Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Deflection aware smart structures by artificial intelligence algorithm

  • Qingyun Gao (FAIR FRIEND Institute of Intelligent Manufacturing, Hangzhou Vocational & Technical College) ;
  • Yun Wang (FAIR FRIEND Institute of Intelligent Manufacturing, Hangzhou Vocational & Technical College) ;
  • Zhimin Zhou (FAIR FRIEND Institute of Intelligent Manufacturing, Hangzhou Vocational & Technical College) ;
  • Khalid A. Alnowibet (Statistics and Operations Research Department, College of Science, King Saud University)
  • Received : 2023.06.12
  • Accepted : 2024.05.11
  • Published : 2024.05.25
⟨ Previous Next ⟩

Abstract

There has been an increasing interest in the construction of smart buildings that can actively monitor and react to their surroundings. The capacity of these intelligent structures to precisely predict and respond to deflection is a crucial feature that guarantees both their structural soundness and efficiency. Conventional techniques for determining deflection often depend on intricate mathematical models and computational simulations, which may be time- and resource-consuming. Artificial intelligence (AI) algorithms have become a potent tool for anticipating and controlling deflection in intelligent structures in response to these difficulties. The term "deflection-aware smart structures" in this sense refers to constructions that have AI algorithms installed that continually monitor and analyses deflection data in order to proactively detect any problems and take appropriate action. These structures anticipate deflection across a range of operating circumstances and environmental factors by using cutting-edge AI approaches including deep learning, reinforcement learning, and neural networks. AI systems are able to predict real-time deflection with high accuracy by using data from embedded sensors and actuators. This capability enables the systems to identify intricate patterns and linkages. Intelligent buildings have the potential to self-correct in order to reduce deflection and maximize performance. In conclusion, the development of deflection-aware smart structures is a major stride forward for structural engineering and has enormous potential to enhance the performance, safety, and dependability of designed systems in a variety of industries.

Keywords

Acknowledgement

The authors extend their appreciation to King Saud University, Saudi Arabia for funding this work through Researchers Supporting Project number (RSP2024R305), King Saud University, Riyadh, Saudi Arabia.

References

  1. Al Nuaimi, E., Al Neyadi, H., Mohamed, N. and Al-Jaroodi, J. (2015), "Applications of big data to smart cities", J. Internet Servic. Applicat., 6, 25. https://doi.org/10.1186/s13174-015-0041-5
  2. Bhardwaj, K.K., Banyal, S., Sharma, D.K. and Al-Numay, W. (2022), "Internet of things based smart city design using fog computing and fuzzy logic", Sustain. Cities Soc., 79, 103712. https://doi.org/10.1016/j.scs.2022.103712
  3. Bibri, S.E. and Krogstie, J. (2017a), "Smart sustainable cities of the future: An extensive interdisciplinary literature review", Sustain. Cities Soc., 31, 183-212. https://doi.org/10.1016/j.scs.2017.02.016
  4. Bibri, S.E. and Krogstie, J. (2017b), "ICT of the new wave of computing for sustainable urban forms: Their big data and context-aware augmented typologies and design concepts", Sustain. Cities Soc., 32, 449-474. https://doi.org/10.1016/j.scs.2017.04.012
  5. Cao, Y. and AlKubaisy, Z.M. (2022), "Integration of computer-based technology in smart environment in an EFL structures", Smart Struct. Syst., Int. J., 29(2), 375-387. https://doi.org/10.12989/sss.2022.29.2.375
