Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Numerical simulations of non-Newtonian fluids are indispensable for optimization and monitoring of several industrial processes such as crude oil transportation, nuclear cooling, geothermal and fossil fuel production. The governing equations derived for non-Newtonian fluid models result in nonlinear...
| Main Authors: | Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.23682 / |
| Published: |
Elsevier Ltd
2021
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108401817&doi=10.1016%2fj.eswa.2021.115409&partnerID=40&md5=34452051662d4ca0a7014a69b429be7e http://eprints.utp.edu.my/23682/ |
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