Andrei Shishkin | Searcharxiv

arXiv2026

Influence of passenger head-position uncertainty on infection risk predictions

We investigate the influence of natural head movement on the infection risk posed by airborne pathogens using a CFD-based forward risk prediction model. Quasi-Monte-Carlo simulations are used to obtain the resulting infection risk distributions by representing head movement via probability distributions of parameters describing the position and orientation of each passenger's breathing zone. A significant impact of fore/aft and lateral head position on infection risk was found and should be accounted for to increase robustness when predictions of local, seat-specific infection risks are used to guide design and policy decisions. Unlike the sampling-based Monte Carlo approach, estimates of the statistical moments of the risk distributions and sensitivities, calculated using first-order second-moment and higher-order methods, were found to inadequately capture the dependencies between head movement components and infection risk.

q-bio.QM↗

arXiv2010

Analysis of Multipoint Correlations in Direct Numerical Simulation

We examine the Markov properties of the three velocity components of a turbulent flow generated by a DNS simulation of the flow around an airfoil section. The spectral element code Nektar has been used to generate a well resolved flow field around an fx79w-151a airfoil profile at a Reynolds number of Re=5000 and an angle of attack of α = 12°. Due to a homogeneous geometry in the spanwise direction, a Fourier expansion has been used for the third dimension of the simulation. In the wake of the profile the flow field shows a von Karman street like behavior with the vortices decaying in the wake which trigger a turbulent field. Time series of the 3D flow field were extracted from the flow at different locations to analyze the stochastic features. In particular the existence of Markov properties in the flow have been shown for different cases in the surrounding of the airfoil. This is of basic interest as it indicates that fine structures of turbulence can be replaced by stochastic processes. Turbulent and Markovian scales are being determined in the turbulent field and limits of standard Gaussian Langevin processes are being determined by the reconstruction of a flow field in time and space.

physics.flu-dyn↗