Combined peridynamic theory and kinetic theory of fracture for solder joint fatigue life prediction

E. Madenci, C. Diyaroglu, Y. Zhang, F. Baber, I. Guven

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study presents an approach that combines the kinetic theory of fracture with peridynamic theory to predict solder joint fatigue life in electronic packages. It is applied to two different package types whose measured life values are reported in literature. The nonlinear finite element analyses of the global package model and sub-model of the critical joint provide the boundary conditions for the peridynamic model. Both the finite element and peridynamic analyses are performed in the ANSYS framework by using the available elements and options. This new approach captures the experimentally observed damage topology in a solder joint. Although the initial and final fatigue life predictions are acceptable, the predictions can certainly be improved with accurate values of activation energy and activation volume for materials employed in the package.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 70th Electronic Components and Technology Conference, ECTC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages236-248
Number of pages13
ISBN (Electronic)9781728161808
DOIs
StatePublished - Jun 2020
Event70th IEEE Electronic Components and Technology Conference, ECTC 2020 - Orlando, United States
Duration: Jun 3 2020Jun 30 2020

Publication series

NameProceedings - Electronic Components and Technology Conference
Volume2020-June
ISSN (Print)0569-5503

Conference

Conference70th IEEE Electronic Components and Technology Conference, ECTC 2020
CountryUnited States
CityOrlando
Period6/3/206/30/20

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Combined peridynamic theory and kinetic theory of fracture for solder joint fatigue life prediction'. Together they form a unique fingerprint.

Cite this