  Citation: Duda, D.; Yanovych, V.; Tsymbalyuk, V.; Uruba, V.Effect of Manufacturing Inaccuracies on the Wake Past Asymmetric Airfoil by PIV. Energies 2022, 15, 1227. https:// doi.org/10.3390/en15031227 Academic Editors: Antonio Crespo and Rob J. M. Bastiaans Received: 2 December 2021 Accepted: 31 January 2022 Published: 8 February 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article Effect of Manufacturing Inaccuracies on the Wake Past Asymmetric Airfoil by PIV Daniel Duda 1, * , Vitalii Yanovych 1,2 , Volodymyr Tsymbalyuk 1 and Václav Uruba 1,2 1 Faculty of Mechanical Engineering, University of West Bohemia, Univerzitní 22, 306 14 Pilsen, Czech Republic; yanovych@kke.zcu.cz (V.Y.); tsymv@kke.zcu.cz (V.T.); uruba@kke.zcu.cz (V.U.) 2 Institute of Thermomechanics, Czech Academy of Sciences, Dolejškova 5, 180 00 Prague, Czech Republic * Correspondence: dudad@kke.zcu.cz; Tel.: +420-377-638-146 Abstract: The effect of manufacturing geometry deviations on the flow past a NACA 64(3)-618 asymmetric airfoil is studied. This airfoil is 3D printed according to the coordinates from a public database. An optical high-precision 3D scanner, GOM Atos, measures the difference from the idealized model. Based on this difference, another model is prepared with a physical output closer to the ideal model. The velocity in the near wake (0–0.4 chord) is measured by using the Particle Image Velocimetry (PIV) technique. This work compares the wakes past three airfoil realizations, which differ in their similarity to the original design (none of the realizations is identical to the original design). The chord-based Reynolds number ranges from 1.6 × 10 4 to 1.6 × 10 5 . The ensemble average velocity is used for the determination of the wake width and for the rough estimation of the drag coefficient. The lift coefficient is measured directly by using force balance. We discuss the origin of turbulent kinetic energy in terms of anisotropy (at least in 2D) and the length-scales of fluctuations across the wake. The spatial power spectral density is shown. The autocorrelation function of the cross-stream velocity detects the regime of the von Karmán vortex street at lower velocities. Keywords: particle image velocimetry; wake; 3D scanning; NACA 64-618; turbulent kinetic energy; spectrum 1. Introduction Fluid flow is a highly non-linear problem that still lacks a reasonable solution. One of the general effects of non-linearity is the unpredictable response to even small perturbations or changes of the boundary conditions. The scale of possible responses to a small geometry perturbation ranges from almost zero effect to a linear response and up to a complex change of flow state. The famous butterfly effect represents this behavior with the example of a small butterfly that can alter the evolution path of a turbulent system [1]. As there is a large number of such micro-events, the evolution path of the entire system is unpredictable. However, the statistical properties can be predicted quite reasonably. This feature is used in modern computational fluid dynamics, which does not solve the non-linear Navier–Stokes equations on a fine mesh with the resolution of the Kolmogorov length-scale, but it solves only much larger cells with a direct link to the geometry of the boundary conditions under the assumption that the behavior at smaller scales follows some of the turbulence models. The relatively low-cost computational fluid dynamics are used in thorough exper- iments in the area of industrial design and optimization. However, the computational methods need validation and verification [2], which are mainly based on the comparison with an appropriate experiment, which does not need to fit in all parameters, but at least the main geometrical and fluid properties might be met. This is where the problem with geometry becomes important—the object used in the experimental study is different from the desired design used in the computational approach. As the quality needs to increase, even smaller deviations between numerical and experimental results can be accepted. As Energies 2022, 15, 1227. https://doi.org/10.3390/en15031227 https://www.mdpi.com/journal/energies