DOI QR코드

DOI QR Code

In-situ stresses ring hole measurement of concrete optimized based on finite element and GBDT algorithm

  • Chen Guo (School of Human Settlements and Civil Engineering, Xi'an Jiaotong University) ;
  • Zheng Yang (School of Human Settlements and Civil Engineering, Xi'an Jiaotong University) ;
  • Yanchao Yue (School of Human Settlements and Civil Engineering, Xi'an Jiaotong University) ;
  • Wenxiao Li (School of Human Settlements and Civil Engineering, Xi'an Jiaotong University) ;
  • Hantao Wu (School of Human Settlements and Civil Engineering, Xi'an Jiaotong University)
  • 투고 : 2024.01.01
  • 심사 : 2024.03.11
  • 발행 : 2024.10.25

초록

The in-situ stresses of concrete are an essential index for assessing the safety performance of concrete structures. Conventional methods for pore pressure release often face challenges in selecting drilling ring parameters, uncontrollable stress release, and unstable detection accuracy. In this paper, the parameters affecting the results of the concrete ring hole stress release method are cross-combined, and finite elements are used to simulate the combined parameters and extract the stress release values to establish a training set. The GridSearchCV function is utilized to determine the optimal hyperparameters. The mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) are used as evaluation indexes to train the gradient boosting decision tree (GBDT) algorithm, and the other three common algorithms are compared. The RMSE of the GBDT algorithm for the test set is 4.499, and the R2 of the GBDT algorithm for the test set is 0.962, which is 9.66% higher than the R2 of the best-performing comparison algorithm. The model generated by the GBDT algorithm can accurately calculate the concrete in-situ stresses based on the drilling ring parameters and the corresponding stress release values and has a high accuracy and generalization ability.

