Abstract
Selection of appropriate ground motion (GM) records for nonlinear dynamic analysis (NDA) of structures plays a crucial role to estimate structural responses reasonably. In this study, a multi-functional solution model utilizing stochastic harmony search (HS) algorithm is proposed to obtain scaled or unscaled real GM component sets for uni-directional analysis of two-dimensional structural models and GM component pair sets for bi-directional analysis of three-dimensional structural models. The solution model allows to consider compatibility between target spectrum and both mean spectrum and individual spectra besides desired spectral variability. Uniform hazard spectrum, conditional mean spectrum or scenario-based spectrum can be selected as target spectrum. Combined response spectra of selected component pairs such as SRSS, geometric mean and maximum directional can also be handled by the solution model. To demonstrate the efficiency of the solution model, various examples were presented. In addition, a sensitivity analysis was performed to evaluate the effect of HS parameters on the solution accuracy. Results show that the proposed solution model can be regarded as efficient to obtain appropriate GM record sets to be used for NDAs within a probabilistic seismic design and/or performance assessment framework.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abrahamson NA (1992) Non-stationary spectral matching. Seism Res Lett 63(1):30
Akkar S, Sandikkaya MA, Bommer JJ (2014a) Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East. Bull Earthq Eng 12(1):311–339. https://doi.org/10.1007/s10518-013-9461-4
Akkar S, Sandıkkaya MA, Senyurt M, Sisi Azari A, Ay BO, Traversa P, Douglas J, Cotton F, Luzi L, Hernandez B, Godey S (2014b) Reference database for seismic ground-motion in Europe (RESORCE). Bull Earthq Eng 12(1):359–387. https://doi.org/10.1007/s10518-013-9506-8
Ambraseys NN, Douglas J, Rinaldis D, Berge-Thierry C, Suhadolc P, Costa G, Sigbjornsson R, Smit P (2004) Dissemination of European strong-motion data. CD-ROM Collection, Engineering and Physical Sciences Research Council, Swindon
Ancheta TD, Darragh RB, Stewart JP, Seyhan E, Silva WJ, Chiou BSJ, Wooddell KE, Graves RB, Kottke AR, Boore DM, Kishida T, Donahue JL (2014) NGA-West2 database. Earthq Spectra 30(3):989–1005. https://doi.org/10.1193/070913EQS197M
Araújo M, Macedo L, Marques M, Castro JM (2016) Code-based record selection methods for seismic performance assessment of buildings. Earthq Eng Str Dyn 45:129–148
Arora JS (2004) Introduction to optimum design. Elsevier, California
ASCE 7-16 (2016) Minimum design loads for buildings and other structures. American Society of Civil Engineers, Reston
Ay BO, Akkar S (2012) A procedure on ground motion selection and scaling for nonlinear response of simple structural systems. Earthq Eng Struct Dyn 41(12):1693–1707. https://doi.org/10.1002/eqe.1198
Baker JW (2011) Conditional mean spectrum: tool for ground-motion selection. J Struct Eng 137(3):322–331. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000215
Baker JW, Cornell C (2005) Vector-valued ground motion intensity measures for probabilistic seismic demand analysis. John A, Blume Earthquake Engineering Center, Stanford, CA
Baker JW, Lee C (2018) An improved algorithm for selecting ground motions to match a conditional spectrum. J Earthq Eng 22(4):708–723. https://doi.org/10.1080/13632469.2016.1264334
Baltzopoulos G, Baraschino M, Giorgio M, Iervolino I (2020) Why determining the number of code spectrum-matched records based on usual statistics is an ill-posed problem. 17th World Conference on Earthquake Engineering. Sendai
Beyer K, Bommer JJ (2007) Selection and scaling of real accelerograms for bidirectional loading: a review of current practice and code provisions. J Earthq Eng 11(1):13–45. https://doi.org/10.1080/13632460701280013
Boore DM (2006) Orientation-independent measures of ground motion. Bull Seismol Soc Am 96(4A):1502–1511. https://doi.org/10.1785/0120050209
Boore DM (2010) Orientation-independent, nongeometric-mean measures of seismic intensity from two horizontal components of motion. Bull Seismol Soc Am 100(4):1830–1835. https://doi.org/10.1785/0120090400
Bradley BA (2010) A generalized conditional intensity measure approach and holistic ground-motion selection. Earthq Eng Struct Dyn 39(12):1321–1342. https://doi.org/10.1002/eqe.995
Carballo JE, Cornell CA (2000). Probabilistic seismic demand analysis: spectrum matching and design. Stanford University. Report No: RMS-41
Coello CAC (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Meth Appl Mech Eng 191(11):1245–1287. https://doi.org/10.1016/S0045-7825(01)00323-1
Datta TK (2010) Seismic analysis of structures. John Wiley & Sons, Singapore
