Добірка наукової літератури з теми "Computational modeling in solid-state phase transformation of metal and alloys"

AbstractThe return mapping algorithms (RMAs) presented here are designed for use with pressure-dependent thermoviscoplastic constitutive models involving irreversible effects associated with solid–solid phase transformations. During the volume solid–solid phase transformations occurring under mechanical loads, an “anomalous” plasticity, the so-called “TRansformation Induced Plasticity” (TRIP), is generated at much lower stress levels than those related to the yield stress of the material in the context of the classical plasticity. TRIP mechanisms are superimposed on the classical plasticity which is liable to occur in the case of metallic materials. Based on a non-standard generalized material framework, two different models are presented in which an “associative” plastic flow is introduced in the context of classical plasticity and a “non-associative” flow rule in the context of TRIP-like plasticity. In this paper, a complete algorithmic treatment of these two rate-dependent constitutive models is therefore proposed with the associated consistent tangent operator for dealing the quasi-surface irreversible solid–solid transformations which can appear in metal alloys during specific thermomechanical solicitations. The predictive abilities of the presented numerical procedure for modelling this kind of the irreversible solid–solid transformations involving two plasticity processes are tested and assessed by performing a two-dimensional finite-element analysis on some numerical examples.

In the numerical analysis of manufacturing processes of metal parts, many material properties depending on, for example, the temperature or stress state, must be taken into account. Often these data are dependent on the temperature changes over time. Strongly non-linear material property relationships are usually represented using diagrams. In numerical calculations, these diagrams are analyzed in order to take into account the coupling between the properties. An example of these types of material properties is the dependence of the kinetics of phase transformations in the solid state on the rate and history of temperature change. In literature, these data are visualized Continuous Heating Transformation (CHT) and Continuous Cooling Transformation (CCT) diagrams. Therefore, it can be concluded that time series analysis is important in numerical modeling. This analysis can also be performed using neural networks. This work presents a new approach to storing and analyzing the data contained in the discussed CCT diagrams. The application of Long-Short-Term Memory (LSTM) neural networks and their architecture to determine the correct values of phase fractions depending on the history of temperature change was analyzed. Moreover, an area of research was elements that determine what type of information should be stored by LSTM network coefficients, e.g., whether the network should store information about changes of single phase transformations, or whether it would be better to extract data from differences between several networks with similar architecture. The purpose of the studied network is strongly different from typical applications of artificial neural networks. The main goal of the network was to store information (even by overfitting the network) rather than some form of generalization that allows computation for unknown cases. Therefore, the authors primarily investigated in the ability of the layer-based LSTM network to store nonlinear time series data. The analyses presented in this paper are an extension of the issues presented in the paper entitled “Model of the Austenite Decomposition during Cooling of the Medium Carbon Steel Using LSTM Recurrent Neural Network”.

Solid-state diffusional phase transformations are vital approaches for controlling of the material microstructure and thus tailoring the properties of metals and alloys. To exploit this mean to a full extent, much effort is paid on the reliable and efficient modeling and simulation of the phase transformations. This work gives an overview of the developments in theoretical research of solid-state diffusional phase transformations and the current status of various numerical simulation techniques such as empirical and analytical models, phase field, cellular automaton methods, Monte Carlo models and molecular dynamics methods. In terms of underlying assumptions, physical relevance, implementation and computational efficiency for the simulation of phase transformations, the advantages and disadvantages of each numerical technique are discussed. Finally, trends or future directions of the quantitative simulation of solid-state diffusional phase transformation are provided.

The present paper investigates the microstructural features and associated hardening state of three different martensitic stainless steels (CX13, XD15 and MLX17 produced by Aubert&Duval), subjected to three different thermomechanical treatments, aimed at producing hard materials for tribological applications. It is thus shown that all treatments (cementation, HF quenching or Age Hardening) are efficient to produce hard surfaces. The bulk martensitic state is also studied. Although the three martensites look somewhat different, it is shown that the transformation always obeys the KS orientation relationship with some variant selection, which produces a significant amount of twin boundaries. These results are quite different from those found in low C steels. Based on a quantitative analysis of the EBSD microstructures, a quantification of the various relative hardening contributions (phase transformation, grain size, dislocation density, solid solution effect or precipitation) is then proposed.

AbstractLow modulus materials that can shape-morph into different three-dimensional (3D) configurations in response to external stimuli have wide-ranging applications in flexible/stretchable electronics, surgical instruments, soft machines and soft robotics. This paper reports a shape-programmable system that exploits liquid metal microfluidic networks embedded in an elastomer matrix, with electromagnetic forms of actuation, to achieve a unique set of properties. Specifically, this materials structure is capable of fast, continuous morphing into a diverse set of continuous, complex 3D surfaces starting from a two-dimensional (2D) planar configuration, with fully reversible operation. Computational, multi-physics modeling methods and advanced 3D imaging techniques enable rapid, real-time transformations between target shapes. The liquid-solid phase transition of the liquid metal allows for shape fixation and reprogramming on demand. An unusual vibration insensitive, dynamic 3D display screen serves as an application example of this type of morphable surface.