키워드

참고문헌

  1. Ali-Benyahia, K., Kenai, S., Ghrici, M., Sbartai, Z.M. and Elachachi, S.M. (2023), "Analysis of the accuracy of in-situ concrete characteristic compressive strength assessment in real structures using destructive and non-destructive testing methods", Constr. Build. Mater., 366, 130161. https://doi.org/101016/jconbuildmat2022130161. 101016/jconbuildmat2022130161
  2. Allain, M., Ple, O., Prime, N., Roux, E. and Vacher, P. (2023), "In situ DIC method to determine stress state in reinforced concrete structures", Measure., 210, 112483. https://doi.org/101016/jmeasurement2023112483. 101016/jmeasurement2023112483
  3. Bagher Shemirani, A., and Lawaf, M.P. (2024), "Prediction of tensile strength of concrete using the machine learning methods", Asian J. Civil Eng., 25(2), 1207-1223. https://doi.org/10.1007/s42107-023-00837-5.
  4. Bengio, Y. and Grandvalet, Y. (2004), "No unbiased estimator of the variance of k-fold cross-validation", J. Mach. Learn. Res., 5, 1089-1105.
  5. Chen, S., Zhang, H., Zykova, K.I., Touchaei, H.G., Yuan, C., Moayedi, H. and Le, B.N. (2023), "Computational intelligence models for predicting the frictional resistance of driven pile foundations in cold regions", Comput. Concrete, 32(2), 217-232. https://doi.org/10.12989/cac.2023.32.2.217.
  6. Coelho, S.A. and Araujo, D.L. (2023), "Nonlinear finite element model of the beam-to-column connection for precast concrete frames with high ratio of the continuity tie bars", Comput. Concrete, 31(1), 53-69. https://doi.org/10.12989/cac.2023.31.1.053.
  7. Dabli, A., Bambole, A. and Bajoria, K. (2020), "Evaluation of in-place stress in concrete by incremental hole drilling", ACI Mater. J., 117, 27-35. https://doi.org/10.14359/51724612.
  8. Deng, N.C. and Tang, P.F. (2020) (2020), "Research on in situ stress measurements in reinforced concrete beams based on the core-drilling method", Adv. Civil Eng., 2020, 1-11. https://doi.org/101155/2020/8832614. 101155/2020/8832614
  9. Eidgahee, D.R., Soleymani, A., Hasani, H., Kontoni, D.P.N. and Jahangir, H. (2023), "Flexural capacity estimation of FRP reinforced T-shaped concrete beams via soft computing techniques", Comput. Concrete, 32(1), 1-13. https://doi.org/10.12989/cac.2023.32.1.001.
  10. Elmo, D. and Mitelman, A. (2021), "Modeling concrete fracturing using a hybrid finite-discrete element method", Comput. Concrete, 27(4), 297-304. https://doi.org/10.12989/cac.2021.27.4.297.
  11. Erdal, H., Erdal, M., Simsek, O. and Erdal, H.I. (2018), "Prediction of concrete compressive strength using non-destructive test results", Comput. Concrete, 21(4), 407-417. https://doi.org/10.12989/cac.2018.21.4.407.
  12. Friedman, J.H. (2002), "Stochastic gradient boosting", Comput. Stat. Data Anal., 38(4), 367-378. https://doi.org/101016/S0167-9473(01)00065-2. 101016/S0167-9473(01)00065-2
  13. Haavisto, J., Husso, A. and Laaksonen, A. (2021), "Compressive strength of core specimens drilled from concrete test cylinders", Struct. Concrete, 22(S1), E683-E695. https://doi.org/101002/suco202000428. 101002/suco202000428
  14. Idriss, L.K. and Owais, M. (2024), "Global sensitivity analysis for seismic performance of shear wall with high-strength steel bars and recycled aggregate concrete", Constr. Build. Mater., 411, 134498. https://doi.org/10.1016/j.conbuildmat.2023.134498.
  15. Jang, D., Bang, J., Yoon, H.N., Seo, J., Jung, J., Jang, J.G. and Yang, B. (2022), "Deep learning-based LSTM model for prediction of long-term piezoresistive sensing performance of cement-based sensors incorporating multi-walled carbon nanotube", Comput. Concrete, 30(5), 301-310. https://doi.org/10.12989/cac.2022.30.5.301.
  16. Ji, Y., Chen, A., Chen, Y., Han, X., Li, B., Gao, Y., Liu, C. and Xie, J. (2023), "A state-of-the-art review of concrete strength detection/monitoring methods: With special emphasis on PZT transducers", Constr. Build. Mater., 362, 129742. https://doi.org/101016/jconbuildmat2022129742. 101016/jconbuildmat2022129742
  17. Kumar, A., Arora, H.C., Kapoor, N.R., Kontoni, D.P.N., Kumar, K., Jahangir, H. and Bhushan, B. (2023), "Practical applicable model for estimating the carbonation depth in fly-ash based concrete structures by utilizing adaptive neuro-fuzzy inference system", Comput. Concrete, 32(2), 119-138. https://doi.org/10.12989/cac.2023.32.2.119.
  18. Kumar, A., Arora, H.C., Kumar, K., Garg, H. and Jahangir, H. (2023), "Development of efficient prediction model of FRP-to-concrete bond strength using curve fitting and ANFIS methods", Arab. J. Sci. Eng., 49(4), 5129-5158. https://doi.org/10.1007/s13369-023-08328-0.
  19. Li, B., Fang, H., Yang, K., Zhang, X., Du, X., Wang, N. and Guo, X. (2022), "Impact of erosion voids and internal corrosion on concrete pipes under traffic loads", Tunnel. Undergr. Sp. Technol., 130, 104761. https://doi.org/101016/jtust2022104761. 101016/jtust2022104761
  20. Li, F., Wu, P. and Yan, X. (2015), "Analysis and monitoring on jacking construction of continuous box girder bridge", Comput. Concrete, 16(1), 49-65. https://doi.org/10.12989/cac.2015.16.1.049.
  21. Liu, Z., Chen, C., Huang, Y., Huang, J. and Deng, D. (2024), "To in-situ construct a layer of ductile and dense skin in protecting the born concrete matrix of reinforced concrete", Constr. Build. Mater., 411, 134544. https://doi.org/10.1016/j.conbuildmat.2023.134544.
  22. Marra, L., Fabbro, S., Kuffa, M. and Wegener, K. (2023), "Geometric-kinematic model for reinforced concrete core drilling", Int. J. Adv. Manuf. Technol., 125(7-8), 3149-3158. https://doi.org/101007/s00170-022-10787-y. 101007/s00170-022-10787-y
  23. Mathar, J. (1933), "Determination of initial stresses by measuring the deformations around drilled holes", J. Fluids Eng., 56, 249-254. https://doi.org/101115/14019712. 101115/14019712
