This study attempts to optimize parameters for the microbubble drag reduction in a turbulent flow based on experimental measurements. Five parameters were investigated: three are control factors (the area of air injection, bubble size, and the rate of air injection) and two are indicative factors (flow speed and the measured position of local shear stress). An integrated approach of combining the Taguchi method with artificial neural networks (ANN) is proposed, implementing the optimum parameter design in this study. Based on the experimental results, analysis of variance concluded that, among the control factors, the rate of air injection has the greatest influence on microbubble drag reduction, while bubble size has the least. The investigation of drag reduction characteristics revealed that the drag ratio decreases with an increasing rate of air injection. However, if the rate of air supplied exceeds a certain value, the efficiency of drag reduction can drop. In the case of optimum parameter design, a 21% drag reduction and an S/N ratio of 1.976 dB were obtained.
SUMMARYAn important way of increasing the speed and lowering the fuel consumption of ships is by decreasing the frictional drag. One of the most promising techniques for reducing drag is the use of air bubbles. The goal of this investigation is to establish a set of optimum robust parametric levels for drag reduction by a mixture (air-water) film in turbulent channel flow. Based on the conditions laid out by the Taguchi orthogonal array method, turbulent flows, with air bubbles injected into a channel, are simulated using commercial computational fluid dynamics software. The local shear stress on the upper wall is computed to evaluate the efficiency of drag reduction. Many factors can affect drag reduction. The factors investigated in this study are the rate of air injection, bubble size, area of air injection, flow speed, and measured position of the shear stress. These factors have been investigated through the analysis of variance, which has revealed that the rate of air injection and water flow speed dominate the efficiency of drag reduction by a mixture film. According to the results, the drag can be reduced by an average of 83.4%; and when the configuration of the parametric levels is optimum the maximum drag reduction of 88.5% is achieved.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.