Structural Engineering and Mechanics

  • 제67권3호
  • /
  • Pages.301-310
  • /
  • 2018
  • /
  • 1225-4568(pISSN)
  • /
  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Metamodel based multi-objective design optimization of laminated composite plates

  • Kalita, Kanak (Department of Aerospace Engineering and Applied Mechanics, Indian Institute of Engineering Science and Technology) ;
  • Nasre, Pratik (Department of Aerospace Engineering and Applied Mechanics, Indian Institute of Engineering Science and Technology) ;
  • Dey, Partha (Department of Mechanical Engineering, Academy of Technology) ;
  • Haldar, Salil (Department of Aerospace Engineering and Applied Mechanics, Indian Institute of Engineering Science and Technology)
  • 투고 : 2018.03.06
  • 심사 : 2018.05.25
  • 발행 : 2018.08.10
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper, a multi-objective multiparameter optimization procedure is developed by combining rigorously developed metamodels with an evolutionary search algorithm-Genetic Algorithm (GA). Response surface methodology (RSM) is used for developing the metamodels to replace the tedious finite element analyses. A nine-node isoparametric plate bending element is used for conducting the finite element simulations. Highly accurate numerical data from an author compiled FORTRAN finite element program is first used by the RSM to develop second-order mathematical relations. Four material parameters-${\frac{E_1}{E_2}}$, ${\frac{G_{12}}{E_2}}$, ${\frac{G_{23}}{E_2}}$ and ${\upsilon}_{12}$ are considered as the independent variables while simultaneously maximizing fundamental frequency, ${\lambda}_1$ and frequency separation between the $1^{st}$ two natural modes, ${\lambda}_{21}$. The optimal material combination for maximizing ${\lambda}_1$ and ${\lambda}_{21}$ is predicted by using a multi-objective GA. A general sensitivity analysis is conducted to understand the effect of each parameter on the desired response parameters.

