PhD Oral Exam - Seyedramin Ghoreshilangrodi, Mechanical Engineering
Vorticity-Based Polynomial Adaptation for Unsteady Flows
This event is free
School of Graduate Studies
When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.
Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.
Aerospace applications, including but not limited to the aerodynamics of slats and flaps, the aeroacoustics of complete landing gear configurations, and the performance prediction of air brakes, spoilers, fans, and turbines, benefit from high-fidelity scale resolving approaches such as Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES). These approaches are shown to be accurate in complex unsteady flow regimes where current industry-standard Reynolds-averaged Navier-Stokes (RANS) methods often fail. For example, recent research has demonstrated that DNS can be utilized for analysis of complete jet engine low-pressure turbine cascades at their designed operating condition. High-order unstructured spatial discretizations such as Flux Reconstruction (FR) are particularly appealing for LES simulations of unsteady turbulent flows as they are capable of resolving the flow more efficiently; however, their computational cost remains relatively high, preventing their industrial use. Therefore, given the inherent computational cost of high-order methods, it is crucial to deploy strategies to minimize the overall computational cost of LES while attaining comparable accuracy. A practical approach is to limit the use of high-order elements to regions where higher resolution is required for an accurate discrete approximation of the solution, reducing the total number of Degrees of Freedom (DOF). This can be achieved by locally increasing or decreasing the solution polynomial degree to adjust resolution and order of accuracy to achieve an accurate and cost-efficient simulation, a practice which is called polynomial adaptation or p-adaptation. LES can also benefit from the computational power of state-of-the-art hardware architectures by taking advantage of parallel computing, which can achieve a significant speed-up by decomposing the domain and solving the problem concurrently. Parallel computing also provides a larger memory capacity and higher bandwidth, resulting in better performance. However, combining polynomial adaptation with a massively parallel computation can cause overhead because p-adaptation tends to change the degree of solution polynomials locally, leaving the computational domain unbalanced. To maintain parallel efficiency, Dynamic Load Balancing (DLB) techniques have been exploited. The current work introduces a novel dynamically load-balanced polynomial adaptation method for simulations of unsteady flows in the vicinity of complex geometries using the flux reconstruction scheme. This approach is applied to both two-dimensional and three-dimensional studies while for the latter we make use of Implicit LES (ILES), which relies on the dissipation error of the numerical scheme to act as a subgrid-scale model to dissipate the kinetic energy from the smallest turbulent scales in the flow.
We verify the utility of our dynamically load-balanced adaptation approach when applied to the Arbitrary Lagrangian-Eulerian (ALE) form of the compressible Navier-Stokes equations for a range of applications on moving and deforming domains. Specifically, we verify the ALE and DLB implementation by performing simulations of an Euler Vortex (EV), and then illustrate the accuracy and efficiency of the adaptation routine by performing simulations of flow over an oscillating circular cylinder with two different flow settings, dynamic stall of a 2D NACA 0012 airfoil undergoing heaving and pitching motions, and flow over a Vertical Axis Wind Turbine (VAWT) composed of two NACA 0012 airfoils. We further illustrate the accuracy and efficiency of the routine when applied to transitional and turbulent flows by performing simulations of a shallow dynamic stall of a 3D SD 7003 airfoil undergoing heaving and pitching motions and transitional flow over a 3D circular cylinder. Results demonstrate that the dynamically load-balanced adaptation algorithm can track regions of interest, such as vortices and boundary layers, and yields a significant speed-up when applied to parallel simulations. We also demonstrate the scalability of the algorithm and the capability of DLB to distribute uniform computational load among processors.