromigration of Cu did not cause detectable stress change outside the Cu-depleted region, except for the significant stress development from the Al2Cu precipitation at the anode end which appeared to initiate the fracture in the passivation. Preliminary finite difference modeling was undertaken to simulate the experimental observations, from which important parameters dictating electromigration in Al(Cu) line were extracted: an apparent effective valence of −5.6 and −1.9 for Cu and Al in Al(Cu), respectively, and a critical Cu concentration of 0.16 at. % above which Al grain boundary diffusion is effectively blocked.

Physics↗
DOE OSTI2026

Micromechanical and fatigue in situ synchrotron characterization of an additively manufactured superalloy with porosity

Additive manufacturing (AM) has the potential to transform component production, but its widespread adoption is constrained by defects, such as pores, that compromise structural integrity. Here, this study investigates the influence of porosity on the micromechanical and fatigue response of AM Inconel 718 (IN718), a widely used aerospace superalloy. One baseline specimen with minimal stochastic porosity and another intentionally seeded with lack of fusion (LOF) pores were examined using high-energy X-ray diffraction microscopy (HEDM) and micro-computed tomography during cyclic loading. Fatigue cracks in the LOF specimen initiated more frequently and at lower cycle counts than in the baseline specimen. The number fraction of fatigue cracks that grew was comparatively higher in the LOF specimen. Grain-level metrics, including stress and diffraction spot widths, were quantified using far-field HEDM. Across the thousands of grains detected in both specimens, the pores in the LOF specimen increased the variability of stress and spot width evolution in the azimuthal direction, the latter serving as a surrogate measure of plastic deformation. However, no correlations emerged between these metrics and grain proximity to fatigue crack initiation sites or pores, underscoring the limitations of grain-averaged metrics for predicting fatigue. Nonetheless, the rich dataset reported here provides a foundation for future modeling efforts.

High-energy X-ray diffraction microscopy↗
DOE OSTI2020

The weakly nonlinear response and nonaffine interpretation of the Johnson–Segalman/Gordon–Schowalter model

We derive new analytical solutions for the non-affine Johnson-Segalman/Gordon-Schowalter (JS/GS) constitutive equation with a general relaxation kernel in medium-amplitude oscillatory shear (MAOS) deformation. The results show time-strain separable (TSS) nonlinearity, therefore providing new physically-meaningful interpretation to the heuristic TSS nonlinear parameter in MAOS. The upper-convected, lower-convected, and corotational Maxwell models are all subsets of the results presented here. The model assumes that the microscale elements causing stress in the material slip compared to the continuum deformation. We introduce a visualization of the non-affine deformation field that acts on stress-generating elements to reinforce the hysical interpretation of the JS/GS class of models. Lastly, a case study is presented where previously published results, from fitting TSS models to MAOS data, can be re-interpreted based on the concept of non-affine motion of the JS/GS framework.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Crystal plasticity model of residual stress in additive manufacturing using the element elimination and reactivation method

Selective laser melting is receiving increasing interest as an additive manufacturing technique. Residual stresses induced by the large temperature gradients and inhomogeneous cooling process can favour the generation of cracks. In this work, a crystal plasticity finite element model is developed to simulate the formation of residual stresses and to understand the correlation between plastic deformation, grain orientation and residual stresses in the additive manufacturing process. The temperature profile and grain structure from thermal-fluid flow and grain growth simulations are implemented into the crystal plasticity model. An element elimination and reactivation method is proposed to model the melting and solidification and to reinitialize state variables, such as the plastic deformation, in the reactivated elements. The accuracy of this method is judged against previous method based on the stiffness degradation of liquid regions by comparing the plastic deformation as a function of time induced by thermal stresses. The method is used to investigate residual stresses parallel and perpendicular to the laser scan direction, and the correlation with the maximum Schmid factor of the grains along those directions. The magnitude of the residual stress can be predicted as a function of the depth, grain orientation and position with respect to the molten pool. The simulation results are directly comparable to X-ray diffraction experiments and stress–strain curves.

