Stephen P. Harris

Analysis of safety relief valve proof test data to optimize lifecycle maintenance costs

Proof test results were analyzed and compared with a proposed life cycle curve or hazard function and the limit of useful life. Relief valve proof testing procedures, statistical modeling, data collection processes, and time-in-service trends are presented. The resulting analysis of test data allows for the estimation of a probability of failure on demand (PFD). Extending maintenance intervals to the limit of useful life as well as methodologies and practices for improving relief valve performance and reliability are discussed. A generic cost-benefit analysis and an expected life cycle cost reduction concludes that

Simulation modeling for maritime port security

90 million maintenance dollars might be avoided for a population of 3000 valves over 20 years.

Extending Pressure Relief Valve Inspection Intervals by Using Statistical Analysis of Proof Test Data

United States ports must be prepared for the threat of a small-vessel attack using weapons of mass destruction (WMD). To reduce the risk of such an attack, modeling was conducted at the Savannah River National Laboratory (SRNL) in Aiken, South Carolina, to develop options for redeployment of existing maritime law enforcement resources, deployment of new resources, and optimal use of geographic terrain. Agent-based modeling (ABM) implemented by the Automated Vulnerability Evaluation for Risks of Terrorism (AVERT®) software was used to conduct computer-based simulation modeling. The port-specific models provided estimates for the probability of encountering an adversary based on allocated resources under varying environmental conditions and traffic flow rates. Defensive resources include patrol and response platforms, some of which may be more appropriate in particular environmental conditions. A diverse range of potential adversary and attack scenarios was assessed for a large area port and also for a port with a narrow inlet, thereby identifying vulnerable pathways. For chokepoint operations, the probability of encountering an adversary was estimated for various configurations and operational tempos. As traffic flow increased, the probability of encountering an adversary decreased because the adversary could assimilate into traffic, while security forces were preoccupied inspecting pleasure craft. However, there was a significant increase in the probability of encountering an adversary (P(Encounter)) when additional patrols were added. Noted was a decreasing marginal benefit of additional patrols at low traffic levels. In open water, use of helicopters on patrol substantially increased the P(Encounter) by directing on-water security to target vessels. This capability was due to the far-reaching vision and speed capabilities of helicopters. As a result of ABM, more effective countermeasures can be deployed with available resources to reduce the risk of a small-vessel attack using WMD. The models can be expanded to all ports in the United States using generic models similar to those presented herein that can be matched to any port based on its size and shape.

Validation of spring operated pressure relief valve time-to-failure†

This paper correlates as-received relief valve test results with current inspection intervals and presents conclusions based on statistical analysis. During the past three year period over 500 used valve proof test records from a site population of 3500 safety relief valves were acquired and reviewed. Collection and analysis of spring-loaded relief valve test data continues with the goal being to increase the test intervals within guidelines, reduce costs, and maintain safety margins. Based on current test intervals of 1–7 years, time in service appears to have a minimal effect on valve performance. Seat material and inlet size are identified as having a statistically significant impact on valve performance. An increase in TP/SP of 1–2% per year was noted for soft seated, small inlet sizes. Photographs of failed valve internals and discussion of failure causes are included.Copyright

The Effects of Maintenance Actions on the PFDavg of Spring Operated Pressure Relief Valves

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.

Statististical Performance Evaluation of Soft Seat Pressure Relief Valves

The safety integrity level (SIL) of equipment used in safety instrumented functions is determined by the average probability of failure on demand (PFDavg) computed at the time of periodic inspection and maintenance, i.e., the time of proof testing. The computation of PFDavg is generally based solely on predictions or estimates of the assumed constant failure rate of the equipment. However, PFDavg is also affected by maintenance actions (or lack thereof) taken by the end user. This paper shows how maintenance actions can affect the PFDavg of spring operated pressure relief valves (SOPRV) and how these maintenance actions may be accounted for in the computation of the PFDavg metric. The method provides a means for quantifying the effects of changes in maintenance practices and shows how these changes impact plant safety.

Estimated SIL Levels and Risk Comparisons for Relief Valves as a Function of Time-in-Service

Risk-based inspection methods enable estimation of the probability of failure on demand for spring-operated pressure relief valves at the United States Department of Energys Savannah River Site in Aiken, South Carolina. This paper presents a statistical performance evaluation of soft seat spring operated pressure relief valves. These pressure relief valves are typically smaller and of lower cost than hard seat (metal to metal) pressure relief valves and can provide substantial cost savings in fluid service applications (air, gas, liquid, and steam) providing that probability of failure on demand (the probability that the pressure relief valve fails to perform its intended safety function during a potentially dangerous over pressurization) is at least as good as that for hard seat valves. The research in this paper shows that the proportion of soft seat spring operated pressure relief valves failing is the same or less than that of hard seat valves, and that for failed valves, soft seat valves typically have failure ratios of proof test pressure to set pressure less than that of hard seat valves.

STATISTICAL SAMPLING FOR IN-SERVICE INSPECTION OF LIQUID WASTE TANKS AT THE SAVANNAH RIVER SITE

Risk-based inspection methods enable estimation of the probability of spring-operated relief valves failing on demand at the United States Department of Energys Savannah River Site (SRS) in Aiken, South Carolina. The paper illustrates an approach based on application of the Frechet and Weibull distributions to SRS and Center for Chemical Process Safety (CCPS) Process Equipment Reliability Database (PERD) proof test results. The methodology enables the estimation of ANSI/ISA-84.00.01 Safety Integrity Levels (SILs) as well as the potential change in SIL level due to modification of the maintenance schedule. Current SRS practices are reviewed and recommendations are made for extending inspection intervals. The paper compares risk-based inspection with specific SILs as maintenance intervals are adjusted. Groups of valves are identified in which maintenance times can be extended as well as different groups in which an increased safety margin may be needed.

The Effects of Maintenance Actions on the Average Probability of Failure on Demand of Spring Operated Pressure Relief Valves

Savannah River Remediation, LLC (SRR) is implementing a statistical sampling strategy for In-Service Inspection (ISI) of Liquid Waste (LW) Tanks at the United States Department of Energys Savannah River Site (SRS) in Aiken, South Carolina. As a component of SRSs corrosion control program, the ISI program assesses tank wall structural integrity through the use of ultrasonic testing (UT). The statistical strategy for ISI is based on the random sampling of a number of vertically oriented unit areas, called strips, within each tank. The number of strips to inspect was determined so as to attain, over time, a high probability of observing at least one of the worst 5% in terms of pitting and corrosion across all tanks. The probability estimation to determine the number of strips to inspect was performed using the hypergeometric distribution. Statistical tolerance limits for pit depth and corrosion rates were calculated by fitting the lognormal distribution to the data. In addition to the strip sampling strategy, a single strip within each tank was identified to serve as the baseline for a longitudinal assessment of the tank safe operational life. The statistical sampling strategy enables the ISI program to develop individual profiles of LW tank wall structural integrity that collectively provide a high confidence in their safety and integrity over operational lifetimes.