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A comparison of fatigue lifetime prediction models applied to variable amplitude loading

Nahuel Micone (UGent) , Tom Nottebaere and Wim De Waele (UGent)
Author
Organization
Abstract
The loads imposed on e.g. offshore structures can vary considerably with time. Lifetime prediction methodologies need to consider possible acceleration and retardation of the crack growth rate due to load sequences. Models based on a linear accumulation of damage will have a limited accuracy and are not considered as a valuable asset in lifetime prediction of structures subjected to variable amplitude loading. This necessitates more complex nonlinear damage evolution models that can be applied in a so-called cycle-by-cycle analysis. In this paper, a comparison is made between three cumulative damage models (Miner, modified Miner and weighted average) and two yield zone models (Wheeler and Willenborg). Experimental data of fatigue crack growth in offshore steel subjected to sequential loading is used as basis of the comparison. The modified Miner model is the most promising of the cumulative damage models but the determination of the parameter α requires laboratory tests. Evaluation of the effects of variation in the model input parameters on estimated lifetime reveals a large influence for the Miner and weighted average approaches.
Keywords
fatigue, variable amplitude, Miner, Wheeler, Willenborg

Citation

Please use this url to cite or link to this publication:

Chicago
Micone, Nahuel, Tom Nottebaere, and Wim De Waele. 2017. “A Comparison of Fatigue Lifetime Prediction Models Applied to Variable Amplitude Loading.” Ed. Stijn Hertelé and Jeroen Van Wittenberghe. Sustainable Construction and Design 8 (1).
APA
Micone, N., Nottebaere, T., & De Waele, W. (2017). A comparison of fatigue lifetime prediction models applied to variable amplitude loading. (S. Hertelé & J. Van Wittenberghe, Eds.)SUSTAINABLE CONSTRUCTION AND DESIGN, 8(1).
Vancouver
1.
Micone N, Nottebaere T, De Waele W. A comparison of fatigue lifetime prediction models applied to variable amplitude loading. Hertelé S, Van Wittenberghe J, editors. SUSTAINABLE CONSTRUCTION AND DESIGN. 2017;8(1).
MLA
Micone, Nahuel, Tom Nottebaere, and Wim De Waele. “A Comparison of Fatigue Lifetime Prediction Models Applied to Variable Amplitude Loading.” Ed. Stijn Hertelé & Jeroen Van Wittenberghe. SUSTAINABLE CONSTRUCTION AND DESIGN 8.1 (2017): n. pag. Print.
@article{8529317,
  abstract     = {The loads imposed on e.g. offshore structures can vary considerably with time. Lifetime prediction methodologies need to consider possible acceleration and retardation of the crack growth rate due to load sequences. Models based on a linear accumulation of damage will have a limited accuracy and are not considered as a valuable asset in lifetime prediction of structures subjected to variable amplitude loading. This necessitates more complex nonlinear damage evolution models that can be applied in a so-called cycle-by-cycle analysis.
In this paper, a comparison is made between three cumulative damage models (Miner, modified Miner and weighted average) and two yield zone models (Wheeler and Willenborg). Experimental data of fatigue crack growth in offshore steel subjected to sequential loading is used as basis of the comparison. The modified Miner model is the most promising of the cumulative damage models but the determination of the parameter \ensuremath{\alpha} requires laboratory tests. Evaluation of the effects of variation in the model input parameters on estimated lifetime reveals a large influence for the Miner and weighted average approaches.},
  author       = {Micone, Nahuel and Nottebaere, Tom and De Waele, Wim},
  editor       = {Hertel{\'e}, Stijn and Van Wittenberghe, Jeroen},
  issn         = {2032-7471},
  journal      = {SUSTAINABLE CONSTRUCTION AND DESIGN},
  language     = {eng},
  number       = {1},
  title        = {A comparison of fatigue lifetime prediction models applied to variable amplitude loading},
  url          = {http://dx.doi.org/10.21825/scad.v8i1.6809},
  volume       = {8},
  year         = {2017},
}

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