Abstract

This paper presents a numerical study on the influence of material parameters and loading variability in the plastic crack tip opening displacement (CTOD) results. For this purpose, AA7050-T6 was selected as reference material and a middle-cracked tension specimen geometry was considered. The studied input parameters were the Young’s modulus, Poisson’s ratio, isotropic and kinematic hardening parameters and the maximum and minimum applied loads. The variability of the input parameters follows a Gaussian distribution. First, screening design-of-experiments were performed to identify the most influential parameters. Two types of screening designs were considered: one-factor-at-a-time and fractional factorial designs. Three analysis criteria were adopted, based on: main effect, index of influence and analysis of variance. Afterwards, metamodels were constructed to establish relationships between the most influential parameters and the plastic crack tip opening displacement (CTOD) range, based on two types of designs: Face-Centered Central Composite Design and Box-Behnken design. Finally, the metamodels were validated, enabling the expeditious evaluation of the variability in the plastic CTOD range; in addition, the variability in the fatigue crack growth rate was also evaluated.

Highlights

  • Fatigue is the main failure mechanism in components submitted to cyclic loads

  • This paper concerns a numerical study on the influence of material parameters and loading variability in the plastic crack tip opening displacement (CTOD) range of AA7050-T6 on M(T) specimens

  • The most influential input parameters were identified based on the analysis of two types of screening design of experiments (DOE) approaches (OFAT and fractional factorial design (FFD)), according to three analysis criteria (Main Effect, Index of Influence and Analysis of Variance (ANOVA))

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Summary

Introduction

Design against fatigue based on damage tolerance approach assumes the presence of intrinsic defects, such as cracks. Technological processes like casting, machining, welding and additive manufacturing are known to produce small defects. Accurate assessments of fatigue crack growth (FCG) rates are needed to define the time between inspections. Several models have been proposed in the literature to quantify the FCG rate as a function of loading and/or material parameters (e.g., [1,2,3]). These models are deterministic, i.e., assume that there is a well-defined relation between these parameters and FCG rate

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