The numerical simulation of physical problems involves capturing various phenomena occurring simultaneously at different scales in a single simulation. For example, considering aeroacoustic problems, the noise generating flow and the propagation of the sound waves in the far-field need to be taken into account. The increasing computational capacities and the development of modern supercomputers allow for more detailed studies of complex multi-physics and multi-scale problems. In this work, the sound generation by moving obstacles and its propagation up to the far-field is of particular interest. For this purpose, a high-order Discontinuous Galerkin method is utilized to discretize the fluid dynamic equations. These high-order methods are exceptionally efficient as they only require a few degrees of freedom to represent smooth solutions. Therefore, they are often deployed for, e.g., the acoustics far-field, where a homogenous flow field can be found. From the computational perspective on modern high-performing architectures, few degrees of freedom are an exceptional advantage, with memory bandwidth being a bottleneck on modern systems. Additionally, the ratio between communication and computation is minimal due to the loose connection of computational elements at their respective interfaces, which is an additional advantage of these methods, when considering distributed and massively parallel computing systems.
However, the high-order representation of complex geometries has been a critical limitation for their application in various fields. The representation of geometrical shapes has to be appropriate to preserve the quality of the numerical solution, which has been discretized with high-order. Incorporating meshing techniques such as body-fitted meshes might not be robust in the workflow for the simulation. They are required to withstand different scenarios that are common, such as scenarios with general complex geometries inside the simulation domain. They can become expensive in computation when involving simulations with multiple geometries and even more when geometries can move. In these cases, the embedded method, also known as immersed boundary method, provides a promising prospect. In this work, the Brinkman penalization technique is applied to model multiple complex and moving geometries.
Moving rigid bodies are common in engineering applications. The sound emitted due to the motion and the flow disturbance by geometries is of particular interest, as awareness of environmental impact in society has grown in recent years. Therefore, predicting the produced noise is a common responsibility in different fields, such as the design of wind turbines. These simulations have a complex nature and require an efficient strategy to facilitate them feasibly. Therefore we deploy the partitioned coupling approach, where the complex and large simulation domain is decomposed into smaller subdomains. Each subdomain is configured such that the occurring phenomena can be precisely captured. It results in an efficient strategy allowing for the simulation of various scales and physics, such as the large-scale simulation in this work. The simulation includes the motion of an airfoil and the induced noise that spreads over a large domain.