Advances in concrete construction

  • 제18권4호
  • /
  • Pages.253-266
  • /
  • 2024
  • /
  • 2287-5301(pISSN)
  • /
  • 2287-531X(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Application of artificial neural networks for buckling prediction in functionally graded concrete sports structures and efficiency enhancement

  • Shuo Dong (Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology) ;
  • Wen Pan (Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology) ;
  • Jing Zhao (State Key Laboratory of Energy Resources)
  • 투고 : 2023.09.10
  • 심사 : 2024.11.13
  • 발행 : 2024.10.25
⟨ 이전 논문 다음 논문 ⟩

초록

This work describes a unique technique for forecasting the buckling behavior of functionally graded concrete (FGC) structures, with a focus on their use in sports engineering. Traditional prediction methods, which may rely on basic assumptions, fail to give the necessary accuracy for complicated material compositions. Artificial neural networks (ANNs) provide a versatile and adaptable approach to detecting complex patterns in FGC systems, particularly for sports infrastructure and equipment design. The ANN model displays versatility across different materials and structural designs, including stadium construction, sports equipment, and high-performance athletic surfaces, thanks to comprehensive training and validation on multiple FGC configurations. The ANN model exceeds standard analytical approaches in terms of speed and accuracy, demonstrating its effectiveness in anticipating crucial buckling stresses in dynamic, high-impact situations characteristic of sporting activities. This paper investigates the combination of artificial neural networks, image processing, and risk assessments, highlighting their importance in influencing design decisions. This work advances our understanding of the flexural properties of FGC structures, especially in athletic situations, allowing for the design of safer, more reliable, and performance-enhancing sports facilities. This technology offers engineers with an excellent tool for designing innovative and resilient sports-specific systems.

키워드

과제정보

This work was supported by Yunnan Province Provincial and Municipal Integration Major Special Science and Technology Plan Project "Key points of seismic and vibration dual control composite isolation in engineering structures technical study". (202202AH210004)

참고문헌

  1. Afshar, A., Nouri, G., Ghazvineh, S. and Hosseini Lavassani Seyed, H. (2024), "Machine-Learning Applications in Structural Response Prediction: A Review", Practice Period. Struct. Des. Constr., 29(3), p. 03124002. https://doi.org/10.1061/PPSCFX.SCENG-1292
  2. Ahumada, M., Jacques, E., Calderon, C. and Martinez-Gomez, F. (2019), "Porosity in Biomaterials: A Key Factor in the Development of Applied Materials in Biomedicine", In: Handbook of Ecomaterials, pp. 3503-3522. https://doi.org/10.1007/978-3-319-68255-6_162
  3. Albahri, A.S., Khaleel, Y.L., Habeeb, M.A., Ismael, R.D., Hameed, Q.A., Deveci, M., Homod, R.Z., Albahri, O.S., Alamoodi, A.H. and Alzubaidi, L. (2024), "A systematic review of trustworthy artificial intelligence applications in natural disasters", Comput. Electr. Eng., 118, p. 109409. https://doi.org/10.1016/j.compeleceng.2024.109409
