Scientific Computing Seminar

Due to the high computational cost, time-dependence, and complexity of aeroacoustic simulations, constrained shape optimization for noise reduction is difficult to perform using traditional optimization methods such as adjoint-based gradient methods. In this work, a tailored version of the surrogate management framework (SMF) (Booker et al., 1999) has been implemented and applied to optimize noise reduction for an airfoil trailing-edge using several shape parameters and constraints. The SMF method provides a robust and efficient alternative to gradient-based methods. Using SMF, design space exploration is performed not with the expensive actual function but with an inexpensive surrogate function. The use of a polling step in the SMF guarantees convergence to a local minimum of the cost function on a mesh in the parameter space. In the trailing-edge problem, constraints on lift and drag are enforced using the filter method of Audet and Dennis (2000). Within the framework of this method, a penalty function is systematically added to the surrogate model to aid in searching the design space. Using this method, several interesting and surprising optimal shapes have been identified, all of which resulted in significant reduction of trailing-edge noise (as much as 80%). These shapes have provided motivation to study the physics of the flow, and in particular, the trade-off between noise reduction and loss of lift.