Duct Shape Optimization Using Multi-Objective and Geometrically Constrained Adjoint Solver 2019-01-0823
In the recent years, adjoint optimization has gained popularity in the automotive industry with its growing applications. Since its inclusion in the mainstream commercial CFD codes and its continuously added capabilities over the years, its productive usage became readily available to many engineers that were previously limited to those that were able to utilize the customized source code. The purpose of this work is to demonstrate using the commercial adjoint solver a method to optimize duct shape that meets multiple design objectives simultaneously. To overcome one of the biggest challenges in the duct design, i.e. the severe packaging constraints, the method here uses geometrically constrained adjoint to ensure that the optimum shape always fits into the user-defined packaging space. In this work, Adjoint Solver and the Surface Sensitivity Model in Star-CCM+ are used to develop the optimization method. A java macro is then utilized to automate the entire optimization cycles. The issues during the optimization process, mostly related to the morphing of mesh, are addressed and the solution to avoid the issues is proposed. As a test case, a rear floor duct is used for the shape optimization where the goal is to reduce the pressure drop and the duct size simultaneously. The prediction shows a significant reduction in both through a small shape change. As a validation, surfaces of the optimized design and the baseline design are extracted from their mesh and 3D-printed, and has undergone air-flow bench test. The test results showed good agreement against the CFD results, confirming the validity of the optimization method.