Oğuz Uzol

E-mail

uzol@metu.edu.tr

Department

Department of Aerospace Engineering

ORCID

0000-0002-0553-2853

Scopus Author ID

6602531818

Web of Science Researcher ID

ABA-1645-2020

An experimental investigation of the effects of a boundary layer inflow on the wake characteristics of a model wind turbine and a porous disk Öztürk, Buğrahan; Hassanein, Abdelrahman; Akpolat, M. Tuğrul; Abdulrahim, Anas; Perçin, Mustafa; Uzol, Oğuz (2025-07-01) This paper presents the results of an experimental study that focuses on the details of the wake development characteristics of a model wind turbine and a porous disk under boundary layer inflow conditions. Measurements ar...
A Data-Driven Approach for the Prediction of Reynolds Number Effects on Wind Turbine Airfoil Aerodynamic Polars Özgören, Ahmet Can; Uzol, Oğuz (2025-03-01) This study presents a data-driven approach to extrapolate and predict Reynolds number effects on wind turbine airfoil polars. For this purpose, a database is created using experimentally obtained aerodynamic coefficients f...
Boundary Layer Transition Measurements on NLF(1)-0416 Airfoil using Infrared Thermography and Comparisons with 2D RANS Predictions Çağdaş Kalayc, Ahmet; Aslan, Ezgi; Orbay Akcengiz, Ezgi; Sezer Uzol, Nilay; Uzol, Oğuz (2025-01-01) This study presents an experimental and numerical investigation on the boundary layer transition characteristics of the NLF(1)-0416 airfoil. The experiments are conducted in the large-scale subsonic wind tunnel of METU Cen...
Airfoil Shape Manipulation Using Pressure-Driven Soft Actuators Yurtsever, Betül Keçici; Şahin, Melin; Uzol, Oğuz (2025-01-01) This paper presents a comprehensive analysis of the response characteristics of pressure-driven soft actuators and their application in airfoil shape manipulation, focusing on certain regions such as the leading edge, trai...
Inverse Airfoil Design Using Attention-Enhanced Deep Neural Networks Eriş, Görkem Mahir; Özgören, Ahmet Can; Uzol, Oğuz (2025-01-01) This paper presents an attention-enhanced deep learning-based framework for airfoil inverse design that leverages the PARSEC parameterization methodology. A model is developed to predict the PARSEC parameters that define a...
Machine Learning Based Predictions of Airfoil Aerodynamic Coefficients for Reynolds Number Extrapolations Özgören, Ahmet Can; Acar, Deniz Alper; Kamrak, Recep; Eriş, Görkem Mahir; Özdemir, Yasin; Sezer Uzol, Nilay; Uzol, Oğuz (2024-01-01) This study investigates the application of various machine learning (ML) algorithms for predicting two critical aerodynamic coefficients, i.e. the maximum lift coefficient (C l max ) and the minimum drag coefficient (C d m...
Transition Measurements on NLF(1)-0416 Airfoil Using Infrared Thermography Kalaycı, Ahmet Çağdaş; Doğan, Batuhan; Perçin, Mustafa; Uzol, Oğuz (2023-11-21)
Aeroelastic Analysis of DTU 10 MW Reference Wind Turbine Under Icing Conditions KEPEZ, DENİZ; Uzol, Oğuz; Özgen, Serkan (2023-05-23)
Proper Orthogonal Decomposition (POD) of the Wake Flow Field of a Model Wind Turbine and a Porous Disc under Different Freestream Turbulence Intensity Conditions Öztürk, Buğrahan; Hassanein, Abdelrahman; Tuǧrul Akpolat, M.; Abdulrahim, Anas; Perçin, Mustafa; Uzol, Oğuz (2023-01-01) The effects of freestream turbulence intensity on the wake development of a model wind turbine and a porous disc are investigated through Proper Orthogonal Decomposition (POD) analysis. The capability of porous discs for r...
Monte-Carlo simulations based hub height optimization using FLORIS for two interacting onshore wind farms Kutukcu, Gokay; Uzol, Oğuz (2022-11-01) This study focuses on finding the optimum hub height (i.e., tower height) distributions for two interacting on-shore wind farms that are located on relatively complex terrain. Different optimization scenarios are studied, ...

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