When a small crack is detected and quantitatively sized and located in a pressure vessel or piping by nondestructive methods, we can estimate the 95 % lower confidence limit of the fatigue or creep rupture life, or, the minimum time to failure (mTF) of the vessel or piping by applying the classical law of fracture mechanics for crack growth, if we know the " local physics"   well, i.e., the crack growth exponent of the specific vessel or piping material, and the crack measurement data, including a good estunate of their uncertainties.  In this paper, we design an intelligent piping maintenance code by developing a decision making and risk management model, where the cost of a decision to schedule a repair as soon as a crack is found is compared with that of a decision to delay until next scheduled outage, or, that of a more pro-active decision to monitor the crack to buy time and gather new information for making a better estimate of the mTF as the basis for a second round of maintenance decision making.  An extension of the decision making model to include utility functions is also presented. A numerical example is included to illustrate the feasibility of this intelligent decision making code. Significance and limitations of the code are presented and discussed.


Design of an Intelligent Piping Maintenance Code for Oil / Gas Pipeline, Powerplant & Chemical Processing Plant Management Decision Making

Division / Sponsors: 
Pressure Vessels & Piping (PVP)


Paper Proceedings: https://asmedigitalcollection.asme.org/PVP/PVP2020/volume/83815

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