Title of article :
Reliability analysis of pipelines carrying H2S for risk based inspection of heavy water plants
Author/Authors :
a Santosh، نويسنده , , Gopika Vinod، نويسنده , , O.P. Shrivastava، نويسنده , , R.K. Saraf، نويسنده , , A.K. Ghosh، نويسنده , , H.S. Kushwaha، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2006
Pages :
8
From page :
163
To page :
170
Abstract :
Reliability analysis of pipelines containing corrosion defects due to H2S is presented. The pipeline carrying H2S is more susceptible to the internal corrosion thereby reducing the pipelineʹs load carrying capacity. The objective of this study is to obtain the pipelinesʹ failure probabilities that are required in establishing a Risk Based Inspection (RBI) programme for heavy water plants. The reliability assessment of pipelines involves the estimation of failure pressure and evaluating the limit state function. Several failure pressure models were studied for this purpose and it was found that the modified B31G failure pressure model is most suitable for the pipeline failure pressure modeling. Due to the presence of non-linearity in the limit state function and non-normal variables, the first order reliability method has been employed for carrying out the reliability analysis. The uncertainty of the random variables on which the limit state function depends is modeled using normal and non-normal probabilistic distributions. The failure probabilities and the categories of the pipelines connected to the first pair of first stage of exchange towers are presented. In addition, a sensitivity analysis was carried out on random variables involved in the problem. The results of sensitivity analysis are also presented.
Keywords :
Failure pressure models , Corrosion due to H2S , Sensitivity analysis , Reliability index , Risk-based inspection , First Order Reliability Methods
Journal title :
Reliability Engineering and System Safety
Serial Year :
2006
Journal title :
Reliability Engineering and System Safety
Record number :
1187418
Link To Document :
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