TL;DR
This paper compares deterministic and stochastic methods for solving the Boltzmann equation to quantify thermally-driven flows in microsystems, highlighting the accuracy and limitations of various kinetic models.
Contribution
It evaluates the performance of DGFS, BGK, ESBGK, Shakhov, and DSMC methods in modeling thermo-stress convection at microscale, providing insights into their accuracy and applicability.
Findings
BGK under-predicts heat-flux and flow speed
ESBGK closely matches DSMC results
S-model over-predicts flow parameters
Abstract
When the flow is sufficiently rarefied, a temperature gradient, for example, between two walls separated by a few mean free paths, induces a gas flow---an observation attributed to the thermo-stress convection effects at microscale. The dynamics of the overall thermo-stress convection process is governed by the Boltzmann equation---an integro-differential equation describing the evolution of the molecular distribution function in six-dimensional phase space---which models dilute gas behavior at the molecular level to accurately describe a wide range of flow phenomena. Approaches for solving the full Boltzmann equation with general inter-molecular interactions rely on two perspectives: one stochastic in nature often delegated to the direct simulation Monte Carlo (DSMC) method; and the others deterministic by virtue. Among the deterministic approaches, the discontinuous Galerkin fast…
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