S. Giwa
Biomedical Engineering · 2015–2021
A researcher in the Science corpus: 4 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Biomedical Engineering — 115 citations into it
- Mechanical Engineering — 82 citations into it
- Computational Mechanics — 45 citations into it
Whom S. Giwa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ali J. Chamkha
- Mohsen Sheikholeslami
- J. Eastman
- Yimin Xuan
- E. Abu‐Nada
- T. Baby
- L. S. Sundar
- Qiang Li
- Stephen U. S. Choi
- Masoud Afrand
Papers from S. Giwa's perspective
Ordered by how strongly the researchers S. Giwa trusts endorse each paper. Same corpus, a different order for every researcher.
- ANOMALOUSLY INCREASED EFFECTIVE THERMAL CONDUCTIVITIES OF ETHYLENE GLYCOL-BASED NANOFLUIDS CONTAINING COPPER NANOPARTICLES
- Enhancement of fluid thermal conductivity by the addition of single and hybrid nano-additives
- Convective heat transfer and friction factor correlations of nanofluid in a tube and with inserts: A review
- Investigation of thermal and electrical conductivity of graphene based nanofluids
- Experimental investigation on cavity flow natural convection of Al2O3–water nanofluids ☆
- Electrohydrodynamic free convection heat transfer of a nanofluid in a semi-annulus enclosure with a sinusoidal wall
- Mechanisms of heat flow in suspensions of nano-sized particles (nanofluids)
- Convective Transport in Nanofluids
- Numerical simulation of natural convection of nanofluid in a square enclosure: Effects due to uncertainties of viscosity and thermal conductivity
- HEAT TRANSFER AUGMENTATION IN A TWO-SIDED LID-DRIVEN DIFFERENTIALLY HEATED SQUARE CAVITY UTILIZING NANOFLUIDS
Their papers
- Modelling of Nicotiana Tabacum L. Oil Biodiesel Production: Comparison of ANN and ANFIS (2021) — 62 citations
- A review of magnetic field influence on natural convection heat transfer performance of nanofluids in square cavities (2020) — 195 citations
- Influence of base fluid, temperature, and concentration on the thermophysical properties of hybrid nanofluids of alumina–ferrofluid: experimental data, modeling through enhanced ANN, ANFIS, and curve fitting (2020) — 183 citations
- Prediction of selected biodiesel fuel properties using artificial neural network (2015) — 57 citations