Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Phase Field Model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A phase field framework for capillary-induced fracture in unsaturated porous media: Drying-induced vs. hydraulic cracking

This work introduces a unified mathematical framework to replicate both desiccation-induced and hydraulic fracturing in low-permeable unsaturated porous materials observed in experiments. The unsaturated porous medium is considered as a three-phase solid–liquid–gas effective medium of which each constituent occupies a fraction of the representative elementary volume. As such, an energy-minimization-based phase-field model (PFM) is formulated along with the Biot’s poroelasticity theory to replicate the sub-critical crack growth in the brittle regime. Unlike hydraulic fracturing where the excess pore liquid pressure plays an important role at the onset and propagation of cracks, desiccation cracks are mainly driven by deformation induced by water retention. Therefore, the wettability of the solid skeleton may affect the evolution of the capillary pressure (suction) and change the path-dependent responses of the porous media. This air–water–solid interaction may either hinder or enhance the cracking occurrence. This difference of capillary effect on crack growth during wetting and drying is replicated by introducing retention-sensitive degradation mechanisms in our phase field fracture approach. To replicate the hydraulic behaviors of the pore space inside the host matrix and that of the cracks, the path-dependent changes of the intrinsic permeability due to crack growth and porosity changes are introduced to model the flow conduit in open and closed cracks. Numerical examples of drying-induced and hydraulic fracturing demonstrate the capability of the proposed model to capture different fracture patterns, which qualitatively agrees with the fracture mechanisms of related experiments documented in the literature.

42 ENGINEERING↗
DOE OSTI2021

Modeling and simulation of vascular tumors embedded in evolving capillary networks

Here in this work, we present a coupled 3D–1D model of solid tumor growth within a dynamically changing vascular network to facilitate realistic simulations of angiogenesis. Additionally, the model includes erosion of the extracellular matrix, interstitial flow, and coupled flow in blood vessels and tissue. We employ continuum mixture theory with stochastic Cahn–Hilliard type phase-field models of tumor growth. The interstitial flow is governed by a mesoscale version of Darcy’s law. The flow in the blood vessels is controlled by Poiseuille flow, and Starling’s law is applied to model the mass transfer in and out of blood vessels. The evolution of the network of blood vessels is orchestrated by the concentration of the tumor angiogenesis factors (TAFs); blood vessels grow towards the increasing TAFs concentrations. This process is not deterministic, allowing random growth of blood vessels and, therefore, due to the coupling of nutrients in tissue and vessels, makes the growth of tumors stochastic. We demonstrate the performance of the model by applying it to a variety of scenarios. Numerical experiments illustrate the flexibility of the model and its ability to generate satellite tumors. Simulations of the effects of angiogenesis on tumor growth are presented as well as sample-independent features of cancer.

3D–1D coupled blood flow models↗
DOE OSTI2026

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2012

Multiscale Simulation of Thermo-mechanical Processes in Irradiated Fission-reactor Materials

This report contains a summary of progress made on the subtask area on phase field model development for microstructure evolution in irradiated materials, which was a part of the Computational Materials Science Network (CMSN) project entitled: Multiscale Simulation of Thermo-mechanical Processes in Irradiated Fission-reactor Materials. The model problem chosen has been that of void nucleation and growth under irradiation conditions in single component systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy

Spatially resolved time and voltage-dependent polarization dynamics in PbTiO 3 thin films is explored using dynamic piezoresponse force microscopy (D-PFM) in conjunction with interferometric displacement sensing. This approach gives rise to 4D data sets containing information on bias-dependent relaxation dynamics at each spatial location without long-range electrostatic artifacts. To interpret these data sets in the absence of defined physical models, we employ a non-negative tensor factorization method which clearly presents the data as a product of simple behaviors allowing for direct physics interpretation. Correspondingly, we perform phase-field modeling finding the existence of ‘hard’ and ‘soft’ domain wall edges. This approach can be extended to other multidimensional spectroscopies for which even exploratory data analysis leads to unsatisfactory results due to many components in the decomposition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Models of dislocation glide and strengthening mechanisms in bcc complex concentrated alloys

Abstract The mechanical response of complex concentrated alloys (CCAs) deviates from that of their pure and dilute counterparts due to the introduction of a combinatorially sized chemical concentration dimension. Compositional fluctuations constantly alter the energy landscape over which dislocations move, leading to line roughness and the appearance of defects such as kinks and jogs under stress and temperature conditions where they would ordinarily not exist in pure metals and dilute alloys. The presence of such chemical defects gives rise to atomic-level mechanisms that fundamentally change how CCAs deform plastically at meso- and macroscales. In this article, we provide a review of recent advances in modeling dislocation glide processes in CCAs, including atomistic simulations of dislocation glide using molecular dynamics, kinetic Monte Carlo simulations of edge and screw dislocation motion in refractory CCAs, and phase-field models of dislocation evolution over complex energy landscapes. We also discuss pathways to develop comprehensive simulation methodologies that connect an atomic-level description of the compositional complexity of CCAs with their mesoscopic dislocation-mediated plastic response with an eye toward improved design of CCA with superior mechanical response. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiphase phase-field approach for solid–solid phase transformations via propagating interfacial phase in HMX

