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At least 1,225 records · Page 68

Physics-informed Bayesian machine learning case study: Integral blade rotors

This paper provides a physics-informed Bayesian machine learning (PIBML) description and case study. The PIBML approach applies three physics-based models to establish the initial beliefs before testing to determine the probability of milling stability (or prior). These include: receptance coupling substructure analysis (RCSA) prediction for the tool tip frequency response functions; finite element software prediction of the mechanistic force model coefficients; and a spindle speed-dependent power law model for process damping. Testing was then performed to identify optimal stable machining conditions using an expected improvement in material removal rate criterion. The prior probability of stability was updated using the test results to determine the posterior probability of stability. The test results were compared to the parameter recommendations provided by the endmill manufacturer. A demonstration integral blade rotor was machined at the optimal stable machining conditions for 304 stainless steel and 6061-T6 aluminum. Finally, the disagreement between manufacturer recommendations and milling performance in both materials tested emphasizes the need for broad implementation of PIBML approaches to increase machining productivity and efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Void coalescence and ductile failure in IN718 investigated via high-energy synchrotron X-ray tomography and diffraction

Ductile failure through the growth and coalescence of voids is of particular relevance for many engineering materials. Yet, the lack of experimental measurements of the mechanical state of the material at an appropriate length scale has limited further understanding of the regime of ductile failure. In this study, local grain-scale experimental measurements are used to determine their relevance for describing and predicting ductile failure. Additive manufactured materials, due to the presence of inherent porosity, as well as the ability to tailor internal porosity, provides a promising avenue to study ductile failure. Selective laser melting is used to manufacture a specially designed specimen with two large, internal voids, in addition to the natural porosity, which is characteristic to the production process. The initial porosity and its evolution upon tensile loading are characterized via micro tomography. Several locations of void coalescence are captured in the sample, revealing activity of multiple modes of failure. Finite element simulations, with a simplified J2 plasticity model, instantiated with the initial void structure, is deployed, in which geometric localizations of stress concentration corresponded with experimentally observed sites of coalescence but was inadequate in capturing the appropriate failure mechanism. Furthermore, from the experimental results of the far-field high-energy diffraction microscopy, the heterogeneous micromechanical state is identified and tracked around voids due to the local grain interactions. These experiments determine narrow bands of low stress triaxiality, at the onset of failure, which highlight the path of coalescence through intervoid shearing. Diffraction spot spreading analysis aided characterization of intragranular plasticity and strain heterogeneity, which can be coupled with high triaxiality to form the conditions inducive for coalescence through intervoid necking. In this study, the experimentally determined grain-scale description of the micromechanical state provides a physical basis that can accurately capture both the sites and the mechanism of void coalescence at the onset of ductile failure.

36 MATERIALS SCIENCE↗

Discrete dislocation dynamics for crystal RVEs. Part 1: Periodic network kinematics

A novel implementation of the dislocation flux boundary condition in discrete dislocation dynamics is presented. The continuity of the individual dislocation loops in a periodic representative crystal volume (RVE) is enforced across the boundary of the RVE with the help of a dual topological description for representing dislocation line kinematics in two equivalent spaces representing the deforming crystal, the RVE and the unbounded crystal spaces. The former describes the motion of the dislocations in the simulated crystal RVE whereas the latter represents the motion of dislocations in an infinite space containing all replicas of the RVE. A mapping between the two spaces forms the basis of the implementation of flux boundary condition. The implementation details are discussed in the context of statistical homogeneity of bulk crystals undergoing macroscopically homogeneous plastic deformation. In this case, the boundary nodes associated with dislocation segments bear no relevance in the motion of the dislocations. Finally, some test cases are presented and discussed to establish the proposed approach.

42 ENGINEERING↗

Integrated simulation, machine learning, and experimental approach to characterizing fracture instability in indentation pillar-splitting of materials

Measuring fracture toughness of materials at small scales remains challenging due to limited experimental testing configurations. A recently developed indentation pillar-splitting method has shown promise of improved flexibility in fracture toughness measurements at the microscale, partly due to the occurrence of an unusual fracture instability, i.e., a transition from stable to unstable crack propagation. In spite of growing interest in this method, the underlying mechanism of this phenomenon is yet to be elucidated. Furthermore, we provide a comprehensive description of fracture instability in indentation pillar-splitting by combining in situ experiments with high-fidelity simulations based on cohesive zone and J-integral methods. In addition, a machine-learning-based solution for predicting the critical indentation load of fracture instability is established through Gaussian processes regression for broad use of this method by the community.

