<p>This study presents an optimization framework for improving the aerodynamic performance of a square cylinder by optimizing the placement of a pair of dielectric barrier discharge (DBD) plasma actuators using Kriging-enhanced Genetic Algorithm (GA). High-fidelity Navier-Stokes simulations at Reynolds numbers ranging from 1 to 300 provide baseline insights into flow separation, vortex shedding, and aerodynamic force fluctuations. Plasma actuators are modeled as body forces, with configurations explored through Latin Hypercube Sampling (LHS) within a Design of Experiments (DoE) framework. The optimization process is refined by using adaptive infill sampling, guided by Expected Improvement (EI), to efficiently identify optimal actuator placements. The comparative analysis of predicted and actual force coefficients validates the effectiveness of the Kriging model, GA, and infill sampling for optimizing the location of plasma actuators. Results highlight that (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">$y/h = \pm 1$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>y</mi> <mo stretchy="false">/</mo> <mi>h</mi> <mo>=</mo> <mo>±</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation>) is the most optimized location for steady plasma actuation, where it achieved 55.73% reduction in drag and 98.08% significant reduction in lift oscillations, relative to the baseline condition (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">$C_{d,\text {avg}} = 1.44$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>C</mi> <mrow> <mi>d</mi> <mo>,</mo> <mtext>avg</mtext> </mrow> </msub> <mo>=</mo> <mn>1.44</mn> </mrow> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$C_{l,\text {rms}} = 0.453$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>C</mi> <mrow> <mi>l</mi> <mo>,</mo> <mtext>rms</mtext> </mrow> </msub> <mo>=</mo> <mn>0.453</mn> </mrow> </math></EquationSource> </InlineEquation>). Comprehensive flow physics analysis, including flow streamlines, velocity profiles, power spectral density, and turbulence intensity, combined with comparisons to other potential actuator locations (<InlineEquation ID="IEq4"> <EquationSource Format="TEX">$y/h = \pm 0.8, \pm 0.7, \pm 0.6$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>y</mi> <mo stretchy="false">/</mo> <mi>h</mi> <mo>=</mo> <mo>±</mo> <mn>0.8</mn> <mo>,</mo> <mo>±</mo> <mn>0.7</mn> <mo>,</mo> <mo>±</mo> <mn>0.6</mn> </mrow> </math></EquationSource> </InlineEquation>), further confirms the superiority of steady plasma actuation at the suggested optimized location. These findings underscore the robustness of Kriging-assisted GA optimization in plasma-based flow control, offering an energy-efficient solution for drag reduction and vortex suppression in aerospace, automotive, and civil engineering applications.</p>

Optimal placement of plasma actuators on a square cylinder for flow control using Kriging-enhanced genetic algorithm

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2026年5月13日

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Muhammad Hamza,
Yi Yu,
Fahad Nawaz,
Xuanshi Meng

摘要

This study presents an optimization framework for improving the aerodynamic performance of a square cylinder by optimizing the placement of a pair of dielectric barrier discharge (DBD) plasma actuators using Kriging-enhanced Genetic Algorithm (GA). High-fidelity Navier-Stokes simulations at Reynolds numbers ranging from 1 to 300 provide baseline insights into flow separation, vortex shedding, and aerodynamic force fluctuations. Plasma actuators are modeled as body forces, with configurations explored through Latin Hypercube Sampling (LHS) within a Design of Experiments (DoE) framework. The optimization process is refined by using adaptive infill sampling, guided by Expected Improvement (EI), to efficiently identify optimal actuator placements. The comparative analysis of predicted and actual force coefficients validates the effectiveness of the Kriging model, GA, and infill sampling for optimizing the location of plasma actuators. Results highlight that ( $y/h = \pm 1$ $y / h = \pm 1$ ) is the most optimized location for steady plasma actuation, where it achieved 55.73% reduction in drag and 98.08% significant reduction in lift oscillations, relative to the baseline condition ( $C_{d,\text {avg}} = 1.44$ $C_{d, avg} = 1.44$ , $C_{l,\text {rms}} = 0.453$ $C_{l, rms} = 0.453$ ). Comprehensive flow physics analysis, including flow streamlines, velocity profiles, power spectral density, and turbulence intensity, combined with comparisons to other potential actuator locations ( $y/h = \pm 0.8, \pm 0.7, \pm 0.6$ $y / h = \pm 0.8, \pm 0.7, \pm 0.6$ ), further confirms the superiority of steady plasma actuation at the suggested optimized location. These findings underscore the robustness of Kriging-assisted GA optimization in plasma-based flow control, offering an energy-efficient solution for drag reduction and vortex suppression in aerospace, automotive, and civil engineering applications.