키워드

참고문헌

  1. Abu-Odeh, A.Y. and Jones, H.L. (1998), "Optimum design of composite plates using response surface method", Compos. Struct., 43(3), 233-242. https://doi.org/10.1016/S0263-8223(98)00109-3
  2. Boussaid, I., Lepagnot, J. and Siarry, P. (2013), "A survey on optimization metaheuristics", Informat. Sci., 237, 82-117. https://doi.org/10.1016/j.ins.2013.02.041
  3. Haykin, S.S. (2001), Neural Networks: A Comprehensive Foundation, Tsinghua University Press, China.
  4. Heinonen, O. and Pajunen, S. (2011), "Optimal design of stiffened plate using metamodeling techniques", J. Struct. Mech., 44(3), 218-230.
  5. Jafarian, F., Amirabadi, H. and Sadri, J. (2015), "Experimental measurement and optimization of tensile residual stress in turning process of Inconel718 superalloy", Measure., 63, 1-10.
  6. Jafarian, F., Amirabadi, H., Sadri, J. and Banooie, H.R. (2014), "Simultaneous optimizing residual stress and surface roughness in turning of Inconel718 superalloy", Mater. Manufact. Proc., 29(3), 337-343. https://doi.org/10.1080/10426914.2013.864413
  7. Jafarian, F., Taghipour, M. and Amirabadi, H. (2013), "Application of artificial neural network and optimization algorithms for optimizing surface roughness, tool life and cutting forces in turning operation", J. Mech. Sci. Technol., 27(5), 1469-1477. https://doi.org/10.1007/s12206-013-0327-0
  8. Jafarian, F., Umbrello, D., Golpayegani, S. and Darake, Z. (2016), "Experimental investigation to optimize tool life and surface roughness in Inconel718 machining", Mater. Manufact. Proc., 31(13), 1683-1691. https://doi.org/10.1080/10426914.2015.1090592
  9. Ju, S., Shenoi, R.A., Jiang, D. and Sobey, A.J. (2013), "Multiparameter optimization of lightweight composite triangular truss structure based on response surface methodology", Compos. Struct., 97, 107-116. https://doi.org/10.1016/j.compstruct.2012.10.025
  10. Kalita, K. and Haldar, S. (2017), "Eigenfrequencies of simply supported taper plates with cut-outs", Struct. Eng. Mech., 63(1), 103-113. https://doi.org/10.12989/SEM.2017.63.1.103
  11. Kalita, K., Dey, P. and Haldar, S. (2018), "Robust genetically optimized skew laminates", J. Mech. Eng. Sci.
  12. Kalita, K., Ramachandran, M., Raichurkar, P., Mokal, S.D. and Haldar, S. (2016), "Free vibration analysis of laminated composites by a nine node isoparametric plate bending element", Adv. Compos. Lett., 25(5), 108.
  13. Kalita, K., Shivakoti, I. and Ghadai, R.K. (2017), "Optimizing process parameters for laser beam micro-marking using a genetic algorithm and particle swarm optimization", Mater. Manufact. Proc., 32(10), 1101-1108. https://doi.org/10.1080/10426914.2017.1303156
  14. Keblouti, O., Boulanouar, L., Azizi, M.W. and Yallese, M.A. (2017), "Effects of coating material and cutting parameters on the surface roughness and cutting forces in dry turning of AISI 52100 steel", Struct. Eng. Mech., 61(4), 519-526. https://doi.org/10.12989/sem.2017.61.4.519
  15. Kilickap, E. and Huseyinoglu, M. (2010), "Selection of optimum drilling parameters on burr height using response surface methodology and genetic algorithm in drilling of AISI 304 stainless steel", Mater. Manufact. Proc., 25(10), 1068-1076. https://doi.org/10.1080/10426911003720854
  16. Kilickap, E., Huseyinoglu, M. and Yardimeden, A. (2011), "Optimization of drilling parameters on surface roughness in drilling of AISI 1045 using response surface methodology and genetic algorithm", Int. J. Adv. Manufact. Technol., 52(1-4), 79-88. https://doi.org/10.1007/s00170-010-2710-7
  17. Kim, D., Kim, D.H., Cui, J., Seo, H.Y. and Lee, Y.H. (2009), "Iterative neural network strategy for static model identification of an FRP deck", Steel Compos. Struct., 9(5), 445-455. https://doi.org/10.12989/scs.2009.9.5.445
  18. Mills, K.L., Filliben, J.J. and Haines, A.L. (2015), "Determining relative importance and effective settings for genetic algorithm control parameters", Evolut. Comput., 23(2), 309-342. https://doi.org/10.1162/EVCO_a_00137
  19. Mukhopadhyay, T., Dey, T.K., Chowdhury, R. and Chakrabarti, A. (2015), "Structural damage identification using response surface based multi-objective optimization: A comparative study", Arab. J. Sci. Eng., 40(4), 1027-1044. https://doi.org/10.1007/s13369-015-1591-3
  20. Mukhopadhyay, T., Dey, T.K., Dey, S. and Chakrabarti, A. (2015), "Optimisation of fibre-reinforced polymer web core bridge deck. A hybrid approach", Struct. Eng. Int., 25(2), 173-183. https://doi.org/10.2749/101686614X14043795570778
  21. Pajunen, S. and Heinonen, O. (2014), "Automatic design of marine structures by using successive response surface method", Struct. Multidiscipl. Optim., 49(5), 863-871. https://doi.org/10.1007/s00158-013-1013-7
  22. Pan, S.S., Lei, S., Tan, Y.G. and Zhang, Z. (2011), "Reliability analysis for lateral stability of tongwamen bridge", Steel Compos. Struct., 11(5), 423-434. https://doi.org/10.12989/scs.2011.11.5.423
  23. Rahman, M.S., Islam, M.S., Do, J. and Kim, D. (2017), "Response surface methodology based multi-objective optimization of tuned mass damper for jacket supported offshore wind turbine", Struct. Eng. Mech., 63(3), 303-315. https://doi.org/10.12989/SEM.2017.63.3.303
  24. Shadish, W.R., Clark, M.H. and Steiner, P.M. (2008), "Can nonrandomized experiments yield accurate answers? A randomized experiment comparing random and nonrandom assignments", J. Am. Stat. Assoc., 103(484), 1334-1344. https://doi.org/10.1198/016214508000000733
  25. Shi, J.W., Nakatani, A. and Kitagawa, H. (2004), "Vibration analysis of fully clamped arbitrarily laminated plate", Compos. Struct., 63(1), 115-122. https://doi.org/10.1016/S0263-8223(03)00138-7
  26. Xiang, S., Shi, H., Wang, K.M., Ai, Y.T. and Sha, Y.D. (2010), "Thin plate spline radial basis functions for vibration analysis of clamped laminated composite plates", Eur. J. Mech.-A/Sol., 29(5), 844-850. https://doi.org/10.1016/j.euromechsol.2010.02.012
  27. Yardimeden, A., Kilickap, E. and Celik, Y.H. (2014), "Effects of cutting parameters and point angle on thrust force and delamination in drilling of CFRP", Mater. Test., 56(11-12), 1042-1048. https://doi.org/10.3139/120.110666

피인용 문헌

  1. PSO-tuned support vector machine metamodels for assessment of turbulent flows in pipe bends vol.37, pp.3, 2018, https://doi.org/10.1108/ec-05-2019-0244
  2. Metamodel-based parametric study of composite laminates vol.810, pp.None, 2020, https://doi.org/10.1088/1757-899x/810/1/012051
  3. Finite element model updating of long-span cable-stayed bridge by Kriging surrogate model vol.74, pp.2, 2018, https://doi.org/10.12989/sem.2020.74.2.157
  4. Accurate estimation of DLC thin film hardness using genetic programming vol.111, pp.6, 2020, https://doi.org/10.3139/146.111911
  5. Topology and size optimization of truss structures using an improved crow search algorithm vol.77, pp.6, 2018, https://doi.org/10.12989/sem.2021.77.6.779