Structural Engineering and Mechanics

  • 제84권1호
  • /
  • Pages.35-48
  • /
  • 2022
  • /
  • 1225-4568(pISSN)
  • /
  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Application of artificial neural networks in the analysis of the continuous contact problem

  • Yaylaci, Ecren Uzun (Surmene Faculty of Marine Science, Karadeniz Technical University) ;
  • Oner, Erdal (Department of Civil Engineering, Bayburt University) ;
  • Yaylaci, Murat (Department of Civil Engineering, Recep Tayyip Erdogan University) ;
  • Ozdemir, Mehmet Emin (Department of Civil Engineering, Cankiri Karatekin University) ;
  • Abushattal, Ahmad (Department of Physics, Al-Hussein Bin Talal University) ;
  • Birinci, Ahmet (Department of Civil Engineering, Karadeniz Technical University)
  • 투고 : 2021.12.19
  • 심사 : 2022.08.10
  • 발행 : 2022.10.10
⟨ 이전 논문 다음 논문 ⟩

초록

This paper investigates the artificial neural network (ANN) to predict the dimensionless parameters for contact pressures and contact lengths under the rigid punch, the initial separation loads, and the initial separation distances of a contact problem. The problem consisted of two elastic infinitely layers (EL) loaded by means of a rigid cylindrical punch and resting on a half-infinite plane (HP). Firstly, the problem was formulated and solved theoretically using the Theory of Elasticity (ET). Secondly, the contact problem was extended based on the ANN. External load, the radius of punch, layer heights, and material properties were created by giving examples of different values used at the training and test stages of ANN. Finally, the accuracy of the trained neural networks for the case was tested using 134 new data, generated via ET solutions to determine the best network model. ANN results were compared with ET results, and well agreements were achieved.

키워드

참고문헌

  1. Adeli, H. and Yeh, C. (1989), "Perceptron learning in engineering design", Comput. Aid. Civil Infrastr. Eng., 4(4), 247-256. https://doi.org/10.1111/j.1467-8667.1989.tb00026.x.
  2. Adeli, H. and Hung, S. (1995), Machine Learning: Neural Networks, General Algorithms, and Fuzzy Systems, Wiley, New York.
  3. Adeli, H. (2001), "Neural networks in civil engineering: 1989-2000", Comput. Aid. Civil Infrastr. Eng., 16(2), 126-142. https://doi.org/10.1111/0885-9507.00219.
  4. Adiyaman, G., Yaylaci, M. and Birinci, A. (2015), "Analytical and finite element solution of a receding contact problem", Struct. Eng. Mech., 54(1), 69-85. https://doi.org/10.12989/sem.2015.54.1.069.
  5. Adiyaman, G., Birinci, A., Oner, E. and Yaylaci, M. (2016), "A receding contact problem between a functionally graded layer and two homogeneous quarter planes", Acta Mechanica, 227(3), 1753-1766. https://doi.org/10.1007/s00707-016-1580-y.
  6. Aizikovich, S.M., Mitrin. B.I., Seleznev. N.M., Wang, Y.C. and Volkov, S.S. (2016), "Influence of a soft FGM interlayer on contact stresses under a beam on an elastic foundation", Struct. Eng. Mech., 58(4), 613-625. https://doi.org/10.12989/sem.2016.58.4.613.
  7. Al-Furjan, M.S.H., Farrokhian, A., Keshtegar, B., Kolahchi, R. and Trung, B.T. (2020), "Higher order nonlocal viscoelastic strain gradient theory for dynamic buckling analysis of carbon nanocones", Aerosp. Sci. Technol., 107, 106259. https://doi.org/10.1016/j.ast.2020.106259.
  8. Al-Furjan, M.S.H., Farrokhian, A., Mahmoud, S.R. and Kolahchi, R. (2021a) "Dynamic deflection and contact force histories of graphene platelets reinforced conical shell integrated with magnetostrictive layers subjected to low-velocity impact", Thin Wall. Struct., 163, 107706. https://doi.org/10.1016/j.tws.2021.107706.