  6. Caragliu, A., Del Bo, C. and Nijkamp, P. (2013), "Smart cities in Europe", In: Creating Smart-er Cities., 18, 65-82.
  7. Chase, J.G., Tomlinson, H., Rodgers, G.W., Xu, C., Avot, V. and Zhou, C. (2023), "Accuracy and robustness of hysteresis loop analysis in the identification and monitoring of plastic stiffness for highly nonlinear pinching structures", Smart Struct. Syst., Int. J., 31(2), 101-111. https://doi.org/10.12989/sss.2023.31.2.101
  8. Chen, C.W. (2023), "Can smart cities bring happiness to promote sustainable development? Contexts and clues of subjective wellbeing and urban livability", Develop. Built Environ., 13, 100108. https://doi.org/10.1016/j.dibe.2022.100108
  9. Chen, L., Xiong, H., He, Y., Li, X. and Kong, Q. (2022), "Monitoring moisture content of timber structures using PZT-enabled sensing and machine learning", Smart Struct. Syst., Int. J., 29(4), 589-598. https://doi.org/10.12989/sss.2022.29.4.589
  10. Chen, C., Yang, H., Song, K., Liang, D., Zhang, Y. and Ni, J. (2023), "Dissolution feature differences of carbonate rock within hydro-fluctuation belt located in the Three Gorges Reservoir Area", Eng. Geol., 327, 107362. https://doi.org/10.1016/j.enggeo.2023.107362
  11. Chu, Z., Cheng, M. and Yu, N.N. (2021), "A smart city is a less polluted city", Technological Forecasting and Social Change., 172, 121037. https://doi.org/10.1016/j.techfore.2021.121037
  12. Durbin, F. (1974), "Numerical inversion of Laplace transforms: an efficient improvement to Dubner and Abate's method", Comput. J., 17, 371-376. https://doi.org/10.1093/comjnl/17.4.371
  13. Feng, Q. and Liang, Y. (2022), "Development of piezoelectric-based technology for application in civil structural health monitoring", Earthq. Res. Adv., 3(2), 100154. https://doi.org/10.1016/j.eqrea.2022.100154
  14. Feng, Y., Mohammadi, M., Wang, L., Rashidi, M. and Mehrabi, P. (2021), "Application of artificial intelligence to evaluate the fresh properties of self-consolidating concrete", Mater., 14, 4885. https://doi.org/10.3390/ma14174885
  15. Firouzianhaji, A., Usefi, N., Samali, B. and Mehrabi, P. (2021), "Shake table testing of standard cold-formed steel storage rack", Appl. Sci., 11, 1821. https://doi.org/10.3390/app11041821
  16. Gilhooley, D.F., Batra, R.C., Xiao, J.R., McCarthy, M.A. and Gillespie Jr, J.W. (2007), "Analysis of thick functionally graded plates by using higher-order shear and normal deformable plate theory and MLPG method with radial basis functions", Compos. Struct., 80, 539-552. https://doi.org/10.1016/j.compstruct.2006.07.007
  17. Gordan, M., Sabbagh-Yazdi, S.R., Ismail, Z., Ghaedi, K., Carroll, P., McCrum, D. and Samali, B. (2022), "State-of-the-art review on advancements of data mining in structural health monitoring", Measur., 193, 110939. https://doi.org/10.1016/j.measurement.2022.110939
  18. Guo, H. and Zhang, J. (2023), "Expansion of sandwich tubes with metal foam core under axial compression", J. Appl. Mech., 90, 051008. https://doi.org/10.1115/1.4056686
  19. Guo, Y., Tang, Z. and Guo, J. (2020), "Could a smart city ameliorate urban traffic congestion? A quasi-natural experiment based on a smart city pilot program in China", Sustainab., 12, 2291. https://doi.org/10.3390/su12062291
  20. Han, S., Zheng, D., Mehdizadeh, B., Nasr, E.A., Khandaker, M.U., Salman, M. and Mehrabi, P. (2023a), "Sustainable design of self-consolidating green concrete with partial replacements for cement through neural-network and fuzzy technique", Sustainab., 15, 4752. https://doi.org/10.3390/su15064752
