Multiscale particle-in-cell modelling for advanced high strength steels

Advanced High Strength Steels (AHSS) offer outstanding characteristics for efficient and economic use of steel. The unique features of AHSS are direct result of careful heat treatment that creates martensite in the steel microstructure. Martensite and carbon content in the microstructure greatly affects the mechanical properties of AHSS, underlining more importance on microstructural discontinuities and their multiphase characteristics. In this paper, we present the Multiscale Particle-In-Cell (MPIC) method for microstructural modelling of AHSS. A specific particle method [1] usually used in fluid mechanics is adapted and implemented in a parallel multiscale framework. This multiscale method is based on homogenisation theories; with Particle-In-Cell (PIC) method in both micro and macroscale, and offers several advantages in comparison to finite element (FE) based formulation. Application of this method to a benchmark uniaxial tension test is presented and compared with conventional FE solutions.

Multiphase material modelling by multiscale particle-in-cell method

A particle-based method for multiscale modeling of multiphase materials such as Dual Phase (DP) and Transformation Induced Plasticity (TRIP) steels has been developed. The multiscale Particle-In-Cell (PIC) method benefits from the many advantages of the FEM and mesh-free methods, and to bridge the micro and macro scales through homogenization. The conventional mesh-based modeling methods fail to give reasonable and accurate predictions for materials with complex microstructures. Alternatively in the multiscale PIC method, the Lagrangian particles moving in an Eulerian grid represent the material deformation at both the micro and macro scales. The uniaxial tension test of two phase and three-phase materials was simulated and compared with FE based simulations. The predictions using multiscale PIC method showed that accuracy of field variables could be improved by up to 7%. This can lead to more accurate forming and springback predictions for materials with important multiphase microstructural effects.

The configuration evolution and macroscopic elasticity of fluid-filled closed cell composites : micromechanics and multiscale homogenization modelling

For fluid-filled closed cell composites widely distributed in nature, the configuration evolution and effective elastic properties are investigated using a micromechanical model and a multiscale homogenization theory, in which the effect of initial fluid pressure is considered. Based on the configuration evolution of the composite, we present a novel micromechanics model to examine the interactions between the initial fluid pressure and the macroscopic elasticity of the material. In this model, the initial fluid pressure of the closed cells and the corresponding configuration can be produced by applying an eigenstrain at the introduced fictitious stress-free configuration, and the pressure-induced initial microscopic strain is derived. Through a configuration analysis, we find the initial fluid pressure has a prominent effect on the effective elastic properties of freestanding materials containing pressurized fluid pores, and a new explicit expression of effective moduli is then given in terms of the initial fluid pressure. Meanwhile, the classical multiscale homogenization theory for calculating the effective moduli of a periodical heterogeneous material is generalized to include the pressurized fluid "inclusion" effect. Considering the coupling between matrix deformation and fluid pressure in closed cells, the multiscale homogenization method is utilized to numerically determine the macroscopic elastic properties of such composites at the unit cell level with specific boundary conditions. The present micromechanical model and multiscale homogenization method are illustrated by several numerical examples for validation purposes, and good agreements are achieved. The results show that the initial pressure of the fluid phase can strengthen overall effective bulk modulus but has no contribution to the shear modulus of fluid-filled closed cell composites.

Multiscale modelling of stress and strain partitioning in high strength dual phase steels

Multiscale modelling of stress and strain partitioning in DP steel was carried out using both realistic microstructure-based RVE models as well as stochastic microstructures generated by Monte Carlo method. The stochastic microstructure models were shown to resemble that of realistic microstructures, enabling research on the specific aspects of the microstructure that could be difficult to control and study during experimental work. One such feature of the realistic microstructures studied in this work was the grain size and microstructure morphology. The microstructures were generated with varying average grain sizes while all other parameters, such as boundary conditions, material properties and volume fractions of martensite and ferrite were kept constant. It is found that the effect of grain size is much more pronounced during the initial localisation of the plastic deformation at and around the interface of the phases. In addition, the decrease in ductility and increase in strength of the DP steels are directly related to the refinement of grain sizes of each phase and the stress-strain partitioning in between them.

Multiscale microstructure engineering of steels

The development of modern steels is based on the tailoring of the microstructure to achieve the required properties. While historically this was performed at the micrometre scale length, there is now the scope to undertake this at the nanoscale or atom scale. The present paper reviews recent work related to the development of ultrafine and nanoscale microstructures in steel as well as changes at shorter scale lengths, such as cluster formation and solute effects. This includes the development of ultrafine ferrite through phase transformation, nanoscale and ultrafine bainite, precipitation and cluster strengthening and bake hardening of steels. A key element of the present work has been the use of atom probe tomography to unlock the nature of these structures.