  9. Al-Furjan, M.S.H., Hajmohammad, M.H., Shen, X., Rajak, D.K. and Kolahchi, R. (2021b), "Evaluation of tensile strength and elastic modulus of 7075-T6 aluminum alloy by adding SiC reinforcing particles using vortex casting method", J. Alloys. Compd., 886, 161261. https://doi.org/10.1016/j.jallcom.2021.161261.
  10. Azizkhani, M., Kadkhodapour, J., Anaraki, A.P., Hadavand, B.S. and Kolahchi, R. (2020), "Study of body movement monitoring utilizing nano-composite strain sensors contaning Carbon nanotubes and silicone rubber", Steel Compos. Struct., 35(6), 779-788. https://doi.org/10.12989/scs.2020.35.6.779.
  11. Cakiroglu, E., Comez, I. and Erdol, R. (2005), "Application of artificial neural network to double receding contact problem with a rigid stamp", Struct. Eng. Mech., 21, 205-220. https://doi.org/10.12989/sem.2005.21.2.205.
  12. Dawson, C.W. and Wilby, R. (1998), "An artificial neural network approach to rainfall-runoff modelling", Hydrol. Sci. J., 43(1), 47-66. https://doi.org/10.1080/02626669809492102.
  13. Erdogan, F., Gupta, G. and Cook, T.S. (1973), "Numerical solution of singular integral equations", Methods of Analysis and Solutions of Crack Problems, Springer, Dordrecht.
  14. Faramoushjan, S.G., Jalalifar, H. and Kolahchi, R. (2021), "Mathematical modelling and numerical study for buckling study in concrete beams containing carbon nanotubes", Adv. Concrete Constr., 11(6), 521-529. https://doi.org/10.12989/acc.2021.11.6.521.
  15. Fath, A.H., Madanifar, F. and Abbasi, M. (2020), "Implementation of multilayer perceptron (MLP) and radial basis function (RBF) neural networks to predict solution gas-oil ratio of crude oil systems", Petroleum, 6, 80-91. https://doi.org/10.1016/j.petlm.2018.12.002.
  16. Hajmohammad, M.H., Farrokhian, A. and Kolahchi, R. (2021), "Dynamic analysis in beam element of wave-piercing Catamarans undergoing slamming load based on mathematical modelling", Ocean Eng., 234, 109269. https://doi.org/10.1016/j.oceaneng.2021.109269.
  17. Hecht-Nielsen, R. (1988), "Neurocomputing: picking the human brain", IEEE Spectr., 25(3), 36-41. https://doi.org/10.1109/6.4520.
  18. Hore, S., Chatterjee, S., Sarkar, S., Dey, N., Ashour, A. S., Balas-Timar, D. and Balas, V.E. (2016), "Neural-based prediction of structural failure of multistoried RC buildings", Struct. Eng. Mech., 58(3), 459-473. https://doi.org/10.12989/sem.2016.58.3.459.
  19. Huang, R.B., Du, Q.S., Wei, Y.T., Pang, Z.W., Wei, H. and Chou, K.C. (2009), "Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design", J. Theor. Biol., 256(3), 428-435. https://doi.org/10.1016/j.jtbi.2008.08.028.
  20. Kalogirou, S.A. (2001), "Artificial neural networks in renewable energy systems applications: A review", Renew. Sustain. Energy Rev., 5(4), 373-401. https://doi.org/10.1016/S1364-0321(01)00006-5.
  21. Keshtegar, B., Xiao, M., Kolahchi, R. and Trung, N.T. (2020), "Reliability analysis of stiffened aircraft panels using adjusting mean value method", AIAA J., 58(12), 5448-5458. https://doi.org/10.2514/1.J059636.
  22. Keshtegar, B., Nehdi, M.L., Trung, N.T. and Kolahchi, R. (2021), "Predicting load capacity of shear walls using SVR-RSM model", Appl. Soft Comput., 112, 107739. https://doi.org/10.1016/j.asoc.2021.107739.
