Optimization of Tuned Mass Damper for Submerged Floating Tunnel with Frequency-Domain Dynamics Simulation
Abstract - 513
PDF

Keywords

Optimization
Genetic algorithm
Tuned mass damper
Discrete module beam
Submerged floating tunnel

How to Cite

Jin, C. ., Kim, S.-J., & Kim, M. (2022). Optimization of Tuned Mass Damper for Submerged Floating Tunnel with Frequency-Domain Dynamics Simulation. Journal of Advances in Applied & Computational Mathematics, 9, 147–156. https://doi.org/10.15377/2409-5761.2022.09.11

Abstract

In this study, the Tuned Mass Damper (TMD) optimization is carried out to reduce the resonant motion of Submerged Floating Tunnel (SFT) under wave excitations. The SFT dynamics is evaluated in frequency domain; a new approach to cost-effectively optimizing TMD parameters for a moored system is suggested. Discrete-Module-Beam (DMB) method is used to model the Tunnel; mooring lines are included as equivalent stiffness matrix through static-offset tests by the fully coupled model. Since the frequency-domain dynamics simulation model is employed, a significant reduction in optimization time can be achieved. TMD is installed at the tunnel’s mid-length to mitigate the lateral motion of the Tunnel and coupled with the Tunnel with translational and rotational springs and dampers. The optimization process for TMD parameters is performed through the Genetic Algorithm (GA). The GA generates the TMD mass and spring and damping coefficients. The dynamics simulation is performed under wave conditions and this process is repeated until the stopping criteria is satisfied. Results demonstrate that TMD with optimized parameters significantly reduces the lateral motion, especially near the system’s lowest lateral natural frequency. This frequency-domain optimization also works as intended with significantly decreased optimization time.

https://doi.org/10.15377/2409-5761.2022.09.11
PDF

References

Jin C, Kim M, Chung WC, Kwon D-S. Time-domain coupled analysis of curved floating bridge under wind and wave excitations. Ocean Syst Eng. 2020; 10: 399-414.

Jin C, Kim M-H. Tunnel-mooring-train coupled dynamic analysis for submerged floating tunnel under wave excitations. Appl Ocean Res. 2020; 94: 102008. https://doi.org/10.1016/j.apor.2019.102008

Kim G-J, Kwak H-G, Jin C, Kang H, Chung W. Three-dimensional equivalent static analysis for design of submerged floating tunnel. Mar Struct. 2021; 80: 103080. https://doi.org/10.1016/j.marstruc.2021.103080

Lee J, Jin C, Kim M. Dynamic response analysis of submerged floating tunnels by wave and seismic excitations. Ocean Syst Eng. 2017; 7: 1-19. https://doi.org/10.12989/ose.2017.7.1.001

Jin C, Kim M. The effect of key design parameters on the global performance of submerged floating tunnel under target wave and earthquake excitations. CMES-Comput Model Eng Sci. 2021; 128: 315-37. https://doi.org/10.32604/cmes.2021.016494

Jin C, Kim M-H. Time-domain hydro-elastic analysis of a SFT (submerged floating tunnel) with mooring lines under extreme wave and seismic excitations. Appl Sci. 2018; 8: 2386. https://doi.org/10.3390/app8122386

Lu W, Ge F, Wang L, Wu X, Hong Y. On the slack phenomena and snap force in tethers of submerged floating tunnels under wave conditions. Mar Struct. 2011; 24: 358-76. https://doi.org/10.1016/j.marstruc.2011.05.003

Yanik A, Aldemir U, Bakioglu M. Seismic vibration control of three-dimensional structures with a simple approach. J Vibrat Eng Technol. 2016; 4: 235-47.

Wu Q, Zhao X, Zheng R, Minagawa K. High response performance of a tuned-mass damper for vibration suppression of offshore platform under earthquake loads. Shock Vibrat. 2016; 7383679: 1-11. https://doi.org/10.1155/2016/7383679

Lee H, Wong S-H, Lee R-S. Response mitigation on the offshore floating platform system with tuned liquid column damper. Ocean Eng. 2006; 33: 1118-42. https://doi.org/10.1016/j.oceaneng.2005.06.008

Wu B, Shi P, Wang Q, Guan X, Ou J. Performance of an offshore platform with MR dampers subjected to ice and earthquake. Struct Cont Health Monit. 2011; 18: 682-97. https://doi.org/10.1002/stc.398

Zribi M, Almutairi N, Abdel-Rohman M, Terro M. Nonlinear and robust control schemes for offshore steel jacket platforms. Nonlinear Dyn. 2004; 35: 61-80. https://doi.org/10.1023/B:NODY.0000017499.49855.14

Jin C, Chung WC, Kwon D-S, Kim M. Optimization of tuned mass damper for seismic control of submerged floating tunnel. Eng Struct. 2021; 241: 112460. https://doi.org/10.1016/j.engstruct.2021.112460

Den Hartog JP. Mechanical vibrations. New York: Dover Publications 1985.

