Numerical and experimental study on CFRP structure optimization for coefficient of thermal expansion

Numerical and experimental study on CFRP structure optimization for coefficient of thermal expansion

Автор: Pasechnik K.A., Obvertkin I.V., Vlasov A.Y.

Журнал: Вестник Пермского национального исследовательского политехнического университета. Механика @vestnik-pnrpu-mechanics

Статья в выпуске: 3, 2023 года.

Бесплатный доступ

This paper explores the optimization macrostructure to reach a stable low coefficient of thermal expansion αx of a composite with carbon fibers. To limit the search area, a necessary condition for the existence of αx local minima is proposed, expressed in terms of the radii of hyperspheres in the design space of the angular orientation of the layers transformed by the PСA algorithm. The analysis of the structure variants characterized by low αx shows different sustainability to lamina properties variability. Multi-criteria optimization was carried out. The objective functions are expectation E(αx) and variance Var(αx). The analysis of Pareto fronts and probability density functions make it possible to estimate the reachability of the calculated αx under given conditions of lamina properties variability. The reduction variance opportunity of αx distribution by modifying the polymer matrix with MWCNTs under conditions of reinforcing fibers disorientation and lamina properties variability is investigated. The microstructure modification of the polymer composite material allows to reduce the Var(αx) by 91.61 % with a volume ratio of MWCNTs up to 1 %. Requirement thermomechanical properties are reached by determining the orientation of anisotropic layers. Based on the obtained optimal structures, specimens of CFRP with 0, 1 and 2 vol.% MWCNTs were made. Scanning electron microscopy using FE-SEM Hitachi S-5500 was performed to check the uniformity of distribution and compatibility of the epoxy matrix and MWCNTs. The measurement of αx is determined using a TAInstrumentsQ400 thermomechanical analyzer. Measured αx of specimens is in the range from 6.2·10-8 to 1.98·10-7 1/K. The structure optimization approach proposed in this paper makes it possible to obtain a set of solutions with a consistently low αx in the range up to 1·10-7 1/K. The transformation of the design space of the layers’ orientation angles and the limitation of the search area allowed to reduce the range of solutions under consideration by 83.9 %.

Еще

Optimization of macrostructure of hybrid composite, stable low coefficient of thermal expansion of composite, mwcnts, pca, nsga-ii, mori - tanaka model

Короткий адрес: https://sciup.org/146282671

IDR: 146282671   |   DOI: 10.15593/perm.mech/2023.3.10

Список литературы Numerical and experimental study on CFRP structure optimization for coefficient of thermal expansion

