Response Prediction Analysis of RC Frame Structures Using Support Vector Machine Algorithm

Shouliang  Qu; Xuefeng  Jiao; Xi  Chen; Jun  Zhao

doi:10.6180/jase.202502_28(2).0013

Response Prediction Analysis of RC Frame Structures Using Support Vector Machine Algorithm

Civil Engineering

Shouliang Qu¹ , Xuefeng Jiao², Xi Chen¹, and Jun Zhao¹

¹China Second Metallurgy Group Corporation Limited, Baotou 014000, China

²Shandong Huake Planning Architectural Design Co. Ltd, Liaocheng, 252000, China

Received: December 11, 2023
Accepted: February 22, 2024
Publication Date: April 16, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202502_28(2).0013

To more accurately predict the structural response under seismic actions, this paper takes two reinforced concrete frame structures with 9- and 11-stories as examples and utilizes the Support vector machine (SVM) algorithm to analyze the efficiency of 6 scalar and 15 vector intensity measures (IMs) in predicting the response of RC frame structures. The time required to determine hyperparameters using a grid search optimization algorithm is also provided. The results show that when using scalar IMs for prediction, SI can better predict the structural response of 9-story structure, S_a(T) can better predict the structural response of 11-story structure, and the hyperparameters of the model can be determined in a relatively short time. When using vector IMs for prediction, the best vector IMs for prediction is [PGV, Sa(T)], and the determination coefficient R 2 of the training and testing sets reaches 0.96 or above, with the standard deviation (β) below 0.3 . Compared with the best prediction results based on scalar IMs, the β is significantly reduced, both by more than 20%. This conclusion provides a theoretical basis for quantitatively evaluating the degree of structural damage caused by seismic motion.

Keywords: Support vector machine; grid search optimization; intensity measures; structural response; prediction model

[1] S.-K. Au and J. L. Beck, (2003) “Subset simulation and its application to seismic risk based on dynamic analysis" Journal of engineering mechanics 129(8): 901–917. DOI: 10.1061/(ASCE)0733-9399(2003)129:8(901).
[2] F. Jalayer and J. Beck, (2008) “Effects of two alternative representations of ground-motion uncertainty on probabilistic seismic demand assessment of structures" Earthquake engineering & structural dynamics 37(1): 61–79. DOI: 10.1002/eqe.745.
[3] S. K. Shahi and J. W. Baker, (2011) “An empirically calibrated framework for including the effects of near-fault directivity in probabilistic seismic hazard analysis" Bulletin of the Seismological Society of America 101(2): 742–755. DOI: 10.1785/0120100090.
[4] B. Huang, S. Günay, and W. Lu, (2022) “Seismic assessment of freestanding ceramic vase with shaking table testing and performance-based earthquake engineering" Journal of Earthquake Engineering 26(15): 7956–7978. DOI: 10.1080/13632469.2021.1979132.
[5] R. Montuori, E. Nastri, V. Piluso, and P. Todisco, (2020) “A simplified performance based approach for the evaluation of seismic performances of steel frames" Engineering Structures 224: 111222. DOI: 10.1016/j.engstruct.2020.111222.
[6] A. Filiatrault, D. Perrone, R. J. Merino, and G. M. Calvi, (2021) “Performance-based seismic design of nonstructural building elements" Journal of Earthquake Engineering 25(2): 237–269. DOI: 10.1080/13632469.2018.1512910.
[7] V. Chandrikka and D. S. Rajkumar. “Development of Sustainable Earthquake Resistant Building for Future Generations”. In: International Conference on Civil Engineering Innovative Development in Engineering Advances. Springer, 239–249. DOI: 10.1007/978-981-99-6233-4_22.
[8] N. Afzali and S. Hamzehloo, (2018) “Evaluating the role of recycling materials in construction industry (Case study: City of Tehran)" Journal of Environmental Friendly Materials 2(2): 49–58.
[9] Y. Lieping, M. Qianli, and M. Zhiwei, (2009) “Study on earthquake intensities for seismic analysis of structures" Journal of Earthquake Engineering and Engineering Vibration 29(4): 9–22.
[10] J. W. Baker and C. A. Cornell, (2008) “Vector-valued intensity measures for pulse-like near-fault ground motions" Engineering structures 30(4): 1048–1057. DOI: 10.1016/j.engstruct.2007.07.009.
[11] Y. Zhou, N. Su, and X. Lu, (2013) “Study on intensity measure of incremental dynamic analysis for high-rise structures" Jianzhu Jiegou Xuebao(Journal of Building Structures) 34(2): 53–60.
[12] Z. Zi-lan, S. Yi-yao, Z. Li-bin, Z. Cheng-ming, Z. Mi, and D. Xiu-li, (2020) “Ground motion intensity measures and dynamic response indexes of metro station structures" Chinese Journal of Geotechnical Engineering 42(3): 486–494. DOI: 10.11779/CJGE202003010.
[13] Y. YH and W. XP, (2020) “Validity assessment of a new vector-valued intensity parameter of earthquake ground motion" Journal of Jiangxi University of Science and Technology 41(3): 1–8.
[14] A. Yazdani and K. Yazdannejad, (2019) “Estimation of the seismic demand model for different damage levels" Engineering Structures 194: 183–195. DOI: 10.1016/j.engstruct.2019.05.071.
[15] F. Jalayer, J. Beck, and F. Zareian, (2012) “Analyzing the sufficiency of alternative scalar and vector intensity measures of ground shaking based on information theory" Journal of Engineering Mechanics 138(3): 307–316. DOI: 10.1061/(ASCE)EM.1943-7889.0000327.
[16] M. o. H. China and U. R. D. of the People’s Republic of. Code for seismic design of buildings.GB50011-2010. Standard. 2010.
[17] S. J. Venture, (2000) “State of the art report on systems performance of steel moment frames subject to earthquake ground shaking" FEMA 355C:
[18] B. Standard, (2005) “Eurocode 8: Design of structures for earthquake resistance" Part 1: 1998–1.
[19] Y. Can-tian, X. Li-li, L. Ai-qun, Z. De-min, and L. Lide, (2018) “Intensity measures for seismically isolated tall buildings" Engineering Mechanics 35(8): 21–29. DOI: 10.6052/j.issn.1000-4750.2017.07.0531.
[20] P. Tothong and C. A. Cornell, (2008) “Structural performance assessment under near-source pulse-like ground motions using advanced ground motion intensity measures" Earthquake Engineering Structural Dynamics 37(7): 1013–1037. DOI: 10.1002/eqe.792.
[21] L. Ye, Q. Ma, Z. Miao, H. Guan, and Y. Zhuge, (2013) “Numerical and comparative study of earthquake intensity indices in seismic analysis" The Structural Design of Tall and Special Buildings 22(4): 362–381. DOI: 10.1002/tal.693.
[22] D. Yang, J. Pan, and G. Li, (2009) “Non-structurespecific intensity measure parameters and characteristic period of near-fault ground motions" Earthquake Engineering Structural Dynamics 38(11): 1257–1280. DOI: 10.1002/eqe.889.
[23] H. Ebrahimian, F. Jalayer, A. Lucchini, F. Mollaioli, and G. Manfredi, (2015) “Preliminary ranking of alternative scalar and vector intensity measures of ground shaking" Bulletin of Earthquake Engineering 13: 2805–2840. DOI: 10.1007/s10518-015-9755-9.