Prediction Of Microstructure Evolution Research Articles

Comparative study of displacement cascades simulated with ‘magnetic’ potentials and Mendelev-type potential in α-Fe

Different interatomic potentials produce displacement cascades with different features, and hence they significantly influence the results obtained from the displacement cascade simulations. The displacement cascade simulations in α-Fe have been carried out by molecular dynamics with three ‘magnetic’ potentials (MP) and Mendelev-type potential in this paper. Prior to the cascade simulations, the ‘magnetic’ potentials are hardened to suit for cascade simulations. We find that the peak time, maximum of defects, cascade volume and cascade density with ‘magnetic’ potentials are smaller than those with Mendelev-type potential. There is no significant difference within statistical uncertainty in the defect production efficiency with Mendelev-type potential and the second ‘magnetic’ potential at the same cascade energy, but remarkably smaller than those with the first and third ‘magnetic’ potential. Self interstitial atom (SIA) clustered fractions with ‘magnetic’ potentials are smaller than that with Mendelev-type potential, especially at the higher energy, due to the larger interstitial formation energies which result from the ‘magnetic’ potentials. The defect clustered fractions, which are input data for radiation damage accumulation models, may influence the prediction of microstructural evolution under radiation.

Prediction of microstructure in laser powder bed fusion process

Additive manufacturing (AM) processes are receiving widespread attention due to the ability to create or repair precision engineering components without use of any die or mold. Currently, the approach to obtain a specific user defined/as-desired or conformal/epitaxial microstructure is a challenging and expensive iterative process. Modeling and validation of solidification microstructure can be leveraged to reduce iteration cost in obtaining a desired microstructure. Numerical Volume-of-fluid based method incorporating Marangoni convection can accurately predict the resultant melt pool geometry and temperature distribution which can serve as an input in prediction of microstructure evolution in solidifying mushy region. Hence, in the present study, computational fluid dynamics (CFD) analysis is used to predict melt pool characteristics and phase field modeling is employed to simulate microstructure evolution in the as-deposited state for laser powder bed fusion (LPBF) process. Different features of LPBF microstructure such as segregation of secondary elements, dendrite sizes, dendritic orientation, dendritic morphology, and surface roughness are investigated and validated through comparison with experimental results. Phase-field model suggests strong dependency of dendrite orientation on surface roughness and scan speed and suggests potential of columnar flip or oriented-to-misoriented transition at higher scan speed. Segregation of the secondary elements is found to be the dominant factor in resultant dendrite width in the range of 1–3 μm. Furthermore, the developed method can easily be extended to predict the change in orientation of dendrites as new layers are built atop previous layers.

Application of morphological synthesis for understanding electrode microstructure evolution as a function of applied charge/discharge cycles

Morphological synthesis operations were employed for understanding electrode microstructure transformations and evolution accompanying the application of charge/discharge cycles to electrochemical storage systems (batteries). Using state-of-the-art morphological algorithms, it was possible to predict microstructure evolution in porous Si electrodes for Li-ion batteries with reasonable accuracy. The developed techniques could be considered supplementary to a phase-field mesoscopic approach to microstructure evolution that is based upon clear and definitive changes in the appearance of microstructure. However, unlike in phase field, the governing equations for the morphological approach are geometry, not physics, based. A similar non-physics-based approach to understanding different phenomena was attempted with the introduction of cellular automata. It is anticipated that morphological synthesis will represent a useful supplementary tool to phase field and will render assistance to unraveling the underlying microstructure–property relationships. The paper contains data on electrochemical characterization of different electrode materials that was conducted in parallel to the morphological study.

Precise Prediction of Microstructural Properties with Minimal Experimental Effort for the Nickel-Base Alloy Inconel 718

