Design of bio-inspired computational intelligence technique for solving steady thin film flow of Johnson-Segalman fluid on vertical cylinder for drainage problems
详细信息 查看全文
- 作者：Muhammad Asif Zahoor Rajaa ; muhammad.asif@ciit-attock.edu.pk" class="auth_mail" title="E-mail the corresponding author ; rasifzahoor@yahoo.com" class="auth_mail" title="E-mail the corresponding author ; asif.phdee10@iiu.edu.pk" class="auth_mail" title="E-mail the corresponding author ; Fiaz Hussain Shaha ; fsgillani@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Abdul Ahad Khana ; ahadkhanyousafzai@hotmail.com" class="auth_mail" title="E-mail the corresponding author ; Najeeb Alam Khanb ; njbalam@yahoo.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Thin film flow ; Non-Newtonian fluids ; Computational fluid dynamics ; Artificial Neural Networks ; Genetic algorithms ; Active-set algorithm
- 刊名：Journal of the Taiwan Institute of Chemical Engineers
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：60
- 期：Complete
- 页码：59-75
- 全文大小：6843 K
文摘
- class="listitem" id="list_celist0001">
- class="label">•
Bio-inspired computing technique is designed for solving steady thin film flow of Johnson–Segalman fluid on vertical cylinder for drainage problems.
- class="label">•
Strength of neural networks is exploited for modeling of drainage problems.
- class="label">•
Hybrid computing GA–ASA is used to train the design parameters of the networks.
- class="label">•
Successfully evaluated drainage problems for each case of all the four scenarios.
- class="label">•
Worth of scheme is established with closely matched result with Adams method.
- class="label">•
Statistical performance indices validate accuracy and convergence of the scheme.