36 MATERIALS SCIENCE↗

A constitutive framework for rocks undergoing solid dissolution

Here, we formulate a time-dependent damage theory for rocks subjected to mechanical deformation and solid dissolution. The constitutive description is inspired by the transition state theory, which states that the rate of dissolution is a function of the reactive surface area measured through the crack density in the volume. We use a gradient-enhanced damage framework in which damage depends on the deformation of the material as well as on the amount of solid mass dissolved over time. The gradient-enhanced formulation is characterized by a three-field variational formulation with the solid displacement, nonlocal equivalent strain, and nonlocal rate of solid dissolution as the basic state variables. Traditionally, time-independent damage theories have only allowed damage to increase with increasing external load. In the proposed framework, the degree of damage may increase due to solid dissolution even when the external load is held fixed. In this way, solid dissolution is viewed as a process that is responsible for bringing about rate-dependent effects such as creep and stress-relaxation, which are two common features of geomaterial behavior.

42 ENGINEERING↗

A parametric study of slow dynamic nonlinear elasticity with comparisons to models

Several phenomenological models that aspire to quantitative description of anomalous nonlinear mesoscopic elasticity are reviewed and compared with laboratory measurements. This class of nonlinearity, best known perhaps for slow dynamics and aging, is seen widely in imperfectly consolidated granular solids but is not well understood. Typical slow dynamic tests show that a modest conditioning oscillatory "pump" strain depresses material stiffness, which then recovers like the logarithm of time after conditioning ceases. Several phenomenological models based on physical arguments have been proposed that predict the material stiffness response to arbitrary pump strain histories during conditioning and recovery. Approximate closed form and numerical solutions to the models are presented that predict the quantitative influence of three key pump parameters: the pump's strain amplitude, the pump's strain rate, and the pump’s duration. Laboratory measurements on Berea sandstone, concrete and a confined single aluminum bead find that slow dynamic responses are linear in pump strain and independent of pump frequency. Measurements also show that, after pump-off, stiffness recovers over times far longer than the pump duration. These observations and others are compared to model predictions. One of the considered models, based on a picture of fast brittle damage and slow healing, successfully matches all these behaviors.

36 MATERIALS SCIENCE↗

Features of relaxation modes in soft magnetic metallic glasses and their correlation with magnetic ordering

Although the anneal-induced relaxation process of Fe-based metallic glasses has been widely reported, there is a lack of a systematic description of the relaxation modes of atoms. Here, in this work, the relaxation modes of FeSiBPC metallic glasses and their relationship with magnetic ordering have been investigated. A two-stage relaxation behavior has been observed, and the pinning effect of Curie temperature is found in the first stage. The short-range ordering involved in the β relaxation in the first stage is confined and facilitated by magnetic ordering. It causes a smaller E β compared to that of non-magnetic metallic glasses. In the second stage, the pinning effect disappears. It is mainly the medium-range rearrangements involved in α relaxation that begins to yield the influence on magnetic ordering. This work uncovers the inner magnet-influenced β relaxation in Fe-based metallic glasses and provides insights into the interaction between structural arrangement during relaxation and magnetic ordering.

36 MATERIALS SCIENCE↗

Predicting zeolites’ stability during the corrosion of nuclear waste immobilization glasses: Comparison with glass corrosion experiments

During the long-term corrosion of nuclear waste glasses under nuclear waste disposal conditions, the precipitation of zeolitic phases has been linked to a delayed acceleration in glass corrosion (known as “Stage III”). Hence, predicting the thermodynamic propensity for zeolites to form upon the dissolution of nuclear waste glasses is key to ensure their long-term performance. Here, we compile a unified, internally-consistent thermodynamic database “clay20” to estimate the stability of clay and feldspar phases relevant to nuclear waste immobilization glasses, including beidellite(Mg, Ca, Na, K), kaolinite, montmorillonite(Mg, Ca, Na, K), nontronite(Mg, Ca, Na, K), saponite(Ca, Na, K), and albite. Based on this, we report a geochemical modeling method allowing us to predict the stability of secondary phases (including zeolites, calcium–silicate–hydrate gels, and clays) upon the dissolution of nuclear waste immobilization glasses. We show that this approach offers a realistic description of the stability of the secondary phases forming during the dissolution of two archetypical model nuclear glasses (namely, the International Simple Glass, ISG, and WVUTh-203) under conditions relevant to nuclear waste disposal (T = 90°C, p = 1 bar) as a function of pH. We find that the formation of silica and clay secondary phases is thermodynamically favored at low pH (pH < 10), whereas, in contrast, zeolite (analcime) and calcium–silicate–hydrate phases are favored at high pH (pH > 10.5). This suggests that thermodynamics (i.e., not solely kinetics) plays a key role in determining the range of solution pH wherein stage III corrosion may occur, i.e., when zeolite formation is favored.

