Bayesian Inspection Interval for Aboveground Storage Tanks
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Solution Overview
Problem
Current methods for determining the time to the next out-of-service inspection of steel aboveground storage tanks are overly conservative, leading to unnecessary maintenance and operational downtime, and do not effectively account for the condition of the tank bottom, resulting in high costs and potential environmental risks.
Innovation Solution
A method combining in-service measurements of tank bottom thickness, corrosion rate, and integrity using Bayesian survival analysis to determine the time to the next out-of-service inspection (TNI) through the integration of Equivalent Risk (TNI-ER) and additional measurements, allowing for the update of inspection intervals based on the tank's actual condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fixed inspection intervals are used, then safety is maintained through frequent inspections, but operational downtime and costs increase due to unnecessary inspections
Solution Approach 1:
The inspection interval is changed from a fixed time-based parameter to a condition-based parameter. The method uses measured corrosion rates and tank bottom thickness to dynamically determine the inspection interval, allowing extensions when conditions are good and maintaining short intervals when degradation is detected. This resolves the contradiction by making inspections necessary rather than routine.
Solution Approach 2:
The tank effectively monitors its own condition through the measurement of corrosion rates and thickness parameters. The data collected from the tank itself (corrosion measurements, thickness readings) is used to determine when inspection is needed, eliminating the need for external assumptions about inspection timing. The tank's actual condition drives the inspection schedule.
2Reliability
If conservative inspection schedules are implemented, then risk of tank failure is reduced, but maintenance costs increase due to frequent out-of-service inspections
Solution Approach 1:
The method implements continuous feedback through corrosion rate measurements and thickness monitoring. These measurements feed into a model that updates the inspection interval recommendation. When measurements show low corrosion and adequate thickness, the system feedbacks an extended interval, reducing unnecessary maintenance costs while maintaining safety through condition-based decision making.
Solution Approach 2:
The inspection interval transitions from a static, predetermined value to a dynamic parameter that adjusts based on measured conditions. The method continuously evaluates current tank state (corrosion rate, thickness, remaining life) and adjusts the next inspection timing accordingly, optimizing the balance between safety and cost.
3Productivity
If in-service measurements are used to extend inspection intervals, then operational efficiency improves, but measurement and analysis complexity increases
Solution Approach 1:
The complex assessment is segmented into distinct measurable parameters: corrosion rate, tank bottom thickness, and remaining life calculation. Each parameter is measured or calculated separately using standardized methods, then integrated into the overall inspection interval determination. This segmentation makes the complex process manageable and systematic.
Solution Approach 2:
The method introduces an intermediate computational model that processes raw measurement data (corrosion rates, thickness readings) and transforms them into actionable inspection interval recommendations. This intermediary layer handles the complexity of Bayesian updating and probability calculations, shielding operators from the mathematical complexity while enabling advanced analysis.
Data Source
AI summary
Methods for quantitatively determining the time (TNI) between (1) the application of this method and (2) the time at which an out-of-service internal inspection of a steel, field-erected, aboveground storage tank (AST) containing a petroleum product or water should be performed. These methods combine in-service measurements of the thickness, integrity, and corrosion rate of the tank bottom with an empirical corrosion rate cumulative frequency distribution (CFD) for the tank of interest to develop a Bayesian tank bottom survival probability distribution to determine TNI. During this entire TNI time period, the risk of tank bottom failure is less than at the time these methods were applied. If available, the results of a previous out-of-service API 653 internal inspection are also used. These methods are applied to a single tank and can be applied at any time during the service life of a tank to check or update the internal inspection interval that was previously determined that is based on the condition of the tank bottom. These methods focus on refined petroleum applications, but they can be applied to a wide range of liquid products providing the maximum corrosion rate CFD of the tank bottom can be determined.