Effect of creep on the failure probability of bolted flange joints. (April 2015)

• Record Type: Journal Article
• Authors: Mourya, R.K.; Banerjee, A.; Sreedhar, B.K.
• Is Part Of: Engineering failure analysis. Volume 50(2015:Apr.)
• Page Start: 71
• Page End: 87
• Publication Date: 2015-04
• Subjects: Flange joint of SG -- Creep-relaxation -- Deformation compatibility model -- Failure probability -- Sensitivity analysis; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2015.01.005
• Languages: English
• ISSNs: 1350-6307

Abstract

Graphical abstract: Highlights: Establish the temperature field in representative flange joint assembly. Development of analytical model to predict the load relaxation on gasket. Validation of theoretical model using 3-D structural analysis. Probabilistic analysis to quantify effects of uncertainties using Monte-Carlo simulation. Sensitivity analysis to identify the critical design parameters. Abstract: The case of a bolted flange joint that is part of a model steam generator (SG) for sodium-cooled fast reactor (SFR) is studied to establish the statistical nature of the time to failure due to relaxation of gasket stress. Continued relaxation over a period of time lowers the gasket stresses to a critical sealing limit, causing failure due to leakage, one of the key modes of failure of bolted joints. An analytical model based on deformation compatibility is used to predict gasket load relaxation with time, which includes flexibility and creep behavior of joint members. A corresponding structural analysis was carried out to validate the analytical model. A probabilistic approach is taken to quantify the effect of uncertainties associated with the design variables on the failure of joint using the analytical model. In order to obtain probability of joint failure, Monte-Carlo sampling method was used for statistical trials. Further, sensitivity analysis was carried out to identify the critical design parameters.