Multiscale evaluation of thermal dependence in the glucocorticoid response of vertebrates

Environmental temperature has profound effects on animal physiology, ecology, and evolution. Glucocorticoid (GC) hormones, through effects on phenotypic performance and life history, provide fundamental vertebrate physiological adaptations to environmental variation, yet we lack a comprehensive understanding of how temperature influences GC regulation in vertebrates. Using field studies and metaand comparative phylogenetic analyses, we investigated how acute change and broadscale variation in temperature correlated with baseline and stress-induced GC levels. Glucocorticoid levels were found to be temperature and taxon dependent, but generally, vertebrates exhibited strong positive correlations with acute changes in temperature. Furthermore, reptile baseline, bird baseline, and capture stressinduced GC levels to some extent covaried with broadscale environmental temperature. Thus, vertebrate GC function appears clearly thermally influenced. However, we caution that lack of detailed knowledge of thermal plasticity, heritability, and the basis for strong phylogenetic signal in GC responses limits our current understanding of the role of GC hormones in species’ responses to current and future climate variation.

Application of radial return mapping algorithm for finite strain elastoplasticity in a hybrid finite element and particle-in-cell model

The radial return mapping algorithm within the computational context of a hybrid Finite Element and Particle-In-Cell (FE/PIC) method is constructed to allow a fluid flow FE/PIC code to be applied solid mechanic problems with large displacements and large deformations. The FE/PIC method retains the robustness of an Eulerian mesh and enables tracking of material deformation by a set of Lagrangian particles or material points. In the FE/PIC approach the particle velocities are interpolated from nodal velocities and then the particle position is updated using a suitable integration scheme, such as the 4th order Runge-Kutta scheme[1]. The strain increments are obtained from gradients of the nodal velocities at the material point positions, which are then used to evaluate the stress increment and update history variables. To obtain the stress increment from the strain increment, the nonlinear constitutive equations are solved in an incremental iterative integration scheme based on a radial return mapping algorithm[2]. A plane stress extension of a rectangular shape J2 elastoplastic material with isotropic, kinematic and combined hardening is performed as an example and for validation of the enhanced FE/PIC method. It is shown that the method is suitable for analysis of problems in crystal plasticity and metal forming. The method is specifically suitable for simulation of neighbouring microstructural phases with different constitutive equations in a multiscale material modelling framework.

Analytic prediction of structural stress-strain relations of microstructured metal

Nanostructured and ultra-fine grained metals have higher strength but extremely limited ductility compared to coarse grained metals. However, their ductility can be greatly improved by introducing a specific range of grain sizes in the microstructures. In the paper, multiscale unit cell approach (UCA) is developed and applied to predict the averaged stress-strain relations of the multiscale microstructure metals. The unit cell models are three-phase structured at different scale lengths of 100 nm, 1 μm and 10 μm with different volume fractions and periodic boundary conditions. The contributions of multi-scale microstructures to the macroscopic structural properties of metals are also studied using a analytic approach—two-step mean-field method (TSMF), where three microstructural parameters are introduced and thus mechanical properties such as strength and ductility are presented as a function of these parameters. For verification of these proposed numerical and theoretical algorithms, the structural properties of the pure nickel with three-grain microstructures are studied and the results from FEA and the proposed theory have good agreement.

Stereo correspondence estimation using multiwavelets scale-space representation-based multiresolution analysis

A multiresolution technique based on multiwavelets scale-space representation for stereo correspondence estimation is presented. The technique uses the well-known coarse-to-fine strategy, involving the calculation of stereo correspondences at the coarsest resolution level with consequent refinement up to the finest level. Vector coefficients of the multiwavelets transform modulus are used as corresponding features, where modulus maxima defines the shift invariant high-level features (multiscale edges) with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps. Illuminative variation that can exist between the perspective views of the same scene is controlled using scale normalization at each decomposition level by dividing the details space coefficients with approximation space. The problems of ambiguity, explicitly, and occlusion, implicitly, are addressed by using a geometric topological refinement procedure. Geometric refinement is based on a symbolic tagging procedure introduced to keep only the most consistent matches in consideration. Symbolic tagging is performed based on probability of occurrence and multiple thresholds. The whole procedure is constrained by the uniqueness and continuity of the corresponding stereo features. The comparative performance of the proposed algorithm with eight famous existing algorithms, presented in the literature, is shown to validate the claims of promising performance of the proposed algorithm.