Simulation-Based Investigation of a Probability of Detection (POD) Model Using Phased Array Ultrasonic Testing (PAUT) Technique
Journal article, 2022

Probability of detection (POD) as a metric for quantifying the capability of inspection procedures in nondestructive evaluation (NDE), has been applied and evolved in industries since 1970s. Progress had been noted when certain statistical functions were brought up to model POD behavior, including log-normal model (also referred as Probit model). This model had been concluded to be the best fit and therefore has been widely used in many studies, while the involved assumptions and conditions were not carefully addressed and explored. To make flexible POD datasets available for specific inspection procedures and reduce the number of expensive experiments needed, model-assisted POD (MAPOD) is an alternative. This paper addresses a pure simulation-based POD procedure of an inspection scenario involving phased array ultrasonic testing (PAUT) on lack-of-fusion defects in additive manufactured (AM) components. The mathematical simulations are performed by an ultrasonic testing (UT) simulation software, simSUNDT, developed at Chalmers University of Technology in Sweden. Resulted inspection datasets with the proposed data processing steps are evaluated in terms of the assumptions and conditions of log-normal POD model, with the purpose of discussing the POD model validity under different circumstances. Simulation-based POD curves are finally compared with several discrete POD values at some defect sizes, calculated through massive computations from physics-model based metamodel. Comparisons and observations confirm satisfactory application of log-normal POD model despite some violations in model hypotheses.

Nondestructive evaluation (NDE)

Phased array ultrasonic testing (PAUT)



Numerical simulation


Xiangyu Lei

Chalmers, Industrial and Materials Science, Engineering Materials

Håkan Wirdelius

University West

Anders Rosell

GKN Aerospace Services

Journal of Nondestructive Evaluation

0195-9298 (ISSN) 1573-4862 (eISSN)

Vol. 41 2 40

Subject Categories

Probability Theory and Statistics



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