Fluid Properties Extraction in Confined Nanochannels with Molecular Dynamics and Symbolic Regression Methods

In this paper, we propose an alternative road to calculate the transport coefficients of fluids and the slip length inside nano-conduits in a Poiseuille-like geometry. These are all computationally demanding properties that depend on dynamic, thermal, and geometrical characteristics of the implied f...

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Bibliographic Details
Published in:Micromachines (Basel) 2023-07, Vol.14 (7), p.1446
Main Authors: Angelis, Dimitrios, Sofos, Filippos, Papastamatiou, Konstantinos, Karakasidis, Theodoros E
Format: Article
Language:English
Subjects:
Atoms & subatomic particles
Boundary conditions
Datasets
diffusion coefficient
Equilibrium
Fluid dynamics
Genetic algorithms
Heat conductivity
Hypotheses
Interpolation
Mathematical analysis
Molecular dynamics
Nanochannels
Regression analysis
shear viscosity
Simulation
slip length
thermal conductivity
Transport properties
Velocity
Viscosity
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Summary:In this paper, we propose an alternative road to calculate the transport coefficients of fluids and the slip length inside nano-conduits in a Poiseuille-like geometry. These are all computationally demanding properties that depend on dynamic, thermal, and geometrical characteristics of the implied fluid and the wall material. By introducing the genetic programming-based method of symbolic regression, we are able to derive interpretable data-based mathematical expressions based on previous molecular dynamics simulation data. Emphasis is placed on the physical interpretability of the symbolic expressions. The outcome is a set of mathematical equations, with reduced complexity and increased accuracy, that adhere to existing domain knowledge and can be exploited in fluid property interpolation and extrapolation, bypassing timely simulations when possible.
ISSN:2072-666X
2072-666X
DOI:10.3390/mi14071446