Nonlinear hysteretic modeling and parameter identification of steel strip winding reinforced composite pipe

Abstract

Steel strip winding reinforced composite pipe (SSRCP) is often used for oil and gas transportation in shallow sea. Its hysteresis characteristics under the action of low cycle load can effectively absorb external energy, which is beneficial to ensure the stability of marine structures such as ships and drilling platforms. In this paper, considering the nonlinear contact between layers, a finite element model is established to analyze the nonlinear hysteretic characteristics of SSRCP under cyclic bending load. Based on the Bouc-Wen (BW) model, an improved BW model was proposed to describe the hysteretic properties of SSRCP by introducing asymmetric factor and intensity enhancement factor. The hysteretic energy dissipation was regarded as the parameter to be identified, and the model was divided into 4 sections according to the loading law to reduce the difficulty of solving equations. Based on simulation data, PSO, GA and SA (Particle Swarm Optimization, Genetic Algorithm, and Simulated Annealing) stochastic intelligent optimization algorithm was used to identify the parameters of the improved BW model. The results show that the PSO algorithm has high calculation accuracy and efficiency, and the improved BW model can accurately describe the hysteresis characteristics of SSRCP under cyclic bending load.