Computing property variability of polycrystals induced by grain size and orientation uncertainties

Multiscale computational methods that link microscale models to macro-properties have practical significance. It is difficult to obtain probability distribution functions (PDFs) that provide a complete representation of microstructural variability in three-dimensional polycrystalline materials using limited information since this inverse problem is highly ill-posed. We use the maximum entropy (MaxEnt) principle to compute a PDF of microstructures based on given information about a microstructural system. Microstructural features are incorporated into the maximum entropy framework using data obtained from experiments or simulations. Microstructures are sampled from the computed MaxEnt PDF using concepts from computational geometry and Voronoi cell tessellations. These microstructures are then interrogated in virtual deformation tests, and by using homogenization techniques the variability of non-linear macro-properties is computed.     

Application of ICME to Engineer Fatigue-Resistant Ni-Base Superalloys Microstructures

Critical rotating components used in the hot section of gas turbine engines are subject to cyclic loading conditions during operation, and the life of these structures is governed by their ability to resist fatigue. Since it is well known that microstructural parameters, such as grain size, can significantly influence the fatigue behavior of the material, the conventional processes involved with the manufacture of these structures are carefully controlled in an effort to engineer the resulting microstructure. For a commercial Ni-base superalloy, RR1000, the development of process models and deformation mechanism maps has enabled not only control of the resultant grain size but also the ability to tailor and manipulate the resulting grain boundary character distribution. The increased level of microstructural control was coupled with a physics-based fatigue model to form an integrated computational materials engineering framework that was used to guide the design of damage-tolerant microstructures. Simulations from a 3D crystal plasticity finite element model were used to identify microstructural features associated with strain localization during cyclic loading and to guide the design of polycrystalline microstructures optimized for fatigue resistance. Conventionally processed and grain boundary engineered forgings of a commercial Ni-based superalloy, RR1000, were produced to validate the design methodology. For nominally equivalent grain sizes, high-resolution strain maps generated via digital image correlation confirmed that the high density of twin boundaries in the grain boundary engineered material were desirable microstructural features as they contribute to limiting the overall length of persistent slip bands that often serve as precursors for the nucleation of fatigue cracks.     

Spectral representation of higher-order localization relationships for elastic behavior of polycrystalline cubic materials

A computationally efficient higher-order spectral framework has been formulated for the calculation of the elastic localization tensors for polycrystalline material systems using the generalized spherical harmonics as the Fourier basis. This new approach offers tremendous potential for rapid analysis of the elastic performance of a very large set of microstructures in any selected polycrystalline material system. The spectral framework transforms the complex integral relations for local stress and strain fields (derived from established generalized composite theories) into relatively simple algebraic expressions involving polynomials of structure parameters and morphology-independent influence coefficients. These coefficients need to be established only once for a given material system. In this paper, we formulate and demonstrate a viable approach to establishing the values of the second-order influence coefficients for cubic polycrystals by calibration to the results of micromechanical finite element models.     

Strategies for integration of 3-D experimental data with modeling and simulation

For the most comprehensive modeling and prediction of materials behavior at the microscale, experimentally measured three-dimensional (3-D) microstructural datasets must be incorporated as initial input into computational models. Although the capability to collect and store large amounts of 3-D microstructural data is advancing continuously, computational resources for the processing and simulation can limit the amount of data that can be analyzed. Depending on the features and properties of interest, several approaches can be applied to optimize processing, reduce the amount of data that needs to be simulated, and increase the efficiency of simulations to maximize the statistical significance of microstructure analyses. This paper presents examples of four such approaches to efficient integration of large 3-D datasets into modeling and simulations of mechanical behavior in an efficient yet statistically significant manner.     

Plastic deformation of nanocrystalline aluminum at high temperatures and strain rate

The deformation of nanocrystalline aluminum was studied using molecular dynamics simulation at homologous temperatures up to 0.97. The microstructures and stress–strain response were examined in a polycrystalline and bicrystal configuration. The activation energies for dislocation-based deformation as well as grain boundary sliding and migration were quantified by fitting simulation data to temperature using an Arrhenius relation. The activation energy for the flow stress response suggests that deformation is largely accommodated by sliding and migration of grain boundaries. This is in agreement with simulated microstructures, indicating a negligible degree of dislocation interaction within each grain, and microstructural observations from high strain rate processes are also consistent with this result. A steady-state grain size is maintained in the recrystallized structure following yielding due to boundary migration and grain rotation mechanisms, rather than by diffusion-based dislocation climb.     

