dc.description.abstract |
Mitigation of “hot spots” in microelectromechanical
systems (MEMS) employing in situ microchannel systems
requires a comprehensive picture of the maldistribution of the
working fluid and uniformity of cooling within the same. In
this paper, detailed simulations employing parallel microchannel
systems with specialized manifold-channel configurations,
i.e., U, I, and Z, have been performed. Eulerian–Lagrangian
discrete phase model (DPM) and effective property model with
water and alumina–water nanofluid as working fluids have
been employed. The distributions of the dispersed particulate
phase and continuous phase have been observed to be, in
general, different from the flow distribution, and this has been
found to be strongly dependent on the flow configuration.
Accordingly, detailed discussions on the mechanisms governing
such particle distribution patterns have been proposed. Particle
maldistribution has been conclusively shown to be influenced by
various migration and diffusive phenomena, such as Stokesian
drag, Brownian motion, thermophoretic drift, and so on. To
understand the uniformity of cooling within the device, which
is of importance in real-time scenario, an appropriate figure of
merit has been proposed. It has been observed that uniformity
of cooling improved using nanofluid as working fluid as well
as enhanced relative cooling in hot zones, providing evidence
of the “smart” nature of such dispersions. To further quantify
this smart effect, real-time mimicking hot-spot scenarios have
been computationally probed with nanofluid as the coolant. A
silicon-based microchip emitting nonuniform heat flux (gathered
from real-time monitoring of an Intel Core i7–4770 3.40-GHz
quad-core processor) under various processor load conditions
has been studied, and the evidence of enhanced cooling of
hot spots has been obtained from DPM analysis. This paper
sheds insight on-the behavior of nonhomogeneous dispersions in
complex flow domains and the caliber of nanofluids in cooling
MEMS more uniformly and “smarter” than base fluids. |
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