  23. Kolahchi, R. and Kolahdouzan, F. (2021a), "A numerical method for magneto-hygro-thermal dynamic stability analysis of defective quadrilateral graphene sheets using higher order nonlocal strain gradient theory with different movable boundary conditions", Appl. Math. Model., 91, 458-475. https://doi.org/10.1016/j.apm.2020.09.060.
  24. Kolahchi, R., Keshtegar, B. and Trung, N.T. (2021b), "Optimization of dynamic properties for laminated multiphase nanocomposite sandwich conical shell in thermal and magnetic conditions", J. Sandw. Struct. Mater., 24(1), 643-662. https://doi.org/10.1177/10996362211020388.
  25. Kolahchi, R., Tian, K., Keshtegar, B., Li, Z., Trung, N.T. and Thai, D.K. (2022), "AK-GWO: a novel hybrid optimization method for accurate optimum hierarchical stiffened shells", Eng. Comput., 38, 29-41. https://doi.org/10.1007/s00366-020-01124-6.
  26. Kostinakis, K.G. and Morfidis, K.E. (2020), "Optimization of the seismic performance of masonry infilled R/C buildings at the stage of design using artificial neural networks", Struct. Eng. Mech., 75(3), 295-309. https://doi.org/10.12989/sem.2020.75.3.295.
  27. Krenk, S. (1975), "On quadrature formulas for singular integral equations of the first and the second kind", Quart. Appl. Math., 33(3), 225-232. https://doi.org/10.1090/qam/448967.
  28. Liu, Z., Yan, J. and Mi, C. (2018), "On the receding contact between a two-layer inhomogeneous laminate and a half-plane.", Struct. Eng. Mech., 66(3), 329-341. https://doi.org/10.12989/sem.2018.66.3.329.
  29. Mansouri, I., Safa, M., Ibrahim, Z., Kisi, O., Tahir, M. M., Baharom, S. and Azimi, M. (2016), "Strength prediction of rotary brace damper using MLR and MARS", Struct. Eng. Mech., 60(3), 471-488. https://doi.org/10.12989/sem.2016.60.3.471.
  30. McCulloch, W.S. and Pitts, W. (1943), "A logical calculus of the ideas immanent in nervous activity", Bull. Math. Biol., 5(4), 115-133. https://doi.org/10.1007/BF02478259.
  31. Mercier, J.P., Zambelli, G. and Kurz, W. (2002), Introduction to Materials Science, Elsevier, Paris, France.
  32. Meyers, R.A. (1987), Encyclopedia of Physical Science and Technology, Academic Press.
  33. Motezaker, M., Kolahchi, R., Rajak, D.K. and Mahmoud, S.R. (2021), "Influences of fiber reinforced polymer layer on the dynamic deflection of concrete pipes containing nanoparticle subjected to earthquake load", Polym. Compos., 42(8), 4073-4081. https://doi.org/10.1002/pc.26118.
  34. Nandal, M., Mor, N. and Sood, H. (2021), "An overview of use of artificial neural network in sustainable transport system", Computational Methods and Data Engineering, 83-91.
  35. Negassi, M., Suarez-Ibarrola, R., Hein, S., Miernik, A. and Reiterer, A. (2020), "Application of artificial neural networks for automated analysis of cystoscopic images: A review of the current status and future prospects", World J. Urol., 38, 2349-2358. https://doi.org/10.1007/s00345-019-03059-0.
  36. Nriagu, J.O. (2019), Encyclopedia of Environmental Health, Elsevier, Amsterdam, Netherlands.
  37. Oner, E. and Birinci, A. (2014), "Continuous contact problem for two elastic layers resting on an elastic half infinite plane", J. Mech. Mater. Struct., 9(1), 105-119. https://doi.org/10.2140/jomms.2014.9.105.
  38. Oner, E., Yaylaci, M. and Birinci, A. (2014), "Solution of a receding contact problem using an analytical method and a finite element method", J. Mech. Mater. Struct., 9(3), 333-345. https://doi.org/10.2140/jomms.2014.9.333.
  39. Oner, E., Yaylaci, M. and Birinci, A. (2015), "Analytical solution of a contact problem and comparison with the results from FEM", Struct. Eng. Mech., 54(4), 607-622. https://doi.org/10.12989/sem.2015.54.4.607.