  4. Athanasopoulos, N., Gavalas, E. and Papaefthymiou, S. (2019), "Prediction of pipeline collapse due to hydrostatic pressure", Int. J. Struct. Integr., 10(1), 55-66. https://doi.org/10.1108/IJSI-06-2018-0033
  5. Bai, Y., Alzahrani, B., Baharom, S. and Habibi, M. (2022), "Semi-numerical simulation for vibrational responses of the viscoelastic imperfect annular system with honeycomb core under residual pressure", Eng. Comput., 38(5), 3699-3724. https://doi.org/10.1007/s00366-020-01191-9
  6. Chen, R.-S., Zhang, H.-Y., Hao, X.-K., Yu, H.-X., Shi, T., Zhou, H.-S., Wang, R.-B., Zhao, Z.-F. and Wang, P. (2024), "Experimental study on ultimate bearing capacity of short thin walled steel tubes reinforced with high-ductility concrete", Structures, 68, p. 107109. https://doi.org/10.1016/j.istruc.2024.107109
  7. Chiu, H.T. and Shiang, T.Y. (2007), "Effects of insoles and additional shock absorption foam on the cushioning properties of sport shoes", J. Appl. Biomech., 23(2), 119-127. https://doi.org/10.1123/jab.23.2.119
  8. Dai, Z., Wu, S., Habibi, M. and Elhosiny Ali, H. (2023), "Application of point interpolation mesh-free method for magneto/electro rheological vibrations of sandwich conical panels", Aerosp. Sci. Technol., 135, 108180. https://doi.org/10.1016/j.ast.2023.108180
  9. Daneshvar, D., Behnood, A. and Robisson, A. (2022), "Interfacial bond in concrete-to-concrete composites: A review", Constr. Build. Mater., 359, p. 129195. https://doi.org/10.1016/j.conbuildmat.2022.129195
  10. Ding, L., Van Coile, R., Botte, W. and Caspeele, R. (2021), "Performance Assessment of an Energy–Based Approximation Method for the Dynamic Capacity of RC Frames Subjected to Sudden Column Removal Scenarios", Appl. Sci., 11(16). https://doi.org/10.3390/app11167492
  11. Ehyaei, J., Akbarshahi, A. and Shafiei, N. (2017), "Influence of porosity and axial preload on vibration behavior of rotating FG nanobeam", Adv. Nano Res., Int. J., 5(2), 141-169. https://doi.org/10.12989/anr.2017.5.2.141
  12. Fan, S., He, T., Li, W., Zeng, C., Chen, P., Chen, L. and Shu, J. (2024), "Machine learning-based classification of quality grades for concrete vibration behaviour", Automat. Constr., 167, p. 105694. https://doi.org/10.1016/j.autcon.2024.105694
  13. Ge, J., Hong, Y., Zeng, R., Li, Y. and Habibi, M. (2023), "Increasing the attractiveness of physical education training with the involvement of nanotechnology", Adv. Concrete Constr., Int. J., 16(6), 291-302. https://doi.org/10.12989/acc.2023.16.6.291
  14. Ghadiri, M., Shafiei, N. and Alavi, H. (2017a), "Thermo-mechanical vibration of orthotropic cantilever and propped cantilever nanoplate using generalized differential quadrature method", Mech. Adv. Mater. Struct., 24(8), 636-646. https://doi.org/10.1080/15376494.2016.1196770
  15. Ghadiri, M., Shafiei, N. and Babaei, R. (2017b), "Vibration of a rotary FG plate with consideration of thermal and Coriolis effects", Steel Compos. Struct., Int. J., 25(2), 197-207. https://doi.org/10.12989/scs.2017.25.2.197
  16. Ghasemi, M., Zhang, C., Khorshidi, H., Zhu, L. and Hsiao, P.-C. (2023), "Seismic upgrading of existing RC frames with displacement-restraint cable bracing", Eng. Struct., 282, p. 115764. https://doi.org/10.1016/j.engstruct.2023.115764