In this study, a thermodynamically consistent multiphase phase-field theory has been formulated to describe temperature-induced solid–solid phase transformations via an interfacial phase. This theory satisfies all thermodynamic equilibrium and stability conditions. It allows us to formulate the analytical solutions of the interface profile, energy, width, and velocity for each of the propagating solid–melt and solid–solid interfaces. The formation of the intermediate melt during solid–solid phase transformation has been studied hundreds of degrees below melting temperature in the HMX energetic crystal. The effect of the penalizing term in the phase-field model and two nanoscale material parameters on the appearance and degree of disordering of intermediate melt has been analyzed for the non-equilibrium interface. The developed approach is applicable to phase transitions in geological, pharmaceutical, ferroelectric, colloidal, and superhard materials where phase transformations occur via the intermediate phase.

Roy, Arunabha M. (ORCID:000000034790726X)↗
DOE OSTI2023

Understanding the Effect of Electrochemical Properties and Microstructure on the Microgalvanic Corrosion of Mg Alloys via Phase-Field Simulations

In this work, we apply a phase-field model to gain insights into the corrosion behavior of Mg alloys. Specifically, we study the effect of electrochemical properties of the materials and their environment and the spatial distribution of second phases in a magnesium alloy. To this end, we perform sensitivity analyses in which we separately vary the exchange current density and corrosion potential of the second phase, as well as the electrolyte conductivity. We describe the effects of these parameters on the corrosion current and the resulting corrosion-front morphology. We also confirm that the ratio between the Wagner length, calculated for the anodic phase, and the initial width of the anodic domain is a good predictor of the morphological characteristic of the corroding surface. In addition, we examine the effect of the microstructure on the corrosion behavior in both 2D and 3D systems by varying the shape, size, and distribution of the second-phase regions. Our findings provide insights into the influence of the two-phase microstructure on the corrosion behavior in a magnesium alloy.

Electrochemistry↗
DOE OSTI2022

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Abstract Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast and generalizable surrogate models are needed to alleviate the cost of computationally taxing processes such as in optimization and design of materials. The intrinsic discontinuous nature of the physical phenomena incurred by the presence of sharp phase boundaries makes the training of the surrogate model cumbersome. We develop a framework that integrates a convolutional autoencoder architecture with a deep neural operator (DeepONet) to learn the dynamic evolution of a two-phase mixture and accelerate time-to-solution in predicting the microstructure evolution. We utilize the convolutional autoencoder to provide a compact representation of the microstructure data in a low-dimensional latent space. After DeepONet is trained in the latent space, it can be used to replace the high-fidelity phase-field numerical solver in interpolation tasks or to accelerate the numerical solver in extrapolation tasks.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Watching Domains Grow: In-situ studies of polarization switching by combined Scanning Probe and Scanning Transmission Electron Microscopy

Ferroelectric domain nucleation and growth in multiferroic BiFeO{sub 3} films is observed directly by applying a local electric field with a conductive tip inside a scanning transmission electron microscope. The nucleation and growth of a ferroelastic domain and its interaction with pre-existing 71{sup o} domain walls are observed and compared with the results of phase-field modeling. In particular, a preferential nucleation site and direction-dependent pinning of domain walls are observed due to slow kinetics of metastable switching in the sample without a bottom electrode. These in situ spatially resolved observations of a first-order bias-induced phase transition reveal the mesoscopic mechanisms underpinning functionality of a wide range of multiferroic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Preliminary results addressing material qualification using combined ion irradiation and modeling data

Additively-manufactured (AM) materials have attracted increasing attention in recent years as a new method to make novel and customized components. While AM and conventionally produced materials are compositionally similar, they do possess different microstructures, necessitating assessment of materials produced via AM for their behavior in reactor environments. Some microstructures unique to AM materials, such as compositional micro-inhomogeneity and dislocation cell structures, are of particular importance since they may lead to different radiation performance. The performance of AM materials for advanced nuclear reactor applications is of interest to the Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy. The AMMT program aims to demonstrate its new accelerated development and qualification methods via laser powder bed fusion (LPBF) 316 stainless steel (SS). Focusing on material bearing both 316L and 316H specifications, we integrate ion irradiation and modeling. This year, we focus on answering foundational questions related to process variability, alloy chemistry variation, and microchemical segregation. Experimental results provide information and motivate questions to the modeling effort, which aims to develop the ability to model radiation-driven microstructural evolution in additively-manufactured 316 stainless steel under a variety of advanced reactor conditions, including different temperatures, neutron spectra, and fluxes, in a sort of "virtual experiment". We perform in-situ and ex-situ ion irradiations and microstructural characterizations to support the development of AM materials for reactor applications, develop a phase field model of radiation-induced segregation in additively manufactured material with high angle grain boundaries and dislocation cells, and investigate the effect of carbon and chromium content on point defect behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Three-dimensional microstructural characterization of FBR MOX fuel and the contribution of microstructural features to the thermal conductivity of the fuel

