This is a U.S. Government work and, as such, is in the public domain in the United States of America.
Validation of spring operated pressure relief valve time-to-failure†
Article first published online: 17 AUG 2009
Published 2009 American Institute of Chemical Engineers (AIChE)
Process Safety Progress
Volume 29, Issue 1, pages 55–59, March 2010
How to Cite
Harris, S. P. and Gross, R. E. (2010), Validation of spring operated pressure relief valve time-to-failure. Proc. Safety Prog., 29: 55–59. doi: 10.1002/prs.10344
- Issue published online: 4 FEB 2010
- Article first published online: 17 AUG 2009
- relief valve;
- relief maintenance;
The Savannah River Site operates a relief valve repair shop certified by the National Board of Pressure Vessel Inspectors. Local maintenance forces perform inspection, testing, and repair of ∼1,200 spring-operated relief valves each year as the valves are cycled in from the field.
The Site now has over 7,000 certified test records in the Computerized Maintenance Management System; a summary of that data is presented in this article. In previous articles, several statistical techniques were used to investigate failure on demand and failure rates including a quantal response method for predicting the probability of failure. The nonconservative failure mode is commonly termed “stuck shut”; industry defined as the valve opening at greater than or equal to 1.5 times the cold set pressure. Actual time-to-failure is typically not known, only that failure occurred some time since the last proof test.
The resulting Monte Carlo simulation in this article shows that previous conclusions on the statistical lifetime predictions and failure studies were not as conservative as initially thought. Our simulations use an aging model for lift pressure increase as a function of set pressure, valve manufacturer, and time. This article attempts to answer two questions: (a) what is the predicted failure rate over the chosen maintenance/inspection interval, and (b) do we understand aging and variability sufficiently to estimate risk when basing proof test intervals on proof test results? © 2009 American Institute of Chemical Engineers Process Saf Prog 2010