  21. Han, S., Zhu, Z., Mortazavi, M., El-Sherbeeny, A.M. and Mehrabi, P. (2023b), "Analytical assessment of the structural behavior of a specific composite floor system at elevated temperatures using a newly developed hybrid intelligence method", Build., 13, 799. https://doi.org/10.3390/buildings13030799
  22. He, Z., Li, W., Salehi, H., Zhang, H., Zhou, H. and Jiao, P. (2022), "Integrated structural health monitoring in bridge engineering", Automat. Constr., 136, 104168. https://doi.org/10.1016/j.autcon.2022.104168
  23. He, L., Maalla, A., Zhou, X. and Tang, H. (2024), "Buckling and post-buckling of anisogrid lattice-core sandwich plates with nanocomposite skins", Thin-Wall. Struct., 199, 111828. https://doi.org/10.1016/j.tws.2024.111828
  24. Herath, H.M.K.K.M.B. and Mittal, M. (2022), "Adoption of artificial intelligence in smart cities: A comprehensive review", Int. J. Inform. Manag. Data Insights., 2, 100076. https://doi.org/10.1016/j.jjimei.2022.100076
  25. Horne, J., Beddingfield, E., Knapp, M., Mitchell, S., Crawford, L., Mills, S.B., Wrist, A., Zhang, S. and Summers, R.M. (2020), "Caffeine and Theophylline Inhibit β-Galactosidase Activity and Reduce Expression in Escherichia coli", ACS omega, 5, 32250-32255. https://doi.org/10.1021/acsomega.0c03909
  26. Hu, D., Sun, H., Mehrabi, P., Ali, Y.A. and Al-Razgan, M. (2023), "Application of artificial intelligence technique in optimization and prediction of the stability of the walls against wind loads in building design", Mech. Adv. Mater. Struct., 1-18. https://doi.org/10.1080/15376494.2023.2206208
  27. Jangid, R.S. (2022), "Optimum parameters and performance of tuned mass damper-inerter for base-isolated structures", Smart Struct. Syst., Int. J., 29(4), 549-560. https://doi.org/10.12989/sss.2022.29.4.549
  28. Ju, M., Dou, Z., Li, J.W., Qiu, X., Shen, B., Zhang, D., Yao, F.Z., Gong, W. and Wang, K. (2023), "Piezoelectric materials and sensors for structural health monitoring: fundamental aspects, current status, and future perspectives", Sensors, 23, 543. https://doi.org/10.3390/s23010543
  29. Khan, S. (2022), "Barriers of big data analytics for smart cities development: a context of emerging economies", Int. J. Manag. Sci. Eng. Manag., 17, 123-131. https://doi.org/10.1080/17509653.2021.1997662
  30. Krishankumar, R. and Ecer, F. (2023), "Selection of IoT service provider for sustainable transport using q-rung orthopair fuzzy CRADIS and unknown weights", Appl. Soft Comput., 132, 109870. https://doi.org/10.1016/j.asoc.2022.109870
  31. Lee, Y.Y., Zhao, X. and Liew, K.M. (2009), "Thermoelastic analysis of functionally graded plates using the element-free kp-Ritz method", Smart Mater. Struct., 18, 035007. https://doi.org/10.1088/0964-1726/18/3/035007
  32. Liu, B., Yang, H. and Karekal, S. (2020), "Effect of water content on argillization of mudstone during the tunnelling process", Rock Mech. Rock Eng., 53, 799-813. https://doi.org/10.1007/s00603-019-01947-w
  33. Liu, J., Mohammadi, M., Zhan, Y., Zheng, P., Rashidi, M. and Mehrabi, P. (2021), "Utilizing artificial intelligence to predict the superplasticizer demand of self-consolidating concrete incorporating pumice, slag, and fly ash powders", Mater., 14, 6792. https://doi.org/10.3390/ma14226792
