With the uncertainties related to operating conditions,in-service non-destructive testing(NDT) measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on the failure assessment diagram(FAD) approach has recently become an important concern.However,the point density revealing the probabilistic distribution characteristics of the assessment points is usually ignored.To obtain more detailed and direct knowledge from the reliability analysis,an improved probabilistic fracture mechanics(PFM) assessment method is proposed.By integrating 2D kernel density estimation(KDE) technology into the traditional probabilistic assessment,the probabilistic density of the randomly distributed assessment points is visualized in the assessment diagram.Moreover,a modified interval sensitivity analysis is implemented and compared with probabilistic sensitivity analysis.The improved reliability analysis method is applied to the assessment of a high pressure pipe containing an axial internal semi-elliptical surface crack.The results indicate that these two methods can give consistent sensitivities of input parameters,but the interval sensitivity analysis is computationally more efficient.Meanwhile,the point density distribution and its contour are plotted in the FAD,thereby better revealing the characteristics of PFM assessment.This study provides a powerful tool for the reliability analysis of critical structures.
展开▼
机译:A novel approach for reliability assessment of residual heat removal system for HPR1000 based on failure mode and effect analysis, fault tree analysis, and fuzzy Bayesian network methods
机译:J-integral analysis based on failure assessment diagram and its application to evaluation of crack growth due to cyclic overload in carbon steel pipes
机译:metodi microbiologici Tradizionali e metodi moleculeolari per l'analisi degli integratori alimentari a base di o con probiotici per ujso umano(microbiological and molecular methods for analysis of probiotic Based Food supplements for Human Consumption)。