Zhen-Wu, Bi Yun↗

Evaluation of the anisotropic grain boundaries and surfaces of α -U via molecular dynamics

Alloys based on uranium-zirconium are gaining renewed interest as fuels for the Versatile Test Reactor and a number of microreactor designs. Implementing metallic fuel in reactors creates the need for robust descriptive and predictive fuel performance modeling. Here, the current state of metallic fuel performance modeling relies on empirical equations derived from historical experiments, which may be unreliable when applied outside of their temperature, power, and composition phase space. One area where such data is lacking is the irradiation behavior of alpha -U, specifically tearing and porosity formation at the early stages of irradiation. While grain boundaries likely play a key role in this fuel behavior, relatively little is known about grain boundaries in alpha-U. Thus, we evaluate the grain boundary, surface energy, and work of adhesion of alpha -U utilizing molecular dynamics. Symmetric tilt grain boundaries (STGBs) are analyzed with the tilt plane oriented along each major crystallographic axis, for a total of eighty unique grain boundaries. The effect of temperature, tilt plane, and misorientation angle on interfacial energies are analyzed. The interfacial energies typically increase with temperature and there is significant variance as a function of misorientation angle, irrespective of the tilt plane. At 500 K, the average surface energy (1.23 J/m 2 ) is approximately 1.5 times the grain boundary energy (0.79 J/m 2 ), and the work of adhesion is approximately twice the grain boundary energy (1.68 J/m 2 ). Orientations for the likely formation of twins and likely failure planes are identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Investigation of δ zirconium hydride morphology in a single crystal using quantitative phase field simulations supported by experiments

In light water nuclear reactors, waterside corrosion of the cladding material leads to the production of hydrogen, a fraction of which is picked up by the zirconium cladding and precipitates into brittle hydride particles. These nanoscale hydride particles aggregate into mesoscale hydride clusters. The principal stacking direction of the nanoscale hydrides precipitated in the cladding tube changes from circumferential in the absence of applied stress to radial under circumferential applied stress. A quantitative phase field model has been developed to predict the hydride morphology observed experimentally and identify the mechanisms responsible for nanoscale hydride stacking. The model focuses on nanoscale hydride precipitation in a single zirconium grain with a detailed description of the anisotropic elastic contribution. The model predictions concerning the shape, orientation, and stacking behavior of nanoscale hydride are analyzed and compared with experimental observations. The model accurately accounts for the experimentally observed elongated nanoscale hydride shape and the stacking of hydrides along the basal plane of the hexagonal zirconium matrix. When investigating the role of applied stress in hydride morphology, the model challenges some of the mechanisms previously proposed to explain hydride reorientation. Finally, although hydride reorientation has been hypothesized to be caused by a change in nanoscale hydride shape, the current study shows that these mechanisms are unlikely to occur.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A novel protocol to recycle zirconium from zirconium alloy cladding from used nuclear fuel rods

A potential new zirconium recycling protocol has been demonstrated using unirradiated Zircaloy-based claddings and depleted uranium oxide for the chemical removal of zirconium alloy cladding in used nuclear fuel (UNF) rods from light water reactors. This protocol is based on the application of three new scientific findings. First, a new lower temperature chlorination reaction of zirconium with sulfur monochloride is described. Second, the high solubility of zirconium chloride in thionyl chloride is used to separate it from uranium oxide fuel and fission and activation contaminants. Finally, in the third step, the zirconium chloride is purified by simple recrystallization from thionyl chloride. Utilizing sulfur chloride solvents for a lower temperature liquid-based chemical digestion and purification of zirconium alloy claddings reduces technical complications experienced by current high temperature gas phase chlorination strategies, such as contamination of product streams. This novel protocol has been demonstrated on a 3–50 g scale of unirradiated zirconium alloy, with no significant change in the time required for complete chlorination (3–4 h). This zirconium chlorination protocol has also been performed in the presence of depleted uranium oxide pellets. The depleted fuel pellets do not affect zirconium chlorination, and the chlorination protocol does not chemically or physically alter the fuel pellets. Finally, a preliminary description of an industrial protocol to recycle nuclear grade zirconium from UNF rods is presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Flash electropolishing of BCC Fe and Fe-based alloys

The preparation of transmission electron microscopy (TEM) samples is a critical step in the characterization of materials, and the focused ion beam (FIB) technique is a commonly used method. However, a significant limitation of this technique is the FIB-induced damages on the foil surfaces, which can obscure the real features of interest, particularly in radiation effects studies. To overcome this limitation, this study presents a detailed description of the flash electropolishing technique, which can be used to remove the FIB damage from samples. The flash electropolishing technique has been successfully applied to a range of materials, including Fe, Fe-based model alloys, commercial Fe-Cr alloys, and advanced Fe-Cr alloys, both in their as-received and ion-irradiated states. Furthermore, the parameters used for Fe-Cr model alloys can be adjusted for commercial and advanced alloys with minimal modifications. Further, the study also examined the effects of electropolishing variables, such as perchloric acid concentration, electropolishing temperature, Cr concentration, and voltage. Qualitatively, a general trend and scoping test strategy is explored in our experiments. Overall, the flash electropolishing technique offers a promising solution to the challenges posed by FIB-induced damages in the preparation of TEM samples.

