Accelerated multiscale space–time finite element simulation and application to high cycle fatigue life prediction

2016 ◽  
Vol 58 (2) ◽  
pp. 329-349 ◽  
Author(s):  
Rui Zhang ◽  
Lihua Wen ◽  
Sam Naboulsi ◽  
Thomas Eason ◽  
Vijay K. Vasudevan ◽  
...  
Keyword(s):  
Finite Element ◽  
Fatigue Life ◽  
Finite Element Simulation ◽  
Life Prediction ◽  
High Cycle Fatigue ◽  
Space Time ◽  
Fatigue Life Prediction ◽  
Cycle Fatigue ◽  
Element Simulation

Application of Artificial Neural Network for Fatigue Life Prediction

2005 ◽  
Vol 297-300 ◽  
pp. 96-101
Author(s):  
Ishak Abdul Azid ◽  
Lee Kor Oon ◽  
Ong Kang Eu ◽  
K.N. Seetharamu ◽  
Ghulam Abdul Quadir
Keyword(s):  
Neural Network ◽  
Finite Element ◽  
Fatigue Life ◽  
Solder Joint ◽  
Finite Element Simulation ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Element Simulation ◽  
Parametric Studies ◽  
Solder Joint Fatigue

An extensively published and correlated solder joint fatigue life prediction methodology is incorporated by which finite element simulation results are translated into estimated cycles to failure. This study discusses the analysis methodologies as implemented in the ANSYSTM finite element simulation software tool. Finite element models are used to study the effect of temperature cycles on the solder joints of a flip chip ball grid array package. Through finite element simulation, the plastic work or the strain-energy density of the solder joints are determined. Using an established methodology, the plastic work obtained through simulation is translated into solder joint fatigue life [1]. The corresponding results for the solder joint fatigue life are used for parametric studies. Artificial Neural Network (ANN) has been used to consolidate the parametric studies.

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