Artificial neural network model for turbulence promoter-assisted crossflow microfiltration of particulate suspensions

CORC > 青岛生物能源与过程研究所 > 中国科学院青岛生物能源与过程研究所 > 膜分离与催化团队

	Artificial neural network model for turbulence promoter-assisted crossflow microfiltration of particulate suspensions
	Liu, Yuanfa 1,2; He, Gaohong 1; Tan, Ming 1,3; Nie, Fei 1; Li, Baojun 1
刊名	DESALINATION
	2014-04-01
卷号	338 期号:1 页码:57-64
关键词	Artificial neural network Genetic algorithm Turbulence promoter Fouling Flux improvement efficiency
英文摘要	In this study, an artificial neural network (ANN) model for the turbulence promoter-assisted crossflow microfiltration (CFMF) process was successfully established, in which the inlet velocity, transmembrane pressure (TMP) and feed concentration were taken as inputs, and the flux improvement efficiency (FIE) by turbulence promoter was taken as output. Using the trained ANN model, the FIE can be predicted under CFMF operation conditions that are not included in the training database. It reveals that the FIE first increases and then decreases with increasing either TMP or inlet velocity, and increases with increasing feed concentration. Among three input variables, TMP has the most important effect on the FIE. The optimization of MP operation conditions was largely dependent on the feed concentration. The high FIE can be obtained by exerting both high inlet velocity (>0.7 m/s) and low TMP ( <30 kPa) at a relatively low feed concentration ( <1 g/L), and both high inlet velocity (>0.7 m/s) and high IMP (>70 kPa) at a relatively high feed concentration (>8 g/L). This study provides a useful guide for the applications of turbulence promoter in CFMF processes. (C) 2014 Elsevier B.V. All rights reserved.
WOS标题词	Science & Technology ; Technology ; Physical Sciences
类目[WOS]	Engineering, Chemical ; Water Resources
研究领域[WOS]	Engineering ; Water Resources
关键词[WOS]	GENETIC ALGORITHM ; CERAMIC MEMBRANES ; PERMEATE FLUX ; OPTIMIZATION ; PERFORMANCE ; PREDICTION ; ULTRAFILTRATION ; INSERTS ; DECLINE ; BAFFLE
收录类别	SCI
语种	英语
WOS记录号	WOS:000335544600008
公开日期	2014-03-01
内容类型	期刊论文
源URL	[http://ir.qibebt.ac.cn:8080/handle/337004/1546]
专题	青岛生物能源与过程研究所_膜分离与催化团队
作者单位	1.Dalian Univ Technol, Sch Chem Engn, R&D Ctr Membrane Sci & Technol, State Key Lab Fine Chem, Dalian 116012, Peoples R China 2.Dalian Polytech Univ, Sch Text & Mat Engn, Dalian, Peoples R China 3.Chinese Acad Sci, Qingdao Inst Bioenergy & Bioproc Technol, Key Lab Biobased Mat, Qingdao 266101, Peoples R China
推荐引用方式 GB/T 7714	Liu, Yuanfa,He, Gaohong,Tan, Ming,et al. Artificial neural network model for turbulence promoter-assisted crossflow microfiltration of particulate suspensions[J]. DESALINATION,2014,338(1):57-64.
APA	Liu, Yuanfa,He, Gaohong,Tan, Ming,Nie, Fei,&Li, Baojun.(2014).Artificial neural network model for turbulence promoter-assisted crossflow microfiltration of particulate suspensions.DESALINATION,338(1),57-64.
MLA	Liu, Yuanfa,et al."Artificial neural network model for turbulence promoter-assisted crossflow microfiltration of particulate suspensions".DESALINATION 338.1(2014):57-64.