@article{HasanuzzamanEivaziMerboldetal.2022, author = {Hasanuzzaman, Gazi and Eivazi, Hamidreza and Merbold, Sebastian and Egbers, Christoph and Vinuesa, Ricardo}, title = {Enhancement of PIV measurements via physics-informed neural networks}, doi = {10.1088/1361-6501/aca9eb}, year = {2022}, abstract = {Physics-informed neural networks (PINN) are machine-learning methods that have been proved to be very successful and effective for solving governing equations of fluid flow. In this work we develop a robust and efficient model within this framework and apply it to a series of two-dimensional three-component (2D3C) stereo particle-image velocimetry datasets, to reconstruct the mean velocity field and correct measurements errors in the data. Within this framework, the PINNsbased model solves the Reynolds-averaged-Navier-Stokes (RANS) equations for zeropressure-gradient turbulent boundary layer (ZPGTBL) without a prior assumption and only taking the data at the PIV domain boundaries. The TBL data has different flow conditions upstream of the measurement location due to the effect of an applied flow control via uniform blowing. The developed PINN model is very robust, adaptable and independent of the upstream flow conditions due to different rates of wall-normal blowing while predicting the mean velocity quantities simultaneously. Hence, this approach enables improving the mean-flow quantities by reducing errors in the PIV data. For comparison, a similar analysis has been applied to numerical data obtained from a spatially-developing ZPGTBL and an adverse-pressure-gradient (APG) TBL over a NACA4412 airfoil geometry. The PINNs-predicted results have less than 1\% error in the streamwise velocity and are in excellent agreement with the reference data. This shows that PINNs has potential applicability to shear-driven turbulent flows with different flow histories, which includes experiments and numerical simulations for predicting high-fidelity data.}, subject = {Machine learning; Particle image velocimetry; Turbulent boundary layer; Large Eddy Simulation; Measurement; Maschinelles Lernen; Turbulente Grenzschicht; Physikalisch informiertes neuronales Netz; Messung; Turbulente Grenzschicht; Neuronales Netz; Maschinelles Lernen; Particle-Image-Velocimetry}, language = {en} } @phdthesis{Hasanuzzaman2021, author = {Hasanuzzaman, Gazi}, title = {Experimental investigation of turbulent boundary layer with uniform blowing at moderate and high Reynolds numbers}, doi = {10.26127/BTUOpen-5566}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-55660}, school = {BTU Cottbus - Senftenberg}, year = {2021}, abstract = {Experimental investigation in turbulent boundary layer flows represents one of the canonical geometries of wall bounded shear flows. Utmost relevance of such experiments, however, is applied in the engineering applications in aerospace and marine industries. In particular, continuous effort is being imparted to explore the underlying physics of the flow in order to develop models for numerical tools and to achieve flow control. Within the scope of this Ph. D. topic, application of active control method such as micro-blowing effect in the incompressible, zero pressure gradient turbulent boundary layer was investigated. Turbulent boundary layer flow is particularly interesting as well as challenging due to the presence of different interacting scales which are increasingly becoming significant as the flow inertial conditions keeps growing. Therefore, energy content of the coherent structures in outer layer becomes stronger and necessitates measurements in relatively large Reynolds number. Present control experiments in turbulent boundary layer can be split into two different work segments, where one is objected towards the data measurements in turbulent boundary layer over smooth surface with and without any external perturbation. Here, perturbation is applied in the form of wall normal blowing while keeping the magnitude of blowing very low compared to the free stream velocity. For the subsequent results reported here, magnitude of blowing ratio was varied between 0\%~6\%. In the first part of the present thesis e.g. 0.415×10e+3≤Reτ≤1.160×10e+3, measurements were performed at the Brandenburg University of Technology wind tunnel. Non-intrusive Laser Doppler Anemometry was applied to carry out a series of measurements on a zero pressure gradient flat plate turbulent boundary layer. Blowing ratio through the perforated surface was varied between 0.17\%~1.52\% of the free stream velocity. To a maximum of 50\% reduction in friction drag was achieved. For the measurements on the upper range of the stated Reynolds number, were conducted at the boundary layer wind tunnel. This boundary layer wind tunnel offers a spatially developed turbulent boundary layer over a flat plate within 2.2×10e+3≤Reτ≤5.5×10e+3 with an excellent spatial resolution. With the help of Stereo Particle Image Velocimetry technique, measurement of the velocity components were obtained covering entire boundary layer in streamwise wall normal plane. In addition, time resolved measurements were also obtained in spanwise and wall-normal plane in order to look into the morphology of turbulent structures immediately above the blowing area.}, subject = {Turbulent boundary layer; Drag reduction; Particle Image Velocimetry (PIV); Laser Doppler Anemometry (LDA); Friction drag; Turbulente Grenzschicht; Particle Image Velocimetry; Laser-Doppler-Anemometrie; Mikro-Ausblasen; Reibungswiderstand; Turbulente Grenzschicht; Particle-Image-Velocimetry; Reibungswiderstand; Laser-Doppler-Anemometrie; Ausblasen}, language = {en} } @phdthesis{MalteseMelettideOliveira2021, author = {Maltese Meletti de Oliveira, Gabriel}, title = {High-performance computing and laboratory experiments on strato-rotational instabilities}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-54408}, school = {BTU Cottbus - Senftenberg}, year = {2021}, abstract = {Stratified vortices can be found from small to large scales in geophysical and astrophysical flows. On the one hand, tornadoes and hurricanes can lead to devastation and even a large number of casualties. On the other hand, vortices can distribute heat and momentum in the atmosphere which is important for a habitable environment on Earth. In the astrophysical context, accretion disks (from which solar systems are formed) can be seen as stratified vortices. In such systems, understanding the mechanisms that can result in an outward transport of angular momentum is a central problem. For a planet or star to be formed in a disk, angular momentum has to be carried away from its center to allow matter aggregation by gravity; otherwise, its rotation speed would be far too large, avoiding this matter aggregation (and the consequent star formation) to happen. In such gas systems, turbulence is the most likely mechanism to achieve such a large angular momentum transport. However, it was shown that the flow profile of accretion disks is stable with respect to purely shear instabilities, and the question arises about how the turbulence can be generated. Among other candidates, the strato-rotational instability (SRI) has attracted attention in recent years. The SRI is a purely hydrodynamic instability that can be modeled by a classical Taylor-Couette (TC) system with stable density stratification due to axial salinity or temperature gradients. In this thesis, a combined experimental and high-performance computing study of new specific behaviors of the strato-Rotational Instability (SRI) is performed. The density stratification causes a change in the marginal instability transition when compared to classical non-stratified TC systems, making the flow unstable in regions where - without stratification - it would be stable. This characteristic makes the SRI a relevant phenomenon in planetary and astrophysical applications, particularly in accretion disk theory. Despite many advances in the understanding of strato-rotational flows, the confrontation of experimental data with non-linear numerical simulations remains relevant, since it involves linear aspects and non-linear interactions of SRI modes which still need to be better understood. These comparisons also reveal new non-linear phenomena and patterns not yet observed in the SRI, that can contribute to our understanding of geophysical flows.}, subject = {Rotating flow; Stratified flow; Pattern formation; Particle image velocimetry; High performance computing; Rotierende Str{\"o}mungen; Geschichtete Str{\"o}mungen; Musterbildung; Particle image velocimetry; Direkte numerische Simulation; Rotationsstr{\"o}mung; Turbulente Str{\"o}mung; Schichtenstr{\"o}mung; Direkte numerische Simulation; Particle-Image-Velocimetry; Musterbildung}, language = {en} }