Demir A, Palanci M, Kayhan AH (2020) Evaluation of supplementary constraints on dispersion of EDPs using real ground motion record sets. Arab J Sci Eng 45:8379–8401. https://doi.org/10.1007/s13369-020-04719-9
Ergun M, Ates S (2013) Selecting and scaling ground motion time histories according to Eurocode-8 ASCE and 7–05. Earthq Struct 5(2):129–142
EUROCODE-8 (2004) Design provisions for earthquake resistance of structures, Part 1: General rules, seismic actions and rules for buildings. European Committee for Standardization, Brussels
Fahjan YM (2008) Selection and scaling of real earthquake accelerograms to fit the Turkish Design Spectra. Teknik Dergi 19(3):4423–4444
Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. SIMULATION 76(2):60–68. https://doi.org/10.1177/003754970107600201
Georgioudakis M, Fragiadakis M (2020) Selection and scaling of ground motions using multicriteria optimization. J Struct Eng 146(11):04020241. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002811
Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison- Wesley, Boston
Ha S, Han S (2016) An efficient method for selecting and scaling ground motions matching target response spectrum mean and variance. Earthq Eng Struct Dyn 45(8):1381–1387. https://doi.org/10.1002/eqe.2702
Han SW, Seok SW (2014) Efficient procedure for selecting and scaling ground motions for response history analysis. J Struct Eng 140:06013004. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000881
Hancock J, Bommer JJ, Stafford PJ (2008) Numbers of scaled and matched accelerograms required for inelastic dynamic analyses. Earthq Eng Struct Dyn 37(14):1585–1607. https://doi.org/10.1002/eqe.827
Huang YN, Whittaker AS, Luco N, Hamburger RO (2011) Scaling earthquake ground motions for performance-based assessment of buildings. J Struct Eng 137:311–321. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000155
Iervolino I (2017) Assessing uncertainty in estimation of seismic response for PBEE. Earthq Eng Struc Dyn 46:1711–1723. https://doi.org/10.1002/eqe.2883
Iervolino I, Maddaloni G, Cosenza E (2008) Eurocode-8 compliant real record sets for seismic analysis of structures. J Earthq Eng 12:54–90. https://doi.org/10.1080/13632460701457173
Iervolino I, Maddaloni G, Cosenza E (2009) A note on selection of time-histories for seismic analysis of bridges in Eurocode 8. J Earthq Eng 13(8):1125–1152. https://doi.org/10.1080/13632460902792428
Iervolino I, Galasso C, Cosenza E (2010) REXEL: computer aided record selection for code-based seismic structural analysis. Bull Earthq Eng 8:339–362. https://doi.org/10.1007/s10518-009-9146-1
Jayaram N, Lin T, Baker J (2011) A computationally efficient ground-motion selection algorithm for matching a target response spectrum mean and variance. Earthq Spectra 27(3):797–815. https://doi.org/10.1193/1.3608002
Katsanos EI, Sextos AG (2013) ISSARS: an integrated software environment for structure-specific earthquake ground motion selection. Adv Eng Softw 58:70–85. https://doi.org/10.1016/j.advengsoft.2013.01.003
Katsanos EI, Sextos AG (2018) Structure-specific selection of earthquake GMs for the reliable design and assessment of structures. Bull Earthq Eng 16(2):583–611. https://doi.org/10.1007/s10518-017-0226-3
Katsanos EI, Sextos AG, Manolis GD (2010) Selection of earthquake ground motion records: a state-of the-art-review from a structural engineering perspective. Soil Dyn Earthq Eng 30:157–169. https://doi.org/10.1016/j.soildyn.2009.10.005
Kaveh A, Talahatari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213(3–4):267–289. https://doi.org/10.1007/s00707-009-0270-4
Kaveh A, Hosseini OK, Mohammadi S, Jari VRK, Keyhani A (2014) Optimum selection and scaling of accelerograms required in time history analysis of spatial structures. Int J Optim Civ Eng 4(4):525–547
Kaveh A, Moghanni RM, Javadi SM (2019) Ground motion record selection using multi-objective optimization algorithms: a comparative study. Period Polytechnica Civ Eng 63(3):812–822. https://doi.org/10.3311/PPci.14354
Kayhan AH (2016) Scaled and unscaled ground motion sets for uni-directional and bi-directional dynamic analysis. Earthq Struct 10(3):563–588. https://doi.org/10.12989/eas.2016.10.3.563
Kayhan AH, Demir A (2016) Statistical evaluation of drift demands of RC frames using code-compatible real ground motion record sets. Struct Eng Mech 60(6):953–977. https://doi.org/10.12989/sem.2016.60.6.953
Kayhan AH, Korkmaz KA, Irfanoglu A (2011) Selecting and scaling real ground motion records using harmony search algorithm. Soil Dyn Earthq Eng 31(7):941–953. https://doi.org/10.1016/j.soildyn.2011.02.009
Kayhan AH, Demir A, Palanci M (2018) Statistical evaluation of maximum displacement demands of SDOF systems by code compatible nonlinear time history analysis. Soil Dyn Earthq Eng 115:513–530. https://doi.org/10.1016/j.soildyn.2018.09.008
