International Journal of Plasticity最新文献

This study develops a novel crystal plasticity (CP) model incorporating deformation-induced martensitic transformation (DIMT) and transformation-induced plasticity (TRIP) effect to predict the complex interplay between microstructural evolution and mechanical behavior in a third-generation advanced high-strength steel QP980. This model introduces phenomenological theory of martensite crystallography (PTMC) based TRIP theory and DIMT kinetics grounded on nucleation-controlled phenomenon. Notably, the DIMT model is improved by utilizing a geometric approach for calculating shear band intersections. A virtual multiphase representative volume element (RVE) based on the Voronoi tessellation is generated for the QP980 steel, which comprises ferrite, martensite, and retained austenite (RA). The study highlights how phase transformation affects mechanical properties, notably the strengthening from transformed martensite and the mechanical alterations in RA due to the TRIP effect. The DIMT kinetics dependent on stress states such as uniaxial tension (UT), uniaxial compression (UC), plane strain tension (PST), and equi-biaxial tension (EBT) are analyzed using the developed model. The role of microstructural surroundings on martensitic transformation is also examined. Furthermore, analysis under biaxial loading angles using the model reveals an asymmetric yield surface, with more pronounced changes in yield stress in the tensile region due to accelerated transformation behaviors, as opposed to the more gradual transformations in the compressive region. This study provides valuable insights into the deformation mechanisms of the third-generation advanced high-strength steels including relationship between plastic anisotropy, transformation kinetics, and microstructural evolution.

To elucidate the relationship between microstructural characteristics and mechanical properties in additively manufactured (AM) maraging steel, this study introduces a computational approach that addresses two fundamental challenges. Firstly, it addresses the creation of representative volume elements (RVEs) that mimic the observed microstructural complexities, such as meltpool boundaries, prior austenite grains, packets and blocks of lath martensite. This is accomplished through the application of Potts Monte-Carlo methods and grain segmentation techniques in accordance with the Kurdjumov–Sachs orientation relationship. Secondly, this study develops a comprehensive crystal plasticity (CP) model encompassing both bcc and fcc plasticity. Inspired by atomistic and discrete dislocation dynamics studies, the proposed CP model incorporates characteristics intrinsic to bcc plasticity, including non-Schmid effects, dislocation and precipitate strengthening, and Hall–Petch type strengthening of elongated martensitic blocks. Utilizing the created RVEs and the proposed CP framework, finite element simulations are conducted based on an update-Lagrangian formulation. The purpose of this study is to investigate the deformation behavior, texture evolution, tension–compression asymmetry, and evolution in dislocation density in RVEs representative of as-built and heat-treated samples of maraging steel. This computational approach and its findings deepen our understanding of the intricate interplay between microstructural characteristics and mechanical properties in maraging steel and also provide valuable guidelines for refining its additive manufacturing and heat treatment processes.

Multi-principal element alloys (MPEAs) have drawn great interest due to their superior mechanical properties compared to the conventional alloys. However, it is unclear in these two aspects: i) how to predict the brittle-to-ductile transition temperature (BDTT) and fracture toughness of MPEAs using theory and model; ii) how to quantify the influences of the complicated alloy composition variation and microstructural parameter on the BDTT and fracture toughness of MPEAs. These issues are critical to both the underlying mechanisms and practical engineering applications. Here, we develop a dislocation theory-based model accounting for the modified lattice friction stress model, the composition-dependent strength model, and the critical energy model to determine the BDTT and corresponding fracture toughness in body-centered cubic MPEAs. The calculated yield stress and BDTT of the as-cast MPEA agree well with the experiments. Subsequently, the BDTT and fracture toughness of TiVNbTa-based MPEAs are obtained as a function of the element concentration fluctuation. The effects of microstructure parameters, such as component randomness and short-range ordering described by the standard deviation of the interplaner potential perturbation and short-range correlation length, on the BDTT and fracture toughness are further elucidated. Importantly, a microstructure-based BDT criterion is proposed to evaluate whether MPEA is ductile or brittle at a given temperature. These results are conducive to the development and application of MPEAs in extreme environments.

We propose a physics informed, neural network-based elasto-viscoplasticity (NN-EVP) constitutive modeling framework for predicting the flow response in metals as a function of underlying grain size. The developed NN-EVP algorithm is based on input convex neural networks as a means to strictly enforce thermodynamic consistency, while allowing high expressivity towards model discovery from limited data. It utilizes state-of-the-art machine learning tools within PyTorch’s high-performance library providing a flexible tool for data-driven, automated constitutive modeling. To test the performance of the framework, we generate synthetic stress–strain curves using a power law-based model with phenomenological hardening at small strains and test the trained model for strain amplitudes beyond the training data. Next, experimentally measured flow responses obtained from uniaxial deformations are used to train the framework under large plastic deformations. Additionally, the Hall–Petch relationship corresponding to grain size strengthening is discovered by training flow response as a function of grain size, also leading to efficient extrapolation. Furthermore, a deployment framework of the discovered neural network constitutive laws is demonstrated with finite element analysis procedures. The present work demonstrates a successful integration of neural networks into elasto-viscoplastic constitutive laws, providing a robust automated framework for constitutive model discovery that can efficiently generalize, while also providing insights into predictions of flow response and grain size-property relationships in metals and metallic alloys under large plastic deformations.

