Probabilistic fatigue integrity assessment in multiple crack growth analysis associated with equivalent initial flaw and material variability

Chau-Dinh, Thanh; Zi, Goangseup; Lee, Won Woo; Kong, Jun

doi:10.1016/j.engfracmech.2016.02.018

Cited by 29 publications

(16 citation statements)

References 42 publications

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“…However, the variability of the material, loading, geometry, temperature, etc., introduces uncertainty in the results. In this context, there are two main procedures to overcome the influence of sources of uncertainties [4]: (i) the use of safety factors, which is the conservative solution usually adopted to accommodate uncertainties, and (ii) performing stochastic analysis, which is often supported by probabilistic fatigue models (e.g., [5,6]), metamodeling techniques (e.g., [7][8][9][10][11][12][13]) and more recently by digital twin approaches (e.g., [14,15]). In the context of stochastic fatigue analysis, a probabilistic fracture mechanics approach to predict the fatigue life of aircraft wing attachment bulkheads was proposed by White [16].…”

Section: Introductionmentioning

confidence: 99%

Numerical Study on the Variability of Plastic CTOD

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 99%

Numerical Study on the Variability of Plastic CTOD

et al. 2020

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“…Liu et al [8] put forward a new life prediction model which is based on crack growth formula, but, due to the complexity of computation, they only use the Monte Carlo method for calculation. To overcome the difficulties in the life-cycle reliability analysis of MSD, Kim et al [9] adopt the Gaussian process (GP) response surface model for calculation, and the accuracy and advantages of the proposed method were verified by a number of experimental results and numerical examples. Zou and Yang [10] make an improvement in which the first-order second-moment method is used to calculate the reliability of structure, but the established model does not take the randomness of initial crack length into consideration, and, in practical engineering, the crack length plays an important role in the calculation of crack lifetime.…”

Section: Introductionmentioning

confidence: 99%

Multiple Failure Modes Reliability Modeling and Analysis in Crack Growth Life Based on JC Method

Sun

Liu

Zhang

et al. 2017

Mathematical Problems in Engineering

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The fatigue crack growth (FCG) phenomenon generally exists in large mechanical structures. Due to the influences of varied kinds of random factors, the safety evaluation of structure in FCG is under great uncertainty. In this paper, based on the reliability theory, the limit state equations of fracture failure and static strength failure were derived firstly, and the parameters in those equations were regarded as random variables that follow the normal distribution or log-normal distribution. According to the limit state equations, the JC method (equivalent normalizing method) was used to calculate the reliability indexes under the different failure modes of structure in every stress cycle. Based on the reliability indexes and correlation of the two failure modes, the joint failure probability was obtained. In the end, a specific computation example was given, and the curve of joint failure probability in multiple failure modes was used for comparison with the result of single failure mode. The results indicated that the reliability analysis based on multiple failure modes was more reasonable, and the evaluation of reliability could be obtained in fatigue crack growth process.

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“…Thus, appropriate treatment of uncertainty in fatigue design has become a significant topic with widespread interest [17]- [24]. Prior work on statistical or probabilistic aspects of fatigue includes modeling of the variability in material properties (e.g., elastic modulus, fracture toughness, yield strength) [6], [17], [25]- [27], equivalent initial flaw size (EIFS) [21], [28]- [30], microstructures as well as defects [31]- [35], stress-life data [36]- [39], and under multiaxial conditions [40]- [45]. Generally, two aspects need to be addressed for probabilistic fatigue design: a valid PoF-based fatigue model and a probabilistic framework for treating both the random material variables and the uncertainty on model parameters in the fatigue model [46], which has been reviewed in detail recently by Pineau et al [47].…”

Section: Introductionmentioning

confidence: 99%

“…Since structural integrity of engineering components are directly affected by physical variability, statistical uncertainty, model uncertainty and errors [3]- [5], quantifying and controlling these uncertainties are essential to enhance the competitiveness in designing fatigue critical products such as turbine engines and railway axles [6]- [9]. Moreover, the development and application of probabilistic approaches with Physics-of-Failure (PoF)-based methods is imperative for valid structural integrity assessment of engineering components under complex loadings, i.e.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic framework for multiaxial LCF assessment under material variability

Zhu

Foletti

Beretta

2017

International Journal of Fatigue

154

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Abstract:The influence of material variability upon the multiaxial LCF assessment of engineering components is missing for a comprehensive description. In this paper, a probabilistic framework is established for multiaxial LCF assessment of notched components by using the Chaboche plasticity model and Fatemi-Socie criterion. Simulations from experimental results of two steels reveal that the scatter in fatigue lives can be well described by quantifying the variability of four material parameters . A procedure for choosing the safety factor for fatigue design has been derived by using first order approximation.

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Probabilistic fatigue integrity assessment in multiple crack growth analysis associated with equivalent initial flaw and material variability

Cited by 29 publications

References 42 publications

Numerical Study on the Variability of Plastic CTOD

Numerical Study on the Variability of Plastic CTOD

Multiple Failure Modes Reliability Modeling and Analysis in Crack Growth Life Based on JC Method

Probabilistic framework for multiaxial LCF assessment under material variability

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