Papers › Industrial scale large eddy simulations (LES) with adaptive octree meshes using...
Industrial scale large eddy simulations (LES) with adaptive octree meshes using immersogeometric analysis
Kumar Saurabh, Boshun Gao, Milinda Fernando, Songzhe Xu, Makrand A. Khanwale, Biswajit Khara, Ming-Chen Hsu, Adarsh Krishnamurthy, Hari Sundar, Baskar Ganapathysubramanian
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
We present a variant of the immersed boundary method integrated with octree meshes for highly efficient and accurate Large-Eddy Simulations (LES) of flows around complex geometries. We demonstrate the scalability of the proposed method up to 𝒪(32K) processors. This is achieved by (a) rapid in-out tests; (b) adaptive quadrature for an accurate evaluation of forces; (c) tensorized evaluation during matrix assembly. We showcase this method on two non-trivial applications: accurately computing the drag coefficient of a sphere across Reynolds numbers 1-10⁶ encompassing the drag crisis regime; simulating flow features across a semi-truck for investigating the effect of platooning on efficiency.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections