基于BP神经网络和CFD数值模拟的气旋浮罐结构优化及性能预测

doi:10.12034/j.issn.1009-606X.217135

过程工程学报 ›› 2017, Vol. 17 ›› Issue (5): 918-925.DOI: 10.12034/j.issn.1009-606X.217135

基于BP神经网络和CFD数值模拟的气旋浮罐结构优化及性能预测

蔡小垒¹，陈家庆^2*，孔祥功²，刘美丽²，俞接成²，姬宜朋²

1. 北京化工大学机电工程学院，北京 100029；2. 北京石油化工学院机械工程学院，北京 102617

收稿日期:2017-02-17 修回日期:2017-03-05 出版日期:2017-10-20 发布日期:2017-10-10
通讯作者: 陈家庆 Jiaqing@bipt.edu.cn
基金资助:
北京市属高等学校“长城学者”培养计划资助项目;北京市自然科学基金重点项目

Structure Optimization and Performance Prediction of Compact Flotation Unit Using BP Neural Network and Computational Fluid Dynamics

Xiaolei CAI¹, Jiaqing CHEN^2*, Xianggong KONG², Meili LIU², Jiecheng YU², Yipeng JI²

1. School of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China;
2. School of Mechanical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China

Received:2017-02-17 Revised:2017-03-05 Online:2017-10-20 Published:2017-10-10
Contact: CHEN Jia-qing Jiaqing@bipt.edu.cn

摘要/Abstract

摘要： 采用CFD模拟和BP神经网络结合的方法，对BIPTCFU-III型气旋浮装置主体设备气旋浮罐的入口管径、环形缝隙宽度、高径比和稳流筒直径等主要结构参数进行了优化，研究了结构参数对分离效率的影响. 结果表明，优化后气旋浮罐分离效率从81.07%提升至92.82%，预测值与模拟值的偏差仅为1.15%；增大稳流筒直径、提高高径比、增大入口管径和减小环形缝隙宽度有利于强化油水两相的运移和分离过程，提高分离效率.

关键词: 采油污水, 气旋浮, BP神经网络, CFD数值模拟, 结构优化, 性能预测

Abstract: The method of BP neural network coupled with computational fluid dynamics (CFD) was used to optimize the structural parameters of inlet diameter, annular gap width, ratio of height to diameter and concentric inner cylinder diameter of compact flotation unit. The effects of these structural parameters on the separation efficiency were also predicted. The results showed that the separation efficiency of the CFU after optimization has been improved from 81.07% to 92.82% and the deviation between estimation and actual value is only 1.15%. Increasing distribution flow tube diameter, the ratio of height to diameter and the inlet diameter and decreasing the width of annular gap are beneficial to strengthen oil?water transmission and improve the separation efficiency.

Key words: Oily wastewater, Compact flotation unit, BP neural network, Computational Fluid Dynamics, Structural optimization, Performance prediction

蔡小垒陈家庆孔祥功刘美丽俞接成姬宜朋. 基于BP神经网络和CFD数值模拟的气旋浮罐结构优化及性能预测[J]. 过程工程学报, 2017, 17(5): 918-925.

Xiaolei CAI Jiaqing CHEN Xianggong KONG Meili LIU Jiecheng YU Yipeng JI. Structure Optimization and Performance Prediction of Compact Flotation Unit Using BP Neural Network and Computational Fluid Dynamics[J]. Chin. J. Process Eng., 2017, 17(5): 918-925.

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基于BP神经网络和CFD数值模拟的气旋浮罐结构优化及性能预测

Structure Optimization and Performance Prediction of Compact Flotation Unit Using BP Neural Network and Computational Fluid Dynamics

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