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Shalchi Tousi, Mehdi, Emrany, Zakia, Tarighi, Payam. (1406). Comparative Study on Optimal Distribution of Viscous Dampers Using Genetic Algorithm and Intelligent Water Drops Under Energy-Compatible Endurance Time Excitations. پژوهشنامه مدیریت اجرایی, 3(3), 87-101. doi: 10.22080/ceas.2026.32472.1125
Mehdi Shalchi Tousi; Zakia Emrany; Payam Tarighi. "Comparative Study on Optimal Distribution of Viscous Dampers Using Genetic Algorithm and Intelligent Water Drops Under Energy-Compatible Endurance Time Excitations". پژوهشنامه مدیریت اجرایی, 3, 3, 1406, 87-101. doi: 10.22080/ceas.2026.32472.1125
Shalchi Tousi, Mehdi, Emrany, Zakia, Tarighi, Payam. (1406). 'Comparative Study on Optimal Distribution of Viscous Dampers Using Genetic Algorithm and Intelligent Water Drops Under Energy-Compatible Endurance Time Excitations', پژوهشنامه مدیریت اجرایی, 3(3), pp. 87-101. doi: 10.22080/ceas.2026.32472.1125
Shalchi Tousi, Mehdi, Emrany, Zakia, Tarighi, Payam. Comparative Study on Optimal Distribution of Viscous Dampers Using Genetic Algorithm and Intelligent Water Drops Under Energy-Compatible Endurance Time Excitations. پژوهشنامه مدیریت اجرایی, 1406; 3(3): 87-101. doi: 10.22080/ceas.2026.32472.1125

Comparative Study on Optimal Distribution of Viscous Dampers Using Genetic Algorithm and Intelligent Water Drops Under Energy-Compatible Endurance Time Excitations

Civil Engineering and Applied Solutions
مقاله 6، دوره 3، شماره 3، مهر 2027، صفحه 87-101    اصل مقاله (1.91 M)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/ceas.2026.32472.1125
نویسندگان
Mehdi Shalchi Tousi* ؛ Zakia Emrany؛ Payam Tarighi
Department of Civil Engineering, Faculty of Technology and Engineering, Ahlul Bayt International University, Tehran, Iran
تاریخ دریافت: 30 تیر 1405،  تاریخ بازنگری: 21 مرداد 1405،  تاریخ پذیرش: 14 مهر 1405 
چکیده
Nonlinear time-history analysis (NLTHA) remains one of the most rigorous tools for evaluating the seismic performance of structures; however, its high computational cost limits practical application within optimization frameworks. The endurance time (ET) method, which applies intensifying accelerograms to structures, enables continuous assessment of seismic demands across multiple hazard levels with a significantly reduced number of analyses. This study investigates the optimal distribution of fluid viscous dampers (FVDs) in a three-story deficient steel moment-resisting frame using the ET method, subject to performance-level constraints prescribed by ASCE/SEI 41-06 at the life safety (LS) and collapse prevention (CP) levels. Two metaheuristic algorithms – a standard genetic algorithm (GA) and the intelligent water drops (IWD) algorithm – are employed in a controlled comparative setting with identical modeling assumptions, objective functions, and constraint formulations. The optimization problem is formulated to minimize the total damping demand while satisfying interstory drift ratio (IDR) limits at basic safety earthquake (BSE) hazard levels BSE-1 and BSE-2. The study further extends the formulation to a multi-objective framework that simultaneously addresses peak drift, peak floor acceleration, and total damper cost. Results demonstrate that both algorithms concentrate the dominant damping contribution at the second story, consistent with the fundamental mode deformation profile. The IWD algorithm exhibits faster convergence and achieves a marginally lower total damping coefficient (approximately 6-9% reduction in mean IDR) compared with GA, while both algorithms satisfy the prescribed performance limits. Validation against conventional NLTHA confirms that ET-based predictions remain within an acceptable engineering error margin of less than 12%. Energy balance analyses indicate that FVDs dissipate approximately 35-45% of seismic input energy, confirming the efficacy of the supplemental damping system.
