This study experimentally quantified the structure-property relations with respect to fatigue of an extruded AZ61 magnesium alloy and captured the behavior with a microstructure-sensitive MultiStage Fatigue Model. Experiments were conducted in the extruded and transverse directions under low and high cycle strain control fatigue conditions. The cyclic behavior of this alloy displayed varying degrees of cyclic hardening depending on the strain amplitude and the specimen orientation. The fracture surfaces of the fatigued specimens were analyzed using a scanning electron microscope in order to quantify structure-property relations with respect to microstructural features. Correlations between particle size, nearest neighbor distance, and grain size as a function of failure cycles were quantified. Finally, a multistage fatigue model based on the structure-property relations quantified in this study was employed to capture the anisotropic fatigue damage of the AZ61 magnesium alloy.

Understanding the effects of uncertainty on modeling has seen an increased focus as engineering disciplines rely more heavily on computational modeling of complex physical processes to predict system performance and make informed engineering decisions. These computational methods often use simplified models and assumptions with models calibrated using uncertain, averaged experimental data. This commonplace method ignores the effects of uncertainty on the variation of modeling output. Qualitatively, uncertainty is the possibility of error existing from experiment to experiment, from model to model, or from experiment to model. Quantitatively, uncertainty quantification (UQ) methodologies seek to determine the how variable an engineering system is when subjected to variation in the factors that control it. Often performed in conjunction, sensitivity analysis (SA) methods seek to describe what model factor contributes the most to variation in model output. UQ and SA methodologies were employed in the analysis of the Modified Embedded Atom Method (MEAM) model for a pure aluminum, a microstructure sensitive fatigue crack growth model for polycarbonate, and the MultiStage Fatigue (MSF) model for AZ31 magnesium alloy. For the MEAM model, local uncertainty and sensitivity measures were investigated for the purpose of improving model calibrations. In polycarbonate fatigue crack growth, a Monte Carlo method is implemented in code and employed to investigate how variations in model input factors effect fatigue crack growth predictions. Lastly, in the analysis of fatigue life predictions with the MSF model for AZ31, the expected fatigue performance range due to variation in experimental parameters is investigated using both Monte Carlo Simple Random Sampling (MCSRS) methods and the estimation of first order effects indices using the Fourier Amplitude Sensitivity Test (FAST) method.

The goal of this study is to investigate the microstructure and microstructure-based fatigue (MSF) model of additively-manufactured (AM) metallic materials. Several challenges associated with different metals produced through additive manufacturing (Laser Enhanced Net Shaping – LENS®) have been addressed experimentally and numerically. Significant research efforts are focused on optimizing the process parameters for AM manufacturing; however, achieving a homogenous, defectree AM product immediately after its fabrication without postabrication processing has not been fully established yet. Thus, in order to adopt AM materials for applications, a thorough understanding of the impact of AM process parameters on the mechanical behavior of AM parts based on their resultant microstructure is required. Therefore, experiments in this study elucidate the effects of process parameters – i.e. laser power, traverse speed and powder feed rate – on the microstructural characteristics and mechanical properties of AM specimens. A majority of fatigue data in the literature are on rotation/bending test of wrought specimens; however, few studies examined the fatigue behavior of AM specimens. So, investigating the fatigue resistance and failure mechanism of AM specimens fabricated via LENS® is crucial. Finally, a microstructure-based MultiStage Fatigue (MSF) model for AM specimens is proposed. For calibration of the model, fatigue experiments were exploited to determine structure-property relations for an AM alloy. Additional modifications to the microstructurally-based MSF Model were implemented based on microstructural analysis of the fracture surfaces – e.g. grain misorientation and grain orientation angles were added to the MSF code.