Deformation and creep modeling in polycrystalline Ti–6Al alloys

This paper develops an experimentally validated computational model for titanium alloys accounting for plastic anisotropy and time-dependent plasticity for analyzing creep and dwell phenomena. A time-dependent crystal plasticity formulation is developed for hcp crystalline structure, with the inclusion of microstructural crystallographic orientation distribution. A multi-variable optimization method is developed to calibrate crystal plasticity parameters from experimental results of single crystals of α-Ti–6Al. Statistically equivalent orientation distributions of orientation imaging microscopy data are used in constructing the polycrystalline aggregate model. The model is used to study global and local response of the polycrystalline model for constant strain rate, creep, dwell and cyclic tests. Effects of stress localization and load shedding with orientation mismatch are also studied for potential crack initiation.     

多晶材料细观力学建模与模拟软件的开发与应用

Thermal Prophet-RVE是最近自主开发的一款基于实际微观组织数据的多晶材料细观力学模拟软件.本文着重对其软件架构、基本功能及技术特点进行介绍,并模拟了铁素体/马氏体双相钢生产过程马氏体相变引起的变形和双相组织在拉伸载荷作用下的细观力学行为.结果表明,基于材料实际微观组织数据构建的微结构模型能够高度还原组织...     

Predicting phase equilibrium,phase transformation,and microstructure evolution in titanium alloys

Phase transformation and microstructural evolution in commercial titanium alloys are extremely complex. Traditional models that characterize microstructural features by average values without capturing the anisotropy and spatially varying aspects may not be sufficient to quantitatively define the microstructure and hence to allow for establishing a robust microstructure-property relationship. This article discusses recent efforts in integrating thermodynamic modeling and phase-field simulation to develop computational tools for quantitative prediction of phase equilibrium and spatiotemporal evolution of microstructures during thermal processing that account explicitly for precipitate morphology, spatial arrangement, and anisotropy. The rendering of the predictive capabilities of the phase-field models as fast-acting design tools through the development of constitutive equations is also demonstrated. For more information, contact Y.-Z. Wang, Department of Materials Science & Engineering, Ohio State University, 2041 College Road, Columbus, OH 43221, USA; (614) 292-0682; fax (614) 292-1537; e-mail wang.363@osu.edu.     

Damage evolution during microcracking of brittle solids

Microcracking due to thermal expansion and elastic anisotropy is examined via computer simulations with a microstructural-based finite element model. Random polycrystalline microstructures are generated via Monte Carlo Potts-model simulations. Microcrack formation and propagation due to thermal expansion anisotropy is investigated in these microstructures using a Griffith-type failure criterion in a microstructural-based finite element model called OOF. Effects of the grain size distribution on the accumulation of microcrack damage, as well as on the threshold for microcrack initiation, are analysed. Damage evolution is rationalised by statistical considerations, i.e. damage accumulation is correlated with the statistical distributions of microstructural parameters.     

Work-hardening/softening behaviour of b.c.c. polycrystals during changing strain paths: I. An integrated model based on substructure and texture evolution,and its prediction of the stress–strain behaviour of an IF steel during two-stage strain paths

For many years polycrystalline deformation models have been used as a physical approach to predict the anisotropic mechanical behaviour of materials during deformation, e.g. the r-values and yield loci. The crystallographic texture was then considered to be the main contributor to the overall anisotropy. However, recent studies have shown that the intragranular microstructural features influence strongly the anisotropic behaviour of b.c.c. polycrystals, as revealed by strain-path change tests (e.g. cross effect, Bauschinger effect). This paper addresses a method of incorporating dislocation ensembles in the crystal plasticity constitutive framework, while accounting for their evolution during changing strain paths. Kinetic equations are formulated for the evolution of spatially inhomogeneous distributions of dislocations represented by three dislocation densities. This microstructural model is incorporated into a full-constraints Taylor model. The resulting model achieves for each crystallite a coupled calculation of slip activity and dislocation structure evolution, as a function of the crystallite orientation. Texture evolution and macroscopic flow stress are obtained as well. It is shown that this intragranular–microstructure based Taylor model is capable of predicting quantitatively the complex features displayed by stress–strain curves during various two-stage strain paths.     

Evaluation of multilayer perceptron and self-organizing map neural network topologies applied on microstructure segmentation from metallographic images

Artificial neuronal networks have been used intensively in many domains to accomplish different computational tasks. One of these tasks is the segmentation of objects in images, like to segment microstructures from metallographic images, and for that goal several network topologies were proposed. This paper presents a comparative analysis between multilayer perceptron and self-organizing map topologies applied to segment microstructures from metallographic images. The multilayer perceptron neural network training was based on the backpropagation algorithm, that is a supervised training algorithm, and the self-organizing map neural network was based on the Kohonen algorithm, being thus an unsupervised network. Sixty samples of cast irons were considered for experimental comparison and the results obtained by multilayer perceptron neural network were very similar to the ones resultant by visual human inspection. However, the results obtained by self-organizing map neural network were not so good. Indeed, multilayer perceptron neural network always segmented efficiently the microstructures of samples in analysis, what did not occur when self-organizing map neural network was considered. From the experiments done, we can conclude that multilayer perceptron network is an adequate tool to be used in Material Science fields to accomplish microstructural analysis from metallographic images in a fully automatic and accurate manner.     

