We propose numerical approaches to reduce the sampling noise of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) solution. A hybrid CFD-MD approach provides higher-resolution solution near the solid obstacle and better efficiency than a pure particle-based simulation technique. However, applications up to now are limited to extreme velocity conditions, since the magnitude of statistical error in sampling particles’ velocity is very large compared to the continuum velocity. Considering technical difficulties of infinitely increasing MD domain size, we propose and experiment a number of numerical alternatives to suppress the excessive sampling noise in solving moderate-velocity flow field. They are the sampling of multiple replicas, virtual stretching of sampling layers in space, and linear fitting of multiple temporal samples. We discuss the pros and cons of each technique in view of solution accuracy and computational cost.

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