The Data-Driven Modeling of Pressure Loss in Multi-Batch Refined Oil Pipelines with Drag Reducer Using Long Short-Term Memory (LSTM) Network

The Data-Driven Modeling of Pressure Loss in Multi-Batch Refined Oil Pipelines with Drag Reducer Using Long Short-Term Memory (LSTM) Network

Due to the addition of the drag reducer in refined oil pipelines for increasing the pipeline throughput as well as reducing energy consumption, the classical method based on the Darcy-Weisbach Formula for precise pressure loss calculation presents a large error. Additionally, the way to accurately c...

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Bibliographic Details
Main Authors: Shengshi Wang, Lianyong Zuo, Miao Li, Qiao Wang, Xizhen Xue, Qicong Liu, Shuai Jiang, Jian Wang, Xitong Duan
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Energies
Subjects:
drag reducer
multi-batch refined oil pipelines
pressure loss
long short-term memory (LSTM) network
Online Access:https://www.mdpi.com/1996-1073/14/18/5871

Internet

https://www.mdpi.com/1996-1073/14/18/5871

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