The numerical modeling of water/FMWCNT nanofluid flow and heat transfer in a backward-facing contracting channel
By Abdullah A. A. A. Al-Rashed, Omid Ali Akbari, Ali Heydari, Davood Toghraie, Majid Zarringhalam, Gholamreza Ahmadi Sheikh Shabani, A. Seifi, Marjan Goodarzi. 2018
182 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/d5f1bdcd08156d1fdfff4b48b3a4a2a1413c50fe
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Mohammad Reza Safaei
- Hooman Yarmand
- Masoud Afrand
- Cong Qi
- A. Hajizadeh
- N. Zulkifli
- Arash Karimipour
- Davood Toghraie
In Mechanical Engineering
- Mohammad Reza Safaei
- Hooman Yarmand
- Masoud Afrand
- Cong Qi
- Davood Toghraie
- Arash Karimipour
- Marjan Goodarzi
- Omid Ali Akbari
Citations in the corpus
- Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data (2019, background): “Many researchers also investigated the effect of adding nanoparticles to cavities and channels and many other devices, considering the better coefficient of thermal conductivity of nanofluids than simple fluids and, observed that the addition of nanoparticles would increase the heat transfer rate [2”