Fatigue Crack Growth prediction on A310 aircraft wing using static analysis

Habib, Shahroz; Yousuf, Waleed Bin; Mairaj, Tariq; Khalid, Shah

doi:10.1109/ibcast.2017.7868038

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Leser et al [9] validated the crack growth modeling method using damage diagnosis data based on structural health monitoring, and a probabilistic prediction of RUL is formed for a metallic, single-edge notch tension specimen with a fatigue crack growing under mixed-mode conditions. Habib et al [10] evaluated the stress of A310 aircraft wings during each loading cycle through a finite element analysis, and they predicted the RUL of A310 wings using the Paris Law technique based on linear elastic fracture mechanics. Chen et al [11] developed a novel computational modelling technique for the prediction of crack growth in load bearing orthopaedic alloys subjected to fatigue loading, which can predict the RUL of parts through the crack path.…”

Section: Prefacementioning

confidence: 99%

Remaining Useful Life Prediction of the Concrete Piston Based on Probability Statistics and Data Driven

Yue-jin

et al. 2021

Applied Sciences

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This paper proposes a method on predicting the remaining useful life (RUL) of a concrete piston of a concrete pump truck based on probability statistics and data-driven approaches. Firstly, the average useful life of the concrete piston is determined by probability distribution fitting using actual life data. Secondly, according to condition monitoring data of the concrete pump truck, a concept of life coefficient of the concrete piston is proposed to represent the influence of the loading condition on the actual useful life of individual concrete pistons, and different regression models are established to predict the RUL of the concrete pistons. Finally, according to the prediction result of the concrete piston at different life stages, a replacement warning point is established to provide support for the inventory management and replacement plan of the concrete piston.

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Section: Prefacementioning

confidence: 99%

Remaining Useful Life Prediction of the Concrete Piston Based on Probability Statistics and Data Driven

Yue-jin

et al. 2021

Applied Sciences

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“…The contour deflections are shown for X, Y, and Z directions by taking the example of NACA 4415 aerofoil shape with different thickness. Habib et al [3] studied fatigue crack growth prediction on A310 aircraft wing using static analysis. The comparison between predicted and actual crack growth is predicted and states that the Paris law model is effective.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Crack on Aeroplane Wing at Different Positions using ANSYS Software

Paricharak¹,

Lotake²,

Mane³

et al. 2019

International Journal of New Technology and Research

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The present study revivals the analysis of crack on aeroplane wing at different positions. Also states the deformation of wing structure against the different positions of crack on aeroplane wing. For this study the NACA 4412 Clark-y profile is used to generate aerofoil shape of aeroplane A320. Again the model is generated in CATIA v5 R21 software for further analysis. The ANSYS is used to carry out harmonic response analysis for prediction of deformation against pre loading condition at different positions of crack on wing. This shows the variation in results for different positions of cracks on wing to decide the maximum deformation of wing structure.

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Comprehensive Remaining Useful Life Prediction for Rolling Element Bearings Based on Time-Varying Particle Filtering

Cui

Wang

et al. 2022

IEEE Trans. Instrum. Meas.

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Fatigue Crack Growth prediction on A310 aircraft wing using static analysis

Cited by 3 publications

References 7 publications

Remaining Useful Life Prediction of the Concrete Piston Based on Probability Statistics and Data Driven

Remaining Useful Life Prediction of the Concrete Piston Based on Probability Statistics and Data Driven

Analysis of Crack on Aeroplane Wing at Different Positions using ANSYS Software

Comprehensive Remaining Useful Life Prediction for Rolling Element Bearings Based on Time-Varying Particle Filtering

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