The prediction of microstructure evolution in addition to the macroscopic material strength, material flow and temperature evolution is becoming increasingly important as more and more complex materials, with properties that are heavily influenced by their microstructure, are being used. This in turn requires refined microstructure models to be parameterized. Compared to flow curve models, the experimental effort for the parameterization of microstructure models increases due to the inclusion of grain size and recrystallization effects. Therefore plenty of experiments are usually performed to fully characterize the material at hand. The increasing versatility of testing machines, like dilatometry with easily variable temperatures, in addition to the growing expenses that go along with increasing the number of experiments for high cost materials, leads to the question whether performing all those experiments is really justified. In this paper the microstructure model StrucSim is parameterized for the nickel-base alloy Inconel 718 and coupled online with a finite-element (FE) simulation to predict the material behaviour during double compression tests. StrucSim combines multiple constitutive equations into a single consistent material model representing also the microstructure. Therefore these constitutive equations are parameterized to their respective metal-physical phenomena to find the initial parameters for StrucSim. Afterwards the set of final parameters is determined by optimizing the initial parameters using the StrucSim algorithm interconnecting the constitutive equations to define a reference model. The reference model is later compared to different final parameter sets parameterized based on reduced experimental data. Beforehand the reference model is coupled with the FE software Simufact.forming to simulate double compression tests and compare them to experiments as a validation of the reference model. Here forces are predicted with a mean deviation (root of the sum of squared relative errors) of 7.6 % and grains sizes with a mean deviation of about 8 μm from the measurements. Afterwards the influence of reducing the available data during parameterization of StrucSim is investigated to evaluate the possibility of reducing the experimental effort. It is shown that when using only 50 % of the data the quality can be maintained with the reduced model. When simulating the double compression tests a comparable deviation regarding the forces and grain sizes is achieved. Reducing the number of experiments by 50 % during materials characterization therefore appears feasible.

Latent heat saturation in microstructural evolution by severe plastic deformation

During plastic deformation, most of the dissipated work is released as heat, but a fraction of it, usually small, is stored in the microstructure, is called latent heat and is associated with the network of dislocations that develops. The rate of energy storage in the microstructure divided by the rate of plastic dissipation is defined as the latent heat capacity. Latent heat remains stored in the microstructure of cold worked specimens after quenching. This energy is associated with modified mechanical properties, e.g. hardness, and is released upon annealing. Saturation of this stored energy has been observed in experiments after a specific amount of plastic deformation is reached. A thermodynamically consistent model for continuous dynamic recrystallization is proposed in this paper with the aim of explaining the phenomenon of latent heat saturation and relating it to grain refinement. The proposed model has three essential features: (i) the latent heat increases in the specimen during plastic deformation as plastic work is continuously dissipated; (ii) the rate of latent heat storage per unit work, i.e. the latent heat capacity, is related to the internal architecture of the microstructure and decreases to zero as a consequence of microstructural evolution; (iii) the relationship between the latent heat and the microstructure is described through the use of two parameters: (a) the dislocation density and (b) the average grain diameter. A comparison of the proposed model with experiments is reported and a validation for the prediction of microstructural evolution, as well as the evolution of the latent heat and latent heat capacity, is provided.

(Invited) Numerical Simulation of Sintering Process in Solid Oxide Fuel Cell Anode

Solid oxide fuel cell (SOFC) is expected as a promising energy conversion device because of its high efficiency and fuel flexibility. It is widely known that electrode microstructures are of great importance for attaining high performance as well as high reliability of SOFCs. In the SOFC fabrication processes, sintering of sub-micron scale ceramic and metallic powders is one of the most important step to achieve efficient and reliable electrodes. In addition, microstructural changes in SOFC anodes associated with particle sintering during high temperature operation may lead to severe performance degradation. Thus, in order to develop more reliable electrodes of SOFC, a method that can offer quantitative information of sintering behavior at the sub-micron scale is highly demanded.Accurate prediction of microstructure evolution during sintering, even in single-phase systems, is still very challenging. This is because sintering behavior is deeply affected by the three-dimensional (3D) complex geometries of the powder compacts, such as grain and pore size distributions, their shapes, relative density and coordination number, etc. Among many types of numerical approaches, a mesoscale kinetic Potts Monte Carlo (KMC) method has the potential to overcome this difficulty [1]. This method is capable of capturing three dimensional microstructural evolution from the initial to the final stages of solid-state sintering. However, the underlying kinetics at the sub-micron scale are not yet completely understood. Validation of the results using quantitative 3D microstructure data is indispensable to develop a numerical simulation tool which can reproduce proper sintering trajectory of real powder sintering. In the present study, KMC simulations of nickel (Ni) and nickel oxide - yttria stabilized zirconia (NiO-YSZ) composite are carried out starting from the green powder microstructure obtained using focused ion beam - scanning electron microscopy (FIB–SEM). Quantitative topological changes during sintering of real powder compacts are obtained by FIB–SEM. This technique offers a great advantage because of its high resolution, which is sufficient to capture the 3D geometric nature of sub-micron-sized powder compacts (typically < 1/10 of the powder size). The simulated temporal trajectories of microstructural parameters are compared with the experimental data from FIB-SEM to verify the numerical modeling results. [1] Hara, S., Ohi, A. and Shikazono, N., Sintering Analysis of Sub-Micron-Sized Nickel Powders: Kinetic Monte Carlo Simulation Verified by FIB-SEM Reconstruction, J. Power Sources, 276, pp. 105-112 (2015).