کلیدواژه‌ها
Endurance time method؛ Fluid viscous damper؛ Structural optimization hysteretic energy؛ Genetic algorithm؛ Intelligent water drops
مراجع
  1. Soong, T. T., Dargush, G. F. Passive Energy Dissipation Systems in Structural Engineering. 1st ed. New York (NY): John Wiley & Sons, Inc.; 1997.
  2. Symans, M. D., Constantinou, M. C. Semi-active control systems for seismic protection of structures: a state-of-the-art review. Engineering Structures, 1999; 21: 469–487. doi:10.1016/S0141-0296(97)00225-3.
  3. Takewaki, I. Building Control with Passive Dampers: Optimal Performance-based Design for Earthquakes. 1st ed. Chichester (UK): John Wiley & Sons, Inc.; 2009.
  4. Chopra, A. K. Dynamics of Structures: Theory and Applications to Earthquake Engineering. 5th ed. Indianapolis (IN): Pearson; 2017.
  5. The American Society of Civil Engineers (ASCE). ASCE/SEI 41-06: Seismic Rehabilitation of Existing Buildings. Reston (VA): ASCE; 2007. doi:10.1061/9780784408841.
  6. Estekanchi, H. E., Vafai, A., Sadeghazar, M. Endurance Time Method for Seismic Analysis and Design of Structures. Scientia Iranica, 2004; 11: 361–370.
  7. Estekanchi, H. E., Valamanesh, V., Vafai, A. Application of Endurance Time method in linear seismic analysis. Engineering Structures, 2007; 29: 2551–2562. doi:10.1016/j.engstruct.2007.01.009.
  8. Riahi, H. T., Estekanchi, H. E. Seismic assessment of steel frames with the endurance time method. Journal of Constructional Steel Research, 2010; 66: 780–792. doi:10.1016/j.jcsr.2009.12.001.
  9. Holland, J. H. Adaptation in Natural and Artificial Systems. 1st ed. Ann Arbor (MI): University of Michigan Press; 1975.
  10. Goldberg, D. E. Genetic Algorithms in Search, Optimization, and Machine Learning. ed. Reading (MA): Addison-Wesley; 1989.
  11. Shah-Hosseini, H. Problem solving by intelligent water drops. In: 2007 IEEE Congress on Evolutionary Computation; 2007 Sep 25–28; Singapore, Singapore. p. 3226–3231. doi:10.1109/CEC.2007.4424885.
  12. Shah-Hosseini, H. The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm. International Journal of Bio-Inspired Computation, 2009; 1: 71–79. doi:10.1504/IJBIC.2009.022775.
  13. Kaveh, A., Talatahari, S. Optimal design of skeletal structures via the charged system search algorithm. Structural and Multidisciplinary Optimization, 2010; 41: 893–911. doi:10.1007/s00158-009-0462-5.
  14. Shirkhani, A., Farahmand Azar, B., Charkhtab Basim, M., Mashayekhi, M. Performance-based optimal distribution of viscous dampers in ‎structure using hysteretic energy compatible endurance time excitations. Numerical Methods in Civil Engineering, 2021; 5: 46–55. doi:10.52547/nmce.5.3.46.
  15. Pollini, N. Fail-safe optimization of viscous dampers for seismic retrofitting. Earthquake Engineering & Structural Dynamics, 2020; 49: 1599–1618. doi:10.1002/eqe.3319.
  16. Bakhshinezhad, S., Mohebbi, M. Multi-objective optimal design of semi-active fluid viscous dampers for nonlinear structures using NSGA-II. Structures, 2020; 24: 678–689. doi:10.1016/j.istruc.2020.02.004.
  17. Aydin, E., Boduroglu, M. H., Guney, D. Optimal damper distribution for seismic rehabilitation of planar building structures. Engineering Structures, 2007; 29: 176–185. doi:10.1016/j.engstruct.2006.04.016.