  17. Greve, L. and van de Weg, B.P. (2022), "Surrogate modeling of parametrized finite element simulations with varying mesh topology using recurrent neural networks", Array, 14, p. 100137. https://doi.org/10.1016/j.array.2022.100137
  18. Gu, X., He, J., Wang, Z., Li, M., Habibi, M. and Hashemabadi, D. (2023), "Application of hyperbolic differential quadrature method for vibration responses of the electrorheological disk", Eng. Anal. Bound. Elem., 155, 599-615. https://doi.org/10.1016/j.enganabound.2023.05.035
  19. Guo, Y., Maalla, A., Habibi, M. and moradi, Z. (2024), "Electroelastic wave dispersion in the rotary piezoelectric NEMS sensors/actuators via nonlocal strain gradient theory", Mec. Syst. Signal Process., 216, p. 111453. https://doi.org/10.1016/j.ymssp.2024.111453
  20. Habibi, M., Habibi, M., Toghroli, E., Safa, M. and Shariati, M. (2024), "Frequency responses of a graphene oxide reinforced concrete structure", Eídos, 17(24), 63-79. https://doi.org/10.29019/eidos.v17i24.1382
  21. Han, A., Yang, Q., Chen, Y. and Li, J. (2024), "Failure-distribution-dependent H∞ fuzzy fault-tolerant control for nonlinear multilateral teleoperation system with communication delays", Electronics, 13(17), p. 3454. https://doi.org/10.3390/electronics13173454
  22. He, L., Chen, B., Liu, Q., Chen, H., Li, H., Chow, W.T., Tang, J., Du, Z., He, Y. and Pan, J. (2024a), "A quasi-exponential distribution of interfacial voids and its effect on the interlayer strength of 3D printed concrete", Addit. Manuf., 89, p. 104296. https://doi.org/10.1016/j.addma.2024.104296
  23. He, L., Pan, J., Hee, Y.S., Chen, H., Li, L.G., Panda, B. and Chow, W.T. (2024b), "Development of novel concave and convex trowels for higher interlayer strength of 3D printed cement paste", Case Stud. Constr. Mater., 21, p. e03745. https://doi.org/10.1016/j.cscm.2024.e03745
  24. Hou, F., Wu, S., Moradi, Z. and Shafiei, N. (2021), "The computational modeling for the static analysis of axially functionally graded micro-cylindrical imperfect beam applying the computer simulation", Eng. Comput., 38, 3217-3235. https://doi.org/10.1007/s00366-021-01456-x
  25. Huang, H., Chen, Z., Zhao, M., Wang, B. and Ye, Y. (2024), "Seismic performance of frame with middle partially encased composite brace and steel-hollow core partially encased composite spliced frame beam", J. Build. Eng., 95, p. 110226. https://doi.org/10.1016/j.jobe.2024.110226
  26. Jermsittiparsert, K., Ghabussi, A., Forooghi, A., Shavalipour, A., Habibi, M., won Jung, D. and Safa, M. (2022), "Critical voltage, thermal buckling and frequency characteristics of a thermally affected GPL reinforced composite microdisk covered with piezoelectric actuator", Mech. Based Des. Struct. Mach., 50(4), 1331-1353. https://doi.org/10.1080/15397734.2020.1748052
  27. Jia, S., Niu, X., Jia, F. and Mahmoudi, T. (2023), "Advantages and disadvantages of renewable energy-oil-environmental pollution-from the point of view of nanoscience", Adv. Concrete Constr., Int. J., 16(1), 69-78. https://doi.org/10.12989/acc.2023.16.1.069
  28. Kavzoglu, T. (2009), "Increasing the accuracy of neural network classification using refined training data", Environ. Modell. Softw., 24(7), 850-858. https://doi.org/10.1016/j.envsoft.2008.11.012