316 stainless steel↗
DOE OSTI2026

Long-Length SiC/SiC Tube Irradiation Experiment at LWR Temperatures Inserted into HFIR

This report describes the pre-irradiation characterization and successful assembly of a High Flux Isotope Reactor (HFIR) irradiation experiment designed to assess radiation-induced lateral bowing of silicon carbide fiber–reinforced, silicon carbide matrix composite (SiC/SiC) components under a radial fast neutron flux gradient at representative light-water reactor (LWR) temperatures of approximately 300 °C. The over-arching goal of this work is to validate thermomechanical models of SiC/SiC composite fuel assembly distortion used to predict the extent of lateral bowing and dose at which bowing reaches a maximum value. Ultimately, these models are used to ensure that fuel assembly distortion does not block coolant channels, interfere with control rod/blade movements, and/or impact local reactivity. The experiment contains six cladding tube specimens that are approximately 558.5 mm long with representative pressurized water reactor (PWR) outer and inner diameters of 9.5 mm and 7.5 mm, respectively. The specimens were thoroughly characterized prior to irradiation using traditional dimensional inspection and surface profilometry so that these measurements can later be compared with similar measurements that will be made post-irradiation to determine radiation-induced deformations. Furthermore, fine engraving markers were inscribed along the outer surfaces of the specimen and mapped using analytic photography and a three-dimensional stage. This technique allowed for accurate measurements of the marker spacings, which can be compared with similar measurements that will be made post-irradiation to provide local radiation-induced strain mapping. A light curtain optical micrometer was also employed to measure the pre-irradiation bowing of each specimen. The experiment was successfully assembled and inserted into position VXF-19 for HFIR cycle 516, which began May 12, 2026. The experiment will be removed after cycle 519, which is currently scheduled to end in December 2026.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

FutureTense

Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we “future-proof” vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, “grand challenge” problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, “FutureTense”, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.

Gans, Jason↗
DOE OSTI2023

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Large eddy simulation of lean blow-off in swirl-stabilized flame with the subgrid dissipation concept

The lean blow-off mechanism of the premixed swirl flame is numerically investigated by large eddy simulation (LES) with the subgrid dissipation concept (SDC) combustion model. Three simulated cases cover stable, near blow-off, and transient conditions. Compared with the experiment, the LES-SDC approach captures the flow and combustion features for stable and near blow-off conditions. More importantly, the predictions of the blowoff procedure and duration agree satisfactorily with the experiment, indicating that the LES-SDC approach is a promising tool for predicting strong, unsteady turbulent combustion processes. Further, the numerical results are used to investigate the blow-off mechanism. Two stages in the blow-off procedure are specified. The first is the necking and extinction of the downstream flame surface, and the second is the shrinking of the upstream flame surface. The blow-off mechanism is well explained by the theory of stretched flame extinction. At the end of the recirculation zone, the large negative radial velocity pushes the flame to the central line. The combustion process here can be abstracted as the stretched counter-flame of the reactant-reactant configuration. The excessive flame stretch dominates the flame extinction and triggers the blow-off event. The upstream flame resists the intense stretch with the help of hot product recirculation, and the combustion here can be idealized as the counter-flame of the reactant-product configuration. The alignment of the temperature gradient and flow velocity, together with the excessive stretch, clearly indicates the tendency of flame local extinction. A Damköhler number-based blow-off criterion is raised from the mean flow strain rate and laminar flame bulk extinction strain rate.

42 ENGINEERING↗
DOE OSTI2024

Vacancy-mediated transport and segregation tendencies of solutes in fcc nickel under diffusional creep: A density functional theory study

The Nabarro-Herring (NH) diffusional creep theory postulates the vacancy-mediated transport of atoms under a stress gradient as the creep mechanism under low-stress and high-temperature conditions. In multicomponent alloys, we premise that this stress-assisted flow of vacancies to and from grain boundaries will produce elemental segregation. An observation of such segregation, validated with theoretical predictions, can provide the necessary experimental evidence for the occurrence of NH creep. Theoretical calculations of the segregation tendencies via analyzing the dominant solute diffusion mechanisms and the difference in diffusivities of the elements are therefore essential. To this end, this study applies density functional theory calculations of migration barriers and solute-vacancy binding energies as input to the self-consistent mean-field theory to assess the vacancy-mediated diffusion mechanisms, transport coefficients, and segregation tendencies of Co, Cr, Mo, Re, Ta, and W solutes in face-centered-cubic Ni. We find Co, Re, and W to be slow diffusers at high temperatures and Cr, Mo, and Ta to be fast diffusers. Further analysis shows that the slow diffusers tend to always enrich at vacancy sinks over a wide range of temperatures. In contrast, the fast diffusers show a transition from depletion to enrichment as the temperature lowers. Furthermore, our analysis of the segregation tendencies under tensile hydrostatic strains shows that slow diffusers are largely unaffected by the strain and favor enrichment. On the other hand, the fast diffusers exhibit high sensitivity to strain and their segregation tendency can transition from depletion to enrichment at a given temperature. Finally, the transport coefficients calculated in this work are expected to serve as input to mesoscale microstructure models to provide a more rigorous assessment of solute segregation under NH creep conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigation of grain size and geometrically necessary dislocation density dependence of flow stress in Mg-4Al by using nanoindentation

