Design and Optimization of a Diffuser for a Horizontal Axis Hydrokinetic Turbine using Computational Fluid Dynamics based Surrogate Modelling

Abstract

Fossil fuels have remained at the backbone of the global energy portfolio. With the growth in the number of factories, population, and urbanization; the burden on fossil fuels has also been increasing. Most importantly, fossil fuels have been causing damage to the global climate since industrialization. The stated issues can only be resolved by shifting to environment friendly alternate energy options. The horizontal axis hydrokinetic turbine is considered as a viable option for renewable energy production. The aim of this project is the design and optimization of a diffuser for horizontal axis hydrokinetic turbine using computational fluid dynamics based surrogate modeling. The two-dimensional flat plate airfoil is used as a benchmark and flow around the airfoil is simulated using Ansys Fluent. Later, computational fluid dynamics analyses are carried out for baseline diffuser generated from the flat plate airfoil. The performance of this diffuser was optimized by achieving an optimum curved profile at the internal surface of the diffuser. The response surface methodology is used as a tool for optimization. A maximum velocity augmentation of 31.70% is achieved with the optimum diffuser.

Velocity Augmentation Model for an Empty Concentrator-Diffuser-Augmented Wind Turbine and Optimisation of Geometrical Parameters Using Surface Response Methodology

“…The present study, guided by insights from prior research [7,41,43,63] and the fact that the first-order multiple linear model is limited to a 2-level factorial fit due to the strong curvature of the response surface [48], led to the adoption of the more flexible and versatile second-order multiple linear model, or quadratic model. Equation (2) provides this quadratic regression equation for the wind speed augmentation model [7,38,43,64].…”

“…This model combines elements of the k-ε and k-ε turbulence models, as previously mentioned. The current study employed a root mean square (RMS) residual value of 10 −6 as the stopping criterion for continuity, momentum, velocity components, and turbulence equations [64,68,76]. The solution converged after approximately 121 iterations.…”