arXiv subjects

Jakob Dürrwächter

Publications and source records attributed to Jakob Dürrwächter.

3 recordsLinked to original sources

arXiv2023

Data-integrated uncertainty quantification for the performance prediction of iced airfoils

Airfoil icing is a severe safety hazard in aviation and causes power losses on wind turbines. The precise shape of the ice formation is subject to large uncertainties, so uncertainty quantification (UQ) is needed for a reliable prediction of its effects. In this study, we aim to establish a reliable estimate of the effect of icing on airfoil performance through UQ. We use a series of experimentally measured wind tunnel ice shapes as input data. Principal component analysis is employed to construct a set of linearly uncorrelated geometric modes from the data, which serves as random input to the UQ simulation. For uncertainty propagation, non-intrusive polynomial chaos expansion (NIPC), multi-level Monte Carlo (MLMC) and multi-fidelity Monte Carlo control variate (MFMC) methods are employed and compared. As a baseline model, large eddy simulations (LES) are carried out using the discontinuous Galerkin flow solver FLEXI. UQ simulations are carried out with the in-house framework PoUnce. Its focus is on a high level of automation and efficiency considerations in a high performance computing environment. Due to the high number of samples, the simulation tool chain of the baseline model is completely automatized, including a new structured boundary layer grid generator for highly irregular domain shapes. The results show that forces on the airfoil vary considerably due to the uncertain ice shape. All three methods prove to be suited to predict mean and standard deviation. In the Monte Carlo techniques, the choice and performance of low-fidelity models is shown to be decisive for estimator variance reduction. The MFMC method performs best in this study. To our knowledge, there are no UQ studies of iced airfoils based on LES, let alone with advanced UQ methods such as MLMC or MFMC. The present study thus represents a leap in accuracy and level of detail for this application.

physics.flu-dyn↗

arXiv2020

An Efficient Sliding Mesh Interface Method for High-Order Discontinuous Galerkin Schemes

Sliding meshes are a powerful method to treat deformed domains in computational fluid dynamics, where different parts of the domain are in relative motion. In this paper, we present an efficient implementation of a sliding mesh method into a discontinuous Galerkin compressible Navier-Stokes solver and its application to a large eddy simulation of a 1-1/2 stage turbine. The method is based on the mortar method and is high-order accurate. It can handle three-dimensional sliding mesh interfaces with various interface shapes. For plane interfaces, which are the most common case, conservativity and free-stream preservation are ensured. We put an emphasis on efficient parallel implementation. Our implementation generates little computational and storage overhead. Inter-node communication via MPI in a dynamically changing mesh topology is reduced to a bare minimum by ensuring a priori information about communication partners and data sorting. We provide performance and scaling results showing the capability of the implementation strategy. Apart from analytical validation computations and convergence results, we present a wall-resolved implicit LES of the 1-1/2 stage Aachen turbine test case as a large scale practical application example.

cs.CE↗

arXiv2019

A hyperbolicity-preserving discontinuous stochastic Galerkin scheme for uncertain hyperbolic systems of equations

Intrusive Uncertainty Quantification methods such as stochastic Galerkin are gaining popularity, whereas the classical stochastic Galerkin approach is not ensured to preserve hyperbolicity of the underlying hyperbolic system. We apply a modification of this method that uses a slope limiter to retain admissible solutions of the system, while providing high-order approximations in the physical and stochastic space. This is done using a spatial discontinuous Galerkin scheme and a Multi-Element stochastic Galerkin ansatz in the random space. We analyze the convergence of the resulting scheme and apply it to the compressible Euler equations with various uncertain initial states in one and two spatial domains with up to three uncertainties. The performance in multiple stochastic dimensions is compared to the non-intrusive Stochastic Collocation method. The numerical results underline the strength of our method, especially if discontinuities are present in the uncertainty of the solution.

math.NA↗