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Prediction of thermal distribution and fluid flow in the domain with multi-solid structures using Cubic-Interpolated Pseudo-Particle model.

Quyen NguyenMeisam BabanezhadAli Taghvaie NakhjiriMashallah RezakazemiSaeed Shirazian
Published in: PloS one (2020)
A nanofluid is a suspension of very small solid particles in a continuous fluid with significant improvement of heat transfer characteristics in the main liquid. In general, in industrial equipment, the heat transfer rate can be improved with optimization of equipment including the domain structure and using the different types of nanofluids. Still, there is a big challenge to analyze the heat transfer and fluid circulation in the domain. Having nanofluids with experimental observation as using sensors and probes are destructive for the liquid stream and they are costly to observe the details of particles and the original fluid. Over the 20 years, different numerical methods have been implemented in the modeling of the heat and fluid distribution in industrial equipment containing nanofluids. Among all mathematical and numerical methods, Cubic-Interpolated Pseudo-Particle (CIP) model provides a strong potential in the prediction of the fluid structure and heat analysis, when there is a complex structure of thermal walls and high concentration of nanoparticles. However, this method is not frequently used by researchers in nanofluids analysis. In this study, the Cubic-Interpolated Pseudo-Particle model is applied to predict the flow in the square domain. different thermal walls (multi-solid structure) and hot cylindrical wall are specifically used to observe the fluid flow and heat distribution in the domain. Additionally, for a better understanding of the flow in the domain, different numbers of cylinders are used and also different amounts of nanofluid in the continuous fluid are added. The results show that adding more walls in the domain causes the change in the vortex structure. Furthermore, using nanofluid results in better heat transfer rate in the system. The CIP method is also a capable tool to predict the heat and fluid flow in the multi-solid structure domain.
Keyphrases
  • heat stress
  • heavy metals
  • wastewater treatment
  • machine learning
  • living cells
  • high resolution
  • deep learning
  • fluorescent probe