  18. Mohsenian, V., Hajirasouliha, I., Nikkhoo, A. Multi-level Response Modification Factor Estimation for Steel Moment-Resisting Frames Using Endurance-Time Method. Journal of Earthquake Engineering, 2022; 26: 4812–4832. doi:10.1080/13632469.2020.1845875.
  19. Ayyash, A.-J. N. A., Hejazi, F. Development of hybrid performance-based optimization algorithm for structures equipped with vibration damper devices. Archives of Civil and Mechanical Engineering, 2023; 23: 123. doi:10.1007/s43452-023-00665-z.
  20. Artar, M., Carbas, S. Optimum sizing design of steel frame structures through maximum energy dissipation of friction dampers under seismic excitations. Structures, 2022; 44: 1928–1944. doi:10.1016/j.istruc.2022.08.119.
  21. Patsialis, D., Taflanidis, A. A., Giaralis, A. Tuned-mass-damper-inerter optimal design and performance assessment for multi-storey hysteretic buildings under seismic excitation. Bulletin of Earthquake Engineering, 2023; 21: 1541–1576. doi:10.1007/s10518-021-01236-4.
  22. Lara-Valencia, L. A., Caicedo, D., Valencia-Gonzalez, Y. A Novel Whale Optimization Algorithm for the Design of Tuned Mass Dampers under Earthquake Excitations. Applied Sciences, 2021; 11: 6172. doi: 10.3390/app11136172.
  23. Farzam, M. F., Jalali, H. H., Gavgani, S. A. M., Kayabekir, A. E., Bekdaş, G. Current Trends in the Optimization Approaches for Optimal Structural Control. In: S. M. Nigdeli, G. Bekdaş, A. E. Kayabekir, M. Yucel, editors. Advances in Structural Engineering—Optimization: Emerging Trends in Structural Optimization. Cham: Springer International Publishing; 2021. p. 133–179. doi:10.1007/978-3-030-61848-3_5.
  24. Mazza, F., Donnici, A., Labernarda, R. Seismic vulnerability of fixed-base and base-isolated hospitals: blind comparison between shaking table and numerical tests. Procedia Structural Integrity, 2023; 44: 147–154. doi:10.1016/j.prostr.2023.01.020.
  25. Mashayekhi, M., Estekanchi, H. E., Vafai, H., Mirfarhadi, S. A. Development of hysteretic energy compatible endurance time excitations and its application. Engineering Structures, 2018; 177: 753–769. doi:10.1016/j.engstruct.2018.09.089.
  26. Estekanchi, H. E., Mashayekhi, M., Vafai, H. A. Endurance Time Excitation Functions: Intensifying Dynamic Loads for Seismic Analysis and Design. 1st ed. Boca Raton (FL): CRC Press; 2022. doi:10.1201/9781003216681.
  27. Permanent Review Committee of the Code of Practice for Seismic-Resistant Design of Buildings. Iranian Code of Practice for Seismic-Resistant Design of Buildings (Standard No. 2800). 4th ed. Tehran (IR): Road, Housing & Urban Development Research Center; 2014 (In Persian).
  28. Pacific Earthquake Engineering Research Center. PEER Ground Motion Database. 2010. https://ngawest2.berkeley.edu/. (Accessed December 2025).
  29. Tehranizadeh, M., Khademi, M., Shirkhani, A. Seismic assessment of a dual concentrically braced steel structure under near-fault ground motions. Numerical Methods in Civil Engineering, 2022; 7: 28–36. doi:10.52547/nmce.2022.409.
  30. Yang, X.-S. Engineering Optimization: An Introduction with Metaheuristic Applications. 1st ed. Hoboken (NJ): John Wiley & Sons, Inc.; 2010. doi:10.1002/9780470640425.
  31. Katoch, S., Chauhan, S. S., Kumar, V. A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 2021; 80: 8091–8126. doi:10.1007/s11042-020-10139-6.
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