Warburton G. Optimum absorber parameters for various combinations of response and excitation parameters. Earthquake Eng Struct Dyn. 1982; 10: 381-401. https://doi.org/10.1002/eqe.4290100304

Bekdaş G, Nigdeli SM. Mass ratio factor for optimum tuned mass damper strategies. Int J Mechan Sci. 2013; 71: 68-84. https://doi.org/10.1016/j.ijmecsci.2013.03.014

Lin C-C, Wang J-F, Ueng J-M. Vibration control identification of seismically excited mdof structure-PTMD systems. J Sound Vibrat. 2001; 240: 87-115. https://doi.org/10.1006/jsvi.2000.3188

Bekdaş G, Nigdeli SM. Estimating optimum parameters of tuned mass dampers using harmony search. Eng Struct. 2011; 33: 2716-23. https://doi.org/10.1016/j.engstruct.2011.05.024

Yucel M, Bekdaş G, Nigdeli SM, Sevgen S. Estimation of optimum tuned mass damper parameters via machine learning. J Build Eng. 2019; 26: 100847. https://doi.org/10.1016/j.jobe.2019.100847

Ma L, Li N, Guo Y, Wang X, Yang S, Huang M, et al. Learning to optimize: reference vector reinforcement learning adaption to constrained many-objective optimization of industrial copper burdening system. IEEE Transact Cybernet. 2021; (e-pub ahead of print). https://doi.org/10.1109/TCYB.2021.3086501

Ma L, Cheng S, Shi Y. Enhancing learning efficiency of brain-storm optimization via orthogonal learning design. IEEE Transact Syst Man, Cybernet Syst. 2020; 51: 6723-42. https://doi.org/10.1109/TSMC.2020.2963943

Awad A, Hawash A, Abdalhaq B. A Genetic Algorithm (GA) and Swarm Based Binary Decision Diagram (BDD) Reordering Optimizer Reinforced with Recent Operators. IEEE Transact Evolut Comput. 2022; (e-pub ahead of print). https://doi.org/10.1109/TEVC.2022.3170212

Alibrahim H, Ludwig SA. Hyperparameter optimization: comparing genetic algorithm against grid search and bayesian optimization. 2021 IEEE Congress Evolut Comput (CEC); 28 June 2021 - 01 July 2021; Kraków, Poland. IEEE: 2021; p. 1551-9. https://doi.org/10.1109/CEC45853.2021.9504761

Sadek F, Mohraz B, Taylor AW, Chung RM. A method of estimating the parameters of tuned mass dampers for seismic applications. Earthquake Eng Struct Dyn. 1997; 26: 617-35. https://doi.org/10.1002/(SICI)1096-9845(199706)26:6<617::AID-EQE664>3.0.CO;2-Z

Jin C, Kim S-J, Kim M. Vibration control of submerged floating tunnel in waves and earthquakes through tuned mass damper. Int J Naval Architect Ocean Eng. 2022; 14: 100483. https://doi.org/10.1016/j.ijnaoe.2022.100483

Lu D, Fu S, Zhang X, Guo F, Gao Y. A method to estimate the hydroelastic behaviour of VLFS based on multi-rigid-body dynamics and beam bending. Ships Offshore Struct. 2016; 14: 354-62. https://doi.org/10.1080/17445302.2016.1186332

Wei W, Fu S, Moan T, Lu Z, Deng S. A discrete-modules-based frequency domain hydroelasticity method for floating structures in inhomogeneous sea conditions. J Fluids Struct. 2017; 74: 321-39. https://doi.org/10.1016/j.jfluidstructs.2017.06.002

Bakti FP, Jin C, Kim M-H. Practical approach of linear hydro-elasticity effect on vessel with forward speed in the frequency domain. J Fluids Struct. 2021; 101: 103204. https://doi.org/10.1016/j.jfluidstructs.2020.103204

Jin C, Bakti FP, Kim M. Multi-floater-mooring coupled time-domain hydro-elastic analysis in regular and irregular waves. Appl Ocean Res. 2020; 101: 102276. https://doi.org/10.1016/j.apor.2020.102276

Orcina. OrcaFlex User Manual Version 11.0 d. 2020.

Jin C, Bakti FP, Kim M. Time-domain coupled dynamic simulation for SFT-mooring-train interaction in waves and earthquakes. Mar Struct. 2021; 75: 102883. https://doi.org/10.1016/j.marstruc.2020.102883

Etedali S, Rakhshani H. Optimum design of tuned mass dampers using multi-objective cuckoo search for buildings under seismic excitations. Alexandria Eng J. 2018; 57: 3205-18. https://doi.org/10.1016/j.aej.2018.01.009

Marano GC, Greco R, Trentadue F, Chiaia B. Constrained reliability-based optimization of linear tuned mass dampers for seismic control. Int J Solids Struct. 2007; 44: 7370-88. https://doi.org/10.1016/j.ijsolstr.2007.04.012

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2022 Chungkuk Jin, Sung-Jae Kim, MooHyun Kim