Multi-disciplinary and multi-objective optimization problem applied to a morphing blade cascade study

Multi-disciplinary design optimization (MDO) problems incorporate a number of coupled disciplines that need to be simultaneously solved to achieve a complete solution. Such problems are common in turbomachinery blade design, where MDO usually integrates constraints coming from aerodynamics and structural mechanics. In the present work, a multi-disciplinary and multi-objective optimization problem is formulated and applied to a morphing blade cascade study. An aero-structure coupling strategy is also integrated in the framework to take into account the interactions between aerodynamics and structural mechanics. The morphed blade geometry is obtained by means of a shape memory alloy (SMA) actuator that morphs and adapts the blade leading-edge shape to the inflow conditions in order to improve the aerodynamic flow characteristics, and therefore the overall cascade performance. A surrogate-based optimization strategy is applied to find the Pareto points representing the optimal blade configurations in terms of total pressure loss coefficient at design and off-design conditions. Results show a decrease up to 55% in the total pressure loss coefficient at the off-design condition with a Young’s modulus of about 100 GPa and an actuator length between 30 and 45 mm.