The paper presents the aerodynamic optimization of a morphing leading edge airfoil using a parameterization based on the class/shape transformation (CST) technique associated with a dedicated procedure to keep the arc length of the curve constant in order to limit the axial stress of the deformed shapes. The optimization is performed with a standard methodology based on genetic algorithms, comparing the results for three different aerodynamic models. Whereas the solutions obtained with the third model are standard droop nose shapes, those found via transitional models show an uncommon deformation with an upward leading edge deflection. A metamodel-assisted optimization loop is used to solve a known problem, showing that an artificial neural network is able to provide a reduction of the convergence effort when approximating the highly nonlinear relationship between the constant arc length parameterization and the aerodynamic behavior predicted with two of the models.

Modern aeronautic fans are characterised by a transonic flow regime near the blade tip. Transonic cascades enable higher pressure ratios by a complex system of shockwaves arising across the blade passage, which has to be correctly reproduced in order to predict the performance and the operative range. In this paper, we present an accurate two-dimensional numerical modelling of the ARL-SL19 transonic compressor cascade. A large series of data from experimental tests in supersonic wind tunnel facilities has been used to validate a computational fluid dynamic model, in which the choice of turbulence closure resulted critical for an accurate reproduction of shockwave-boundary layer interaction. The model has been subsequently employed to carry out a parametric study in order to assess the influence of main flow variables (inlet Mach number, static pressure ratio) and geometric parameters (solidity) on the shockwave pattern and exit status. The main objectives of the present work are to perform a parametric study for investigating the effects of the abovementioned variables on the cascade performance, in terms of total-pressure loss coefficient, and on the shockwave pattern and to provide a quite large series of data useful for a preliminary design of a transonic compressor rotor section. After deriving the relation between inlet and exit quantities, peculiar to transonic compressors, exit Mach number, mean exit flow angle and total-pressure loss coefficient have been examined for a variety of boundary conditions and parametrically linked to inlet variables. Flow visualisation has been used to describe the shock-wave pattern as a function of the static pressure ratio. Finally, the influence of cascade solidity has been examined, showing a potential reduction of total-pressure loss coefficient by employing a higher solidity, due to a significant modification of shockwave system across the cascade.

Transonic compressors are widely used today in propulsion and industrial applications thanks to their higher specific work compared to subsonic. In this work, the aerodynamic optimization of a two-dimensional Computational Fluid Dynamics (CFD) model of the transonic cascade ARL-SL19 is described. The validated computational model is used for a multi-objective optimization of the cascade at three different inlet Mach numbers using a genetic algorithm and an artificial neural network, with the aim of reducing total pressure loss and increasing maximum pressure ratio. Finally, the optimized shapes on the Pareto fronts are investigated, analyzing mechanisms responsible for loss reduction and enhanced compression. Profiles having the lowest losses have flatter camberlines and reduced acceleration of flow on the suction side, while geometries achieving the highest pressure ratio values have a more cambered shape with a concave suction side.