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Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate model

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Abstract

An efficient reliability-based design optimization method for the support structures of monopile offshore wind turbines is proposed herein. First, parametric finite element analysis (FEA) models of the support structure are established by considering stochastic variables. Subsequently, a surrogate model is constructed using a radial basis function (RBF) neural network to replace the time-consuming FEA. The uncertainties of loads, material properties, key sizes of structural components, and soil properties are considered. The uncertainty of soil properties is characterized by the variabilities of the unit weight, friction angle, and elastic modulus of soil. Structure reliability is determined via Monte Carlo simulation, and five limit states are considered, i.e., structural stresses, tower top displacements, mudline rotation, buckling, and natural frequency. Based on the RBF surrogate model and particle swarm optimization algorithm, an optimal design is established to minimize the volume. Results show that the proposed method can yield an optimal design that satisfies the target reliability and that the constructed RBF surrogate model significantly improves the optimization efficiency. Furthermore, the uncertainty of soil parameters significantly affects the optimization results, and increasing the monopile diameter is a cost-effective approach to cope with the uncertainty of soil parameters.

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References

  1. Williams R, Zhao F, Lee J. Global Offshore Wind Report 2022. Global Wind Energy Council Technical Report. 2022

  2. Ma H, Chen C. Scour protection assessment of monopile foundation design for offshore wind turbines. Ocean Engineering, 2021, 231: 109083

    Article  Google Scholar 

  3. Hamilton B, Battenberg L, Bielecki M, Bloch C, Decker T, Frantzis L, Paidipati J, Wickless A, Zhao F. Offshore Wind Market and Economic Analysis: Annual Market Assessment. Navigant Consulting Inc. Technical Report. 2013

  4. Gentils T, Wang L, Kolios A. Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm. Applied Energy, 2017, 199: 187–204

    Article  Google Scholar 

  5. Tian X, Sun X, Liu G, Deng W, Wang H, Li Z, Li D. Optimization design of the jacket support structure for offshore wind turbine using topology optimization method. Ocean Engineering, 2022, 243: 110084

    Article  Google Scholar 

  6. Kim H G, Kim B J. Design optimization of conical concrete support structure for offshore wind turbine. Energies, 2020, 13(18): 4876

    Article  Google Scholar 

  7. O’Leary K, Pakrashi V, Kelliher D. Optimization of composite material tower for offshore wind turbine structures. Renewable Energy, 2019, 140: 928–942

    Article  Google Scholar 

  8. Ghasemi H, Brighenti R, Zhuang X, Muthu J, Rabczuk T. Optimal fiber content and distribution in fiber-reinforced solids using a reliability and NURBS based sequential optimization approach. Structural and Multidisciplinary Optimization, 2015, 51(1): 99–112

    Article  MathSciNet  Google Scholar 

  9. Wang L, Kolios A, Liu X, Venetsanos D, Cai R. Reliability of offshore wind turbine support structures: A state-of-the-art review. Renewable & Sustainable Energy Reviews, 2022, 161: 112250

    Article  Google Scholar 

  10. Ghasemi H, Kerfriden P, Bordas S P A, Muthu J, Zi G, Rabczuk T. Probabilistic multiconstraints optimization of cooling channels in ceramic matrix composites. Composites. Part B, Engineering, 2015, 81: 107–119

    Article  Google Scholar 

  11. Lee Y S, Choi B L, Lee J H, Kim S Y, Han S. Reliability-based design optimization of monopile transition piece for offshore wind turbine system. Renewable Energy, 2014, 71: 729–741

    Article  Google Scholar 

  12. Yang H, Zhu Y, Lu Q, Zhang J. Dynamic reliability based design optimization of the tripod sub-structure of offshore wind turbines. Renewable Energy, 2015, 78: 16–25

    Article  Google Scholar 

  13. Kamel A, Dammak K, Yangui M, Hami A E, Jdidia M B, Hammami L, Haddar M. A Reliability optimization of a coupled soil structure interaction applied to an offshore wind turbine. Applied Ocean Research, 2021, 113: 102641

    Article  Google Scholar 

  14. Phoon K K, Cao Z J, Ji J, Leung Y F, Najjar S, Shuku T, Tang C, Yin Z Y, Ikumasa Y, Ching J Y. Geotechnical uncertainty, modeling, and decision making. Soil and Foundation, 2022, 62(5): 101189

