Post-fatigue life prediction of glare subjected to low-velocity impact

Document Type : Article

Authors

Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran

Abstract

In this study, at first, the dynamic progressive failure of Glass-Fiber-Reinforced aluminum laminates (GLARE) under low-energy impact with intra laminar damage models implementing strain-based damage evolution laws, Puck failure criteria using ABAQUS-VUMAT,were modeled. For interface delamination, bilinear cohesive model; and for aluminum layers the Johnson-Cook model was implemented;and the fatigue life of the fiber metal laminates of GLARE subjected to impact was obtained; and the numerical and experimental results of the model were compared with each other. With regard to the very good match betweenthe numerical and experimental results, the results of the finite element model were generalized and expanded, and with the use of the multilayer neural network, the numerical model was extracted and then, by applying the meta-innovative algorithm, the maximum fatigue life of GLARE was determined atthe highest level with very low-velocity impact,and the best configuration of three-layer GLARE was selected.The findings indicated that the best configuration of hybrid composite GLARE based on conventional commercial laminates that can tolerate low-velocity impacts with 18J impact energy and a 349MPa fatigue load with a frequency of 10Hz was [Al/0-90-90-0/Al/0-90-0/Al/0-90-90-0/Al] with 13016 cycle lifetime.

Keywords


References
1. Sedaghat, A., Alitavoli, M., Darvizeh, A., et al.
Mathematical, numerical and experimental investigation
of low energy impact on glass ber reinforced
aluminum laminates", J. of Mechanics of Continua
and Mathematical Sciences, 14(3), pp. 83{93 (2019).
2. Alderliesten, R.C. Fatigue crack propagation and
delamination growth in the glare", Ph.D. Thesis, Delft
University of Technology, Delft (2005).
3. Dadej, K., Surowska, B., and Bienias, J. Isostrain
elastoplastic model for prediction of static strength and
fatigue life of ber metal laminates", Int. J. of Fatigue,
110, pp. 31{41 (2018).
4. Park, S.Y., Choi, W.J., Choi, C.H., et al. E ect of
drilling parameters on hole quality and delamination of
hybrid GLARE laminate", Composite Structures, 185,
pp. 684{698 (2017).
5. Li, H., Xu, Y., Hua, X., et al. Bending failure mechanism
and
exural properties of GLARE laminates with
di erent stacking sequences", Composite Structures,
187, pp. 354{363 (2017).
6. Zarei, H., Brugo, T., Belcari, J., et al. Low velocity
impact damage assessment of GLARE ber-metal
laminates interleaved by Nylon 6,6 nano ber mats",
Composite Structures, 167, pp. 123{131 (2017).
7. Kamocka, M., Zglinicki, M., and Mania, R.J. Multimethod
approach for FML mechanical properties prediction",
Composites Part B, 91, pp. 135{143 (2016).
8. Liao, B.B. and Liu, P.F. Finite element analysis of dynamic
progressive failure properties of GLARE hybrid
laminates under low-velocity impact", J. Composite
Materials, 50, pp. 1{14 (2017).
9. Volt, A., Glare History of the Development of a
New Aircraft Material, pp. 35{45, Dordrecht, Kluwer
Academic Publishers Netherlands (2001).
10. Sadighi, M. and Alderliesten, R.C. Impact resistance
of ber metal laminates", Int. J. of Impact Engineering,
49, pp. 77{90 (2012).
11. Wu, G.C. and Yang, J.M. The mechanical behavior of
GLARE laminates for aircraft structures", J Minerals
Metals Mater, 57, pp. 72{79 (2005).
12. Liang, Z.Q. and Xue, Y.D. Performance and application
of GLARE laminates in A380 Airliner. Glass
FRP/CM", Int. J. Composite, 04, pp. 49{51 (2005).
A. Sedaghat et al./Scientia Iranica, Transactions B: Mechanical Engineering 28 (2021) 305{315 315
13. Liang, Z.Q. and Wu, W.J. Comparison of GLARE
laminates with aluminum alloy and its application",
J. of the Minerals, Metals & Materials Society, 57(1),
pp. 72{79 (2006).
14. Syed, A.K., Zhang, X., Mo att, J.E., et al. Fatigue
performance of bonded crack retarders in the presence
of cold worked holes and interference- t fasteners", Int.
J. of Fatigue, 105, pp. 111{118 (2017).
15. Al-Azzawi, A.S., Mc Crory, J., Kawashita, L.F., et
al. Buckling and postbuckling behaviour of glare
laminates containing splices and doublers. Part 1:
Instrumented tests", Composite Structures, 176, pp.
1158{1169 (2017).
16. Wang, W., Rans, C., and Benedictus, R. Analytical
prediction model for non-symmetric fatigue crack
growth in bre metal laminates", Int. J. of Fatigue,
103, pp. 546{556 (2017).
17. Marissen, R. Fatigue crack growth in ARALL, a
hybrid aluminium-aramid composite material, crack
growth mechanisms and quantitative predictions of
the crack growth rate", Dissertation for the Doctoral
Degree, Delft University of Technology (1988).
18. Lapczyk, I. and Hurtado, J.A. Progressive damage
modeling in ber-reinforced materials", Composites
Part A, 38, pp. 2333{2341 (2007).
19. Graupe, D. and Kordilewski, H. A novel largememory
neural network as an aid in medical diagnosis",
IEEE Trans. on Information Technology in
Biomedicine, 5(3), pp. 202{209 (2001).
20. Hagan, M.T. and Menhaj M.B. Training feedforward
networks with the Marquardt algorithm", IEEE Trans.
on Neural Networks, 5, pp. 989{993 (1994).
21. Azadeh, A., Saberi, M., TavakkoliMoghadam, R.,
and Javanmardi, L. An integrated Data envelopment
analysis-arti cial neural network-rough set algorithm
for assessment of personnel eciency", Expert Systems
with Applications, 38, pp. 1364{1373 (2011).
22. Haykin, S., Neural Networks: A Comprehensive Foundation,
pp. 134{168, Prentice Hall, Dehli, India (1990).
23. Lei, Y., He, Z., and Zi, Y. Application of an intelligent
classi cation method to mechanical fault diagnosis",
Expert Systems with Applications, 36, pp. 9941{9948
(2009).
24. Li, B., Chow, M.Y., Tipsuwan, Y., et al. The neuralnetwork-
based motor rolling bearing fault diagnosis",
IEEE Tran. on Industrial Electronics, 47, pp. 1060{
1069 (2000).
25. Soutis, C., Mohamed, G., and Hodzic, A. Modelling
the structural response of GLARE panels to blast
load", Composite Structures, 94, pp. 267{276 (2011).
26. Donadon, M.V., Iannucci, L., Falzon, B., et al.
A progressive failure model for composite laminates
subjected to low-velocity impact damage", Composite
Structures, 86(12), pp. 1232{1252 (2008).
27. Apruzzese, P. and Falzon B. Numerical analysis of
complex failure mechanisms in composite panels", 16th
International Conference on Composite Materials, Kyoto,
Japan, pp. 234{246 (2007).
28. Wang, W., Rans, C., Zhang, Z., and Benedictus,
R. Prediction methodology for fatigue crack growth
behaviour in bre metal laminates subjected to tension
and pin loading", Composite Structures, 185, pp. 176{
182 (2017).
29. Seyed Yaghoubi, A. and Liaw, B. Thickness in
uence
on ballistic impact behaviors of GLARE 5 ber-metal
laminated beams: Experimental and numerical studies",
Composite Structures, 94, pp. 2585{2598 (2012).