A Hybrid FEM-CNN for Image-Based Severity Prediction of Corroded Offshore Pipelines

A Hybrid FEM-CNN for Image-Based Severity Prediction of Corroded Offshore Pipelines

The combination of the Finite Element Method (FEM) with Convolutional Neural Networks (CNNs) presents a key breakthrough in the assessment of the structural integrity of offshore pipelines. The advantage of the standard FEM is in stress visualization, but it is time-consuming due to high computation...

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Bibliografische gegevens
Hoofdauteurs: Mohammad Fadzil Najwa, Muda Mohd Fakri, Abdul Shahid Muhammad Daniel, Aziz Norheliena, Mohd Mohd Hairil, Mohd Amin Norliyati, Mohd Hashim Mohd Hisbany
Formaat: Artikel
Taal:English
Gepubliceerd in: EDP Sciences 2025-01-01
Reeks:E3S Web of Conferences
Online toegang:https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/12/e3sconf_aere2025_04003.pdf

Internet

https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/12/e3sconf_aere2025_04003.pdf

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