Adjoint-based Optimization of Liners for Noise Reduction

在这个项目中，我们的目标是开发一个有效的和创新的框架，以优化声学衬里，降低喷气发动机噪音。特别是，这项研究的目的是提高班轮效率，采用空间可变班轮参数化，涉及大量的设计参数。由于衬里效率强烈依赖于源的位置和流动特性，我们的目标是进行多点优化，以考虑设计点的变化。为此，将使用自动微分技术开发基于底层高阶线性化欧拉解算器的离散伴随解算器。然后，将离散伴随求解器与基于梯度的优化算法相结合，以能够执行声学衬垫的大规模优化。

In this project, we aim to develop an efficient and innovative framework to optimize acoustic liners in reducing the jet engine noise. In particular, this research is aimed at improving the liner efficiency by employing a spatially variable liner parameterization involving a large number of design parameters. Since the liner efficiency strongly depends on the location of the source and the flow properties, we aim at performing multi-point optimization to account for the changes in the design point. For this purpose, a discrete adjoint solver based on the underlying high-order linearized Euler solver will be developed using Automatic Differentiation techniques. The discrete adjoint solver will then be combined with a gradient-based optimization algorithm to able to perform large-scale optimization of acoustic liners.