The plastic deformation behavior of single crystals of orthorhombic η-Fe₂Al₅ has been investigated by micropillar compression at room temperature as a function of crystal orientation and specimen size. Plastic flow is observed even at room temperature by the operation of six slip systems; (001)<010>, (001)<110>, (001)<130>, {$2\bar{2}3$}<110>, {311}<$\bar{1}03$> and {301}<$\bar{1}03$>. The CRSS values for the six identified slip systems are very high all in the range of 1.1∼1.5 GPa and do not vary much with specimen size. In the middle of the stereographic projection, the (001)<010>, (001)<110>, (001)<130> and {$2\bar{2}3$}[110] slip systems operate according to the relative Schmid factors with the similar CRSS values in the range of 1.08∼1.23 GPa. In orientations close to [001], the {311}<$\bar{1}03$> slip system as well as the {301}<$\bar{1}03$> slip system operate with a much higher CRSS values around 1.5 GPa, producing wavy slip traces due to the occurrence of frequent cross-slip among these slip planes. In orientations close to the [100]-[110]-[010] symmetry line, on the other hand, premature failure occurs without the operation of any slip systems, although, the Schmidt factor-wise, the {311}<$\bar{1}03$> and {301}<$\bar{1}03$> slip systems could operate. The selection of slip systems, their CRSS values and the possible dislocation dissociation modes are discussed based on the overlapped atomic volume that occurs during shear along the slip direction on the slip plane, taking into account the partial occupancies of Al atoms in the linear atomic chain along the orthorhombic c-axis direction.

Numerous studies have investigated the strain rate sensitive behaviors of materials, consistently reporting enhanced stress values and increased dislocation density with rising strain rates. Behind these phenomena lies the intrinsic nature of dislocation activity. In this context, we introduce an analysis method within a crystal-plasticity (CP) framework, incorporating molecular dynamics insights for a comprehensive range of strain rates (7.5 × 10⁻⁵/s to 5 × 10⁷/s). This approach offers a refined understanding of strain rate sensitive behaviors, mainly influenced by dislocation movement laws and strain-rate-dependent saturation of dislocation density. We elucidate the impact of deformation loading conditions on Schmidt factors and active slip systems, which are also crucial for understanding variations in SRS. Ultimately, this study underscores the CP method's effectiveness in comprehensive SRS analysis, seamlessly integrating experimental observations with theoretical predictions for advanced material characterization.

Improving the formability of sheet metal is a constant challenge in microforming. In this study, applying normal stresses to the specimen surface is found to be an effective method for improving the ductility of pure titanium sheets. This case only occurs when the normal stress is higher than a critical value. By characterizing the microstructure, it is found that the normal stress induces a change in the deformation mechanism, which improves the work-hardening rate and the capacity for homogeneous deformation. The plastic deformation mechanism of pure titanium thin sheets undergoes a transformation from exclusively slip-based to a multi-mechanistic mode that couples slip, twinning, and FCC phase transformation. Normal stress exacerbate the deformation of surface grains and inhibit surface roughening. Moreover, normal stress activates deformation twins and FCC phase transformation by increasing the Schmid factor of the associated twin/slip systems. FCC phases and deformation twins contribute to enhancing the work-hardening rate through mechanisms such as the dynamic Hall-Petch effect, reorientation texture hardening, and dislocation substructure strengthening. Moreover, they enhance the material's ductility by providing additional deformation modes to accommodate strain. By virtue of the coordinated action of various deformation mechanisms, a more uniform distribution of thickness strain is achieved. It delays onset of plastic instability and enhances the formability of thin sheets. Considering the changes in dislocation density induced by different microstructures, a modified model is constructed. Based on the dislocation density and the surface layer model, this model predicts the flow stress size effect, as well as changes in flow stress and work hardening rate induced by normal stress due to microstructure transformation. This work provides a complete understanding of the mechanical property response and microstructure evolution under normal stress. It also gives a feasible solution for improving the formability of titanium thin sheet in microforming.

The heterogeneous deformation of polycrystalline metals inherently originates from the intergranular deformation incompatibility. This paper proposes physical parameters related to the crystal orientations, the Schmid factor of the most activated slip system, and the misorientation angle to characterize the deformation incompatibility between the adjacent grain couple. A comprehensive multiscale investigation is conducted to reveal the mechanism from intergranular deformation incompatibility to fracture initiation at grain boundaries. At the specimen scale, experimental and numerical uniaxial tensile tests are performed on smooth and pre-notched dog-bone specimens to achieve different loading paths on the materials. The heterogeneous fields of stress triaxiality explains the heterogeneous size of the dimples observed in fractography. At the grain scale, electron backscatter diffraction analysis is conducted to characterize the microstructural properties around the nucleated voids within the materials. Voids are captured at the grain boundaries with directions parallel to the loading direction and intergranular deformation incompatibility is characterized using the proposed parameters. Simulations on the plastic deformation of realistic microstructures are performed to clarify the phenomenon. The results reveal that the fluctuation in stress triaxiality at grain boundaries is ascribed to intergranular deformation incompatibility, leading to fracture initiation at these sites. The relationships between the proposed physical parameters of intergranular deformation incompatibility and fluctuation in stress triaxiality are summarized in all circumstances. Finally, the ductile damage at the grain scale is predicted by the Rice–Tracey model, and the results show that the effects of microstructures on heterogeneous plastic deformation and stress state can be well considered.