TY - JOUR
T1 - Parametric probabilistic approach for cumulative fatigue damage using double linear damage rule considering limited data
AU - Dias, João Paulo
AU - Ekwaro-Osire, Stephen
AU - Cunha, Americo
AU - Dabetwar, Shweta
AU - Nispel, Abraham
AU - Alemayehu, Fisseha M.
AU - Endeshaw, Haileyesus B.
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/10
Y1 - 2019/10
N2 - This work proposes a parametric probabilistic approach to model damage accumulation using the double linear damage rule (DLDR) considering the existence of limited experimental fatigue data. A probabilistic version of DLDR is developed in which the joint distribution of the knee-point coordinates is obtained as a function of the joint distribution of the DLDR model input parameters. Considering information extracted from experiments containing a limited number of data points, an uncertainty quantification framework based on the Maximum Entropy Principle and Monte Carlo simulations is proposed to determine the distribution of fatigue life. The proposed approach is validated using fatigue life experiments available in the literature.
AB - This work proposes a parametric probabilistic approach to model damage accumulation using the double linear damage rule (DLDR) considering the existence of limited experimental fatigue data. A probabilistic version of DLDR is developed in which the joint distribution of the knee-point coordinates is obtained as a function of the joint distribution of the DLDR model input parameters. Considering information extracted from experiments containing a limited number of data points, an uncertainty quantification framework based on the Maximum Entropy Principle and Monte Carlo simulations is proposed to determine the distribution of fatigue life. The proposed approach is validated using fatigue life experiments available in the literature.
KW - Cumulative fatigue damage
KW - Double linear damage rule
KW - Limited data experiments
KW - Maximum Entropy Principle
KW - Uncertainty quantification
UR - http://www.scopus.com/inward/record.url?scp=85067385622&partnerID=8YFLogxK
U2 - 10.1016/j.ijfatigue.2019.06.011
DO - 10.1016/j.ijfatigue.2019.06.011
M3 - Article
AN - SCOPUS:85067385622
VL - 127
SP - 246
EP - 258
JO - International Journal of Fatigue
JF - International Journal of Fatigue
SN - 0142-1123
ER -