64603 2023 eng poster 0 -- -- -- The analysis of pipeline failures due to Microbiologically Influenced Corrosion (MIC) is challenging due to the complex interaction of many influencing parameters including pipeline operation conditions, fluid chemistry and microbiology, as well as the analysis of corrosion features and products. To help address this challenge, an expert system was developed to assist non-specialists in screening internal pipeline corrosion failures due to MIC related threats. To accomplish this, 15 MIC subject matter experts (with a total of 355 man-years of accumulated MIC based experience) were recruited to evaluate a total of 65 MIC failure cases based on real-life scenarios. These case study parameters and the expert elicited results were input into an Artificial Neural Network (ANN) model to create a model system which can screen whether a given failure scenario is one of three outcomes: a) failure is likely due to MIC, b) failure is likely not due to MIC, or c) the conclusion is inconclusive (analysis needs more data/information). The model system had an overall accuracy of 74.8% and it showcases that knowledge from subject matter experts can be captured in a reasonably effective way to screen for possible MIC failures. Based on that, this presentation will provide details of the model development process and key results to date. Important considerations regarding the level of confidence of the diagnoses and variation between expert opinion will also be discussed alongside with ideas on how to improve the model for field applicability. ISMOS 9 Edinburgh, United Kingdom 27.06.2023 30.06.2023 https://doi.org/10.1016/j.engfailanal.2024.108426 publish false true André de Araujo Abilio eng uncontrolled Expert System eng uncontrolled Microbiologically Influenced Corrosion (MIC) eng uncontrolled Oil and Gas Upstream eng uncontrolled Failure Investigation eng uncontrolled Artificial neural networks (ANN) Angewandte Physik 4 Material und Umwelt 4.1 Biologische Materialschädigung und Referenzorganismen 9 Komponentensicherheit 9.1 Komponenten für Energieträger Energie Umwelt Datei im Netzwerk der BAM verfügbar ("Closed Access") Präsentation Wasserstoff Biokorrosion