Kennedy J, Eberhart R (1995) Particle swarm optimization. Proceedings of the ICNN95- International Conference on Neural Networks 4: 1942–1948 doi: https://doi.org/10.1109/ICNN.1995.488968
Kohrangi M, Bazzurro P, Vamvatsikos D, Spillatura A (2017) Conditional spectrum-based ground motion record selection using average spectral acceleration. Earthq Eng Struct Dyn 47(1):265–283. https://doi.org/10.1002/eqe.2873
Kottke A, Rathje E (2008) A semi-automated procedure for selecting and scaling recorded earthquake motions for dynamic analysis. Earthq Spectra 24(4):911–932. https://doi.org/10.1193/1.2985772
Lee KS, Geem ZW, Lee SH, Bae KW (2005) The harmony search heuristic algorithm for discrete structural optimization. Eng Optimiz 37(7):663–684. https://doi.org/10.1080/03052150500211895
Luco N, Bazzurro P (2007) Does amplitude scaling of ground motion records result in biased nonlinear structural drift responses? Earthq Eng Struct Dyn 36(13):1813–1835. https://doi.org/10.1002/eqe.695
Macedo L, Castro J (2017) SelEQ: an advanced ground motion record selection and scaling framework. Adv Eng Software 114:32–47. https://doi.org/10.1016/j.advengsoft.2017.05.005
Mergos P, Sextos A (2019) Selection of earthquake ground motions for multiple objectives using genetic algorithms. Eng Struct 187:414–427. https://doi.org/10.1016/j.engstruct.2019.02.067
Microsoft, (1995) Microsoft Excel—Visual Basic for applications. Microsoft Press, Washington
Moschen L, Medina RA, Adam C (2019) A ground motion record selection approach based on multiobjective optimization. J Earthq Eng 23(4):669–687. https://doi.org/10.1080/13632469.2017.1342302
Naeim F, Alimoradi A, Pezeshk S (2004) Selection and scaling of ground motion time histories for structural design using genetic algorithm. Earthq Spectra 20(2):413–426. https://doi.org/10.1193/1.1719028
Numerical Technologies (2021) NTRAND 3.3: An Excel add-in random number generator powered by Mersenne Twister Algorithm. http://www.ntrand.com. Accessed 20.03.2021
NIST (2011) Selecting and scaling earthquake ground motions for performing response history analyses. Report Number NIST GCR 11–917–15, National Institute of Standards and Technology, East Lansing
Palanci M, Kayhan AH, Demir A (2018) A statistical assessment on global drift ratio demands of mid-rise RC buildings using code-compatible real ground motion records. Bull Earthq Eng 16(11):5453–5488. https://doi.org/10.1007/s10518-018-0384-y
Rao SS (2009) Engineering optimization theory and practice. John Wiley & Sons, New Jersey
Saltelli A, Annoni P (2010) How to avoid a perfunctory sensitivity analysis. Environ Model Softw 25:1508–1517. https://doi.org/10.1016/j.envsoft.2010.04.012
Sextos AG, Katsanos EI, Manolis GD (2011a) EC8-based earthquake record selection procedure evaluation: validation study based on observed damage of an irregular R/C building. Soil Dyn Earthq Eng 31(4):583–597. https://doi.org/10.1016/j.soildyn.2010.10.009
Sextos AG, Katsanos EI, Georgiou A, Faraonis P, Manolis GD (2011b) On the evaluation of EC8-based record selection procedures for the dynamic analysis of buildings and bridges. In: Papadrakakis M, Fragiadakis M, Lagaros ND (eds) Computational methods in earthquake engineering. Springer, Dordrecht, pp 41–65
Shakeri K, Khansoltani E, Pessiki S (2018) Ground motion scaling for seismic response analysis by considering inelastic response and contribution of the higher modes. Soil Dyn Earthq Eng 110:70–85. https://doi.org/10.1016/j.soildyn.2018.04.007
Smerzini C, Galasso C, Iervolino I, Paoluccia R (2014) Ground motion record selection based on broadband spectral compatibility. Earthq Spectra 30(4):1427–1448. https://doi.org/10.1193/052312EQS197M
Storn R, Price K (1997) Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341–359. https://doi.org/10.1023/A:1008202821328
Strukar K, Sipos TK, Jelec M, Nyarko MH (2019) Efficient damage assessment for selected earthquake records based on spectral matching. Earthq Struct 17(3):271–282. https://doi.org/10.12989/eas.2019.17.3.271
TBEC (2018) Turkish building earthquake code. Disaster and Emergency Management Presidency, Ankara
Ye K, Chen Z, Zhu H (2014) Proposed strategy for the application of the modified harmony search algorithm to code-based selection and scaling of ground motions. J Comput Civ Eng 28(6):1–14. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000261
Funding
The authors have not disclosed any funding.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Kayhan, A.H., Demir, A. & Palanci, M. Multi-functional solution model for spectrum compatible ground motion record selection using stochastic harmony search algorithm. Bull Earthquake Eng 20, 6407–6440 (2022). https://doi.org/10.1007/s10518-022-01450-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10518-022-01450-8