Reduced-order models of wall-bounded turbulence

Wall turbulence is a critically important phenomenon for any system where fluid flows past an object. Wall turbulence is responsible for 90% of the drag experienced by a large crude tanker, to give just one example. This project aims to investigate novel ways to model and control wall turbulence by exploiting the presence of recently- discovered large-scale structures. This will ultimately lead to significant reductions in the drag and fuel burnt by transport vehicles.
Person

Principal investigator

Simon Illingworth sillingworth@unimelb.edu.au
Magnifying glass

Area of science

Applied Science, Chemistry, Engineering
CPU

Systems used

Magnus
Computer

Applications used

Python, C
Partner Institution: The University of Melbourne| Project Code: pa4

The Challenge

Fluid mechanics is difficult for a number of reasons. One is that we are limited in what we can measure in experiments and in field measurements. The aim of this proposal is to develop a low-order, physics-based tool for the estimation of fluid flows using limited measurements. The work sets out to exploit the fact that, despite their complexity, fluid flows often contain large-scale coherent features.

The Solution

The development of suitable reduced-order models directly from the underlying physics (the Navier-Stokes equations). These reduced-order models are important because, without them, the equations are too large to be solved. These reduced-order models are then used, together with limited measurements, to estimate the flow elsewhere.

The Outcome

The work has allowed, for the first time, physics-based models to predict important flow features from limited measurements. An important long-term application is the estimation of coherent structures from limited field measurements, and the method would undoubtedly lead to a wide range of applications.

List of Publications

Nardini, M., Illingworth, S. J. & Sandberg, R. D. (2019). Nonlinear reduced-order modeling of the forced and autonomous aeroelastic response of a membrane wing using Harmonic Balance methods. J. Fluids Structures.

Madhusudanan, A., Illingworth, S. J. & Marusic, I. (2019). Coherent large-scale structures from the linearized Navier-Stokes equations. J. Fluid Mech. 873, 89-109.

Vadarevu, S. B., Symon, S., Illingworth, S. J. & Marusic, I. (2019). Coherent structures in the linearized impulse response of turbulent channel flow. J. Fluid Mech. 863, 1190-1203.

Oehler, S. F. & Illingworth, S. J. (2018). Sensor and actuator placement trade-offs for a linear model of spatially developing flows. J. Fluid Mech. 854, 34-55.

Illingworth, S. J., Monty, J. P. & Marusic, I. (2018). Estimating large-scale structures in wall turbulence using linear models. J. Fluid Mech. 842, 146-162.

Nardini, M., Illingworth, S. J. & Sandberg, R. D. (2018). Reduced-order modeling and feedback control of a flexible wing at low Reynolds numbers. J. Fluids Structures 79, 137-157