Soft porous crystals have the ability to undergo large structural transformations upon exposure to external stimuli while maintaining their long-range structural order, and the size of the crystal plays an important role in this flexible behavior. Computational modeling has the potential to unravel mechanistic details of these phase transitions, provided that the models are representative for experimental crystal sizes and allow for spatially disordered phenomena to occur. Here, we take a major step forward and enable simulations of metal-organic frameworks containing more than a million atoms. This is achieved by exploiting the massive parallelism of state-of-the-art GPUs using the OpenMM software package, for which we developed a new pressure control algorithm that allows for fully anisotropic unit cell fluctuations. As a proof of concept, we study the transition mechanism in MIL-53(Al) under various external pressures. In the lower pressure regime, a layer-by-layer mechanism is observed, while at higher pressures, the transition is initiated at discrete nucleation points and temporarily induces various domains in both the open and closed pore phases. The presented workflow opens the possibility to deduce transition mechanism diagrams for soft porous crystals in terms of the crystal size and the strength of the external stimulus.

Precipitation-hardened alloys are one of the most technologically significant materials that are used for structural applications, where an important mode of strengthening is due to the impediment to the movement of dislocations. The alloys, particularly possessing coherent precipitate-matrix interface, give rise to the coherency strain fields producing the coherency stresses in the matrix, which further interact with the dislocations to provide necessary strengthening. In this context, the control of the shape and distribution of the precipitates as a function of material and process parameters is important. In this thesis, we propose a diffuse-interface approach in order to compute the equilibrium shape of precipitates, which also allows us to minimize the grid-anisotropy related issues that occur in the classical sharp interface methods. The method is based on the minimization of the functional consisting of the elastic free energy and the interfacial energy, while the volume of the precipitate is conserved. Using this technique we reproduce the shape bifurcation diagram from 2D simulations for isotropic, inhomogeneous elastic energy with dilatational misfit, which is compared against the analytical solution provided by Johnson-Cahn and an existing sharp interface FEM technique. Thereafter the model has been utilized for the investigation of equilibrium shapes for different combinations of elastic misfit matrices and cubic anisotropy. Additionally, we incorporate the anisotropy in the interfacial energy, which has not been studied by previous sharp interface techniques and investigate its influence on shape bifurcation. Finally, we extend the model to calculate the equilibrium shapes of the precipitate in 3D which resembles the precipitate structures observed in real microstructures. We notice that the nature of shape bifurcation diagram in 3D is different than that observed in 2D, which is principally because there exist multiple variants of precipitate shapes for the same precipitate size e.g. prolate-like or oblate-like structures that are not equivalent. We also compute a range of equilibrium shapes in 3D, that can form as a result of symmetry breaking for different forms of anisotropy in the elastic energy. In the next part of the thesis, we extend the phase-field model for computing the equilibrium shape of single precipitates for consideration of multiple variants that allows us to investigate the equilibrium configurations of precipitates. Here, given the properties of the material such as the magnitude of misfit strain and its signs, the magnitude of the shear moduli and the size of the precipitate, one can determine the equilibrium configuration that can form during solid-state precipitation reactions. Using this method, we investigate three solid-state precipitation reactions, i.e. formation of a core-shell type of precipitates in the microstructure and two symmetry-breaking transitions namely, cubic to tetragonal (typically observed in the superalloys with γ' − γ'' microstructure) and hexagonal to orthorhombic (formation of multi-variant precipitate pattern in Ti-based alloys). We evaluate the criteria for the formation of core-shell type microstructures and show that while the formation of such structures is purely due to interfacial conditions (satisfying the wetting condition), the reaction pathway leading to their formation is assisted by elastic interactions between the precipitates. In the symmetry-breaking transitions, we investigate the formation of equilibrium configurations of the multi-variant precipitates using energetic calculations. Here, we observe that the formation of such configurations involving multiple variants is favored over the nucleation of a single precipitate of the same equivalent volume beyond a certain precipitate size. In the last part of the thesis, we relax the condition of volume preservation of the precipitates and study precipitate growth in a supersaturated matrix in the presence of anisotropy in the elastic energy. To achieve this, we utilize a phase-field model based on the grand-potential formulation for coupling the chemical driving forces with coherency stresses. Using this model we investigate the specific problem of solid-state dendrite formation occurring during certain precipitation reactions. Here, we find that the anisotropy in the elastic energy gives rise to the formation of the dendrite-like structures that are typically observed in solidification microstructures as an effect of the Mullins-Sekerka in stabilities. We determine the dendrite tip shape and tip velocity, as the precipitate grows in size as a function of different materials parameters such as the magnitude of misfit strain, supersaturation in the matrix, and the anisotropy strength in both the energies. We notice that in all the cases, the dendrite tip shape and tip velocity does not achieve steady-state which is in contrast with the dendrites observed during solidification. This modification is due to the presence of coherency stresses.