Active Mathematics & Statistics Physics & Astronomy

Wall Similarity of 2D and 3D Non-Equilibrium Rough Wall Boundary Layers

In plain English

AI plain-English summary

A wind tunnel and a supercomputer are working together to settle a decades-old debate about how rough surfaces affect the flow of air or water over them. Engineers rely on computer models to predict drag, noise, and vibration on aircraft, ships, wind turbines, and pipelines. Those models assume that, far enough from a rough wall, the turbulence behaves the same as it would over a smooth wall—a principle called the wall similarity hypothesis. But the hypothesis has never been rigorously tested for flows that are changing rapidly, such as air accelerating over a wing or water surging past a ship’s hull. This project combines physical experiments at Virginia Tech with advanced simulations at Cambridge to test whether the hypothesis holds under those non-equilibrium conditions. If the hypothesis holds, engineers can trust existing models for a wider range of real-world flows. If it fails, the work will reveal where and why the models break down, pointing toward corrections. The result will improve predictions of drag, fuel consumption, and structural fatigue in transport, energy, and infrastructure. The project is fundamental fluid dynamics—it does not aim to build a product—but a deeper understanding of rough-wall turbulence could eventually reshape how engineers design everything from aircraft wings to offshore wind foundations.

View original technical description
This proposal puts forward a combined experimental and computational study to investigate and precisely assess the wall similarity hypothesis for a broad class of non-equilibrium rough-wall turbulent boundary layers. This issue is crucial to the application of RANS CFD to a vast array of practically relevant flows and to the prediction of separation, drag, performance, flow-induced vibration and noise. The work will combine state of the art experimental capabilities and experience at Virginia Tech, with leading edge computational expertise at the University of Cambridge. In addition to conclusively resolving key scientific issues and bringing new insight into the physics involved, the work will engage and train researchers at the postdoctoral, PhD, undergraduate and high-school levels, enable cross-cultural and interdisciplinary international exchanges, and provide unique research experiences for hundreds of undergraduate engineers.

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Researchers

Ricardo Garcia-Mayoral (Principal Investigator)

Related Research

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Original classification

Research Grant

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