Prediction of global damage index of reinforced concrete building using artificial neural network

References

• Young-Ji Park and A. H.-S. Ang, “Mechanistic seismic damage model for reinforced concrete,” J. Struct. Eng., vol. 111, no. 4, pp. 722–739, 1985. DOI: 10.1061/(ASCE)0733-9445(1985)111:4(722).
   Web of Science ®Google Scholar
• Young-Ji Park, A. H.-S. Ang, Y. K. Asce, and M. Wen, “ASCE, seismic damage analysis of reinforced concrete buildings,” J. Struct. Eng., vol. 111, no. 4, pp. 740–757, 1985. DOI: 10.1061/(ASCE)0733-9445(1985)111:4(722).
   Web of Science ®Google Scholar
• A. J. Kappos, “Seismic damage indices for RC buildings: evaluation of concepts and procedures,” Prog. Struct. Eng. Mater., vol. 1, no. 1, pp. 78–87, 1997. DOI: 10.1002/pse.2260010113.
   Google Scholar
• H. Guan and V. M. Karbhari, “Improved damage detection method based on element modal strain damage index using sparse measurement,” J. Sound Vib., vol. 309, no. 3–5, pp. 465–494, 2008. DOI: 10.1016/j.jsv.2007.07.060.
   Web of Science ®Google Scholar
• E. Dipasquale, J.-W. Ju, A. Askar, and A. S. Qakmak, “Relation between global damage indices and local stiffness degradation,” J. Struct. Eng., vol. 116, no. 5, pp. 1440–1456, 1990. DOI: 10.1061/(ASCE) 0733-9445(1990)116:5(1440).
   Web of Science ®Google Scholar
• J. V. Amiri, Q. Y. Ahmadi, and B. Ganjavi, “Assessment of reinforced concrete buildings with shear wall based on Iranian seismic code (Third Edition),” J. Appl. Sci., vol. 8, no. 23, pp. 4283, 2008. DOI: 10.3923/jas.2008.4274.4283.
   Google Scholar
• X. Lu, Z. Huang, and Y. Zhou, “Global seismic damage assessment of high-rise hybrid structures,” Comput. Concr., vol. 8, no. 3, pp. 311–325, 2011. DOI: 10.12989/cac.2011.8.3.311.
   Web of Science ®Google Scholar
• A. Massumi and B. Monavari, “Energy based procedure to obtain target displacement of reinforced concrete structures,” Struct. Eng. Mech., vol. 48, no. 5, pp. 681–695, 2013. DOI: 10.12989/sem.2013.48.5.681.
   Web of Science ®Google Scholar
• J.-F. Wang, C.-C. Lin, and S.-M. Yen, “A story damage index of seismically excited buildings based on modal frequency and mode shape,” Eng. Struct., vol. 29, no. 9, pp. 2143–2157, 2007. DOI: 10.1016/j.engstruct.2006.10.018.
   Web of Science ®Google Scholar
• A. Ghobarah, H. Abou-Elfath, and A. Biddah, “Response based damage assessment of structures,” Earthquake Engng. Struct. Dyn, vol. 28, no. 1, pp. 79–104, 1999. DOI: 10.1002/(SICI)1096-9845(199901)28:1 < 79::AID-EQE805 > 3.0.CO;2-J.
   Web of Science ®Google Scholar
• S. S. F. Mehanny and G. G. Deierlein, “Seismic damage and collapse assessment of composite moment frames,” J. Struct. Eng., vol. 127, no. 9, pp. 1045–1053, 2001. DOI: 10.1061/(ASCE)0733-9445(2001)127:9(1045).
   Web of Science ®Google Scholar
• E. Bojórquez, A. Reyes-Salazar, A. Terán-Gilmore, and S. E. Ruiz, “Energy based damage index for steel structures,” Steel Compos. Struct., vol. 10, no. 4, pp. 331–360, 2010. DOI: 10.12989/scs.2010.10.4.331.
