Experimental evaluation, sensitivity analyzation and ANN modeling of thermal conductivity of ZnO-MWCNT/EG-water hybrid nanofluid for engineering applications

By M. Hemmat Esfe, S. Esfandeh, Seyfolah Saedodin, Hossein Rostamian. 2017

198 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/f32cd854af8a8da2db1564cc49d6072effb9a7bd

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

1. M. Alhuyi Nazari
2. Mohammad Hossein Ahmadi
3. Roghayeh Ghasempour
4. Omid Mahian
5. Masoud Afrand
6. M. Hemmat Esfe

In Mechanical Engineering

1. M. Alhuyi Nazari
2. Mohammad Hossein Ahmadi
3. Roghayeh Ghasempour
4. Omid Mahian
5. M. Ramezanizadeh

Citations in the corpus

• A proposed model to predict thermal conductivity ratio of Al2O3/EG nanofluid by applying least squares support vector machine (LSSVM) and genetic algorithm as a connectionist approach (2018, methodology): “models utilized temperature and concentration of solid phase as influential variables [37, 39, 40].”