  40. Oner, E., Adiyaman, G. and Birinci, A. (2017), "Continuous contact problem of a functionally graded layer resting on an elastic half plane", Arch. Mech., 69(1), 53-73.
  41. Oner, E. and Birinci, A. (2020), "Investigation of the solution for discontinuous contact problem between a functionally graded (FG) layer and homogeneous half-space", Arch. Appl. Mech., 90, 2799-2819. https://doi.org/10.1007/s00419-020-01750-y.
  42. Oner, E. (2021), "Frictionless contact mechanics of an orthotropic coating/isotropic substrate system", Comput. Concrete., 28(2), 209-220. https://doi.org/10.12989/cac.2021.28.2.209.
  43. Oner, E. (2021), "Two-dimensional frictionless contact analysis of an orthotropic layer under gravity", J. Mech. Mater. Struct., 16(4), 573-594. https://doi.org/10.2140/jomms.2021.16.573.
  44. Oner, E., Sengul Sabano, B., Uzun Yaylaci, E., Adiyaman, G., Yaylaci, M. and Birinci, A. (2022) "On the plane receding contact between two functionally graded layers using computational, finite element and artificial neural network methods", J. Appl. Math. Mech., 102(2). https://doi.org/10.1002/zamm.202100287.
  45. Parol, J., Ben-Nakhi, A., Al-Sanad, S., Al-Qazweeni, J., Al-Duaij, H. J. and Kamal, H. (2019), "Experimental and numerical investigation of reinforced concrete beams containing vertical openings", Struct. Eng. Mech., 72(3), 383-393. https://doi.org/10.12989/sem.2019.72.3.383.
  46. Pradhan, B. and Sameen, M.I. (2020), "Review of traffic accident predictions with neural networks", Laser Scanning Systems in Highway and Safety Assessment, Springer, Switzerland.
  47. Saha, P., Prasad, M.L.V. and Kumar, P.R. (2017), "Predicting strength of SCC using artificial neural network and multivariable regression analysis", Comput. Concrete, 20(1), 31-38. https://doi.org/10.12989/cac.2017.20.1.031.
  48. Schalkoff, R.J. (1997), Artificial Neural Networks, McGraw-Hill Higher Education, New York, USA.
  49. Sundararaj, A., Ravi, R., Thirumalai, P. and Radhakrishnan, G. (1999), "Artificial neural network applications in electrochemistry-a review", Bull. Electrochem., 15(12), 552-555.
  50. Taherifar, R., Zareei, S.A., Bidgoli, M.R. and Kolahchi, R. (2021), "Application of differential quadrature and Newmark methods for dynamic response in pad concrete foundation covered by piezoelectric layer", Comput. Appl. Math., 382, 113075. https://doi.org/10.1016/j.cam.2020.113075.
  51. Trinh, M.C. and Jun, H. (2021), "Stochastic vibration analysis of functionally graded beams using artificial neural networks", Struct. Eng. Mech., 78(5), 529-543. https://doi.org/10.12989/sem.2021.78.5.529.
  52. Trujillo, M.C.R., Alarcon, T.E., Dalmau, O.S. and Ojeda, A.Z. (2017), "Segmentation of carbon nanotube images through an artificial neural network", Soft Comput., 21, 611-625. https://doi.org/10.1007/s00500-016-2426-1.
  53. Uzun Yaylaci, E., Yaylaci, M., Olmez, H. and Birinci, A. (2020), "Artificial neural network calculations for a receding contact problem", Comput. Concrete, 25(6), 551-563. https://doi.org/10.12989/cac.2020.25.6.551.
  54. Vanluchene, R.D. and Sun, R. (1990), "Neural networks in structural engineering", Comput. Aid. Civil Infrastr. Eng., 5(3), 207-215. https://doi.org/10.1111/j.1467-8667.1990.tb00377.x.
  55. Walczak, S. (2018), "Artificial neural networks", Encyclopedia of Information Science and Technology, Fourth Edition, IGI Global.