Models for grain size dependence of flow stress typically ignore contributions from geometrically necessary dislocations (GNDs) in the grain boundary regions. Ashby had proposed the following equation for flow stress (τ) as a function of grain size (d) and effective plastic strain ($\bar{ε}$): $τ = τ_{0} + C'G\sqrt{^{b\bar{ε}}_{d}}$ using an unknown empirical coefficient, C’, In this study, the coefficient, C’, and equation for the grain size dependence of flow stress were investigated in Mg-4Al using nanoindentation. C’ ranges from 1.4 to 7.11 that is related to the hardness difference (∆H0) between the adjacent grains as $C' + 0.62\sqrt{ΔH_{0}}$. Ashby equation was used to predict uniaxial stress-strain curves in grain sizes of 55 µm, 187 µm, and 333 µm. The results showed lower flow stress and lower hardening rate compared to experimentally measured tensile stress-strain response. The discrepancy seems to be a result of hardening effect of SSDs. Here, we propose a modified Ashby equation that takes into account the hardening effect of SSDs and GNDs separately, resulting in a better agreement between calculated and experimentally measured values. This analysis demonstrates estimation of uniaxial stress-strain response using nanoindentation measurements that captures effects of grain size, and strain hardening from SSDs and GNDs. The combination of the revised equation and nanoindentation method will enable rapid exploration of stress-strain response of a diverse range of single-phase polycrystalline alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microstructural Characterization of the Second High Fluence Baffle-Former Bolt Retrieved from a Westinghouse Two-loop Downflow Type PWR

As one of the pressurized water reactor (PWR) internal components, baffle-former bolts (BFBs) are subjected to significant mechanical stress and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and reduced load-carrying capacity of the bolts. In support of evaluating long-term operational performance of materials used in core internal components, the Oak Ridge National Laboratory (ORNL), through the Department of Energy (DOE), Light Water Reactor Sustainability (LWRS) Program, Materials Research Pathway (MRP) has harvested two high fluence BFBs from a commercial Westinghouse two-loop downflow type PWR. The two bolts of interest, i.e. bolts # 4412 and 4416, were withdrawn from service in 2011 as part of a preventative replacement plan. No identification of cracking or potential damage was found for these bolts during their removal in 2011. However, the bolts required a lower torque for removal from the baffle structure than the original torque specified during installation. Irradiation displacement damage levels in the bolts range from 15 to 41 displacements per atom. The goal of this project is to perform detailed microstructural and mechanical property characterization of BFBs following in-service exposures. The information from these bolts will be integral to the LWRS program initiatives in evaluating end of life microstructure and properties. Furthermore, valuable data will be obtained that can be incorporated into model predictions of long-term irradiation behavior and compared to results obtained in high flux experimental reactor conditions. In this report, we present our latest study in FY22 on microstructural characterizations of the second high fluence baffle-former bolt, i.e., bolt # 4412. Analytical electron microscopy and atom probe tomography characterization were performed. The radiation-induced defects in the material add to the large wealth of knowledge for neutron-induced defects in 304/316 grades of stainless steels, specifically for radiation-induced precipitation after high fluence commercial PWR irradiation. The main findings are summarized as follows: 1) The cavity size was considerably larger in the bolt thread section than in the bolt head, with the bolt thread section having a bimodal distribution of cavities greater than ~6 nm in diameter and less than ~3 nm in diameter. The bolt head only had the small-sized cavities. In addition, there was a denuded zone of large cavities near grain boundaries in the thread section of the bolt. 2) Radiation-induced precipitation in the BFB #4412 was highly complex, with the volume fraction, size, and number density of Ni/Si and Cu-rich precipitates depending strongly on the radiation temperature/dose. In many cases, co-precipitates of adjoined clusters were found with Ni/Si-rich precipitates sandwiched between Cu-rich clusters and Mo/Cr/P-rich clusters. 3) Solute segregation out of solution was highest for most solutes in the thread section of the bolt #4412 with the exception of Cu, which experienced more separation out of solution into Curich clusters in the bolt head section. This highlights the difference in the mechanisms for precipitation of Ni/Si clusters, which have the Ni 3 Si phase composition, and precipitation of Cu-rich clusters. 4) There appear to be multiple simultaneous influences that affect the microstructural variation along the length of the bolt that overcomes the ~2X difference in irradiation dose between the bolt head and the bolt thread. The irradiation temperature, thermal/fast neutron ratio variation, potential strain gradient, and exposure to PWR coolant water that each section of the bolt sees may have more influence on the microstructural evolution than the total irradiation dose. The bolt thread and shank, with higher temperature, higher relative fast neutron flux, higher strain, and exposure to coolant but lower dose, underwent more enhanced cavity formation, precipitation, and solute segregation than the bolt head section.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Flexoelectricity and New Phenomena

