Investigation of self-heating and life prediction in CFRP laminates under cyclic shear loading condition based on the infrared thermographic data

•The self-heating phenomenon of CFRP laminates subjected to cyclic shear loading is investigated.•The heat generation per unit volume during fatigue is quantitatively studied.•The heat caused by internal frictions and irreversible changes is separately considered.•A practical methodology is develope...

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Veröffentlicht in:Engineering fracture mechanics 2020-04, Vol.229, p.106971, Article 106971
Hauptverfasser: Huang, Jia, Garnier, Christian, Pastor, Marie-Laetitia, Gong, Xiaojing
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Sprache:eng
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Zusammenfassung:•The self-heating phenomenon of CFRP laminates subjected to cyclic shear loading is investigated.•The heat generation per unit volume during fatigue is quantitatively studied.•The heat caused by internal frictions and irreversible changes is separately considered.•A practical methodology is developed to predict S-N curve with good accuracy. In this work, the shear fatigue behavior of a Carbon Fiber Reinforced Polymer (CFRP) composite has been studied by carrying out tensile test on the laminates [±45°]8. The amount of heat generation rate per unit of volume within CFRP laminate under various cyclic loading condition is investigated by combining experimentation and numerical simulation. The generated heat during fatigue testing is classified into two parts – induced by internal frictions and induced by irreversible changes in CFRP laminates (delamination, crack propagation, …). It is considered that most of the fatigue damage is related to the irreversible changes while internal frictions do not cause any damage. The investigation shows that the total amount of heat generation related to damage is nearly independent of loading stresses. Based on this phenomenon, a rapid methodology is proposed to predict the S-N curve in a short time by measuring the temperature evolution curves under cyclic loading and conducting one or two specimens until final fracture. The prediction area is mostly inside the 95% confidence intervals of the experimental data, which shows a good agreement with the traditional fatigue test.
ISSN:0013-7944
1873-7315
DOI:10.1016/j.engfracmech.2020.106971