36 MATERIALS SCIENCE↗

Implications of point defect accumulation on UO 2 thermal conductivity and fission gas release under accelerated fuel irradiation

Evaluation of thermal properties is a crucial factor for nuclear fuel performance. During reactor operation, the accumulation of fission products and irradiation-induced lattice defects are responsible for degradation in thermal conductivity. Consequently, it affects fuel temperature and fission gas release (FGR) among other Multiphysics processes important for economics and safety analysis. We analyze the implications of point defects (PD) accumulation described using a rate theory (RT) Model on lattice thermal conductivity of UO 2 . Here, we demonstrate that fission rate-dependent point defect concentrations have the largest impact on in-pile thermal conductivity in the periphery of light water reactor fuels below a temperature threshold governed by the migration barrier of defects. Our analysis provides a mechanistic description of this phenomena which current fuel performance codes treat empirically. The reduction of thermal conductivity in the low -temperature rim region acts as additional thermal resistance and leads to a temperature notably larger than suggested by Lucuta thermal conductivity correlation. These effects are anticipated to have notable impacts when fuels are exposed to accelerated radiation. The impact of such point defect-informed treatment of thermal conductivity on fuel performance is evaluated by a detailed analysis of fission gas behavior and its release. We consider several models capturing different stages of fission gas bubble evolution and fission gas release (FGR). Finally, a new fission rate-dependent correction to the Lucuta correlation is proposed. The results show a significant reduction in thermal conductivity at the fuels’ periphery and an increase in fuel centerline temperature specifically at low burnups. Ultimately a modified LC shows a higher FGR compared to the original LC, while the acceleration process results in a reduction in overall FGR.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗

The nature of dynamic local order in CH 3 NH 3 PbI 3 and CH 3 NH 3 PbBr 3

Hybrid organic-inorganic lead-halide perovskites (LHPs) are a class of semiconductors with remarkable properties relevant to optoelectronic applications. The structure-property-function relationship in LHPs, however, is poorly understood, leading to incomplete descriptions of optoelectronic properties and a persistent problem of device degradation due to ion migration. Here, we reveal the true structure to contain an assembly of dynamic, two-dimensional short-range structural correlations in the lead-halide octahedral sublattice, with additional correlations between organic molecules. Here, we propose that these correlations are the origin of large-amplitude halide displacements, which govern charge carrier mobility and the sharpness of the absorption edge. Correlations between organic molecules may introduce regions of transient ferroelectricity or antiferroelectricity, which increase charge carrier lifetime. Finally, the correlations introduce an ion diffusion barrier that is static on the timescale of diffusive jumps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DLHub: Simplifying publication, discovery, and use of machine learning models in science

Machine Learning (ML) has become a critical tool enabling new methods of analysis and driving deeper understanding of phenomena across scientific disciplines. There is a growing need for "learning systems" to support various phases in the ML lifecycle. While others have focused on supporting model development, training, and inference, few have focused on the unique challenges inherent in science, such as the need to publish and share models and to serve them on a range of available computing resources. In this paper, we present the Data and Learning Hub for science (DLHub), a learning system designed to support these use cases. Specifically, DLHub enables publication of models, with descriptive metadata, persistent identifiers, and flexible access control. It packages arbitrary models into portable servable containers, and enables low-latency, distributed serving of these models on heterogeneous compute resources. In this work, we show that DLHub supports low-latency model inference comparable to other model serving systems including TensorFlow Serving, SageMaker, and Clipper, and improved performance, by up to 95%, with batching and memoization enabled. We also show that DLHub can scale to concurrently serve models on 500 containers. Finally, we describe five case studies that highlight the use of DLHub for scientific applications.

97 MATHEMATICS AND COMPUTING↗

Bringing forward the development of battery cells for automotive applications: Perspective of R&D activities in China, Japan, the EU and the USA

The recent development of high-performance Li-ion battery cells has sparked intensive revolutions in our society. After enabling the wireless communication, Li-ion batteries are paving the way towards a full transition to electromobility. However, the search and need for batteries with improved performance and safety at reduced cost is still ongoing. Therefore, substantial economical efforts are put in place. The 12th edition of the annual International Conference on Advanced Lithium Batteries for Automobile Applications (ABAA-12), held in October 2019 in Ulm, Germany, has been an insightful meeting during which policy makers from China, Germany, Japan, the European Commission and the USA provided an in-depth description of their respective visions on how to bring forward this technology. In this paper, we aim to give insights about the presented R&D trends and the current penetration of electric vehicles in the mass market.

25 ENERGY STORAGE↗