It is easy to miss the scientific implications of our recent work on Triboelectricity. Everyone knows that rubbing and contact can produce static electricity; less appreciated is that the thermodynamic driver has been an open question since static electricity was first observed by Thales of Miletus around 585 BC. People think they understand it, for instance one common explanation that can still be found in the current literature is that differences in the work function drives charge transfer, often called the Volta-Helmholtz hypothesis. As summarized in 1967 by Harper, this fails to explain many experimental observations, for instance that charging can occur when two pieces of the same material are rubbed against each other. We are the first to place triboelectricity on a solid foundation rooted in quantum mechanics – the flexoelectric effect. We were able to explain a significant number of previously unexplained phenomena: 1) Bipolar tribocurrents associated with stick-slip, due to the change in sign of the strain gradients. 2) A one-third power scaling of tribocurrents with indentation force. 3) Tribocharging when two identical materials are used, these being due to local variations in the asperities so there are usually local potential differences. 4) Inhomogeneous charging of insulators, related to the statistical nature of asperities. 5) An experimentally observed reversal in the sign of charge transfer for negative and positive curvature, which is related to a change in the sign of the strain gradient. Exploiting our DOE prior funded work on flexoelectricity, we obtained semi-quantitative matching to existing experimental measurements of the surface charge in triboelectric experiments. The work has been well received in the literature. The work has been the focus of a number of popular science press articles, and also formed the basis for a Podcast for children 6-10 “The Rise and Fall of Static Man” posted in December 2019 by NPR as part of their “Wow in the World” series. I was also briefly interviewed by the Chicago PBS station in January 2020. This work are significant for a wide range of energy applications; to quote from an independent source: "Triboelectric power has plenty of potential, says Wenzhuo Wu, an assistant professor of engineering at Purdue. If the basics of static electricity are better understood, we could maximize the efficiency of wind or wave power generators, Wu says. The body's own movement could be used to power internal medical devices. Imagine being able to create a roof shaped to harness the power of a raindrop — the friction of the rain passing over the surface — to generate triboelectricity, powering the building below it." This is the start of new science, some of which we already partially understand such as the role of band bending in charge transfer. We need to understand charge transfer combining elasticity, quantum mechanics, band bending and defect states. These directly involve several of the DOE Grand Challenges: "How do we control material processes at the level of electrons? How do remarkable properties of matter emerge from complex correlations of the atomic or electronic constituents and how can we control these properties? How do we characterize and control matter away—especially very far away— from equilibrium?" I will argue that this work truly falls into the class of disruptive science; it is not just a simple extension, linear science. Not everyone will accept the approach. Since we explain far more about triboelectricity than anyone before, the preponderance of evidence supports the model. The feedback I have received is that many agree with the work, to quote: "The model makes sense, says Michael McAlpine, a professor of engineering at the University of Minnesota. "It's such a simple explanation, I was surprised I didn't put my finger on that," McAlpine says." The proposal received strong reviews. It was also publicized on the Department of Energy Web Site.

16 TIDAL AND WAVE POWER↗