   Web of Science ®Google Scholar
• A. Moustafa, “Damage-based design earthquake loads for single-degree-of-freedom inelastic structures,” J. Struct. Eng., vol. 137, no. 3, pp. 456–467, 2011. DOI: 10.1061/(ASCE)ST.1943-541X.
   Web of Science ®Google Scholar
• J. Carrillo, “Damage index based on stiffness degradation of low-rise RC walls,” Earthquake Eng. Struct. Dyn., vol. 44, no. 6, pp. 831–848, 2015. DOI: 10.1002/eqe.2488.
   Web of Science ®Google Scholar
• H. Li, H. Yang, and J. Hu, “Modal strain energy decomposition method for damage localization in 3D frame structures,” J. Eng. Mech., vol. 132, no. 9, pp. 941–951, 2006. DOI: 10.1061/(ASCE)0733-9399(2006)132:9(941).
   Web of Science ®Google Scholar
• J. W. Kang and J. Lee, “A new damage index for seismic fragility analysis of reinforced concrete columns,” Struct. Eng. Mech., vol. 60, no. 5, pp. 875–890, 2016. DOI: 10.12989/sem.2016.60.5.875.
   Web of Science ®Google Scholar
• M. S. Alhaddad, K. M. Wazira, Y. A. Al-Salloum, and H. Abbas, “Ductility damage indices based on seismic performance of RC frames,” Soil Dyn. Earthquake Eng., vol. 77, pp. 226–237, 2015. DOI: 10.12989/sem.2013.48.5.681.
   Web of Science ®Google Scholar
• N. Cheraghi and F. Taheri, “A damage index for structural health monitoring based on the empirical mode decomposition,” JOMMS, vol. 2, no. 1, pp. 43–61, 2007. DOI: 10.2140/jomms.2007.2.43.
   Google Scholar
• E. Cosenza and G. Manfredi, “Damage indices and damage measures,” Prog. Struct. Eng. Mater., vol. 2, no. 1, pp. 50–59, 2000. DOI: 10.1002/(sici)1528-2716(200001/03)2:1 < 50::aid-pse7 > 3.0.co;2-s.
   Google Scholar
• P. Hait, A. Sil, and S. Choudhury, “Quantification of damage to RC structures: a comprehensive review,” Disaster Adv., vol. 11, no. 12, pp. 41–59, 2018.
   Google Scholar
• P. Hait, A. Sil, and S. Choudhury, “Overview of damage assessment of structures,” Curr. Sci. Indian Acad. Sci., vol. 117, no. 1, pp. 64, 2019. DOI: 10.18520/cs/v117/i1/64-70.
   Web of Science ®Google Scholar
• F. Zahedi Tajrishi, A. Mirza Goltabar Roshan, M. Zeynalian, and J. Vaseghi Amiri, “A new collection of compressed damage indices for multi-damage detection of cold formed steel shear walls based on neural network ensembles,” Can. J. Civ. Eng., vol. 43, no. 12, pp. 1034–1043, 2016. DOI: 10.1139/cjce-2015-0417.
   Web of Science ®Google Scholar
• J. L. Zapico, M. P. González, and K. Worden, “Damage assessment using neural networks,” Mech. Syst. Signal Process., vol. 17, no. 1, pp. 119–125, 2003. DOI: 10.1006/mssp.2002.1547.
   Web of Science ®Google Scholar
• P. Sarkar, B. K. Patir, and D. Menon, “Survey and assessment of seismic safety of multi-storeyed buildings in Guwahati, India. 13th WCEE,” Vancouver, B.C., Canada, Paper No. 1212, 2004.
   Google Scholar
• T. G. Sitharam and A. Sil, “Comprehensive seismic hazard assessment of Tripura and Mizoram states,” J. Earth Syst. Sci., vol. 123, no. 4, pp. 837–857, 2014. DOI: 10.1007/s12040-014-0438-8.