  29. Li, J., Wang, Z., Zhang, S., Lin, Y., Jiang, L. and Tan, J. (2024a), "Task incremental learning-driven Digital-Twin predictive modeling for customized metal forming product manufacturing process", Robot. Comput.-Integr. Manuf., 85, p. 102647. https://doi.org/10.1016/j.rcim.2023.102647
  30. Li, J., Wu, Z., Habibi, M. and Albaijan, I. (2024b), "An inspection of the metal-foam beam considering torsional dynamic responses", Solid State Commun., 391, p. 115638. https://doi.org/10.1016/j.ssc.2024.115638
  31. Liang, Z., Zhao, Y., Yu, H., Habibi, M. and Mahmoudi, T. (2024), "Artificial neural networks coupled with numerical approach for the stability prediction of non-uniform functionally graded microscale cylindrical structures", Structures, 60, p. 105826. https://doi.org/10.1016/j.istruc.2023.105826
  32. Lishner, I. and Shtub, A. (2022), "Using an artificial neural network for improving the prediction of project duration", Mathematics, 10(22), p. 4189. https://doi.org/10.3390/math10224189
  33. Liu, H., Zhao, Y., Pishbin, M., Habibi, M., Bashir, M.O. and Issakhov, A. (2022), "A comprehensive mathematical simulation of the composite size-dependent rotary 3D microsystem via two-dimensional generalized differential quadrature method", Eng. Comput., 38(5), 4181-4196. https://doi.org/10.1007/s00366-021-01419-2
  34. Liu, S., Xu, N., Zhao, N. and Zhang, L. (2024), "Observer-based optimal fault-tolerant tracking control for input-constrained interconnected nonlinear systems with mismatched disturbances", Optimal Control Applicat. Methods, 45(6), 2572-2595. https://doi.org/10.1002/oca.3173
  35. Long, X., Iyela, P.M., Su, Y., Atlaw, M.M. and Kang, S.-B. (2024a), "Numerical predictions of progressive collapse in reinforced concrete beam-column sub-assemblages: A focus on 3D multiscale modeling", Eng. Struct., 315, p. 118485. https://doi.org/10.1016/j.engstruct.202
  36. Long, X., Li, H., Iyela, P.M. and Kang, S.-B. (2024b), "Predicting the bond stress–slip behavior of steel reinforcement in concrete under static and dynamic loadings by finite element, deep learning and analytical methods", Eng. Fail. Anal., 161, p. 108312. https://doi.org/10.1016/j.engfailanal.2024.108312
  37. Lu, D., Ma, C., Du, X., Jin, L. and Gong, Q. (2017a), "Development of a new nonlinear unified strength theory for geomaterials based on the characteristic stress concept", Int. J. Geomech., 17(2), p. 04016058. https://doi.org/10.1061/(ASCE)GM.1943-5622.0000729
  38. Lu, D., Wang, G., Du, X. and Wang, Y. (2017b), "A nonlinear dynamic uniaxial strength criterion that considers the ultimate dynamic strength of concrete", Int. J. Impact Eng., 103, 124-137. https://doi.org/10.1016/j.ijimpeng.2017.01.011
  39. Lu, L., Liao, K., Habibi, M., Safarpour, H. and Elhosiny Ali, H. (2023), "Numerical methods to predict aero thermally induced vibrations of a curved pipe structure reinforced by GPLs", Structures, 55, 1607-1621. https://doi.org/10.1016/j.istruc.2023.06.105
  40. Ma, B., Chen, K.-y., Habibi, M. and Albaijan, I. (2024), "Static/dynamic analyses of sandwich micro-plate based on modified strain gradient theory", Mech. Adv. Mater. Struct., 31(23), 5760-5767. https://doi.org/10.1080/15376494.2023.2219453
  41. Naseem, Z., Zainab, I., Batool, S.R., Uzun, M., Ioanid, A. and Nazeer, M.A. (2024), "An Innovative Approach to Enhance the Durability and Sustainability of Shoe Insoles", Sustainability, 16(21), p. 9195. https://doi.org/10.3390/su16219195