  • Anaya L., Vicente W., Pavanello R. Minimization of the Effective Thermal Expansion Coefficient of Composite Material Using a Multi-scale Topology Optimization Method. EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization / ed. Rodrigues H.C. et al. Cham: Springer International Publishing, 2019, pp. 1055-1060. https://doi.org/10.1007/978-3-319-97773-7_91
  • Zhengchun D. et al. Design and application of composite platform with extreme low thermal deformation for satellite. Compos. Struct. Elsevier Ltd, 2016, Vol. 152, pp. 693-703. https://doi.org/10.1016/j.compstruct.2016.05.073
  • Catapano A., Desmorat B., Vannucci P. Stiffness and Strength Optimization of the Anisotropy Distribution for Laminated Structures. J. Optim. Theory Appl. 2015, Vol. 167, № 1, pp. 118-146. https://doi.org/10.1007/s10957-014-0693-5
  • Kim D. et al. Topology optimization of functionally graded anisotropic composite structures using homogenization design method. Comput. Methods Appl. Mech. Eng. Elsevier B.V., 2020, Vol. 369, pp. 113220. https://doi.org/10.1016/jxma.2020.113220
  • Schaedler de Almeida F. Optimization of laminated composite structures using harmony search algorithm. Compos. Struct. Elsevier Ltd, 2019, Vol. 221, pp. 110852. https://doi.org/10.1016/j. compstruct.2019.04.024
  • Peng X. et al. Multiple-scale uncertainty optimization design of hybrid composite structures based on neural network and genetic algorithm. Compos. Struct. Elsevier Ltd, 2020, Vol. 262, pp. 113371. https://doi.org/10.1016/jxompstruct2020.113371
  • Hao P. et al. Efficient reliability-based design optimization of composite structures via isogeometric analysis // Reliab. Eng. Syst. Saf. Elsevier Ltd, 2021, Vol. 209, pp. 107465. https://doi.org/10.1016Zj.ress.2021.107465
  • das Neves Carneiro G., Conceiçâo Antonio C. Dimensional reduction applied to the reliability-based robust design optimization of composite structures. Compos. Struct. Elsevier Ltd, 2021, Vol. 255, pp. 112937. https://doi.org/10.1016/jxompstruct.2020.112937
  • Sigmund O., Torquato S. Design of materials with extreme thermal expansion using a three-phase topology optimization method. J. Mech. Phys. Solids. Elsevier Ltd, 1997, Vol. 45, № 6, pp. 1037-1067. https://doi.org/10.1016/S0022-5096(96)00114-7
  • Q.S. Sun, Y.D. Feng, J. Guo, et al. High performance epoxy resin with ultralow coefficient of thermal expansion cured by conformation-switchable multi-functional agent. Chemical Engineering Journal, 2022, Vol. 450, pp. 138295. https://doi.org/10.1016/jxej.2022.138295
  • S.R. Wang, Z.Y. Liang, P. Gonnet, Y.H. Liao, B. Wang, C. Zhang. Effect of nanotube functionalization on the coefficient of thermal expansion of nanocomposites. Adv. Funct. Mater., 2007, 17(1), pp. 87-92. https://doi.org/10.1002/adfm.200600760
  • J.K. Ma, T.Y. Shang, L.L. Ren, Y.M. Yao, T. Zhang, J.Q. X ie, B.T. Zhang, X.L. Zeng, R. Sun, J.B. Xu, C.P. Wong. Through-plane assembly of carbon fibers into 3D skeleton achieving enhanced thermal conductivity of a thermal interface material. Chem. Eng. J., 2020, 380, p. 8. https://doi.org/10.1016/jxej.2019.122550
  • Obvertkin, I., K. Pasechnik, h A. Vlasov. The potential of using SWCNTs, MWCNTs and CNFs capable of increasing the composite material dimensional and technological stability as modifiers of a polymer matrix. PNRPU Mechanics Bulletin, 2021, № 4, pp. 98-110. https://doi.org/10.15593/perm.mech/202L4.10
  • K.C. Yung, B.L. Zhu, T.M. Yue, C.S. Xie. Effect of the Filler Size and Content on the Thermomechanical Properties of Particulate Aluminum Nitride Filled Epoxy Composites. J. Appl. Polym. Sci., 2010, 116 (1), pp. 225-236. https://doi.org/10.1002/app.31431
  • C.J. Huang, S.Y. Fu, Y.H. Zhang, B. Lauke, L.F. Li, L. Ye. Cryogenic properties of SiO2/epoxy nanocomposites. Cryogenics, 2005, 45 (6), pp. 450-454. https://doi.org/10.1016/jxryogenics.2005.03.003
  • Ghasemi A.R., Mohammadi M.M., Mohandes M. The role of carbon nanofibers on thermo-mechanical properties of polymer matrix composites and their effect on reduction of residual stresses. Compos Part B Eng, 2015, no. 77, pp. 519-27. https://doi.org/10.1016/jxompositesb.2015.03.065
  • Shokrieh M.M., Akbari S., Daneshvar A. Reduction of residual stresses in polymer composites using nano-additives. Residual Stress Compos Mater, 2014, pp. 350-73, https://doi.org/10.1016/B978-0-12-818817-0.00013-5
  • Pan J., Bian L. A physics investigation for influence of carbon nanotube agglomeration on thermal properties of composites. Mater ChemPhys, 2019, №. 236, https://doi.org/10.1016/j.matchemphys.2019.121777
  • Green K.J. et al. Multiscale fiber reinforced composites based on a carbon nanofiber/epoxy nanophased polymer matrix: Synthesis, mechanical, and thermomechanical behavior. Compos. Part A Appl. Sci. Manuf. Elsevier, 2009, Vol. 40, № 9, pp. 14701475. https://doi.org/10.1016/jxompositesa.2009.05.010