On the use of model alloys as a way to understand the effects of complex deformation conditions on austenite microstructure evolution during hot metal forming processes

During industrial hot metal forming processes, deformed metal undergoes complex strain history that in most cases is non-linear. This very often leads to improper prediction of microstructure evolution and properties of final metal forming products by the computer models that are used currently as in most cases, they are not strain-path sensitive. In the present work, effect of strain path changes on the austenite microstructure evolution has been studied using a special group of model alloys that were designed for this purpose. These alloys are characterised by similar stacking fault energy and flow behaviour to low carbon steels at elevated temperatures, and most of all, by the fact, that austenite in these alloys is stable all the way down to room temperature, what in turn, allows to study its behaviour directly. In the current works, the results of the study of the effects of complex strain path changes on the kinetics of static recrystallisation, strain-induced precipitation process and development of grain boundaries of deformed austenite are shown. Presented results will be very useful as an input data for the computer simulation of metal forming processes towards their improvement in order to take into account full strain path history during deformation processes at elevated temperatures.

Prediction of Mean Grain Size Evolution during the Forging of IN718 Turbine Disc

The microstructure evolution during the cogging, upsetting and hot die forging in the manufacture of IN718 turbine disc has been predicted through coupling the microstructure evolution prediction system developed with a commercial finite element software. The prediction results were in good agreement with the actual ones. Furthermore, the effects of process parameters on the microstructure development during the hot die forging of IN718 turbine disc have been investigated. To design the hot die forging, a uniform function of microstructure has been proposed as the goal function.

Multiscale modeling of tempering of AISI H13 hot-work tool steel – Part 1: Prediction of microstructure evolution and coupling with mechanical properties

In the first part of this two part study, the mechanical properties necessary for the simulation of tempering of an AISI H13 (DIN 1.2344, X40CrMoV5-1) tool steel was derived using physically based precipitation simulations and microstructure–property relationships. For this purpose, the precipitation of fine carbides were simulated using a thermo-kinetic software which allows prediction of the evolution of precipitation/dissolution reactions and the particle sizes. Then, those microstructural findings were coupled with physically based microstructure–property models to predict the yield stress, flow curve and creep properties. The predicted mechanical properties were verified with corresponding experiments and a good agreement was found. In the second part of this study, those properties were coupled with a Finite Element (FE) model in order to predict the relaxation of internal stresses and the evolution of deformations at the macroscopic scale.

FEM analysis of temperature distribution and experimental study of microstructure evolution in friction interface of GH4169 superalloy

Abstract The linear friction welding (LFW) process is a very effective solid-state welding method. Friction process is very significant for temperature distributions on the surface between two contacting workpieces during LFW process. In this paper, a finite element method (FEM) model is implemented to analyze the temperature distributions in friction interface of GH4169 superalloy cylindrical specimens. The simulation studies were conducted using ABAQUS software. Temperature distributions during the simulation of one rotation of the pressure head on the specimen were simulated. Temperature distributions of specimens in the end of different rotations were also investigated. The validation experiments were conducted to validate the simulation results. The detailed microstructure investigations demonstrate that the temperature distributions obtained in the present model are correct. This friction model is able to simulate the friction process of the GH4169 superalloy, but further research about FEM models is still needed for more precise prediction of microstructure evolution in the friction process of this alloy.

Microstructural modeling and numerical simulation of multi-physical fields for martensitic stainless steel during hot forging process of turbine blade

The mechanical properties of forgings mainly depend on the microstructure evolution during closed-die forging process, during which the microstructure mainly undergoes dynamic recovery, dynamic recrystallization, static recovery, static recrystallization, and metadynamic recrystallization. The macroscopic factors such as deformation temperature, strain rate, and strain play a key role in the microstructure evolution when the material composition is given. This paper presents the mathematical models for the prediction of microstructure evolution for martensitic stainless steel based on the hot compression test. A coupled analysis system of flow stress field, temperature field, and microstructure evolution for hot forging was developed based on the commercial software. The forging process of martensitic stainless steel turbine blade was simulated by the developed system. The influence of initial temperature of billet and deformation velocity on the load and finial temperature of forging part was analyzed. The variation of strain, temperature, and recrystallization volume fraction and grain size has been analyzed through simulation of the forging process. Based on the simulation results, the optimum hot forging process for complex forging parts was obtained.

