In situ computed tomography for the characterization of the fatigue damage development in glass fiber-reinforced polyurethane

2019 ◽  
Vol 61 (9) ◽  
pp. 821-828 ◽  
Author(s):  
Daniel Hülsbusch ◽  
Selim Mrzljak ◽  
Frank Walther
2017 ◽  
Vol 742 ◽  
pp. 629-635 ◽  
Author(s):  
Daniel Huelsbusch ◽  
Michael Jamrozy ◽  
Selim Mrzljak ◽  
Frank Walther

In order to optimize resource efficiency, glass fiber-reinforced polymers (GFRP) have been implemented in recent years in a wide range of applications of transport industries. In this context, GFR-epoxy (GFR-EP) is currently being used mainly because of their sufficiently investigated properties and production processes. Polyurethane (PU), however, shows advantages in terms of energy efficiency and damage tolerance. The aim of this study is the characterization of the fatigue behavior of GFR-PU by stepwise exploration of damage development on microscopic level. Therefore, multiple amplitude and constant amplitude tests have been carried out. Hysteresis and temperature measurements were applied in order to investigate the damage processes and correlated with in situ computed tomography (CT) in intermitting tests. The damage development and mechanisms could be characterized and separated. The results confirm known GFRP damage characteristics, whereas also material-specific peculiarities regarding crack development could be revealed.


Polymers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 2250
Author(s):  
Mohammad Amjadi ◽  
Ali Fatemi

Short glass fiber-reinforced (SGFR) thermoplastics are used in many industries manufactured by injection molding which is the most common technique for polymeric parts production. Glass fibers are commonly used as the reinforced material with thermoplastics and injection molding. In this paper, a critical plane-based fatigue damage model is proposed for tension–tension or tension–compression fatigue life prediction of SGFR thermoplastics considering fiber orientation and mean stress effects. Temperature and frequency effects were also included by applying the proposed damage model into a general fatigue model. Model predictions are presented and discussed by comparing with the experimental data from the literature.


2021 ◽  
Author(s):  
Chinnappan Balaji Ayyanar ◽  
S. K. Pradeep Mohan ◽  
C. Bharathiraj ◽  
Sanjay Rangappa ◽  
Suchart Siengchin

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