Finite element modeling for fatigue life prediction of RC beam strengthened with prestressed CFRP based on failure modes

2019 ◽  
Vol 226 ◽  
pp. 111289 ◽  
Author(s):  
Xinyan Guo ◽  
Yilin Wang ◽  
Peiyan Huang ◽  
Zhanbiao Chen
Keyword(s):  
Finite Element ◽  
Fatigue Life ◽  
Finite Element Modeling ◽  
Life Prediction ◽  
Failure Modes ◽  
Fatigue Life Prediction ◽  
Rc Beam ◽  
Element Modeling

The Effect of Intermetallic Compound in Solder Joint Fatigue Life Prediction Using Finite Element Modeling

2003 ◽  
Author(s):  
Mohammad Masum Hossain ◽  
Dereje Agonafer ◽  
Puligandla Viswanadham ◽  
Tommi Reinikainen
Keyword(s):  
Finite Element ◽  
Fatigue Life ◽  
Intermetallic Compound ◽  
Solder Joint ◽  
Finite Element Modeling ◽  
Life Prediction ◽  
Temperature Cycling ◽  
Fatigue Life Prediction ◽  
Element Modeling ◽  
Solder Joint Fatigue

The life-prediction modeling of an electronic package requires a sequence of critical assumptions concerning the finite element models. The solder structures accommodate the bulk of the plastic strain that is generated during accelerated temperature cycling due to the thermal expansion mismatch between the various materials that constitute the package. Finite element analysis is extensively used for simulating the effect of accelerated temperature cycling on electronic packages. There are a number of issues that need to be addressed to improve the current FEM models. One of the limitations inherent to the presently available models is the accuracy in property values of eutectic 63Sn/37Pb solder or other solder materials (i.e. 62Sn/36Pb/2Ag). Life prediction methodologies for high temperature solders (90Pb/10Sn, 95Pb/5Sn, etc.) or lead-free based inter-connects materials, are almost non-existent due to their low volume use or relative infancy. [1] Another major limitation for the models presently available is excluding the effect of intermetallic compound (Cu6Sn5, Cu3Sn) formation and growth between solder joint and Cu pad due to the reflow processes, rework and during the thermal aging. The mechanical reliability of these intermetallic compounds clearly influences the mechanical integrity of the interconnection. The brittle failures of solder balls have been identified with the growth of a number of intermetallic compounds both at the interfaces between metallic layers and in the bulk solder balls. In this paper, the effect of intermetallic compound in fatigue life prediction using finite element modeling is described. A Chip Scale Package 3D Quarter model is chosen to do the FE analysis. Accelerated temperature cycling is performed to obtain the plastic work due to thermal expansion mismatch between the various materials. Solder joint fatigue life prediction methodologies were incorporated so that finite element simulation results were translated into estimated cycles to failure. The results are compared with conventional models that do not include intermetallic effects. Conventionally available material properties are assumed for the eutectic 63Sn/37Pb solder and the intermetallic material properties. The importance of including intermetallic effect in finite element modeling will be discussed.

TTK Chitra tilting disc heart valve model TC2: An assessment of fatigue life and durability

2017 ◽  
Vol 231 (8) ◽  
pp. 758-765 ◽  
Author(s):  
NN Subhash ◽  
Adathala Rajeev ◽  
Sreedharan Sujesh ◽  
CV Muraleedharan
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Fatigue Life ◽  
Heart Valve ◽  
Life Prediction ◽  
Heart Valves ◽  
Failure Modes ◽  
Fatigue Life Prediction ◽  
Element Analysis ◽  
Valve Model

Average age group of heart valve replacement in India and most of the Third World countries is below 30 years. Hence, the valve for such patients need to be designed to have a service life of 50 years or more which corresponds to 2000 million cycles of operation. The purpose of this study was to assess the structural performance of the TTK Chitra tilting disc heart valve model TC2 and thereby address its durability. The TC2 model tilting disc heart valves were assessed to evaluate the risks connected with potential structural failure modes. To be more specific, the studies covered the finite element analysis–based fatigue life prediction and accelerated durability testing of the tilting disc heart valves for nine different valve sizes. First, finite element analysis–based fatigue life prediction showed that all nine valve sizes were in the infinite life region. Second, accelerated durability test showed that all nine valve sizes remained functional for 400 million cycles under experimental conditions. The study ensures the continued function of TC2 model tilting disc heart valves over duration in excess of 50 years. The results imply that the TC2 model valve designs are structurally safe, reliable and durable.

A Hybrid Finite Element Modeling: Artificial Neural Network Approach for Predicting Solder Joint Fatigue Life in Wafer-Level Chip Scale Packages

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Zhiwen Chen ◽  
Zhao Zhang ◽  
Fang Dong ◽  
Sheng Liu ◽  
Li Liu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Finite Element ◽  
Fatigue Life ◽  
Solder Joint ◽  
Finite Element Modeling ◽  
Life Prediction ◽  
Electronic Devices ◽  
Fatigue Life Prediction ◽  
Wafer Level

Abstract Fatigue life prediction of electronic devices is of great importance in both research and industry. Traditionally, fatigue tests and finite element modeling (FEM) are the two main methods. This paper presents a new hybrid approach (FEM combined with artificial neural network, (ANN)) for fatigue life prediction. Finite element models on wafer-level chip scale packages (WLCSP) with different chip thickness, PCB thickness, and solder joint pitches were created to evaluate the effect of structure parameters on the increase in maximum creep strain under thermal fatigue load. Modified Coffin–Manson equation was then employed to estimate the corresponding fatigue life. ANNs were built, and then trained, tested, and optimized with the datasets from modeling to predict increase in maximum creep strain and fatigue life. For the ANN built for strain prediction, prediction accuracy of the optimal network was 97% in accuracy tests and 93% in generalization tests. Accuracy of the other ANN for predicting fatigue life was 94.2% in accuracy tests and 88% in generalization tests. This hybrid method shows very promising application in fatigue life estimation of electronic devices which requires much less time and lower cost.

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