  42. Nath, D., Ankit, Neog, D.R. and Gautam, S.S. (2024), "Application of machine learning and deep learning in finite element analysis: a comprehensive review", Arch. Computat. Methods Eng., 31(5), 2945-2984. https://doi.org/10.1007/s11831-024-10063-0
  43. Parisi, M., La Fauci, G., Pugno, N.M. and Colonna, M. (2023), "Use of shear thickening fluids in sport protection applications: A review", Fronti. Mater., 10, p. 1285995. https://doi.org/10.1016/j.jmrt.2020.07.049
  44. Paturi, U.M.R., Cheruku, S. and Reddy, N.S. (2022), "The role of artificial neural networks in prediction of mechanical and tribological properties of composites—a comprehensive review", Arch. Computat. Methods Eng., 29(5), 3109-3149. https://doi.org/10.1007/s11831-021-09691-7
  45. Peng, S., Habibi, M. and Pourjabari, A. (2023), "Generalized differential quadrature element solution, swarm, and GA optimization technique to obtain the optimum frequency of the laminated rotary nanostructure", Eng. Anal. Bound. Eleme, 151, 101-114. https://doi.org/10.1016/j.enganabound.2023.02.052
  46. Polak, J. and Nowak, M. (2023), "From Structural Optimization Results to Parametric CAD Modeling—Automated, Skeletonization-Based Truss Recognition", Appl. Sci., 13(9), p. 5670. https://doi.org/10.3390/app13095670
  47. Porreca, R., Geropanta, V., Barbera, R.M. and Rocchio, D. (2020), "Remote sensing drones for advanced urban regeneration strategies. The case of San Jose de Chamanga in Ecuador", In: Intelligent Computing and Optimization: Proceedings of the 2nd International Conference on Intelligent Computing and Optimization 2019 (ICO 2019), pp. 620-628. https://doi.org/10.1007/978-3-030-33585-4_60
  48. Qi, L., Wang, Z., Sun, Y., Khorami, M., Mahmoudi, T. and Wu, H. "Modified couple stress and artificial intelligence examination of nonlinear buckling in porous variable thickness cylinder micro sport structures", Mech. Adv. Mater. Struct., 1-19. https://doi.org/10.1080/15376494.2024.2316795
  49. Shafabakhsh, G.H., Ani, O.J. and Talebsafa, M. (2015), "Artificial neural network modeling (ANN) for predicting rutting performance of nano-modified hot-mix asphalt mixtures containing steel slag aggregates", Constr. Build. Mater., 85, 136-143. https://doi.org/10.1016/j.conbuildmat.2015.03.060
  50. Shafiei, N. and Kazemi, M. (2017), "Nonlinear buckling of functionally graded nano-/micro-scaled porous beams", Compos. Struct., 178, 483-492. https://doi.org/10.1016/j.compstruct.2017.07.045
  51. Shi, X., Li, J. and Habibi, M. (2022), "On the statics and dynamics of an electro-thermo-mechanically porous GPLRC nanoshell conveying fluid flow", Mech. Based Des. Struct. Mach., 50(6), 2147-2183. https://doi.org/10.1080/15397734.2020.1772088
  52. Shivanian, E., Ghadiri, M. and Shafiei, N. (2017), "Influence of size effect on flapwise vibration behavior of rotary microbeam and its analysis through spectral meshless radial point interpolation", Appl. Phys. A, 123(5), p. 329. https://doi.org/10.1007/s00339-017-0955-9
  53. Shu, J., Yu, H., Liu, G., Duan, Y., Hu, H. and Zhang, H. (2025), "DF-CDM: Conditional diffusion model with data fusion for structural dynamic response reconstruction", Mech. Syst. Signal Process., 222, p. 111783. https://doi.org/10.1016/j.ymssp.2024.111783