  34. Luo, G., He, K., Wang, Y., Zhou, W., Chen, K., Zhao, L., Xu, T., Li, Z., Li, M., Yang, P. and Wang, K. (2023), "Small blind-area, high-accuracy ultrasonic rangefinder using a broadband multi-frequency piezoelectric micromachined ultrasonic transducer array", Measur. Sci. Technol., 34, 125140. https://doi.org/10.1088/1361-6501/acf682
  35. Mao, J.J. and Zhang, W. (2018), "Linear and nonlinear free and forced vibrations of graphene reinforced piezoelectric composite plate under external voltage excitation", Compos. Struct., 203, 551-565. https://doi.org/10.1016/j.compstruct.2018.06.076
  36. Mehrabi, P., Honarbari, S., Rafiei, S., Jahandari, S. and Alizadeh Bidgoli, M. (2021a), "Seismic response prediction of FRC rectangular columns using intelligent fuzzy-based hybrid metaheuristic techniques", J. Ambient Intell. Humaniz. Comput., 12, 10105-10123. https://doi.org/10.1007/s12652-020-02776-4
  37. Mehrabi, P., Shariati, M., Kabirifar, K., Jarrah, M., Rasekh, H., Trung, N.T., Shariati, A. and Jahandari, S. (2021b), "Effect of pumice powder and nano-clay on the strength and permeability of fiber-reinforced pervious concrete incorporating recycled concrete aggregate", Constr. Build. Mater., 287, 122652. https://doi.org/10.1016/j.conbuildmat.2021.122652
  38. Mi, C., Liu, Y., Zhang, Y., Wang, J., Feng, Y. and Zhang, Z. (2023), "A vision-based displacement measurement system for foundation pit", IEEE Transact. Instrument. Measur., 72. https://doi.org/10.1109/TIM.2023.3311069
  39. Mishra, M., Lourenco, P.B. and Ramana, G.V. (2022), "Structural health monitoring of civil engineering structures by using the internet of things: A review", J. Build. Eng., 48, 103954. https://doi.org/10.1016/j.jobe.2021.103954
  40. Mitchell, J.A. and Reddy, J.N. (1995), "A refined hybrid plate theory for composite laminates with piezoelectric laminae", Int. J. Solids Struct., 32, 2345-2367. https://doi.org/10.1016/0020-7683(94)00229-P
  41. Mock, M.B., Zhang, S., Pniak, B., Belt, N., Witherspoon, M. and Summers, R.M. (2021), "Substrate promiscuity of the NdmCDE N7-demethylase enzyme complex", Biotechnol. Notes, 2, 18-25. https://doi.org/10.1016/j.biotno.2021.05.001
  42. Mock, M.B., Zhang, S., Pakulski, K., Hutchison, C., Kapperman, M., Dreischarf, T. and Summers, R.M. (2024), "Production of 1-methylxanthine via the biodegradation of theophylline by an optimized Escherichia coli strain", J. Biotechnol., 379, 25-32. https://doi.org/10.1016/j.jbiotec.2023.11.005
  43. Nguyen, S.N., Cho, M., Kim, J.S. and Han, J.W. (2022), "Improved thermo-mechanical-viscoelastic analysis of laminated composite structures via the enhanced Lo-Christensen-Wu theory in the laplace domain", Mech. Adv. Mater. Struct., 30(14), 2899-2915. https://doi.org/10.1080/15376494.2022.2064571
  44. Nguyen-Xuan, H., Tran, L.V., Nguyen-Thoi, T. and Vu-Do, H.C. (2011), "Analysis of functionally graded plates using an edge-based smoothed finite element method", Compos. Struct., 93, 3019-3039. https://doi.org/10.1016/j.compstruct.2011.04.028
  45. Qiu, Y. (2019), "Estimation of tail risk measures in finance: Approaches to extreme value mixture modeling", Doctoral dissertation; Johns Hopkins University, Baltimore, MD, USA.
  46. Qiu, Y. and Wang, J. (2024), "A Machine Learning Approach to Credit Card Customer Segmentation for Economic Stability", Presented at the Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, Tianjin, China, October.
