Pipeline HIC Growth Prediction for Targeted Inspection Scheduling

The patent applies preliminary action by performing parametric simulations and design-of-experiment analyses before actual inspections to pre-determine optimal inspection locations, timing, and techniques. This allows the system to focus advanced ultrasonic testing only on high-risk areas identified through mechanistic modeling, rather than requiring comprehensive monitoring of entire pipelines.

The patent creates a virtual copy of the pipeline system through mechanistic models that simulate HIC damage progression. This digital twin allows prediction of crack growth rates and identification of critical locations, enabling targeted physical inspections that reduce the need for extensive advanced ultrasonic testing while maintaining detection precision.

The system performs preliminary mechanistic modeling and parametric simulations to predict HIC damage progression and identify high-risk locations before inspections occur. This allows inspection intervals to be optimized based on predicted damage rates, reducing unnecessary frequent inspections in low-risk areas while maintaining reliability through targeted monitoring of critical locations.

The patent implements dynamic inspection scheduling that adjusts inspection frequency based on real-time predictions from the mechanistic model. As the model predicts increased HIC growth rates in specific locations, inspection frequency at those locations is automatically increased, while locations with stable conditions require less frequent monitoring, optimizing the balance between reliability and time loss.

The patent applies local quality by concentrating advanced ultrasonic testing resources on specific high-risk locations identified through mechanistic modeling, rather than uniformly applying comprehensive mapping to entire pipelines. The system determines local inspection intensity based on predicted HIC damage probability and growth rates at each location, optimizing the balance between measurement precision and computing resource usage.

The patent segments the pipeline into multiple zones with different inspection requirements based on mechanistic model predictions. High-risk segments identified through parametric simulations receive comprehensive advanced ultrasonic testing, while low-risk segments use simpler inspection methods or extended intervals, reducing overall computing time and energy consumption while maintaining adequate monitoring coverage.

The patent creates simplified surrogate models that replicate the behavior of complex mechanistic models. These surrogate models are trained using parametric simulations and design-of-experiment data, then deployed for routine predictions. This copying approach maintains the productivity benefits of mechanistic modeling while reducing the computational complexity and resource requirements for actual deployment.

The system performs extensive parametric simulations and design-of-experiment analyses in advance to pre-compute response surfaces and calibration data. This preliminary action allows the final prediction model to operate with reduced complexity, as the computationally intensive work has already been completed during the modeling phase rather than during routine predictions.