A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by the sonic boom of a high-altitude supersonic body is presented. A Cartesian–Euler flow solver is coupled with an atmospheric propagation tool to create a ground-noise analysis capability. Adjoint formulations for both the flow solver and propagation tool are also coupled to compute noise sensitivities to shape variations in a highly efficient manner. A gradient-based optimizer is then used to minimize objectives that are functions of ground-level noise. Output-based mesh adaptation that is driven directly by ground-level noise is employed to automatically generate meshes during the optimization. The design method was first demonstrated on a simple axisymmetric body with few lengthwise shape variables to evaluate the efficacy and validity of the optimization scheme. This design space was found to contain two local minima. Convergence of the optimization is demonstrated from multiple starting points. In addition, the method is applied to a second example with design variable placement that is guided by the coupled adjoint solution of the first problem. The design method was then applied to a low-boom aircraft at supersonic cruise to optimize control surface deflections. Two noise minimization examples and a noise maximization are presented. All optimized designs resulted in measurable improvements in the ground-level noise objective. Surveys of the design space confirm that the optimization method is effective in finding a local optimum.
Rodriguez et al. (Sun,) studied this question.