    Article  Google Scholar 

  15. Huang Y, He Z, Yashima A, Chen Z, Li C. Multi-objective optimization design of pile-anchor structures for slopes based on reliability theory considering the spatial variability of soil properties. Computers and Geotechnics, 2022, 147: 104751

    Article  Google Scholar 

  16. Gong W, Huang H, Juang C H, Wang L. Simplified-robust geotechnical design of soldier pile-anchor tieback shoring system for deep excavation. Marine Georesources and Geotechnology, 2017, 35(2): 157–169

    Article  Google Scholar 

  17. Haldar S, Sharma J, Basu D. Probabilistic analysis of monopile-supported offshore wind turbine in clay. Soil Dynamics and Earthquake Engineering, 2018, 105: 171–183

    Article  Google Scholar 

  18. Carswell W, Arwade S R, DeGroot D J, Lackner M A. Soil-structure reliability of offshore wind turbine monopile foundations. Wind Energy, 2015, 18(3): 483–498

    Article  Google Scholar 

  19. Oh K Y, Nam W. A fast Monte-Carlo method to predict failure probability of offshore wind turbine caused by stochastic variations in soil. Ocean Engineering, 2021, 223: 108635

    Article  Google Scholar 

  20. Rabiei M, Choobbasti A J. Innovative piled raft foundations design using artificial neural network. Frontiers of Structural and Civil Engineering, 2020, 14(1): 138–146

    Article  Google Scholar 

  21. Nariman N A, Ramadan A M, Mohammad I I. Application of coupled XFEM-BCQO in the structural optimization of a circular tunnel lining subjected to a ground motion. Frontiers of Structural and Civil Engineering, 2019, 13(6): 1495–1509

    Article  Google Scholar 

  22. Ni P, Li J, Hao H, Zhou H. Reliability based design optimization of bridges considering bridge-vehicle interaction by Kriging surrogate model. Engineering Structures, 2021, 246: 112989

    Article  Google Scholar 

  23. Liu X, Lu M, Chai Y, Tang J, Gao J. A comprehensive framework for HSPF hydrological parameter sensitivity, optimization and uncertainty evaluation based on SVM surrogate model—A case study in Qinglong River watershed, China. Environmental Modelling & Software, 2021, 143: 105126

    Article  Google Scholar 

  24. Ozcanan S, Atahan A O. RBF surrogate model and EN1317 collision safety-based optimization of two guardrails. Structural and Multidisciplinary Optimization, 2019, 60(1): 343–362

    Article  Google Scholar 

  25. Ji Y, Yang Z, Ran J, Li H. Multi-objective parameter optimization of turbine impeller based on RBF neural network and NSGA-II genetic algorithm. Energy Reports, 2021, 7: 584–593

    Article  Google Scholar 

  26. Xu K, Wang G, Zhang L, Wang L, Yun F, Sun W, Wang X, Chen X. Multi-objective optimization of jet pump based on RBF neural network model. Journal of Marine Science and Engineering, 2021, 9(2): 236

    Article  Google Scholar 

  27. Herbert-Acero J F, Probst O, Réthoré P E, Larsen G C, Castillo-Villar K K. A review of methodological approaches for the design and optimization of wind farms. Energies, 2014, 7(11): 6930–7016

    Article  Google Scholar 

  28. Chen J, Yang R, Ma R, Li J. Design optimization of wind turbine tower with lattice-tubular hybrid structure using particle swarm algorithm. Structural Design of Tall and Special Buildings, 2016, 25(15): 743–758

    Article  Google Scholar 

  29. Ma Y, Zhang A, Yang L, Hu C, Bai Y. Investigation on optimization design of offshore wind turbine blades based on particle swarm optimization. Energies, 2019, 12(10): 1972

    Article  Google Scholar 

  30. Jonkman J, Butterfield S, Musial W, Scott G. Definition of a 5-MW Reference Wind Turbine for Offshore System Development. National Renewable Energy Laboratory Technical Report (No. NREL/TP-500-38060). 2009

  31. Carswell W, Arwade S R, Johansson J, DeGroot D J. Influence of foundation damping on offshore wind turbine monopile design loads. Marine Structures, 2022, 83: 103154

    Article  Google Scholar 

  32. Liang F, Yuan Z, Liang X, Zhang H. Seismic response of monopile-supported offshore wind turbines under combined wind, wave and hydrodynamic loads at scoured sites. Computers and Geotechnics, 2022, 144: 104640