   Web of Science ®Google Scholar
• Bureau of Indian Standards, “Plain and reinforced concrete. Plain and reinforced concrete – code of practice,” IS, vol. 4562000, 2000.
   Google Scholar
• Bureau of Indian Standards, Criteria for Earthquake Resistant Design of Structures IS 1893 (Part 1) 2016, Sixth Revision, December, 2016.
   Google Scholar
• Bureau of Indian Standards, Ductile design and detailing of reinforced concrete structures subjected to seismic forces- code of practice IS 13920, 2016.
   Google Scholar
• Computer and Structures Inc., Berkley. SAP2000 v.14 Nonlinear, Educational Version, 2006.
   Google Scholar
• A. Kumar, Software for generation of spectrum compatible time history, WCEE, Paper No. 2096, 2004.
   Google Scholar
• Federal Emergency Management Agency (FEMA), NEHRP guidelines for the seismic retrofitting of buildings. FEMA-356. Washington DC, 2000.
   Google Scholar
• T. K. Dutta, Seismic Analysis of Structures. Hoboken, NJ: John Wiley International, 2010.
   Google Scholar
• P. Hait, A. Sil, and S. Choudhury, “Damage assessment of reinforced concrete-framed building considering multiple demand parameters in Indian Codal Provisions,” Iran. J. Sci. Technol. Trans. Civ. Eng., vol. 44, no. S1, pp. 121–139, 2020. DOI: 10.1007/s40996-020-00380-2.
   Google Scholar
• P. Hait, A. Sil, and S. Choudhury, “Seismic damage assessment and prediction using artificial neural network of RC building considering irregularities,” J. Struct. Integrity Mainten., vol. 5, no. 1, pp. 51–69, 2020. DOI: 10.1080/24705314.2019.1692167.
   Web of Science ®Google Scholar
• E. Özer, S. Soyöz, and M. Çelebi, Effect of strong ground motion duration on structural damage, 15th WCEE, pp. 1–9, 2012.
   Google Scholar
• L. Faravelli and A. A. Pisano, “A neural network approach to structure damage assessment,” IEEE Explore, INSPEC Accession, no. 5809501, pp. 585–588, 1997.
   Google Scholar
• J. Rhim and S. W. Lee, “A neural network approach for damage detection and identification of structures,” Comput. Mech., vol. 16, no. 6, pp. 437–443, 1995. DOI: 10.1007/s004660050086.
   Web of Science ®Google Scholar
• N. S. Gulgec, M. Takac, and S. N. Pakzad, “Convolutional neural network approach for robust structural damage detection and localization,” J. Comput. Civ. Eng., vol. 33, no. 3, pp. 04019005–04019005-11, 2019. DOI: 10.1061/(ASCE)CP.1943-5487.0000820.
   Web of Science ®Google Scholar
• X. Wu, J. Ghaboussi, and J. H. Garrett Jr., “Use of neural networks in detection of structural damage,” Comput. Struct., vol. 42, no. 4, pp. 649–659, 1992. DOI: 10.1016/0045-7949(92)90132-J.
   Web of Science ®Google Scholar
• R. P. Bandara, T. H. T. Chan, and D. P. Thambiratnam, “The three-stage artificial neural network method for damage assessment of building structures,” AJSE, vol. 14, no. 1, pp. 13–25, 2013. DOI: 10.7158/S12-036.2013.14.1.
   Google Scholar
• M. A. Shahin, H. R. Maier, and M. B. Jaksa, “Data division for developing neural networks applied to geotechnical engineering,” J. Comput. Civ. Eng., vol. 18, no. 2, pp. 105–114, 2004. DOI: 10.1061/(ASCE)0887-3801(2004)18:2(105).nine denoting a quantity consisting of one more than eight and one less than ten More (Definitions, Synonyms, Translation)
   Web of Science ®Google Scholar