  56. Wani, I.M. and Arora, S. (2020), "Deep neural networks for diagnosis of osteoporosis: A review", Proceedings of ICRIC 2019, 597, 65-78. https://doi.org/10.1007/978-3-030-29407-6_6.
  57. Waziri, B.S., Bala, K. and Bustani, S.A. (2017), "Artificial neural networks in construction engineering and management", IJAEC, 6(1), 50-60. http://doi.org/10.7492/IJAEC.2017.006.
  58. Wui, D. and Wang, G.G. (2021), "Causal artificial neural network and its applications in engineering design", Eng. Appl. Artif. Intell., 97, 104089. https://doi.org/10.1016/j.engappai.2020.104089.
  59. Yan, H., Jiang, Y., Zheng, J., Peng, C. and Li, Q. (2006), "A multilayer perceptron based medical decision support system for heart disease diagnosis", Exp. Syst. Appl., 30(2), 272-281. https://doi.org/10.1016/j.eswa.2005.07.022.
  60. Yaswanth, K.K., Revathy, J. and Gajalakshmi, P. (2021), "Artificial intelligence for the compressive strength prediction of novel ductile geopolymer composites", Comput. Concrete, 28(1), 55-68. https://doi.org/10.12989/cac.2021.28.1.055.
  61. Yaylaci, M., Adiyaman, E., Oner, E. and Birinci, A. (2020), "Examination of analytical and finite element solutions regarding contact of a functionally graded layer", Struct. Eng. Mech., 76(3), 325-336. https://doi.org/10.12989/sem.2020.76.3.325.
  62. Yaylaci, M., Adiyaman, E., Oner, E. and Birinci, A. (2021), "Investigation of continuous and discontinuous contact cases in the contact mechanics of graded materials using analytical method and FEM", Comput. Concrete, 27, 199-210. https://doi.org/10.12989/cac.2021.27.3.199.
  63. Yaylaci, M., Eyuboglu, A., Adiyaman, G., Uzun Yaylaci, E., Oner, E. and Birinci, A. (2021a), "Assessment of different solution methods for receding contact problems in functionally graded layered mediums", Mech. Mater., 154, 103730. https://doi.org/10.1016/j.mechmat.2020.103730.
  64. Yaylaci, M., Yayli, M., Uzun Yaylaci, E., Olmez, H. and Birinci, A. (2021b), "Analyzing the contact problem of a functionally graded layer resting on an elastic half plane with theory of elasticity, finite element method and multilayer perceptron", Struct. Eng. Mech., 78, 585-597. https://doi.org/10.12989/sem.2021.78.5.585.
  65. Yaylaci, M. (2022), "Simulate of edge and an internal crack problem and estimation of stress intensity factor through finite element method", Adv. Nano Res., 12(4), 405-414. https://doi.org/10.12989/anr.2022.12.4.405.
  66. Yaylaci, M., Sengul Sabano, B., Ozdemir, M.E. and Birinci, A. (2022a), "Solving the contact problem of functionally graded layers resting on a homogeneous half-plane and pressed with a uniformly distributed load by analytical and numerical methods", Struct. Eng. Mech., 82(3), 401-416. https://doi.org/10.12989/sem.2022.82.3.401.
  67. Yaylaci, M., Abanoz, M., Uzun Yaylaci, E., Olmez, H., Sekban, M.D. and Birinci, A. (2022b), "Evaluation of the contact problem of functionally graded layer resting on rigid foundation pressed via rigid punch by analytical and numerical (FEM and MLP) methods", Arch. Appl. Mech., 92(6), 1953-1971. https://doi.org/10.1007/s00419-022-02159-5.
  68. Yaylaci, M, Abanoz, M, Uzun Yaylaci, E, Olmez, H, Sekban, M.D and Birinci, A. (2022), "The contact problem of the functionally graded layer resting on rigid foundation pressed via rigid punch", Steel Compos. Struct., 43(5), 661-672. https://doi.org/10.12989/scs.2022.43.5.661.
  69. Yucel, M., Nigdeli, S.M. and Bekdas, G. (2020), "Artificial neural networks (anns) and solution of civil engineering problems: anns and prediction applications", Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineerin, IGI Global.