    Article  Google Scholar 

  33. IEC 61400-3:. Wind Turbines-Part 3: Design Requirements for Offshore Wind Turbines. Geneva: International Electrotechnical Commission, 2009

    Google Scholar 

  34. Chew K H, Tai K, Ng E Y K, Muskulus M. Analytical gradient-based optimization of offshore wind turbine substructures under fatigue and extreme loads. Marine Structures, 2016, 47: 23–41

    Article  Google Scholar 

  35. Jonkman J M, Buhl J M L. FAST User’s Guide Version 6.0. National Renewable Energy Laboratory Technical Report (No. NREL/EL-500-38230). 2005

  36. Jonkman B J. TurbSim User’s Guide Version 1.50. National Renewable Energy Laboratory Technical Report (No. NREL/TP-500-46198). 2009

  37. DNV-OS-J101: Design of Offshore Wind Turbine Structures. Oslo: Det Norske Veritas, 2014

    Google Scholar 

  38. DNV-RP-C205: Environmental Conditions and Environmental Loads. Oslo: Det Norske Veritas, 2010

    Google Scholar 

  39. Stewart G M, Robertson A, Jonkman J, Lackner M A. The creation of a comprehensive metocean data set for offshore wind turbine simulations. Wind Energy, 2016, 19(6): 1151–1159

    Article  Google Scholar 

  40. Yan Y, Yang Y, Bashir M, Li C, Wang J. Dynamic analysis of 10 MW offshore wind turbines with different support structures subjected to earthquake loadings. Renewable Energy, 2022, 193: 758–777

    Article  Google Scholar 

  41. Cao G, Chen Z, Wang C, Ding X. Dynamic responses of offshore wind turbine considering soil nonlinearity and wind-wave load combinations. Ocean Engineering, 2020, 217: 108155

    Article  Google Scholar 

  42. Chen S, Xing J, Yang L, Zhang H, Luan Y, Chen H, Liu H. Numerical modelling of new flap-gate type breakwater in regular and solitary waves using one-fluid formulation. Ocean Engineering, 2021, 240: 109967

    Article  Google Scholar 

  43. Yan Y, Li C, Li Z. Buckling analysis of a 10 MW offshore wind turbine subjected to wind-wave-earthquake loadings. Ocean Engineering, 2021, 236: 109452

    Article  Google Scholar 

  44. Jung S, Kim S R, Patil A, Hung L C. Effect of monopile foundation modeling on the structural response of a 5-MW offshore wind turbine tower. Ocean Engineering, 2015, 109: 479–488

    Article  Google Scholar 

  45. Kawa M, Baginska I, Wyjadlowski M. Reliability analysis of sheet pile wall in spatially variable soil including CPTu test results. Archives of Civil and Mechanical Engineering, 2019, 19(2): 598–613

    Article  Google Scholar 

  46. Damiani R R, Song H, Robertson A N, Jonkman J M. Assessing the importance of nonlinearities in the development of a substructure model for the wind turbine CAE tool FAST. In: Proceedings of OMAE 2013—32nd International Conference on Ocean, Offshore and Arctic Engineering. New York: American Society of Mechanical Engineers, 2013, V008T09A093

    Google Scholar 

  47. Al-Sanad S, Wang L, Parol J, Kolios A. Reliability-based design optimisation framework for wind turbine towers. Renewable Energy, 2021, 167: 942–953

    Article  Google Scholar 

  48. DNVGL-RP-C202: Buckling Strength of Shells. Oslo: Det Norske Veritas, 2017

    Google Scholar 

  49. NORSOK N-004: Design of Steel Structures. Oslo: Norwegian Technology Standards Institution, 2013

    Google Scholar 

Download references

Acknowledgements

This study was supported by the National Natural Science Foundation of China (Grant No. 12072104) and the National Key R&D Program of China (No. 2018YFC0406703).

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Authors and Affiliations

  1. Department of Engineering Mechanics, Hohai University, Nanjing, 211100, China

    Changhai Yu, Xiaolong Lv, Dan Huang & Dongju Jiang

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  1. Changhai Yu
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  2. Xiaolong Lv
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  3. Dan Huang
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  4. Dongju Jiang
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Correspondence to Dan Huang.

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Yu, C., Lv, X., Huang, D. et al. Reliability-based design optimization of offshore wind turbine support structures using RBF surrogate model. Front. Struct. Civ. Eng. 17, 1086–1099 (2023). https://doi.org/10.1007/s11709-023-0976-8

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