Fast and synergetic fatigue life prediction of short fiber reinforced polymer composites from monotonic and cyclic loading behavior

Grasping the fatigue behavior of short fiber reinforced polymers (SFRP) is difficult due to varying microstructures throughout the material cause variations in material properties. To efficiently predict the stress versus number of cycles to failure (S-N) curve of SFRP featuring any microstructure, a synergetic framework stemming from quasi-static damage and cyclic modulus degradation is proposed. Firstly, well-designed tests are conducted, and an intrinsic relationship between the modulus degradation and the fatigue life is captured. Secondly, the microstructure-independent relationships among the first cycle damage (FCD), the stable relative modulus degradation rate (SRMDR), and the fatigue life are deduced and demonstrated from multi-scale perspectives. Finally, FCD-based and SRMDR-based approaches are adopted to generate S-N data in the low-life and high-life regions, respectively. Results indicate that the synergistic method retains the efficiency of the individual method and further reduces the error by more than 80%. Moreover, discoveries herein can equip engineers with powerful S-N prediction tools in practice and reveal the fatigue mechanism of SFRP.

Automated summary

To predict the stress versus number of cycles to failure (S-N) curve of short fiber reinforced polymers (SFRP) with any microstructure, a synergetic framework is proposed, incorporating quasi-static damage and cyclic modulus degradation. Well-designed tests reveal an intrinsic relationship between modulus degradation and fatigue life. Microstructure-independent relationships among first cycle damage (FCD), stable relative modulus degradation rate (SRMDR), and fatigue life are deduced and demonstrated. The FCD-based and SRMDR-based approaches generate S-N data in the low-life and high-life regions, respectively, reducing the error by more than 80%.