A model for ductile damage prediction at low stress triaxialities incorporating void shape change and void rotation

Ductile fracture at the high triaxiality regime is well-known to be controlled by void nucleation, growth and coalescence. However, under low stress triaxiality conditions and general three dimensional finite deformations, damage is still poorly predicted due to the complex loading state and microstructural changes under such a condition. Experimental results have revealed not only void growth, but also important void shape change and void rotation under shear-dominated loading. The ability of ductile damage models to predict both void growth with shape change and void rotation is thus crucial for complex loading applications. In the present study, a Gurson-like nonlinear homogenization-based model (namely GVAR) is proposed and compared with the constitutive models for elasto-plastic porous materials developed in Kailasam and Ponte Castañeda (1998) (VAR model) and Danas and Aravas (2012) (MVAR model). The proposed model is based on ad hoc modifications of the VAR model, to give sufficiently accurate results for void growth at both low and high stress triaxialities and keeping the functional form of the original Gurson model. The VAR and MVAR models were based on rigorous linear comparison composite (LCC) homogenization methods, which can describe the evolution of microstructure of porous materials, represented by the void volume fraction, the aspect ratios and the orientations of general ellipsoidal voids. The proposed GVAR model thus inherits these characteristics and provides a sufficiently accurate void growth formulation (and simple at the same time). In addition, the loading direction is not necessary aligned with the ellipsoidal void axes. These models are implemented in an object-oriented finite element (FE) code. The identification of model parameters and the assessment of the proposed model are then carried out via 3D periodic unit-cell computations subjected to different stress states. Comparative results show that the present model predicts relatively accurately the evolution of void volume fraction, void aspect ratios and void rotation for different initial void shapes, void volume fractions and under different stress triaxiality levels. A qualitative application to a tensile test on a notched round bar shows the efficiency of the model to predict microstructure evolution (i.e. voids volume, shape and orientation) in a real-scale model simulation. This model with few parameters to be identified is thus promising to predict damage under complex loading paths and ready to be applied to complex FE simulations.

Phase-Field Modeling of Microstructure Evolution in Electron Beam Additive Manufacturing

In this study, the microstructure evolution in the powder-bed electron beam additive manufacturing (EBAM) process is studied using phase-field modeling. In essence, EBAM involves a rapid solidification process and the properties of a build partly depend on the solidification behavior as well as the microstructure of the build material. Thus, the prediction of microstructure evolution in EBAM is of importance for its process optimization. Phase-field modeling was applied to study the microstructure evolution and solute concentration of the Ti-6Al-4V alloy in the EBAM process. The effect of undercooling was investigated through the simulations; the greater the undercooling, the faster the dendrite grows. The microstructure simulations show multiple columnar-grain growths, comparable with experimental results for the tested range.

Application of novel physical picture based on artificial neural networks to predict microstructure evolution of Al–Zn–Mg–Cu alloy during solid solution process

The effects of the solid solution conditions on the microstructure and tensile properties of Al–Zn–Mg–Cu aluminum alloy were investigated by in-situ resistivity measurement, optical microscopy (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and tensile test. A radial basis function artificial neural network (RBF-ANN) model was developed for the analysis and prediction of the electrical resistivity of the tested alloy during the solid solution process. The results show that the model is capable of predicting the electrical resistivity with remarkable success. The correlation coefficient between the predicted results and experimental data is 0.9958 and the relative error is 0.33%. The predicted data were adopted to construct a novel physical picture which was defined as “solution resistivity map”. As revealed by the map, the optimum domain for the solid solution of the tested alloy is in the temperature range of 465–475 °C and solution time range of 50–60 min. In this domain, the solution of second particles and the recrystallization phenomenon will reach equilibrium.

Code Validation and Development of User Routines for Microstructural Prediction with Qform

Aim of the present work is to validate the metal forming FE code QForm and to develop user routine for the prediction of microstructure evolution in 6XXX aluminum alloys. Preliminary simulations are carried out in order to select optimal friction models and coefficients among the several formulations available in the code. Numerical results are compared to grid-based visioplasticity experiments: the comparison is performed in term of grid deformation at the billet-tools interfaces, load-stroke behavior and temperatures evolution of die and profile. The optimized friction model and coefficient are then applied in second series of simulations in order to develop the prediction of microstructure evolution. A theoretical model for the grain size and shape evolution of 6XXX aluminum alloys is finally implemented through the use of user routine and compared with experimental observations. The model is found able to properly predict the deformed state of the grains in the fibrous condition.

