A novel explicit filter for the approximate deconvolution in large-eddy simulation on general unstructured grids: a posteriori tests on highly stretched grids

• A novel explicit filter is proposed for LES on general unstructured grids. • The shortcomings of alternative existing filters are manifested. • A multi-objective optimization is designed to determine filter parameters. • A posteriori analyses show improved predictions using the new filter. • The codes for optimizing the filter parameters for a given grid are available. Explicit filters play a pivotal role in the scale separation and numerical stability of advanced Large Eddy Simulation (LES) closures, such as dynamic eddy-viscosity or Approximate Deconvolution (AD) methods. In the present study, it is demonstrated that the performance of commonly used explicit filters applicable to general unstructured grids highly depends on the grid configuration, specifically the cell aspect ratio, which can result in poor filter spectral properties, ultimately leading to large errors and even solution divergence. This study introduces a novel, efficient explicit filter for general unstructured grids, addressing this shortcoming through a combination of a face-averaging technique and recursive filtering. The filter parameters are then determined through a constrained multi-objective optimization, ensuring desirable spectral properties, including high-wavenumber attenuation, filter-width precision, filter stability and positivity, and minimized dispersion and commutation errors. The AD-LES of turbulent channel flow benchmarks using the new filter demonstrate a noticeable improvement in turbulent flow predictions on highly stretched boundary-layer-type grids, particularly in reducing the log-layer mean velocity profile mismatch, compared to simulations using conventional filters. The analyses show that this enhancement is mainly attributed to the sufficient level of attenuation near the Nyquist wavenumber achieved by the new filter in all spatial directions across various grid configurations, among others. The new filter was also successfully tested on unstructured prism grids for the 3D Taylor-Green vortex benchmark.

Authors

Institutions

Publication Details

Journal
International Journal of Heat and Fluid Flow
Published
2026-02-24
DOI
https://doi.org/10.1016/j.ijheatfluidflow.2026.110320
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A novel explicit filter for the approximate deconvolution in large-eddy simulation on general unstructured grids: a posteriori tests on highly stretched grids

E. Amani, Morteza Ghorbani, Mohammad Bagher Molaei
International Journal of Heat and Fluid Flow
Computational Fluid Dynamics and Aerodynamics
article

A novel explicit filter for the approximate deconvolution in large-eddy simulation on general unstructured grids: a posteriori tests on highly stretched grids

E. Amani, Morteza Ghorbani, Mohammad Bagher Molaei
article en

Abstract

• A novel explicit filter is proposed for LES on general unstructured grids. • The shortcomings of alternative existing filters are manifested. • A multi-objective optimization is designed to determine filter parameters. • A posteriori analyses show improved predictions using the new filter. • The codes for optimizing the filter parameters for a given grid are available. Explicit filters play a pivotal role in the scale separation and numerical stability of advanced Large Eddy Simulation (LES) closures, such as dynamic eddy-viscosity or Approximate Deconvolution (AD) methods. In the present study, it is demonstrated that the performance of commonly used explicit filters applicable to general unstructured grids highly depends on the grid configuration, specifically the cell aspect ratio, which can result in poor filter spectral properties, ultimately leading to large errors and even solution divergence. This study introduces a novel, efficient explicit filter for general unstructured grids, addressing this shortcoming through a combination of a face-averaging technique and recursive filtering. The filter parameters are then determined through a constrained multi-objective optimization, ensuring desirable spectral properties, including high-wavenumber attenuation, filter-width precision, filter stability and positivity, and minimized dispersion and commutation errors. The AD-LES of turbulent channel flow benchmarks using the new filter demonstrate a noticeable improvement in turbulent flow predictions on highly stretched boundary-layer-type grids, particularly in reducing the log-layer mean velocity profile mismatch, compared to simulations using conventional filters. The analyses show that this enhancement is mainly attributed to the sufficient level of attenuation near the Nyquist wavenumber achieved by the new filter in all spatial directions across various grid configurations, among others. The new filter was also successfully tested on unstructured prism grids for the 3D Taylor-Green vortex benchmark.

International Journal of Heat and Fluid FlowVol. 119
Sabancı Üniversitesi (TR), Amirkabir University of Technology (IR)
Openalex Percentile: Top 42%
Computational Fluid Dynamics and Aerodynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.