Sebastian Spinner | Searcharxiv

arXiv2026

Modal Analysis of Buffet Effects Induced by Ultrahigh Bypass Ratio Nacelle Installation

Unsteady shock-boundary-layer interaction on the lower surface of a transport-aircraft wing can be caused or amplified by ultrahigh-bypass-ratio underwing nacelle installation. This work analyzes the resulting buffet dynamics on the Airbus XRF-1 configuration at a Mach number of $0.84$, a Reynolds number of $3.3\times 10^6$, and $-4^\circ$ angle of attack using scale-resolving delayed detached eddy simulations and unsteady pressure-sensitive paint measurements. Coherent structures are extracted employing a data-efficient multi-taper spectral POD. Dominant modes occur in the Strouhal number range $St \in [0.1,0.3]$. Surface modes reveal wave-like shock motions that originate near the pylon-wing intersection and propagate inboard towards the fuselage. These shock oscillations are linked to unsteady flow separation downstream of the shock. Additional dominant modes show spanwise oscillations of the separated flow region and shock oscillations phase-linked to shear layer instabilities. The modal analysis of volume data reveals pressure waves connected to these modes traveling upstream above and below the wing.

physics.flu-dyn↗

arXiv2025

An octree-based sampling algorithm for analyzing big simulation data

As computational resources continue to increase, the storage and analysis of vast amounts of data will inevitably become a bottleneck in computational fluid dynamics (CFD) and related fields. Although compression algorithms and efficient data formats can mitigate this issue, they are often insufficient when post-processing large amounts of volume data. Processing such data may require additional high-performance software and resources, or it may restrict the analysis to shorter time series or smaller regions of interest. The present work proposes an improved version of the existing \emph{Sparse Spatial Sampling} algorithm ($S^3$) to reduce the data from time-dependent flow simulations. The $S^3$ algorithm iteratively generates a time-invariant octree grid based on a user-defined metric, efficiently down-sampling the data while aiming to preserve as much of the metric as possible. Using the sampled grid allows for more efficient post-processing and enables memory-intensive tasks, such as computing the modal decomposition of flow snapshots. The enhanced version of $S^3$ is tested and evaluated on the scale-resolving simulations of the flow past a tandem configuration of airfoils in the transonic regime, the incompressible turbulent flow past a circular cylinder, and the flow around an aircraft half-model at high Reynolds and Mach numbers. $S^3$ significantly reduces the number of mesh cells by $35 \%$ to $95\%$ for all test cases while accurately preserving the dominant flow dynamics, enabling post-processing of CFD data on a local workstation rather than HPC resources for many cases.

physics.flu-dyn↗