Bending Fatigue Reliability of Internal Pressured Pipeline

Abstract:

The active learning reliability method in combination with Kriging and Monte Carlo simulation （AK-MCS） is applied to the reliability analysis of the fatigue life of the cantilever internal pressured pipeline under the given working condition （i.e.， 28 MPa internal pressure， 5.06 mm longitudinal displacement cyclic load at free end） by considering the randomness of the design sizes， working load， and material properties. First， the Manson coffin fatigue life model of the pipeline is established by linear regression analysis， according to the results of three-point bending test. Then， the fatigue life failure probability/reliability curve of the hydraulic pipeline is obtained by using AK-MCS， which provides the life prediction value based on the probability for the engineering application of the pressured pipeline. Finally， the fatigue life frequency histogram is obtained by the curve. It is found that the bending fatigue life of the pipeline is generally normal distributed. Moreover， by solving the small probability event problem， it is shown that compared with MCS， AK-MCS reduces the time of the FEM （finite element method） analysis and ensures the accuracy of reliability analysis.

Key words:internal pressured pipeline;fatigue reliability;Kriging surrogate model;Monte Carlo simulation;active learning method