A Direct Numerical Simulation code for the flow in the human nose

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Lorenzo Vecchietti

The analysis of the time-dependent flow field in the complex anatomy of the human nasal cavities is becoming more and more important owing to its diagnostic value, making it a crucial tool for patient-specific surgery planning of the Ear, Nose and Throat medical doctors. Fast as well as accurate numerical tools are required for use in a clinical setting. In this work, we present for the first time a finite-differences computer code that solves the incompressible Navier–Stokes equations by taking as input the STL file generated by a patient-specific CT scan. The code is based on an innovative (existing) immersed-boundary method, is second-order accurate in space, and is written in the CPL language.

Quality and performance are assessed on a laminar steady flow and a turbulent flow, computed for the anatomy of an healthy patient reconstructed from a CT scan. A comparison with the identical case computed with OpenFOAM is carried out. Results of the two codes are coincident, in terms of global quantities (flow rate, pressure drop, nasal resistance), numerical accuracy (which turns out to be second-order in space as measured by the convergence of the flow rate at increasing grid size) and statistics of the flow fields. The fields are compared in terms of both mean quantities and second-order statistics of velocity and pressure.

A detailed analysis of the code performance has been carried out. Presently, the code is still available in a serial version only, and there is significant further optimization to be done before progressing to the parallel version, as revealed by a detailed profiling. However, already at this stage the serial performance provides a 50 times speed-up in comparison to the same problem run with OpenFOAM, with an absolute speed of 1.6 E-7 seconds per time step and per point on an Intel Core i5 desktop CPU. The memory footprint is also reduced by almost 5 times, allowing a clinically significant DNS of a case to be run to create well-converged statistics overnight on a single core of a desktop computer.