Modeling and optimization of dynamic-mechanical properties of hybrid polymer composites by multiple nonlinear neuro-regression method

Abstract

The purpose of this research is to improve the dynamic-mechanical properties of the polypro-pylene filled by artichoke stem (AS) particles and wollastonite (W) in different weight frac-tions. The effect of weight ratios of fillers in polypropylene was mathematically modeled using the data obtained as a result of the experimental work. In the modeling phase, multiple nonlin-ear neuro-regression analysis was used. In this context, proposed linear and nonlinear models have been examined by performing R2training, R2adjusted, R2testing, and boundedness check. The models that satisfy these four criteria were selected as the objective functions for the optimiza-tion phase. Finally, Modified Differential Evolution Algorithm was used to obtain maximum storage modulus and loss modulus by adjusting weight percent ratio of artichoke stem particle and wollastonite. The experimental results and the modeling optimization results showed that when the polypropylene-artichoke stem particle-wollastonite hybrid polymer composite was used instead of other non-hybrid polymer composite, the storage modulus and the loss mod-ulus improved by approximately 40%.

Keywords

• Multiple Nonlinear Neuroregression
• Design and Optimization
• Hybrid Polymer Composites
• Modeling
• Storage Modulus
• Loss Modulus

References

1. REFERENCES
2. [1] Mu B, Tang W, Liu T, Hao X, Wang Q, Ou R, et al. Comparative study of high-density polyethylene-based biocomposites reinforced with various agricultural residue fibers. Ind Crops Prod 2021;172:114053. [CrossRef]
3. [2] Atagür M, Kaya N, Uysalman T, Durmuşkahya C, Sarikanat M, Sever K, et al. A detailed characterization of sandalwood-filled high-density polyethylene composites. J Thermoplast Compos Mater 2020;089270572093915. [CrossRef]
4. [3] Nourbakhsh A, Ashori A, Ziaei Tabari H, Rezaei F. Mechanical and thermo-chemical properties of wood-flour/polypropylene blends. Polym Bull 2010;65:691–700. [CrossRef]
5. [4] Lee SY, Kang IA, Doh GH, Yoon HG, Park BD, Wu Q. Thermal and mechanical properties of wood flour/talc-filled polylactic acid composites: Effect of filler content and coupling treatment. J Thermoplast Compos Mater 2008;21:209–223. [CrossRef]
6. [5] Sever K, Yılmaz M. Evaluation of Mechanical and Thermal Properties of Artichoke Filled Polypropylene Composites: Influence of Wollastonite Hybridization. Emerg Mater Res 2020;9:1–6. [CrossRef]
7. [6] Goyanes SN, Marconi JD, König PG, Martin MD, Mondragon I. Dynamical properties of epoxy composites filled with quartz powder. J Alloys Compd 2000;310:374–377. [CrossRef]
8. [7] Altin A. A comparative study on optimization of machining parameters by turning aerospace materials according to Taguchi method. Int J Simul Multisci Des Optim 2017;8. [CrossRef]

9. [8] Altin A. The effect of the cutting speed on the cutting forces and surface finish when milling chromium 210 cr12 steel hardfacings with uncoated cutting tools. Mater Technol 2014;48:373–378.
10. [9] Madenci E, Onuralp Özkılıç Y, Gemi L. Buckling and free vibration analyses of pultruded GFRP laminated composites: Experimental, numerical and analytical investigations. Compos Struct 2020;254:112806. [CrossRef]
11. [10] Rama Mohan Rao A, Arvind N. A scatter search algorithm for stacking sequence optimisation of laminate composites. Compos Struct 2005;70:383–402. [CrossRef]
12. [11] Savran M, Aydin L. Stochastic optimization of graphite-flax/epoxy hybrid laminated composite for maximum fundamental frequency and minimum cost. Eng Struct 2018;174:675–687. [CrossRef]
13. [12] Hosseinzadeh Y, Jalili S, Khani R. Investigating the effects of flax fibers application on multi-objective optimization of laminated composite plates for simultaneous cost minimization and frequency gap maximization. J Build Eng 2020;32:101477. [CrossRef]
14. [13] Deveci HA, Aydin L, Seçil Artem H. Buckling optimization of composite laminates using a hybrid algorithm under Puck failure criterion constraint. J Reinf Plast Compos 2016;35:1233–1247. [CrossRef]
15. [14] Mohamed O, Masood S, Bhowmik J. Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC- ABS. Materials 2016;9:895. [CrossRef]
16. [15] Bozaci E. Optimization of the alternative treatment methods for Ceiba pentandra (L.) Gaertn (kapok) fiber using response surface methodology. J Text Inst 2019;110:1404–1414. [CrossRef]
17. [16] Savran M, Aydin L, Deveci HA, Gültürk E. Maximization of buckling resistance for lightweight vegetable-based hybrid laminated composites combined with synthetic fibers. In: Jawaid M, Khan A, editors. Vegetable Fiber Composites and their Technological Applications. Composites Science and Technology. Singapore: Springer Singapore; 2021. p. 81–105. [CrossRef]
18. [17] Megahed M, Abo-bakr RM, Mohamed SA. Optimization of hybrid natural laminated composite beams for a minimum weight and cost design. Compos Struct 2020;239:111984. [CrossRef]
19. [18] Öndürücü A, Muzoğlu M. Doğal Lif Takviyeli Kompozitlerin Burkulma Davranışına Deniz Suyunun Etkisi. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 2019;30–39. [CrossRef]
20. [19] Chaudhuri S, Chakraborty R, Bhattacharya P. Optimization of biodegradation of natural fiber (Chorchorus capsularis): HDPE composite using response surface methodology. Iran Polym J 2013;22:865–875. [CrossRef]
21. [20] Rao PD, Kiran CU, Prasad KE. Modeling elastic constants of keratin-based hair fiber composite using response surface method and optimization using grey Taguchi method. In: Venkata Rao R, Taler J, editors. Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing. Vol. 949. Singapore: Springer; 2020. [CrossRef]
22. [21] Yaghoobi H, Fereidoon A. Modeling and optimization of tensile strength and modulus of polypropylene/kenaf fiber biocomposites using Box-Behnken response surface method. Polym Compos 2018;39:E463–E479. [CrossRef]
23. [22] Polatoğlu İ, Aydin L, Nevruz BÇ, Özer S. A Novel Approach for the Optimal Design of a Biosensor. Anal Lett 2020;53:1428–1445. [CrossRef]