Large Eddy Simulations of Fully-Developed Turbulent Flows Over Additively Manufactured Rough Surfaces
Himani Garg, Lei Wang, Guillaume Sahut, Christer Fureby

TL;DR
This study uses high-fidelity LES to analyze turbulent flow over additively manufactured rough surfaces, revealing how surface topography influences turbulence and developing models for better simulation of AM-roughened heat exchangers.
Contribution
It provides a novel LES database for AM rough surfaces and introduces a mixed scaling approach to improve turbulence modeling over such surfaces.
Findings
Logarithmic layer persists even at high roughness levels.
Turbulence strongly depends on surface topography.
Effective wall-normal distance collapses turbulence profiles.
Abstract
In the last decade, progresses in additive manufacturing (AM) have paved the way for optimized heat exchangers, whose disruptive design will depend on predictive numerical simulations. Typical AM rough surfaces show limited resemblance to the artificially constructed rough surfaces that have been the basis of most prior fundamental research on turbulent flow over rough walls. Therefore, a high-fidelity LES database is built to develop and assess novel wall models for AM. This article investigates the flow in rough pipes built from the surfaces created using AM techniques at Siemens based on Nickel Alloy IN939 material. We developed a code to generate the desired rough pipes from scanned planar surfaces and performed high-fidelity LES of turbulent rough pipe flows at Re = 11,700 to reveal the influence of roughness on turbulence, mainly the average roughness height and the Effective…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFluid Dynamics and Turbulent Flows · Heat Transfer Mechanisms · Particle Dynamics in Fluid Flows