  54. Silva, R.F., Coelho, P.G., Gustavo, C.V., Almeida, C.J., Farias, F.W., Duarte, V.R., Xavier, J., Esteves, M.B., Conde, F.M., Cunha, F.G. and Santos, T.G. (2024), "Functionally Graded Materials and Structures: Unified Approach by Optimal Design, Metal Additive Manufacturing, and Image-Based Characterization", Materials, 17(18), p. 4545. https://doi.org/10.3390/ma17184545
  55. Singh, P., Sheikh, J. and Behera, B.K. (2024), "Metal-faced sandwich composite panels: A review", Thin-Wall. Struct., 195, p. 111376. https://doi.org/10.1016/j.tws.2023.111376
  56. Song, G., Zou, Y., Nie, Y., Habibi, M., Albaijan, I. and Toghroli, E. (2024a), "Application of Hashin–Shtrikman bounds homogenization model for frequency analysis of imperfect FG bio-composite plates", J. Mech. Behav. Biomed. Mater., 151, p. 106321. https://doi.org/10.1016/j.jmbbm.2023.106321
  57. Song, Y., Ghafari, Y., Asefnejad, A. and Toghraie, D. (2024b), "An overview of selective laser sintering 3D printing technology for biomedical and sports device applications: Processes, materials, and applications", Optics Laser Technol., 171, p. 110459. https://doi.org/10.1016/j.optlastec.2023.110459
  58. Tang, L., Zhang, L. and Xu, N. (2024), "Optimized backstepping based finite-time containment control for nonlinear multi-agent systems with prescribed performance", Optimal Control Applicat. Methods, 45(5), 2364-2382. https://doi.org/10.1002/oca.3160
  59. Wang, P., Gao, Z., Pan, F., Moradi, Z., Mahmoudi, T. and Khadimallah, M.A. (2022), "A couple of GDQM and iteration techniques for the linear and nonlinear buckling of bi-directional functionally graded nanotubes based on the nonlocal strain gradient theory and high-order beam theory", Eng. Anal. Bound. Elem., 143, 124-136. https://doi.org/10.1016/j.enganabound.2022.06.007
  60. Wang, Z., Zhou, T., Zhang, S., Sun, C., Li, J. and Tan, J. (2023), "Bo-LSTM based cross-sectional profile sequence progressive prediction method for metal tube rotate draw bending", Adv. Eng. Inform., 58, p. 102152. https://doi.org/10.1016/j.aei.2023.102152
  61. Wang, C., Habibi, M. and Mahmoudi, T. (2024a), "Stability analysis of the nonuniform functionally graded cylindrical small-scale beam structures: Application in sport structures", Steel Compos. Struct., Int. J., 52(1), 15-29. https://doi.org/10.12989/scs.2024.52.1.015
  62. Wang, C., Habibi, M. and Mahmoudi, T. (2024b), "Stability analysis of the nonuniform functionally graded cylindrical small-scale beam structures: Application in sport structures", Steel Compos. Struct., Int. J., 52(1), 15-29. https://doi.org/10.12989/scs.2024.52.1.015
  63. Wang, J., Han, J., Zhu, C., Lu, W., Zhang, Y., He, X., Liu, K. and Chen, Y. (2024c), "Structural optimization and engineering application of concrete-filled steel tubular composite supports", Eng. Fail. Anal., 159, p. 108082. https://doi.org/10.1016/j.engfailanal.2024.108082
  64. Wang, T., Zong, G., Zhao, X. and Xu, N. (2024d), "Data-driven-based sliding-mode dynamic event-triggered control of unknown nonlinear systems via reinforcement learning", Neurocomputing, 601, p. 128176. https://doi.org/10.1016/j.neucom.2024.128176
