J. Pipeline Sci. Eng. Unveils Best Paper Award for 2023

After a thorough review and formal recommendation by the editorial board, the 2023 Best Paper Award has been presented to the paper titled “Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network”.

The winning paper is co-authored by Haile Woldesellasse and Solomon Tesfamariam, and was published in the Journal of Pipeline Science and Engineering, Volume 3, Issue 1, 2023. It outlines the application of machine learning algorithms in predicting corrosion pit depth in oil and gas pipelines, and utilizes a cGAN to handle class imbalance problem in a corrosion dataset. The use of cGAN data augmentation was evaluated by training an artificial neural network (ANN) model. Since the one year after its publication, the paper has been cited 10 times.The corresponding author of the study is Dr. Solomon Tesfamariam, a Professor and University Research Chair in the Department of Civil and Environmental Engineering at the University of Waterloo. For over two decades, Professor Tesfamariam has been a leader in pedagogy and research on sustainable design of tall-timber building and decision-making tools for infrastructure (asset) management.In 2023, with the collaborative efforts of all journalists and editorial board members, the Journal of Pipeline Science and Engineering published 22 papers, covering pressing and challenging technical fields in the oil and gas storage and transportation industry. Everyone at the Journal of Pipeline Science and Engineering would like to express their sincere gratitude to the organizations and individuals who have given support and assistance to the development of the journal.

The paper can be downloaded at:

https://www.sciencedirect.com/science/article/pii/S2667143322000634

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