Journal of Pipeline Systems Engineering and Practice cover with an image of pipes on a green background. The journal title, ASCE logo, and Utility Engineering and Surveying Institute logo are displayed as well.
Special Collection on Transformational Impacts of Smart Solutions in the Pipeline Industry

Guest Editors:
Emad Elwakil, Ph.D., P.E., CCE, PMP, Purdue University
Bohong Wang, Ph.D., Zhejiang Ocean University
Jianqin Zheng, Ph.D., China University of Petroleum-Beijing

With the advent of digitalization, smart pipeline engineering is becoming an inevitable choice for the digitalization transformation and high-quality development of pipelines. According to recent studies, vigorously developments of artificial intelligence-based digital twins and smart pipeline networks, such as 5G, Internet of things, cloud computing, big data, etc., help to achieve the smart transformation of the pipeline industry. Artificial intelligence tools are being progressively applied in the research fields of pipeline engineering for purposes such as construction, operating condition forecast, fault detection, maintenance, environmental effect evaluation, etc. The applications of artificial intelligence in water distribution, wastewatercollection, sewers and drainage systems, oil and gas transmission networks, and chemical plants have the potential to utilize the rapidly increased data and improve the operating efficiency and safety of pipelines. The pipeline industry will realize the transition to a new era with high automation, intelligence, digitalization, and networking.

Papers in this Collection

Theory and Machine Learning Modeling for Burst Pressure Estimation of Pipeline with Multipoint Corrosion
ORCID ID iconHongfang Lu, Ph.D., A.M.ASCE; Haoyan Peng; Zhao-Dong Xu, Ph.D., A.M.ASCE; Guojin Qin, Ph.D.; ORCID ID iconMohammadamin Azimi, Ph.D., Aff.M.ASCE; John C. Matthews, Ph.D., A.M.ASCE; and Li Cao
Published online: April 28, 2023

Leveraging Machine Learning for Pipeline Condition Assessment
ORCID ID iconHongfang Lu, Ph.D., A.M.ASCE; Zhao-Dong Xu, Ph.D., A.M.ASCE; Xulei Zang; Dongmin Xi; Tom Iseley, Ph.D., Dist.M.ASCE; ORCID ID iconJohn C. Matthews, Ph.D., A.M.ASCE; and Niannian Wang, Ph.D.
Published online: May 13, 2023

Scheduling of Straight Multiproduct Pipelines Considering the Contamination Control
Yulei Xu; Bin Xu; Jinzhou Song; Zhengbing Li; Yi Guo; Renfu Tu; Yongtu Liang; Hongyang Gao; and Hengyu Wang
Published online: June 22, 2023

A Novel Safety Early Warning Methodology for Pipelines under Landslide Geological Hazard
Siming Liu; Peng Zhang, Ph.D.; Qiao Tang; Sen Wu; and ORCID ID iconYunfei Huang, S.M.ASCE
Published online: October 14, 2023

Intelligent Methods for the Pipeline Operation and Integrity
Yufeng Yang; Qiang Zhang; Xixiang Zhang; Shuyi Xie; Gang Wu; and Lifeng Li
Published online: October 28, 2023

Investigation of Wax-Deposit Thickness in Oil and Water Emulsions Facing the Development Trend of Intelligent Pipeline Operation
ORCID ID iconRongbin Li, Ph.D.; Yuping Zhang; Qiyu Huang; Bin Tao, Ph.D.; Xianbin Huang, Ph.D.; Xiaorui Guan, Ph.D.; Liangliang Li, Ph.D.; and Longjun Cheng, Ph.D.
Published online: January 29, 2024

Two-Stage Disturbance Rejection Control Strategy for Airport Refueling Systems Based on Predictive Control
Peng Liu; Jing Gong; Bohui Shi; and Shangfei Song
Published online: February 15, 2024

Fuzzy Bayesian Network–Based Multidimensional Risk Assessment for Leakage of Blended Hydrogen Natural Gas Pipelines
Yihuan Wang, Ph.D.; Ailin Xia; and ORCID ID iconGuojin Qin, Ph.D.
Published online: February 22, 2024