A developed model updating method based on extended frequency response functions and its application study of offshore structures. (June 2023)

• Record Type: Journal Article
• Authors: Liu, Fushun; Li, Xingguo; Song, Hong; Liu, Dianzi
• Is Part Of: Applied ocean research. Volume 135(2023)
• Publication Date: 2023-06
• Subjects: Model updating -- Frequency response function -- Signature assurance criterion -- Normalized acceleration components -- Improved particle swarm algorithm; Ocean engineering -- Periodicals; 620.416205
• DOI: 10.1016/j.apor.2023.103543
• Languages: English
• ISSNs: 0141-1187

Abstract

Abstract: Accurate finite element (FE) models are extremely vital to the analysis of the dynamic characteristics of engineering structures. However, it is challenging for the frequency response function (FRF)-based model updating method to obtain reliable numerical results as the limited number of FRFs at the selected peak positions usually leads to an unacceptable or failure of model updating. Moreover, the increased number of updating coefficients in complex engineering problems generates nonlinear optimization models with the local solutions by traditional optimization techniques. To tackle these two issues, a new model updating method is proposed to make full use of FRFs extracted from measured field data of structures and the improved particle swarm optimization (PSO) technique for accurately estimating physical parameters of structures. The novelties of this research include: (1) The signature assurance criterion (SAC)-based FRF is evaluated to eliminate the influence of limited frequency points on the accuracy of the updated model using the normalized acceleration component; (2) The enhanced (PSO) is developed to realize the adaptive selection of inertia factors for the better diversity by introducing an average value of the fitness function, and then accurate predictions of updating coefficients within a smaller number of iterations are achieved using the developed constraint factor. The effectiveness of the proposed method is verified by mathematical model of a jacket platform. Results show that the proposed method can accurately obtain the updating coefficients under spatial incomplete condition, and the maximum error of natural frequencies is 0.779% using the accelerations containing 5% noise. To prove the robustness of the proposed method, experimental studies of monopile offshore wind turbine are also conducted and the maximum error of natural frequencies is 1.887% under the consideration of spatial incompleteness represented by the structural stiffness degradation. Finally, the feasibility of the proposed method is evaluated by a test of a complex jacket platform, whose variation is simulated by weakening the connections of some elements. The maximum error of natural frequencies predicted by the updated model is only 4.831% as compared with experimental results. Throughout these examples, the extended FRF model updating method provides engineers and designers with a useful insight into the development of reliable techniques to accurately predict dynamic responses of offshore structures. Highlights: A model updating method based on extended frequency response function is proposed. The accuracy of the proposed method is improved by signature assurance criterion. The intelligent algorithm is developed to efficiently update structural parameters. Results of numerical and experimental tests demonstrate the method's correctness.