Traditionally, airfoil design has been broadly limited to experimental and empirical methods. Over the years, computing power has grown exponentially and computational methods are becoming increasingly relevant. Still, generic airfoils continue to be used in most applications. Such airfoils yield sub-optimal performance and result in compromises in the overall design of the aircraft. With the advent of modern high-performance computing systems and metaheuris-tic optimization algorithms, optimizing airfoils for their specific use cases has become highly feasible. This paper presents a novel optimization framework for airfoils using the Invasive Weed Optimisation algorithm. The presented framework can be implemented using single or multiple objectives with the multi-objective functionality being realized through integration with NSGA-II. Additionally, this framework has the unique ability to operate in two fidelity modes in order to cater to a range of computational capabilities. The low fidelity mode is coupled with XFOIL while the high fidelity mode utilizes a RANS CFD solver on OpenFOAM. To depict the prowess of this framework, two test cases have been shown. The resulting optimized airfoils perform exceedingly well in their use case as compared to conventional airfoils, thereby validating the efficacy of this framework.
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