  47. Quan, X. and Solheim, M.C. (2023), "Public-private partnerships in smart cities: A critical survey and research agenda", City Culture Soc., 32, 100491. https://doi.org/10.1016/j.ccs.2022.100491
  48. Rahimi, A., Alibeigloo, A. and Safarpour, M. (2020), "Three-dimensional static and free vibration analysis of graphene platelet-reinforced porous composite cylindrical shell", J. Vib. Control, 26, 1627-1645. https://doi.org/10.1177/1077546320902340
  49. Rani, S. and Kumar, R. (2022), "Bibliometric review of actuators: Key automation technology in a smart city framework", Materials Today: Proceedings., International Conference on Latest Developments in Materials & Manufacturing, 60, 1800-1807. https://doi.org/10.1016/j.matpr.2021.12.469
  50. Shafiullah, M., Rahman, S., Imteyaz, B., Aroua, M.K., Hossain, M.I. and Rahman, S.M. (2023), "Review of smart city energy modeling in Southeast Asia", Smart Cities., 6, 72-99. https://doi.org/10.3390/smartcities6010005
  51. She, A., Wang, L., Peng, Y. and Li, J. (2023), "Structural reliability analysis based on improved wolf pack algorithm AK-SS", In: Structures, 57, 105289. https://doi.org/10.1016/j.istruc.2023.105289
  52. Shetty, S., Banerjee, S., Tallur, S. and Desai, Y.M. (2023), "Real-time monitoring of residual strength in corroding steel reinforcement using ultrasonic-guided waves and multi-physics modelling", J. Adhes. Sci. Technol., 37(20), 2841-2860. https://doi.org/10.1080/01694243.2022.2159292
  53. Song, M., Kitipornchai, S. and Yang, J. (2017), "Free and forced vibrations of functionally graded polymer composite plates reinforced with graphene nanoplatelets", Compos. Struct., 159, 579-588. https://doi.org/10.1016/j.compstruct.2016.09.070
  54. Song, K., Yang, H., Liang, D., Chen, L. and Jaboyedoff, M. (2024), "Step-like displacement prediction and failure mechanism analysis of slow-moving reservoir landslide", J. Hydrol., 628, 130588. https://doi.org/10.1016/j.jhydrol.2023.130588
  55. Taheri, E., Firouzianhaji, A., Usefi, N., Mehrabi, P., Ronagh, H. and Samali, B. (2019), "Investigation of a method for strengthening perforated cold-formed steel profiles under compression loads", Appl. Sci., 9, 5085. https://doi.org/10.3390/app9235085
  56. Taheri, E., Firouzianhaji, A., Mehrabi, P., Vosough Hosseini, B. and Samali, B. (2020), "Experimental and numerical investigation of a method for strengthening cold-formed steel profiles in bending", Appl. Sci., 10, 3855. https://doi.org/10.3390/app10113855
  57. Taheri, E., Mehrabi, P., Rafiei, S. and Samali, B. (2021), "Numerical evaluation of the upright columns with partial reinforcement along with the utilisation of neural networks with combining feature-selection method to predict the load and displacement", Appl. Sci., 11, 11056. https://doi.org/10.3390/app112211056
  58. Toghroli, A., Mehrabi, P., Shariati, M., Trung, N.T., Jahandari, S. and Rasekh, H. (2020), "Evaluating the use of recycled concrete aggregate and pozzolanic additives in fiber-reinforced pervious concrete with industrial and recycled fibers", Constr. Build. Mater., 252, 118997. https://doi.org/10.1016/j.conbuildmat.2020.118997
  59. Vahidnia, M.H. (2022), "Citizen participation through volunteered geographic information as equipment for a smart city to monitor urban decay", Environ. Monitor. Assess., 195, 181. https://doi.org/10.1007/s10661-022-10796-0