  65. Wang, W., Zhang, J., Habibi, M. and Albaijan, I. (2024e), "Stretchable-thickness model for dynamic responses of graphene origami reinforced badminton sport plate", Mech. Adv. Mater. Struct., 1-13. https://doi.org/10.1080/15376494.2024.2373976
  66. Willard, J., Jia, X., Xu, S., Steinbach, M. and Kumar, V. (2020), "Integrating physics-based modeling with machine learning: A survey", arXiv preprint arXiv:2003.04919. 1(1), 1-34. https://doi.org/10.1145/1122445.1122456
  67. Wu, J. and Habibi, M. (2022), "Dynamic simulation of the ultra-fast-rotating sandwich cantilever disk via finite element and semi-numerical methods", Eng. Comput., 38(5), 4127-4143. https://doi.org/10.1007/s00366-021-01396-6
  68. Wu, X., Ding, S., Niu, B., Xu, N. and Zhao, X. (2024), "Predefined-time event-triggered adaptive tracking control for strict-feedback nonlinear systems with full-state constraints", Int. J. General Syst., 53(3), 352-380. https://doi.org/10.1080/03081079.2023.2276710
  69. Yan, C., Zhang, T., Zheng, T. and Mahmoudi, T. (2024), "Stability characteristic of bi-directional FG nano cylindrical imperfect composite: Improving the performance of sports bikes using carbon nanotubes", Steel Compos. Struct., Int. J., 50(4), 459-474. https://doi.org/10.12989/scs.2024.50.4.459
  70. Yao, Y., Huang, H., Zhang, W., Ye, Y., Xin, L. and Liu, Y. (2022), "Seismic performance of steel-PEC spliced frame beam", J. Constr. Steel Res., 197, p. 107456. https://doi.org/10.1016/j.jcsr.2022.107456
  71. Yin, J., Zou, Y., Li, J., Zhang, W., Li, X. and Habibi, M. (2024), "Dynamic stability and frequency responses of the tilted curved nanopipes in a supersonic airflow via 2D hybrid nonlocal strain gradient theory", Eng. Struct., 301, p. 117240. https://doi.org/10.1016/j.engstruct.2023.117240
  72. Yu, H., Habibi, M., Motamedi, K., Semirumi, D.T. and Ghorbani, A. (2023), "Utilizing stem cells in reconstructive treatments for sports injuries: An innovative approach", Tissue Cell, 83, p. 102152. https://doi.org/10.1016/j.tice.2023.102152
  73. Yu, C., Lin, P., Wu, Z., Habibi, M. and Zhang, W. (2024), "Multi-load effect on the deformation analysis of composite nano reinforced origami sandwich panel", Mech. Adv. Mater. Struct., 1-19. https://doi.org/10.1080/15376494.2024.2367015
  74. Zhang, C., Zhu, D., Luo, Q., Liu, L., Liu, D., Yan, L. and Zhang, Y. (2017), "Major factors controlling fracture development in the Middle Permian Lucaogou Formation tight oil reservoir, Junggar Basin, NW China", J. Asian Earth Sc., 146, 279-295. https://doi.org/10.1016/j.jseaes.2017.04.032
  75. Zhang, J., Lin, G., Vaidya, U. and Wang, H. (2023a), "Past, present and future prospective of global carbon fibre composite developments and applications", Compos. Part B: Eng., 250, p. 110463. https://doi.org/10.1016/j.compositesb.2022.110463
  76. Zhang, P., Song, J. and Mahmoudi, T. (2023b), "Simulation and modeling for stability analysis of functionally graded nonuniform pipes with porosity-dependent properties", Steel Compos. Struct., Int. J., 48(2), 235-250. https://doi.org/10.12989/scs.2023.48.2.235.
  77. Zhang, Q., Zou, X., Wang, Y. and Habibi, M. (2023c), "Study on photocatalytic, electric, and sensing behavior of Co- and Ag-codoped tin dioxide (SnO2) nano particles", Mater. Sci. Eng.: B, 296, p. 116687. https://doi.org/10.1016/j.mseb.2023.116687.
