Robust multidisciplinary design optimization using CFD and advanced evolutionary algorithms

Computation Fluid Dynamics (CFD) has become an important tool in optimization and has seen successful in many real world applications. Most important among these is in the optimisation of aerodynamic surfaces which has become Multi-Objective (MO) and Multidisciplinary (MDO) in nature. Most of these have been carried out for a given set of input parameters such as free stream Mach number and angle of attack. One cannot ignore the fact that in aerospace engineering one frequently deals with situations where the design input parameters and flight/flow conditions have some amount of uncertainty attached to them. When the optimisation is carried out for fixed values of design variables and parameters however, one arrives at an optimised solution that results in good performance at design condition but poor drag or lift to drag ratio at slightly off-design conditions. The challenge is still to develop a robust design that accounts for uncertainty in the design in aerospace applications. In this paper this issue is taken up and an attempt is made to prevent the fluctuation of objective performance by using robust design technique or Uncertainty