Breaking through: The Impact of Turbulence on the Gas-Liquid Interface

Introduction

A rigorous understanding of the role of turbulence, with its wide range of scales and phenomena, on mass transport across a gas-liquid interface (GLI) is one of the remaining challenges in fluid mechanics. Its importance is illustrated by considering that nearly 50% of anthropogenic CO2 is driven into the oceans by a turbulent process we do not fully understand.

Challenges in Understanding Turbulence

We know that turbulence modifies the topology of the GLI from both the liquid and gas sides, but due to the complexity of the problem, we do not understand the dominant mechanisms that control this process or how they connect to mass transfer. My previous work has both shown how turbulence can be tailored in the lab and how the parameters of the turbulence influence shear on a surface, making me well placed to tackle this problem.

Existing Models and Their Limitations

A plethora of models based on limited data exist for mass transfer across a GLI, but they have contrasting backgrounds, parameters, and results. This is indicative that something is missing and that there is a critical need for deeper understanding of the underlying phenomena.

Project Overview: GLITR

GLITR will provide a step change in our understanding of phenomena at the GLI by initiating a paradigm shift in the way lab experiments are conducted, considering the complexity of interacting turbulent gas and liquid flows for the first time.

Innovative Approach

• Tailored turbulence with adjustable intensity and length scales will be generated with an active turbulence generator in both the gas and liquid simultaneously to provide new insight not previously accessible.
• This will result in deformed interfaces that will necessitate the development of new methods to investigate the associated mass transport and fluid mechanics.

Expected Outcomes

Correlations between the tailored turbulence in both the gas and liquid, the surface topology, and the mass transport across the GLI will enable the development of data-driven models and breakthroughs in our understanding of interfacial phenomena while initiating a wholly new way of addressing this problem.