  • Fu S. et al. Some basic aspects of polymer nanocomposites: A critical review. NanoMater. Sci. ElsevierBV, 2019. Vol. 1, № 1, pp. 2-30. https://doi.org/10.1016/j.nanoms.2019.02.006
  • Shirasu K. et al. Negative axial thermal expansion coefficient of carbon nanotubes: Experimental determination based on measurements of coefficient of thermal expansion for aligned carbon nanotube reinforced epoxy composites. Carbon N. Y. Elsevier Ltd, 2015, Vol. 95, pp. 904-909. https://doi.org/10.1016/j. carbon.2015.09.026
  • J.C. Lin, P. Tong, K. Zhang, H.Y. Tong, X.G. Guo, C. Yang , Y. Wu, M. Wang, S. Lin, L. Chen, W.H. Song, Y.P. Sun. Colossal negative thermal expansion with an extended temperature interval covering room temperature in fine-powdered Mn098CoGe. Appl. Phys. Lett., 2016, 109 (24), p. 5. https://doi.org/10.1063/L4972234
  • V.K. Thakur, Y.Z. Li, H.C. Wu, M.R. Kessler. Synthesis, characterization, and functionalization of zirconium tungstate (ZrW2O8) nano-rods for advanced polymer nanocomposites. Polym. Adv. Technol, 2017, 28 (11), pp. 1375-1381. https://doi.org/10.1002/pat.4014
  • T.A. Mary, J.S.O. Evans, T. Vogt, A.W. Sleight. Negative Thermal Expansion from 0.3 to 1050 Kelvin in ZrW2O8, Science, 1996, 272, p. 90. https://doi.org/10.1126/science.272.5258.90
  • B.K. Greve, K.L. Martin, P.L. Lee, P.J. Chupas, K.W. Ch apman, A.P. Wilkinson. Pronounced Negative Thermal Expansion from a Simple Structure: Cubic ScF3. J. Am. Chem. Soc., 2010, 132, p. 15496. https://doi.org/10.1021/ja106711v
  • Zheng, X., Kubozono, H., Yamada, H. et al. Giant negative thermal expansion in magnetic nanocrystals. Nature Nanotech 3, 724726 (2008). https://doi.org/10.1038/nnano.2008.309
  • X. Chu, Z. Wu, C. Huang, R. Huang, Y. Zhou, L. Li. ZrW2O8-doped epoxy as low thermal expansion insulating materials for superconducting feeder system. Cryogenics, 2012, 52(12), pp. 638641. https://doi.org/10.1016/jxryogenics.2012.04.016
  • P. Badrinarayanan, M. Rogalski, H. Wu, X. Wang, W. Yu , M.R. Kessler. Epoxy Composites Reinforced with Negative-CTE ZrW2O8 Nanoparticles for Electrical Applications. Macromol. Mater. Eng., 2013, 298 (2), pp. 136-144.
  • Y.Y. Zhao, F.X. Hu, L.F. Bao, J. Wang, H. Wu, Q.Z. Hua ng, R.R. Wu, Y. Liu, F.R. Shen, H. Kuang, M. Zhang, W.L. Zuo, X. Q. Zheng, J.R. Sun, B.G. Shen. Giant Negative Thermal Expansion in Bonded MnCoGe-Based Compounds with Ni2In-Type Hexagonal Structure. J. Am. Chem. Soc., 2015, 137 (5), pp. 17461749. https://doi.org/10.1002/mame.201100417
  • L.A. Neely, V. Kochergin, E.M. See, H.D. Robinson. Negative thermal expansion in a zirconium tungstate/epoxy composite at low temperatures. J. Mater. Sci., 2014, 49 (1), pp. 392-396. https://doi.org/10.1007/s10853-013-7716-8
  • J. Arvanitidis, K. Papagelis, S. Margadonna, K. Prassides , A.N. Fitch. Temperature-induced valence transition and associated lattice collapse in samarium fulleride. Nature, 2003, 425, p. 599. https://doi.org/10.1038/nature01994
  • K. Shirasu, A. Nakamura, G. Yamamoto, T. Ogasawara, Y . Shimamura, Y. Inoue, T. Hashida. Potential use of CNTs for production of zero thermal expansion coefficient composite materials: An experimental evaluation of axial thermal expansion coefficient of CNTs using a combination of thermal expansion and uniaxial tensile tests. Compos. Pt. A-Appl. Sci. Manuf., 95 (2017), pp. 152-160. https://doi.org/10.10167j.compositesa.2016.12.027
  • R.P. Zhu, C.T. Sun. Effects of Fiber Orientation and Elastic Constants on Coefficients of Thermal Expansion in Laminates. Mech. Adv. Mater. Struct., 10 (2) (2003), pp. 99-107. https://doi.org/10.1080/15376490306733
  • Yoon KJ, Kim J-S. Prediction of Thermal Expansion Properties of Carbon/Epoxy Laminates for Temperature Variation. Journal of Composite Materials. 2000;34(2):90-100. https://doi.org/10.1177/002199830003400201.
  • Polymer nanocomposites. MRS Bull, 2007, № 32, pp. 314-319. https://doi.org/10.1557/mrs2007.229.
  • Chang T., Gao H. Size-dependent elastic properties of a single-walled carbon nanotube via a molecular mechanics model. J MechPhys Solids, 2003, №. 51, pp. 1059-74. https://doi.org/10.1016/S0022-5096 .
  • J. Blank and K. Deb, pymoo: Multi-Objective Optimization in Python. IEEE Access, Vol. 8, pp. 89497-89509, 2020. Polym. Adv. Technol., 2017, 28 (11), pp. 1375-1381. https://doi.org/10.1109/ACCESS.2020.2990567
  • Blank, Julian and Kalyanmoy Deb. A. Running Performance Metric and Termination Criterion for Evaluating Evolutionary Multi- and Many-objective Optimization Algorithms. 2020 IEEE Congress on Evolutionary Computation (CEC), 2020, pp. 1-8. https://doi.org/10.1109/CEC48606.2020.9185546.
Еще
Статья научная
SciUp 2024 © 2024 ©