Fatigue crack growth and life prediction of foam core sandwich composites under flexural loading

2003 ◽  
Vol 59 (4) ◽  
pp. 499-505 ◽  
Author(s):  
Nitin Kulkarni ◽  
Hassan Mahfuz ◽  
Shaik Jeelani ◽  
Leif A. Carlsson
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Life Prediction ◽  
Foam Core ◽  
Sandwich Composites ◽  
Flexural Loading

scholarly journals Uncertainty Quantification in Small-Timescale Model-Based Fatigue Crack Growth Analysis Using a Stochastic Collocation Method

Metals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 646
Author(s):  
Hesheng Tang ◽  
Xueyuan Guo ◽  
Songtao Xue
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Uncertainty Quantification ◽  
Crack Growth ◽  
Collocation Method ◽  
Life Prediction ◽  
Remaining Useful Life ◽  
Stochastic Collocation ◽  
Stochastic Collocation Method ◽  
Model Based

Due to the uncertainties originating from the underlying physical model, material properties and the measurement data in fatigue crack growth (FCG) processing, the prediction of fatigue crack growth lifetime is still challenging. The objective of this paper was to investigate a methodology for uncertainty quantification in FCG analysis and probabilistic remaining useful life prediction. A small-timescale growth model for the fracture mechanics-based analysis and predicting crack-growth lifetime is studied. A stochastic collocation method is used to alleviate the computational difficulties in the uncertainty quantification in the small-timescale model-based FCG analysis, which is derived from tensor products based on the solution of deterministic FCG problems on sparse grids of collocation point sets in random space. The proposed method is applied to the prediction of fatigue crack growth lifetime of Al7075-T6 alloy plates and verified by fatigue crack-growth experiments. The results show that the proposed method has the advantage of computational efficiency in uncertainty quantification of remaining life prediction of FCG.

Mixed-mode fatigue crack growth and life prediction of an automotive adhesive bonding system

2018 ◽  
Vol 189 ◽  
pp. 439-450 ◽  
Author(s):  
Qiuren Chen ◽  
Haiding Guo ◽  
Katherine Avery ◽  
Hongtae Kang ◽  
Xuming Su
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Mixed Mode ◽  
Life Prediction ◽  
Adhesive Bonding ◽  
Bonding System

Fatigue Crack Growth in Blade Attachment of Turbine Disks: Experimental Tests and Life Prediction

2014 ◽  
Vol 4 (2) ◽  
pp. 20140036 ◽  
Author(s):  
S. Foletti ◽  
S. Beretta ◽  
F. Scaccabarozzi ◽  
S. Rabbolini ◽  
L. Traversone
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Life Prediction ◽  
Experimental Tests ◽  
Turbine Disks

Fatigue Crack Growth Prediction Under Random Peaks and Sequence Loading

1989 ◽  
Vol 111 (4) ◽  
pp. 338-344 ◽  
Author(s):  
H. Alawi
Keyword(s):  
Fatigue Crack ◽  
Fatigue Crack Growth ◽  
Crack Growth ◽  
Probabilistic Model ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Constant Amplitude ◽  
Random Loads ◽  
Prediction Techniques ◽  
Experimental Findings

Fatigue crack growth under random amplitude and sequence loading with peaks following the Rayleigh probability density function is simulated using the probabilistic model. Another attempt at fatigue life prediction under the above loads is made by converting random loads in to equivalent constant amplitude. Prediction results are compared with experimental findings. Empirical data for fatigue crack growth under random loads at different frequencies are compared with the results of prediction using the above techniques. Experimental results of three steels are used in this study to compare with the findings of the above prediction techniques. These steels are AISI 1018, AISI 4340 and stainless pH 17-7. It is seen that the probabilistic model produces reliable results. It conservatively predicts fatigue crack growth when no delay mechanism to retard crack growth is introduced.

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