Validation and calibration of computer simulated probability of detection curves from ultrasonic inspection
Abstract
In order to verify and ensure the structural integrity of industrial components, nondestructive testing (NDT) techniques are a powerful tool. Aiming the quantification of reliability of a particular NDT, probability of detection (POD) curves are often used. Given their stochastic nature, POD curves are dependent not only on the physical phenomena that governs the NDT technique but also on other factors, known as uncertainty parameters, which leads to a normally requested 95% confidence level for their estimates. Therefore, in order to satisfy a 95% confidence level, it is necessary to gather a large volume of experimental data, besides a sophisticated control of sizing and location of defects in a test piece, which is very costly.
It is already well established that Model-Assisted PODs have the potential to reduce those costs by generating data through numerical modelling, leading to a prediction of the POD curve using, many times, computer simulation in the process. The present study demonstrates how simulations can be optimised, shedding light on the most significant parameters that result in better agreement between simulated and measured POD curves. Further, it validates simulated POD curves using the software CIVA by comparing them to industrial ultrasonic inspections on API 5L X-65 pipes.
It is already well established that Model-Assisted PODs have the potential to reduce those costs by generating data through numerical modelling, leading to a prediction of the POD curve using, many times, computer simulation in the process. The present study demonstrates how simulations can be optimised, shedding light on the most significant parameters that result in better agreement between simulated and measured POD curves. Further, it validates simulated POD curves using the software CIVA by comparing them to industrial ultrasonic inspections on API 5L X-65 pipes.