  78. Zhang, S., Lai, Y., Chen, K., Habibi, M., Khorami, M. and Haider Mussa, Z. (2023d), "Influence of MWCNT's waviness and aggregation factors on wave dispersion response of MWCNT-strengthened nanocomposite curved beam", Structures, 53, 1239-1249. https://doi.org/10.1016/j.istruc.2023.04.024
  79. Zhang, C., Wen, H., Wang, X., Wen, L., Shen, A., Zhou, G., Wang, Q., She, M., Ma, C., Qiao, Z., Liu, D. and Ma, Y. (2024a), "Formational stages of natural fractures revealed by U-Pb dating and C-O-Sr-Nd isotopes of dolomites in the Ediacaran Dengying Formation, Sichuan Basin, southwest China", GSA Bulletin, 136(11-12), 4671-4688. https://doi.org/10.1130/B37360.1
  80. Zhang, D., Huang, X., Wang, T., Habibi, M., Albaijan, I. and Toghroli, E. (2024b), "Dynamic stability improvement in spinning FG-piezo cylindrical structure using PSO-ANN and firefly optimization algorithm", Mater. Sci. Eng.: B, 302, p. 117210. https://doi.org/10.1016/j.mseb.2024.117210
  81. Zhang, Q., Xie, M., Zhou, D., Habibi, M. and Khorami, M. (2024c), "Bending responses of graphene nanoplatelets reinforced sandwich cylindrical micro panel with piezoelectric layers", Mech. Adv. Mater. Struct., 1-16. https://doi.org/10.1080/15376494.2024.2385008
  82. Zhang, W., Lin, J., Huang, Y., Lin, B. and Liu, X. (2024d), "Experimental and numerical studies on flexural performance of composite beams under cyclic loading", Structures, 70, p. 107728. https://doi.org/10.1016/j.istruc.2024.107728
  83. Zhang, X., Li, J., Cui, Y., Habibi, M., Ali, H.E., Albaijan, I. and Mahmoudi, T. (2023e), "Static analysis of 2D-FG nonlocal porous tube using gradient strain theory and based on the first and higher-order beam theory", Steel Compos. Struct., Int. J., 49(3), 293-306. https://doi.org/10.12989/scs.2023.49.3.293
  84. Zhang, Z., Du, J. and Mahmoudi, T. (2023f), "Green synthesis of silver nanoparticles to the microbiological corrosion deterrence of oil and gas pipelines buried in the soil", Adv. Nano Res., Int. J., 15(4), 355-366. https://doi.org/10.12989/anr.2023.15.4.355
  85. Zhao, H., Wang, H., Chang, X., Ahmad, A.M. and Zhao, X. (2024a), "Neural network-based adaptive critic control for saturated nonlinear systems with full state constraints via a novel event-triggered mechanism", Inform. Sci., 675, p. 120756. https://doi.org/10.1016/j.ins.2024.120756
  86. Zhao, J., Wan, L., Habibi, M. and Brahmia, A. (2024b), "An adaptive neuro-fuzzy approach using IoT data in predicting springback in ultra-thin stainless steel sheets with consideration of grain size", Adv. Nano Res., Int. J., 17(2), 109-124. https://doi.org/10.12989/.2024.17.2.109
  87. Zhiqiang, S., Aiyun, L., Daichang, Z., Shuangjun, L., Habibi, M., Xiaoling, F. and Albaijan, I. (2024), "Application of a folded nanostructure reinforcement for the pole vault curved shell", Mech. Adv. Mater. Struct., 1-15. https://doi.org/10.1080/15376494.2024.2375368
  88. Zhou, X., Lu, D., Du, X., Wang, G. and Meng, F. (2020), "A 3D non-orthogonal plastic damage model for concrete", Comput. Methods Appl. Mech. Eng., 360, p. 112716. https://doi.org/10.1016/j.cma.2019.112716
  89. Zhu, L., Ren, H., Habibi, M., Mohammed, K.J. and Khadimallah, M.A. (2022), "Predicting the environmental economic dispatch problem for reducing waste nonrenewable materials via an innovative constraint multi-objective Chimp Optimization Algorithm", J. Cleaner Product., 365, p. 132697. https://doi.org/10.1016/j.jclepro.2022.132697
  90. Zisong, Z. and Habibi, M. (2024), "AI-assisted prediction of St14 steel sheets formability: Neural-fuzzy systems and crystal plasticity assessments", Structures, 65, p. 106633. https://doi.org/10.1016/j.istruc.2024.106633