Effects of pores and interfaces on effective properties of plasma sprayed zirconia coatings

It is difficult to establish structure–property relationships in plasma sprayed coatings because of their unique and intermingled splat microstructures incorporating networks of various intrinsic process-dependent microdefects. In this paper, these coatings are characterized using two distinctly different approaches, both based on novel experimental techniques and computational modeling tools. In each approach, detailed finite element models are illustrated to represent the porous coatings fabricated with four different types of zirconia feed powder. One approach is based on small-angle neutron scattering (SANS) studies carried out to quantify microstructure. In this approach, the pore morphology is idealized by artificially rebuilding, based on the collective microstructural information obtained in terms of component porosities of three pore systems, their opening dimensions and orientation. The other method relies on image analysis of real microstructural images obtained using scanning electron microscopy (SEM). The finite element mesh for the actual cross-sectional model, generated by thresholding the SEM images, is constructed with the object oriented finite (OOF) element method. Through these two approaches, the effective thermal conductivity and elastic modulus along the spray, as well as the transverse directions are estimated for thermally sprayed yttria-stabilized zirconia (PSZ) coatings. Our results show the effectiveness of these computational approaches for estimating material properties with each approach having its strength and weakness. However, in comparison with experimentally measured properties, there exist some limitations in both approaches. To further probe the source of discrepancy within the measurements, the coatings are thermal cycled to reduce the effect of splat boundaries on properties. Additional models are constructed for these coatings and their analysis is carried out. For the first time, the influence of the splat interfaces on the effective properties of sprayed coatings is quantified.     

Microhardness and wear behaviour of polycrystalline diamond after warm laser shock processing with and without coating

Cutting tools made of ultra-hard materials such as polycrystalline diamonds offer superior wear resistance in precision machining of Aluminium alloys. However, the wear properties of these materials are dependent on their microstructural characteristics such as grain size and binder percentage. In this context, the present paper evaluates the effects of two low-energy fibre laser processes (nanosecond pulse duration) on microstructural changes of polycrystalline diamond composites and consequently investigates wear and friction characteristics and micro hardness properties. Pockets were first achieved using a single mode SPI pulsed fibre laser (1064 nm wavelength) inducing both laser shock processing (LSP) and laser peening without coating (LPwC) and characterised using a combination of scanning electron microscopy (SEM), white light interferometry, energy dispersive X-Ray (EDX) and micro hardness analyses. The as-received and processed materials were tested on a pin-on-disc for the evaluation of their wear performance. An analytical model based on the asperities of pin and disc after wear test is proposed to predict the trend of wear performance of different laser-processed materials. LSP with vinyl and quartz at a scanning speed of 500 mm s⁻¹ achieved a micro-hardness of 110 GPa at a depth of 632 nm. LPwC at 0.8 GW cm⁻² produced hybrid microstructures which share characteristics of laser shock processing and selective laser melted structures. For laser feed speed in the region of 1000 mm s⁻¹, micro-indentation tests revealed an improvement of hardness from 70 GPa to 95 GPa at a depth of 670 nm for LPwC. Tribotest revealed enhanced wear performance for all laser-processed pins and reduced coefficient of friction also validated by increased material removal rate when compared to the as-received material. To the best of authors' knowledge, it is reported for the first time that an improvement of wear performance can be achieved on polycrystalline diamond through LSP and LPwC.     

Nonlinear comminution process modeling based on GA–FNN in the computational comminution system

A new concept named computational comminution is firstly proposed in this paper. Based on information technology, the structure of a computational comminution system (CCS) is built. The study on CCS is very different from the traditional ones for comminution, such as the study based on theoretic models, or the study based on experimental models. As one of the key technologies in CCS, a modeling framework for comminution processes is implemented particularly by employing GA–FNN that can model complex nonlinear processes such as the comminution process of cement by integrating artificial neural networks, fuzzy sets and genetic algorithms. Application results of this modeling method to the Horomill cement comminution process show that the modeling framework discussed in this paper is efficient.     

Critical issues concerning the mechanisms of duplex grain structure formation and interpretation of duplex nio grown on pure ni and cr doped substrates during high-temperature oxidation

Duplex layers are a very important class of film microstructures and form under a wide variety of conditions on a large number of substrates. In this paper, the available models for duplex layer formation are reviewed in detail and the basic assumptions which are based upon them are examined. The mechanisms of formation of the duplex layers based on microstructural observations in pure Ni and Ni-lat.%Cr systems during high-temperature oxidation are addressed.     

Study of the size effects in the electrical resistivity of ultrathin (

Saci Messaadi  Hadria Medouer  Mosbah Daamouche 《Journal of Alloys and Compounds》2010,489(2):609-613