Physical and numerical modelling of backward extrusion of Mg alloy with Al coating

Although Mg alloys possess many attractive properties, their use has been limited due to their poor corrosion resistance. Therefore, in the present paper a process for Al coating on Mg alloys by hot extrusion was investigated. Physical simulations confirmed capabilities of this process and Al coating on a Mg alloy was obtained. Prediction of microstructure evolution and determination of optimal process parameters were the objectives of the present numerical simulations. Cellular automata were used to reach the former goal, while for the latter goal optimization analysis was applied to find the best technological parameters.

FEM Analysis and Experimental Validation of Friction Welding Process of 6xxx Alloys for the Prediction of Welding Quality

In the paper the Friction Welding (FRW) process is investigated by means of FEM simulation and experimental trials on AA 6082-T6 round extruded bars. Tests are realized at different rotational speeds and forging forces: the thermal field is monitored by means of k-type contact thermocouples and a contactless self-calibrating pyrometer. Deform lagrangian code is initially validated and optimized for process simulation of experimental trials then the simulations were used for the analysis of welding quality (through welding criteria) and for the microstructure evolution by means of a model already developed by the authors for aluminum extrusion microstructure evolution prediction.

Prediction of microstructure evolution during multi-stand shape rolling of nickel-base superalloys

AbstractIn this paper, a comprehensive numerical approach to predict the microstructure of nickel-base superalloys during multi-stand shape rolling is presented. This approach takes into account the severe deformation that occurs during each pass and also the possible reheating between passes. In predicting the grain size at the end of the rolling process, microstructural events such as dynamic recrystallization (DRX), metadynamic recrystallization (MDRX), and static grain growth are captured at every deformation step for superalloys. Empirical relationships between the average grain size from various microstructural processes and the macroscopic variables such as temperature (T) and effective strain ( ε ̄ ) and strain rate ( ε ̄ ̇ ) form the basis for the current work. These empirical relationships are based on Avrami equations. The macroscopic variables are calculated using a finite element analysis package wherein the material being rolled is modeled as a non-Newtonian fluid with viscosity that depends on the effective strain rate, strain, and temperature. A two-dimensional transient thermal analysis is carried out between passes that can capture the MDRX and/or static grain growth during the microstructural evolution. The presented microstructure prediction algorithm continuously updates two families of grains, namely, the recrystallized family and strained family at the start of deformation in any given pass. In addition, the algorithm calculates various subgroups within these two families at every deformation step within a pass. As the material undergoes deformation between the rolls, recrystallization equations are invoked depending on critical strain and strain rate conditions that are characteristics of superalloys. This approach predicts the microstructural evolution based on recrystallization kinetics and static grain growth only. The methodology was successfully applied to predict the microstructure evolution during the multi-pass rolling of nickel-base superalloys. The predicted results for Alloy 718 for a 4-stand rolling followed by air cooling and for a 16-stand rolling followed by a combination of air and water cooling are also compared with experimental observations.

Prediction of microstructure evolution during hot forging using grain aggregate model for dynamic recrystallization

In this study, dynamic recrystallization during nonisothermal hot compression test was numerically simulated by finite element analysis using new grain aggregate model for dynamic recrystallization. This model was developed based on mean field approach by assuming grain aggregate as representative element. For each grain aggregate, changes of state variables were calculated using three sub-models for work hardening, nucleation, and nucleus growth. A conventional single parameter dislocation density model was used to calculate change of dislocation density in grains. For modeling nucleation, constant nucleation rate and nucleation criterion developed by Roberts and Ahlblom were used. It was assumed that the nucleation occurs when the dislocation density of certain grain reaches a critical nucleation criterion. Conventional rate theory was used to model nucleus growth. The developed dynamic recrystallization model was validated by comparing with isothermal hot compression of pure copper. Then, the finite element analysis was conducted to predict the local changes of microstructure and average grain size by using the grain aggregate model. The predicted results were compared with nonisothermal hot compression results. The simulation results were in reasonably good agreement with experimentally obtained microstructures and the calculation time was much shorter than cellular automata-finite element method.

Numerical Simulation of Thermomechanical Processes Coupled with Microstructure Evolution

The finite element method is a consolidated tool used in the metal-forming field at an industrial scale. However, further progress is needed regarding the microstructure optimization of components produced by metal-forming processes such as hot forging or rolling. This article presents mathematical models to predict microstructure evolution during hot working, showing an application of mathematical models coupled to a thermomechanical processes' simulation software.