DBD Plasma Actuator Multi-Objective Design Optimization at Reynolds Number 63,000: Baseline Case

Abstract

The working parameters of the dielectric barrier discharge (DBD) plasma actuator were optimized to gain an understanding of the flow control mechanism. Experiments were conducted at a Reynolds number of 63,000 using a NACA 0015 airfoil which was fixed to the stall angle of 12 degrees. The two objective functions are: 1) power consumption (P) and 2) lift coefficient (Cl). The goal of the optimization is to decrease P while maximizing Cl. The design variables consist of input power parameters. The algorithm was run for 10 generations with a total population of 260 solutions. Although the number of generations and population size was limited due to experimental constraints, the algorithm was able to converge and the approximate Pareto-front was obtained. From the objective function space, we observe a relatively linear trend where Cl increases with P and after a certain threshold, the value of Cl seems to saturate. We discuss the results obtained in the objective space in addition to scatter plot matrix and color maps. This article, with its experiment-based approach, demonstrates the robustness of a Multi-Objective Design Optimization method and its feasibility for wind tunnel experiments.

Turbulent separated shear flow control by surface plasma actuator: experimental optimization by genetic algorithm approach

“…Indeed, in complex control scenario, for instance when several actuators are considered individually, when multi-frequency forcing with phase shift [61] or when the second objective function concerns a minimization of the consumed power as in [20], such algorithms may highlight unseen influence of some design variable on the flow and reveal new control mechanisms.…”

“…Active wing morphing has also been investigated in [19] where a two-point optimization design is conducted by interfacing an evolutionary genetic algorithm with a sting balance supporting the wing model in a wind tunnel. Recently, the influence of a flow control system based on dielectric barrier discharge has been optimized by NSGA-II algorithm in a multi-objective optimization approach [20]. Indeed, the autonomous experimental optimization proposed in [20] simultaneously maximizes the lift coefficient estimated by time-averaged pressure measurements and minimizes the electrical power consumed by the actuator.…”

“…Recently, the influence of a flow control system based on dielectric barrier discharge has been optimized by NSGA-II algorithm in a multi-objective optimization approach [20]. Indeed, the autonomous experimental optimization proposed in [20] simultaneously maximizes the lift coefficient estimated by time-averaged pressure measurements and minimizes the electrical power consumed by the actuator. The results are analysed by regarding the trend of the global solutions as well as by inspecting the non-dominated solutions of the multiobjective optimization problem.…”

“…This configuration is well-adapted for defining unsteady flow control approaches because the flow behind a BFS presents a large variety of periodic motions that can be manipulated. The actuator is based on a surface dielectric barrier discharge [24][25][26] operated by applying an AC high-voltage to the air-exposed electrode of the actuator as in [20][21]. Plasma actuators are based on electro-mechanical conversion principle that implies fast energy transfers.…”