An Industrial Scale Simulation Method for Predicting the Contamination Evolution in Long-Distance Multiproduct Pipelines
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 14, Issue 1
Abstract
An industrial scale simulation method (ISSM) has been proposed to predict the contamination evolution and oil quality distribution in multiproduct pipelines. The proposed ISSM consists of two subalgorithms: computational domain tracking method (CDTM) and spatial domain conversion method (SDCM). The computational effort can be greatly reduced by CDTM. SDCM is implemented for flow simulation in industrial scale pipelines. The basic concept of SDCM is adaptively adjusting the spatial mesh resolution according to the spatial distribution of contamination. The communication between spatial meshes with different resolutions is achieved by machine learning technology in SDCM. The validation of training and predicting process in SDCM indicates the artificial neural networks (ANN)-based method could efficiently construct the implicit function between the contamination concentration and spatial coordinates in pipelines. Then, the detailed implementation of ISSM, which is a hybrid of CDTM and SDCM, is given. The accuracy and efficiency are validated by both the direct numerical simulation results and practical experiments in industry multiproduct pipelines. Compared with the direct numerical method, ISSM could greatly improve the computational efficiency. Finally, two applications, mixing dynamics of miscible oil interface and oil quality evolution within long-distance pipelines, are carried out. The results reveal that ISSM can capture the asymmetric distribution phenomenon of the contamination concentration along the pipeline. Furthermore, the quality index of oil product can be tracked within the present framework of ISSM, which could be potentially used to design a quality-based scheduling scheme for industrial multiproduct pipelines.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request, specifically the hybrid method of ADI-PCG-TDMA ISSM including CDTM, SDCM, and the experimental validation data.
Acknowledgments
This work is supported by National Natural Science Foundation of China (No. 51474228). B. Y. Wang who was sponsored by the China Scholarship Council (No. 201806440152).
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 14 • Issue 1 • February 2023
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© 2022 American Society of Civil Engineers.
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Received: Mar 18, 2022
Accepted: Aug 11, 2022
Published online: Oct 17, 2022
Published in print: Feb 1, 2023
Discussion open until: Mar 17, 2023
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