Computational modeling of strain localization and fracture using microstructural information

Strain mapping at various length scales and its relationship to both microstructural features and mechanical behavior has been greatly advanced over the past years through the use of optical, non-contact full-field measurement techniques, capable of measuring 2D and 3D surface deformations. An integrated experimental and numerical approach for the characterization of small scale plasticity under monotonic and cyclic loading is presented in this work

Identification of fatigue precursors via quantitative nondestructive evaluation

Understanding evolving fatigue microstructure–properties–behavior relations is both challenging and needed in view of the time and length scales involved at both coupon and component levels. To reliably formulate quantitative descriptions of remaining useful life for advanced materials recent developments reported in the Integrated Computational Materials Engineering framework including in situ/ex situ experimental observations and high--performance simulations, continuously provide valuable insights. This discussion focuses on describing the role quantitative nondestructive evaluation (NDE) can play in this multidisciplinary effort to identify fundamental mechanisms that dominate fatigue life by presenting results obtained from a range of materials including polycrystalline alloys and fiber-reinforced composites. Emphasis is given on using multimodal NDE data to first identify intervals in time and regions at several length scales in which fatigue damage precursors could be found. Results from targeted observations of the evolution of such precursors are then used to formulate hypotheses on the fatigue behavior which are implemented in analytical and computational models. Challenges and future opportunities created by adopting this type of approach are also discussed

An integrated approach to model strain localization bands in magnesium alloys

Strain localization bands (SLBs) that appear at early stages of deformation of magnesium alloys have been recently associated with heterogeneous activation of deformation twinning. Experimental evidence has demonstrated that such “Lüders-type” band formations dominate the overall mechanical behavior of these alloys resulting in sigmoidal type stress–strain curves with a distinct plateau followed by pronounced anisotropic hardening. To evaluate the role of SLB formation on the local and global mechanical behavior of magnesium alloys, an integrated experimental/computational approach is presented. The computational part is developed based on custom subroutines implemented in a finite element method that combine a plasticity model with a stiffness degradation approach. Specific inputs from the characterization and testing measurements to the computational approach are discussed while the numerical results are validated against such available experimental information, confirming the existence of load drops and the intensification of strain accumulation at the time of SLB initiation

Validation of a cyclic plasticity computational method using fatigue full-field deformation measurements

The evolution of crack tip displacement and strain fields during uniaxial, room temperature, low-cycle fatigue experiments of Nickel superalloy compact tension specimens was measured by a digital image correlation approach and was further used to validate a cyclic plasticity model and corresponding deformation calculations made by a finite elements methodology. The experimental results provided data trends for the opening displacements and near crack tip strains as function of cycles. A finite element model was developed to capture test conditions for a measured crack size. The model captures crack tip plasticity by using a constitutive model calibrated against stress-strain measurements performed on a round bar. Similar quantities were extracted from the model predictions to compare with the digital image correlation measurements for model validation purposes. This type of direct comparison demonstrated that the computational model was capable to adequately capture the crack opening displacements at various stages of the specimen's fatigue life, providing in this way a tool for quantitative cyclic plasticity model validation. In addition, this integrated experimental-computational approach provides a framework to accelerate our understanding related to interactions of fatigue test data and models, as well as ways to inform one another

Data-driven damage model based on nondestructive evaluation

A computational damage model which is driven by material, mechanical behavior and nondestructive evaluation data is presented in this study. To collect material and mechanical behavior damage data, an aerospace grade precipitate-hardened aluminum alloy was mechanically loaded under monotonic conditions inside a Scanning Electron Microscope, while acoustic and optical methods were used to track the damage accumulation process. In addition, to obtain experimental information about damage accumulation at the laboratory scale, a set of cyclic loading experiments was completed using 3-point bending specimens made out of the same aluminum alloy and by employing the same nondestructive methods. The ensemble of recorded data for both cases was then used in a post-processing scheme based on outlier analysis to form damage progression curves which were subsequently used as custom damage laws in finite element simulations. Specifically, a plasticity model coupled with stiffness degradation triggered by the experimentally defined damage curves was used in custom subroutines. The results highlight the effect of the data-driven damage model on the simulated mechanical response of the geometries considered and provide an information workflow that is capable of coupling experiments with simulations that can be used for remaining useful life estimations

