| Artificial neural network model for turbulence promoter-assisted crossflow microfiltration of particulate suspensions | |
| Liu, Yuanfa1,2; He, Gaohong1; Tan, Ming1,3; Nie, Fei1; Li, Baojun1 | |
| 2014-04-01 | |
| 发表期刊 | DESALINATION
 |
| 卷号 | 338期号:1页码:57-64 |
| 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. |
| 文章类型 | Article |
| 关键词 | Artificial Neural Network Genetic Algorithm Turbulence Promoter Fouling Flux Improvement Efficiency |
| WOS标题词 | Science & Technology ; Technology ; Physical Sciences |
| DOI | 10.1016/j.desal.2014.01.015 |
| 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研究方向 | Engineering ; Water Resources |
| WOS类目 | Engineering, Chemical ; Water Resources |
| WOS记录号 | WOS:000335544600008 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.qibebt.ac.cn/handle/337004/1546 |
| 专题 | 膜分离与催化研究组 |
| 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. |
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| Artficial neural net（1346KB） | 开放获取 | CC BY-NC-SA | 浏览 下载 | |||
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