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DINUSINA

Project DINUSINA
Research Area Engineering
Principal Investigator(s) Alfredo Soldati
Institution(s)
  • University of Udine, Italy

Abstract

Nanofluids are dilute liquid suspensions of nanoparticulate solids, including nanoparticles, nanofibers and nanotubes. Experiments have demonstrated that nanofluids can be used to design new-concept heat transfer fluids with properties given by those of the base fluid modulated up to the target, desired amount by the presence of dynamically-interacting, suitably-chosen, discrete nanoparticles. As of today, a clearcut understanding of the modifications of the physical heat transfer mechanisms occurring in nanofluids is still lacking. A possible way to improve the knowledge of these mechanisms is to use accurate and reliable numerical tools such as direct numerical simulation (DNS) and Lagrangian particle tracking (LPT), which may complement complex and costly experiments.
In this project, we propose to perform a comprehensive numerical analysis accounting for mass, momentum and heat transfer mechanisms all together, tailored for the specific case of nanodispersed fluids. Nanoparticles will be modeled as active heat transfer agents interacting both with the temperature field and the velocity field to study heat transfer modifications. To this aim, necessary energy and momentum coupling terms must be incorporated in the governing equations of both phases.
The main objective of the present proposal is thus to investigate microscale heat transfer enhancement mechanisms occurring in nanofluids by means of pseudospectral DNS at high resolution (17 to 135 million grid points) and LPT of large swarms of nanometer-size particles (1 billion), focusing on turbulent channel flow at different values of the Reynolds and Prandtl numbers. Such parametric study is currently unavailable, first because of the challening non-trivial modeling issues, which of course reflect upon the complex interactions between the two phases; and second because of the (unprecedented) huge computational cost required by the high grid resolution combined with the large number of individual nanoparticles to be tracked.

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