  24. McGinnis, M.J. and Pessiki, S. (2016), "Experimental study of the core-drilling method for evaluating in situ stresses in concrete structures", J. Mater. Civil Eng., 28(2), 04015099. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001294.
  25. Miller, D., Ho, N.M. and Talebian, N. (2022), "Monitoring of in-place strength in concrete structures using maturity method - An overview", Struct., 44, 1081-1104. https://doi.org/101016/jistruc202208077. 101016/jistruc202208077
  26. Miyamoto, A., Emoto, H. and Asano, H. (2014), "Advanced performance evaluation system for existing concrete bridges", Comput. Concrete, 14(6), 727-743. https://doi.org/10.12989/cac.2014.14.6.727.
  27. Naseri Nasab, M., Jahangir, H., Hasani, H., Majidi, M.H. and Khorashadizadeh, S. (2023a), "Estimating the punching shear capacities of concrete slabs reinforced by steel and FRP rebars with ANN-Based GUI toolbox", Struct., 50, 1204-1221. https://doi.org/10.1016/j.istruc.2023.02.072.
  28. Natekin, A. and Knoll, A. (2013), "Gradient boosting machines, a tutorial", Front. Neurorobot., 91(4), 21. https://doi.org/103389/fnbot201300021. 103389/fnbot201300021
  29. Nguyen-Sy, T., Wakim, J., To, Q.D., Vu, M.N., Nguyen, T.D. and Nguyen, T.T. (2020), "Predicting the compressive strength of concrete from its compositions and age using the extreme gradient boosting method", Constr. Build. Mater., 260, 119757. https://doi.org/101016/jconbuildmat2020119757. 101016/jconbuildmat2020119757
  30. Parivallal, S., Ravisankar, K., Nagamani, K. and Kesavan, K. (2011), "Core-drilling technique for in-situ stress evaluation in concrete structures", Experiment. Tech., 35(4), 29-34. https://doi.org/101111/j1747-1567201000622x. 101111/j1747-1567201000622x
  31. Pucinotti, R. (2013), "Assessment of in situ characteristic concrete strength", Constr. Build. Mater., 44, 63-73. https://doi.org/101016/jconbuildmat201302041. 101016/jconbuildmat201302041
  32. Ruan, X. and Zhang, Y. (2015), "In-situ stress identification of bridge concrete components using core-drilling method", Struct. Infrastr. Eng., 11(2), 210-222. https://doi.org/101080/157324792013862729. 101080/157324792013862729
  33. Sarfarazi, V., Haeri, H. and Shemirani, A. B. (2018), "Simulation of fracture mechanism of pre-holed concrete model under Brazilian test using PFC3D", Smart Struct. Syst., 22(6), 675-687. https://doi.org/10.12989/sss.2018.22.6.675.
  34. Shang, G. and Chen, J. (2023), "Deep learning of sweep signal for damage detection on the surface of concrete", Comput. Concrete, 32(5), 475-486. https://doi.org/10.12989/cac.2023.32.5.475.
  35. Shemirani, A.B. (2022), "Experimental and numerical studies of concrete bridge decks using ultra high-performance concrete and reinforced concrete", Comput. Concrete, 29(6), 407-418. https://doi.org/10.12989/cac.2022.29.6.407.
  36. Trautner, C., McGinnis, M. and Pessiki, S. (2010), "Analytical and numerical development of the incremental core-drilling method of non-destructive determination of in-situ stresses in concrete structures", J. Strain Anal. Eng. Des., 45(8), 647-658. https://doi.org/101177/030932471004500801. 101177/030932471004500801
  37. Trautner, C., McGinnis, M. and Pessiki, S. (2011), "Application of the incremental core-drilling method to determine in-situ stresses in concrete", Mater. J., 108(3), 290-299. https://doi.org/1014359/51682494. 1014359/51682494
  38. Turker, H.T. (2003), "Theoretical development of the core-drilling method for nondestructive evaluation of stresses in concrete structures", Ph.D. Dissertation, Lehigh University, Bethlehem, PA, USA.
  39. Utepov, Y., Khudaibergenov, O., Kabdush, Y. and Kazkeev, A. (2019), "Prototyping an embedded wireless sensor for monitoring reinforced concrete structures", Comput. Concrete, 24(2), 95-102. https://doi.org/10.12989/cac.2019.24.2.095.
  40. Von Mirbach, D. (2013), "Hole-drilling method for residual stress measurement - consideration of elastic-plastic material properties", Mater. Sci. Forum, 768-769, 174-181. https://doi.org/10.4028/www.scientific.net/MSF.768-769.174.
  41. Xia, J., Zhang, S., Liao, L., Liu, H. and Sun, Y. (2023), "Working stress measurement of prestressed rebars using the magnetic resonance method", Build., 13(6), 1416. https://doi.org/103390/buildings13061416. 103390/buildings13061416
  42. Yang, S., Xu, Z. and Wang, J. (2022), "Prediction on concrete splitting strength from compressive strength of drilling-core", Struct. Concrete, 23(2), 1226-1238. https://doi.org/101002/suco202000577. 101002/suco202000577
  43. Zhang, F.P., Qiu, Z.G. and Jiao, P.F. (2011), "Test analysis of measuring working strains in concrete structures by loophole-drilling strain-gage method", Adv. Mater. Res., 243-249, 5656-5661. https://doi.org/10.4028/www.scientific.net/AMR.243-249.5656.
  44. Zhang, Y., Xu, D. and Liu, C. (2018), "Behavior and stress check of concrete box girders strengthened by external prestressing", Comput. Concrete, 22(2), 133-142. https://doi.org/10.12989/cac.2018.22.2.133.
  45. Zhu, J., Wang, C., Yang, Y. and Wang, Y. (2023), "Hygro-thermal-mechanical coupling analysis for early shrinkage of cast in situ concrete slabs of composite beams: Theory and experiment", Constr. Build. Mater., 372, 130774. https://doi.org/10.1016/j.conbuildmat.2023.130774.
  46. Zhuang, C.X, Zhuang, J.Q. and Jiang, H.R. (2016), "Review of concrete stress testing technologies", J. Highway Transp. Res. Dev., 33(3), 43-51.
  47. Zuccarello, B., Menda, F. and Scafidi, M. (2016), "Error and uncertainty analysis of non-uniform residual stress evaluation by using the ring-core method", Experiment. Mech., 56(9), 1531-1546. https://doi.org/10.1007/s11340-016-0150-5.