סמינר מחלקה של סתיו פינטו - אופטימיזציה נסיונית ומחשובית של צורות סימטריות בציר עם בקרת זרימה
School of Mechanical Engineering Seminar
Monday June 26.6.2023 at 14:00
Wolfson Building of Mechanical Engineering, Room 206
Experimental and Computational Optimization of Axis-symmetric Shapes with Flow Control
Stav (Pinto) Jacob
M.Sc. research under the supervision of
Prof. Avraham (“Avi”) Seifert, Tel Aviv University, Department of Mechanical Engineering
Assoc. Prof. Oksana Stalnov, Technion, Faculty of Aerospace Engineering
In the field of aviation, it is necessary to design aerodynamic bodies with a large internal volume to transport people, cargo, systems, and more. However, "bluff" body geometry with a large volume produces a considerable drag force, thus compromising energy efficiency. This study, conducted as part of the KAMIN Innovation Authority project, aims to design an axisymmetric blunt body geometry by integrating computational and experimental methods to reach geometric optimization of the geometry with the inherent incorporation of Active Flow Control (AFC) technology.
This research is divided into three stages. The first stage involves defining and characterizing the body and the optimization problem. An axisymmetric body geometry was parametrically defined to promote flow separation at the body's rear. This design allows controlled flow reattachment through an AFC, incorporating steady suction from suction slots and steady blowing from the trailing edge, with energy input as a parameter. A decision space and an objective space were defined, and an evolutionary optimization algorithm was selected accordingly.
In the second stage of the study, an optimization procedure and computational fluid dynamics (CFD) calculations were conducted. Various elements were evaluated, including the optimal baseline configuration, optimization strategy, optimal blowing nozzle size, and the suction slot number. The optimization section concluded that using a multi-objective optimization strategy and flow control that includes two adjacent suction slots and a larger blowing nozzle opening significantly improves all optimization parameters - volume, drag, and suction coefficients. Furthermore, defining the decision space is a crucial step in the optimization process and substantially impacts the outcomes.
In the third and final stage, the results of the numerical calculations were verified, and wind tunnel tests were performed on the optimal configuration. Furthermore, a comparison was conducted with the model examined during the initial year of the KAMIN project. Based on the comparison, utilizing an evolutionary optimization process instead of a manual one led to the model's volume and energy efficiency enhancements.
In conclusion, computational optimization and active flow control made it possible to decrease the drag on the model by 34% at a speed of 25 meters per second. Additionally, the internal volume increased by 9%. This study suggests that future research and industrial applications could benefit from optimizing processes and implementing similar flow control systems to enhance performance and energy efficiency.
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