A time-dependent probabilistic fatigue analysis method considering stochastic loadings and strength degradation

Su, Chunbo; Yu, Shui; Wang, Zhonglai; Tayyab, Zafar

doi:10.1177/1687814018785560

Cited by 5 publications

(5 citation statements)

References 41 publications

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“…A cumulative distribution function (CDF) FXi can be assigned to every element xi such that the following conditions are satisfied (Eqns. (12) and 13):…”

Section: Aleatory-type Uncertaintymentioning

confidence: 99%

“…In this particular, three main approaches coexist: (a) probabilistic; (b) Bayesian inference; (c) probability bounds analysis (PBA). A considerable amount of research works is based on the so-called probabilistic methods, for example, [7][8][9][10][11][12][13][14][15][16]. The probabilistic approach is an adequate representation of an UIQ when there is sufficient random data to be representative of the distribution.…”

Section: Introductionmentioning

confidence: 99%

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Bi-level Hybrid Uncertainty Quantification in Fatigue Analysis: S-N Curve Approach

Nonato

2020

Frattura Ed Integrità Strutturale

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Due to its physical complexity, fatigue phenomenon inherently presents a significant number of uncertain parameters to be predicted. In uncertainty quantification (UQ), research has demonstrated that even a small variation in uncertain input quantities (UIQs) may lead to a wide dispersion in the system response quantities (SRQs). In this paper, a bi-level hybrid UQ analysis of a fatigue problem is presented based on the S-N curve approach. The uncertain fatigue analysis presented is able to deal simultaneously with aleatory- and epistemic-type uncertainties in two levels (a SRQ in the first level is a UIQ in the second level). To this end, the proposed scheme is tested for an AISI 4130 clamped beam subjected to a concentrated load, which material information comes from experiments reported in the literature. The UIQs are geometrical parameters, material properties, loading magnitude, and stress, while the SRQs are the stress (which is also a UIQ for fatigue life) and fatigue life. The results evidenced that the uncertain fatigue analysis, instead of providing a unique value for a SRQ, now produces a possible range of values. Therefore, depending on the risk an engineer can take on a design, there will be a corresponding level of optimization achieved.

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“…A cumulative distribution function (CDF) FXi can be assigned to every element xi such that the following conditions are satisfied (Eqns. (12) and 13):…”

Section: Aleatory-type Uncertaintymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bi-level Hybrid Uncertainty Quantification in Fatigue Analysis: S-N Curve Approach

Nonato

2020

Frattura Ed Integrità Strutturale

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“…qukaszewicz 55 suggested a fatigue life evaluation of metals based on a complex stress state. On the contrary, Su et al 56 presented a proposal of two strategies for time-dependent probabilistic fatigue analysis considering stochastic loadings and strength degradation based on the failure transformation and multi-dimensional kernel density estimation method. Kulkarni et al 57 proposed a statistical wind prediction and fatigue analysis for wind turbine composite material blade under dynamic loads.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic S-N fields based on statistical distributions applied to metallic and composite materials: State of the art

Barbosa

Correia

Júnior

et al. 2019

Advances in Mechanical Engineering

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Fatigue life prediction of materials can be modeled by deterministic relations, via mean or median S-N curve approximation. However, in engineering design, it is essential to consider the influence of fatigue life scatter using deterministic-stochastic methods to construct reliable S-N curves and determine safe operation regions. However, there are differences between metals and composites that must be considered when proposing reliable S-N curves, such as distinct fracture mechanisms, distinct ultimate strengths under tension and compression loading, and different cumulative fatigue damage mechanisms including low-cycle fatigue. This study aims at conducting a review of the models used to construct probabilistic S-N fields ( P-S-N fields) and demonstrate the methodologies applied to fit the P-S-N fields that are best suited to estimate fatigue life of the selected materials. Results indicate that the probabilistic Stüssi and Sendeckyj models were the most suitable for composite materials, while, for metals, only the probabilistic Stüssi model presented a good fitting of the experimental data, for all fatigue regimes.7

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“…Bang et al [8] proposed a modification of the UniGrow model to predict total fatigue life with the presence of a short fatigue crack by incorporating short crack propagation into the UniGrow crack growth model. Su et al [ 9], based on the failure transformation and multi-dimensional kernel density estimation methods, proposed two strategies for timedependent probability fatigue analysis considering random load and intensity degradation. A filtering gear reducer was presented as an example to validate the effectiveness of the proposed methods.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Fatigue Reliability Life of Telescopic Rod of an Eccentric Telescopic Rod Conveyor with and without Strength Degradation

Mou¹

2019

IJPE

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Eccentric telescopic rod conveyors are used to convey straw from chain conveyors to the feeding and compression mechanism of the 4FZ-2000A type self-propelled straw harvesting baler. As the main working component, the telescopic rod endures higher dynamic loads while conveying the straw. This will make the telescopic rod prone to fatigue fracture. Therefore, it is necessary to find a feasible model that can accurately estimate the fatigue reliability life of the telescopic rod. In order to ensure the safe working of the eccentric telescopic rod conveyer, a mechanical model of the main bearing parts of the telescopic rod is established, and virtual prototype technology is used to obtain the work load spectrum borne by the telescopic rod. Static analysis of the telescopic rod using the finite element method shows that the telescopic rod experiences multi-axial stress fatigue, and the critical section is determined. The S-N curve equation of the structure modified by the surface mass and stress gradient, critical plane approach, Miner's cumulative fatigue linear damage model, and Gaussian normal distribution model of fatigue life are used to estimate the fatigue life of the telescopic rod. In order to predict the fatigue life of the telescopic rod accurately, fatigue reliability lives are calculated with and without consideration of the strength degradation. The results show that: (1) the fatigue life prediction without considering the strength degradation is far different from practical experience; the results obtained after considering the strength degradation are more conservative and more consistent with the actual fatigue lives. The prediction results are more accurate. (2) When the strength degradation is considered, the modified Gerber correction method is more accurate than the Goodman correction method. The results of this study can provide a reference for the fatigue reliability analysis and optimization of eccentric telescopic rod conveyors.

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A time-dependent probabilistic fatigue analysis method considering stochastic loadings and strength degradation

Cited by 5 publications

References 41 publications

Bi-level Hybrid Uncertainty Quantification in Fatigue Analysis: S-N Curve Approach

Bi-level Hybrid Uncertainty Quantification in Fatigue Analysis: S-N Curve Approach

Probabilistic S-N fields based on statistical distributions applied to metallic and composite materials: State of the art

Comparison of Fatigue Reliability Life of Telescopic Rod of an Eccentric Telescopic Rod Conveyor with and without Strength Degradation

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