Quantifying uncertainty in fatigue crack growth of SLM 316L through advanced predictive modeling

Optimizing structural designs is crucial today, with additive manufacturing, particularly selective laser melting, gaining prominence. Thorough mechanical characterization of new materials remains vital. This paper investigates fatigue crack growth behavior in SLM 316L specimens under cyclic loading...

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Veröffentlicht in:	Fatigue & fracture of engineering materials & structures 2024-09, Vol.47 (9), p.3116-3132
Hauptverfasser:	Haselibozchaloee, Danial, Correia, José A. F. O., Braga, Daniel F. O., Cipriano, Gonçalo, Reis, Luis, Manuel, Lance, Moreira, Pedro M. G. P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Additive manufacturing Bayes theorem Bayesian analysis bootstrap Confidence intervals Crack propagation Cyclic loads fatigue crack growth Fatigue cracks Fatigue failure Fracture mechanics Laser beam melting Linear prediction Manufacturing Markov chains Mechanical properties nonlinear regression Polynomials Prediction models Regression models selective melting manufacturing Statistical analysis Structural design Uncertainty
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