Wavelet-based grid adaptation with consistent treatment of high-order sharp immersed geometries
This work addresses a specific problem in computational fluid dynamics and PDE simulation for researchers and engineers dealing with complex, moving boundaries, representing an incremental improvement in grid adaptation methods.
The paper tackled the challenge of applying wavelet-based grid adaptation to PDEs with sharp immersed geometries, where standard methods lose consistency near boundaries, by proposing a high-order interpolating wavelet transform strategy that maintains wavelet order on arbitrary smooth domains. The results demonstrated effective grid adaptation with a robust, predictable relationship between a user-defined refinement threshold and solution error, validated on static and dynamic problems like Navier-Stokes equations with moving boundaries.
Wavelet-based grid adaptation methods use multiresolution analysis for error estimation, offering a mathematically rigorous approach to adaptive grid refinement when solving Partial Differential Equations (PDEs). However, applying these methods to PDE discretizations with immersed geometries is challenging, as standard interpolating wavelet transforms lose consistency near non-grid-aligned boundary intersections. To address this, we propose a high-order interpolating wavelet transform adaptation strategy compatible with sharp immersed boundary and interface discretizations. The approach performs consistent high-order wavelet transforms on narrow intervals using a 1D polynomial extrapolation technique. To maintain high order, the technique incorporates boundary values and derivatives, which are evaluated from multivariate interpolating polynomials similar to those used in high order immersed finite difference discretizations. Consequently, the proposed approach maintains the wavelet order on any arbitrary smooth multidimensional domain, including near concave geometry sections. This approach enables grid adaptation in complex domains while robustly bounding the numerical error via a manually set refinement threshold. The algorithm's performance is validated on both static and dynamic problems, including the Navier-Stokes equations with moving boundaries and temporally adapting grid resolutions. The results demonstrate that the proposed method enables effective grid adaptation, establishing a robust, predictable relationship between a user-defined refinement threshold and the overall solution error, even for problems with complex, moving boundaries.