Energy dissipation via acoustic emission in ductile crack initiation

This article presents a modeling approach to estimate the energy release due to ductile crack initiation in conjunction to the energy dissipation associated with the formation and propagation of transient stress waves typically referred to as acoustic emission. To achieve this goal, a ductile fracture problem is investigated computationally using the finite element method based on a compact tension geometry under Mode I loading conditions. To quantify the energy dissipation associated with acoustic emission, a crack increment is produced given a pre-determined notch size in a 3D cohesive-based extended finite element model. The computational modeling methodology consists of defining a damage initiation state from static simulations and linking such state to a dynamic formulation used to evaluate wave propagation and related energy redistribution effects. The model relies on a custom traction separation law constructed using full field deformation measurements obtained experimentally using the digital image correlation method. The amount of energy release due to the investigated first crack increment is evaluated through three different approaches both for verification purposes and to produce an estimate of the portion of the energy that radiates away from the crack source in the form of transient waves. The results presented herein propose an upper bound for the energy dissipation associated to acoustic emission, which could assist the interpretation and implementation of relevant nondestructive evaluation methods and the further enrichment of the understanding of effects associated with fracture

Microstructure-Sensitive Investigation of Fracture Using Acoustic Emission Coupled With Electron Microscopy

A novel technique using Scanning Electron Microscopy (SEM) in conjunction with Acoustic Emission (AE) monitoring is proposed to investigate microstructure-sensitive fatigue and fracture of metals. The coupling between quasi in situ microscopy with actual in situ nondestructive evaluation falls into the ICME framework and the idea of quantitative data-driven characterization of material behavior. To validate the use of AE monitoring inside the SEM chamber, Aluminum 2024-B sharp notch specimen were tested both inside and outside the microscope using a small scale mechanical testing device. Subsequently, the same type of specimen was tested inside the SEM chamber. Load data were correlated with both AE information and observations of microcracks around grain boundaries as well as secondary cracks, voids, and slip bands. The preliminary results are in excellent agreement with similar findings at the mesoscale. Extensions of the application of this novel technique are discussed

MICRO CHARACTERIZATION OF MG AND MG ALLOY FOR BIODEGRADABLE ORTHOPEDIC IMPLANTS APPLICATION

ABSTRACT Magnesium as a candidate metallic biomaterial for biodegradable orthopedic implants was evaluated in-vitro in terms of degradation behavior, biocompatibility and mechanical property both in macro-and micro-scale. Micro structure of pure Mg and AZ61 after degradation in both simulated body fluid (SBF) and cell culture environment were analyzed. Different from AZ61, pure Mg degraded at a higher rate and attracted large amount of salt precipitation which formed a layer covering the surface. Much less pitting degradation and salt deposition were observed on both pure Mg and AZ61 in cell culture environment compared to in SBF. After culturing for 7 days, EAhy926 cells growing on AZ61 showed significant higher proliferation rate as of cells growing on pure Mg. Higher proliferation rates indicated that cells grew better on slow-degrading AZ61 than on fast-degrading pure Mg. Cells growing on AZ61 proliferated much better and assembled together to form a consistent tissue-like micro-structure, while cells spread and reached out on the surface of pure Mg, possibly due to low cell density and lack of cellular communication. The elastic modulus and tensile yield strength of magnesium are closer to those of natural bone than other commonly used metallic biomaterials. It was shown that Mg was biodegradable, biocompatible and had appropriate mechanical strength, thus Mg and its alloys showed great potential for deployment in a new generation of biodegradable orthopedic implants

Acoustic emission signal processing framework to identify fracture in aluminum alloys

Acoustic emission (AE) is a common nondestructive evaluation tool that has been used to monitor fracture in materials and structures. The direct connection between AE events and their source, however, is difficult because of material, geometry and sensor contributions to the recorded signals. Moreover, the recorded AE activity is affected by several noise sources which further complicate the identification process. This article uses a combination of in situ experiments inside the scanning electron microscope to observe fracture in an aluminum alloy at the time and scale it occurs and a novel AE signal processing framework to identify characteristics that correlate with fracture events. Specifically, a signal processing method is designed to cluster AE activity based on the selection of a subset of features objectively identified by examining their correlation and variance. The identified clusters are then compared to both mechanical and in situ observed microstructural damage. Results from a set of nanoindentation tests as well as a carefully designed computational model are also presented to validate the conclusions drawn from signal processing