  60. Wang, Q. and Liew, K.M. (2003), "Analysis of wave propagation in piezoelectric coupled cylinder affected by transverse shear and rotary inertia", Int. J. Solids Struct., 40, 6653-6667. https://doi.org/10.1016/S0020-7683(03)00422-0
  61. Wang, M. and Zhou, T. (2023), "Does smart city implementation improve the subjective quality of life? Evidence from China", Technol. Soc., 72, 102161. https://doi.org/10.1016/j.techsoc.2022.102161
  62. Wang, N., Li, X., Lian, X., Zhuang, Q., Wang, J., Li, J., Qian, H., Miao, K., Wang, Y., Luo, X. and Feng, G. (2024), "Acetate Ions Facilitated Immobilization of Highly Dispersed Transition Metal Oxide Nanoclusters in Mesoporous Silica", Inorganic Chemistry, 63(9), 4393-4403. https://doi.org/10.1021/acs.inorgchem.4c00024
  63. Wu, J., Yang, Y., Mehrabi, P. and Nasr, E.A. (2023), "Efficient machine-learning algorithm applied to predict the transient shock reaction of the elastic structure partially rested on the viscoelastic substrate", Mech. Adv. Mater. Struct., 1-25. https://doi.org/10.1080/15376494.2023.2183289
  64. Xia, D., Alexander, A.K., Isbell, A., Zhang, S., Ou, J. and Liu, X.M. (2017), "Establishing a co-culture system for Clostridium cellulovorans and Clostridium aceticum for high efficiency biomass transformation", J. Sci. Heal. Univ. Ala., 14, 8-13.
  65. Yang, H., Song, K. and Zhou, J. (2022), "Automated recognition model of geomechanical information based on operational data of tunneling boring machines", Rock Mech. Rock Eng., 55, 1499-1566. https://doi.org/10.1007/s00603-021-02723-5
  66. Yang, H., Chen, C., Ni, J. and Karekal, S. (2023a), "A hyperspectral evaluation approach for quantifying salt-induced weathering of sandstone", Sci. Total Environ., 885, 163886. https://doi.org/10.1016/j.scitotenv.2023.163886
  67. Yang, H., Ni, J., Chen, C. and Chen, Y. (2023b), "Weathering assessment approach for building sandstone using hyperspectral imaging technique", Heritage Sci.., 11, 70. https://doi.org/10.1186/s40494-023-00914-7
  68. Zhang, X., Tang, Y., Zhang, F. and Lee, C.S. (2016), "A novel aluminum-graphite dual-ion battery", Adv. Energy Mater., 6(11), 1502588. https://doi.org/10.1002/aenm.201502588
  69. Zhang, J., Wang, X., Zhou, L., Liu, G., Adroja, D.T., da Silva, I., Demmel, F., Khalyavin, D., Sannigrahi, J., Nair, H.S. and Duan, L. (2022), "A ferrotoroidic candidate with well-separated spin chains", Adv. Mater., 34(12), 2106728. https://doi.org/10.1002/adma.202106728
  70. Zhong, T., Feng, X., Zhang, Y. and Zhou, J. (2022), "Experimental study on the effect of EC-TMD on the vibration control of plant structure of PSPPs", Smart Struct. Syst., Int. J., 29(3), 457-473. https://doi.org/10.12989/sss.2022.29.3.457
  71. Zhou, J., Qi, Q., Liu, Q., Wang, Z. and Ren, J. (2024), "Determining residual stress profile induced by end milling from measured thin plate deformation", Thin-Wall. Struct., 200, 111862. https://doi.org/10.1016/j.tws.2024.111862
  72. Zhu, Q., Chen, J., Gou, G., Chen, H. and Li, P. (2017), "Ameliorated longitudinal critically refracted-Attenuation velocity method for welding residual stress measurement", J. Mater. Process. Technol., 246, 267-275. https://doi.org/10.1016/j.jmatprotec.2017.03.022