Combination of microstructural characterization, property measurements, and phase field modeling is used to investigate fast breeder reactor (FBR) mixed oxide (MOX) fuel irradiated to burnup of 13.7% fissions per initial metal atom (FIMA). Here, the fuel was characterized at different radial locations, which revealed that grey phase can be present in the central region if it nucleates on five metal precipitates (FMPs). In addition, in the mid-radial region FMPs do not diffuse out of the region once formed and the size of Pd–Te precipitates is dictated by the porosity present in the region. Thermal conductivity measurements were conducted as a function of radial location and the microstructure of the fuel was correlated with the observed trend. Reconstructions of the 3D solid and gaseous fission product structures in different regions of the fuel were used to simulate the effective thermal conductivity (ETC) of the respective regions and determine which microstructural feature has the strongest impact on thermal conductivity. Based on conducted assessment, FMPs and Pd-Te precipitates improve local conductivity of central and mid-radial regions even in the presence of grey phase, but defects are primary contributor to the degradation of thermal conductivity on the periphery of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Topology-generating interfacial pattern formation during liquid metal dealloying

Liquid metal dealloying has emerged as a novel technique to produce topologically complex nanoporous and nanocomposite structures with ultra-high interfacial area and other unique properties relevant for diverse material applications. This process is empirically known to require the selective dissolution of one element of a multicomponent solid alloy into a liquid metal to obtain desirable structures. However, how structures form is not known. Here we demonstrate, using mesoscale phase-field modelling and experiments, that nano/microstructural pattern formation during dealloying results from the interplay of (i) interfacial spinodal decomposition, forming compositional domain structures enriched in the immiscible element, and (ii) diffusion-coupled growth of the enriched solid phase and the liquid phase into the alloy. We highlight how those two basic mechanisms interact to yield a rich variety of topologically disconnected and connected structures. Furthermore, we deduce scaling laws governing microstructural length scales and dealloying kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A New Efficient Quantitative Multi-component Phase Field: Lattice Boltzmann Model for Simulating Ti6Al4V Solidified Dendrite Under Forced Flow

Ti6Al4V is a widely used, multi-component alloy in additive manufacturing, during which the fluid flow in the molten pool significantly affects the solidified dendrites. To predict and further control the microstructure, modeling and simulating the microstructure evolution play a critical role. In this study, a newly developed, efficient, quantitative multi-component phase-field (PF) model is coupled with a lattice Boltzmann (LB) model to simulate Ti6Al4V solidified dendrite evolution under fluid flow. The accuracy and convergence behavior of the model is validated by the Gibbs–Thomson relation at the dendrite tip. Single and multiple two-dimensional (2D) equiaxed dendrite evolution cases under forced flow were simulated. Results show that the dendrite pattern is influenced remarkably by the fluid flow. Underlying mechanisms of the asymmetrical evolution are revealed by discussing the interaction among the flow, composition distribution and dendrite morphology, quantitatively. The dendrite kinetics are also derived, which ascertains the relationship between tip velocity and undercooling and inlet velocity and is the foundation for larger-scale simulation. We believe that the coupled quantitative multi-component PF–LB framework employed in this study helps in investigating the solidified dendrite morphology evolution in a deep and quantitate manner.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A mechanism of defect-enhanced phase transformation kinetics in lithium iron phosphate olivine

Abstract Antisite defects are a type of point defect ubiquitously present in intercalation compounds for energy storage applications. While they are often considered a deleterious feature, here we elucidate a mechanism of antisite defects enhancing lithium intercalation kinetics in LiFePO 4 by accelerating the FePO 4 → LiFePO 4 phase transformation. Although Fe Li antisites block Li movement along the [010] migration channels in LiFePO 4 , phase-field modeling reveals that their ability to enhance Li diffusion in other directions significantly increases the active surface area for Li intercalation in the surface-reaction-limited kinetic regime, which results in order-of-magnitude improvement in the phase transformation rate compared to defect-free particles. Antisite defects also promote a more uniform reaction flux on (010) surface and prevent the formation of current hotspots under galvanostatic (dis)charging conditions. We analyze the scaling relation between the phase boundary speed, Li diffusivity and particle dimensions and derive the criteria for the co-optimization of defect content and particle geometry. A surprising prediction is that (100)-oriented LiFePO 4 plates could potentially deliver better performance than (010)-oriented plates when the Li intercalation process is surface-reaction-limited. Our work suggests tailoring antisite defects as a general strategy to improve the rate performance of phase-changing battery compounds with strong diffusion anisotropy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

ORNL/Thermo4PFM

Library to compute equilibrium compositions and equal chemical potential compositions in binary and ternary alloys. This library supports thermodynamic data formulated according to CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) models, as well as dilute binary alloys. One major aim is to solve the Kim-Kim-Suzuki (KKS) equations to obtain local compositions given a local mixture of two phases. These quantities are then used to evaluate the phase-field model driving force (right handside of time-evolution equation), as well as the energy density

Fattebert, Jean-Luc↗