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Daniel graduated from The University of Melbourne with a BE (Mechatronics) / BCS in 2003, and then went on to complete his PhD (Aeronautics) at the California Institute of Technology in 2009. Then he was a postdoctoral scholar researching climate physics at the NASA Jet Propulsion Laboratory before joining the department as Lecturer in 2012.

Research interests

Daniel is interested in interdisciplinary research centred around fluid mechanics, including large-eddy simulation and modelling, direct numerical simulation, wall-bounded turbulence (especially over roughness), turbulent convection and planetary boundary layers. Daniel's research is fundamental in nature, aimed at developing and improving the predictive tools used in engineering and meteorology.

Turbulence is prevalent in engineering and nature but despite a century of research, the prediction of turbulent flows remains a challenge. Advances at the fundamental level are therefore necessary and, towards this end, Daniel's research distils the complexity of turbulent flows into simple yet essential configurations that, aided by simulation and modelling, yield insights into the inner workings of turbulence.

Open positions

Present members

Michael Xie

PhD 2018–: Turbulent flow over surfaces with spatially varying roughness.

Davide Modesti

Postdoc 2018–: Tailoring aircraft surface textures to minimise drag.

Sebastian Endrikat

PhD 2017–: Tailoring aircraft surface textures to minimise drag.

Amirreza Rouhi

Postdoc 2017–: Turbulent flow over surfaces with spatially varying roughness.
Spatially varying roughness

Past members

Melissa Kozul

PhD 2014–2018: The turbulent boundary layer studied using novel numerical frameworks.
Temporal boundary layer

Present: Norwegian University of Science and Technology (NTNU)

Michael MacDonald

PhD 2013–2017: Numerical simulation of turbulent flows over rough surfaces. PhD thesis
Dense roughness

Postdoc 2017: Tailoring aircraft surface textures to minimise drag.

Present: NASA Jet Propulsion Laboratory

Chong Shen Ng

MPhil 2012–2013: Direct numerical simulation of turbulent natural convection bounded by differentially heated vertical walls. MPhil thesis
Vertical natural convection

PhD 2014–2017: Boundary layer and bulk dynamics in vertical natural convection. PhD thesis
Neat-wall temperature

Present: University of Twente

Refereed journal articles

Refereed conference papers



Open positions

Potential PhD students who are interested in the projects below can email Daniel at daniel.chung@unimelb.edu.au with a cover letter, CV and two academic references. The PhD student will have an undergraduate degree in areas related to fluid mechanics such as aeronautical engineering, mechanical engineering, mathematics or physics. The PhD student will have a strong interest in fundamental fluid mechanics.

"The purpose of computing is insight, not numbers." R. W. Hamming

Tailoring aircraft surface textures to minimise drag (PhD student)

Turbulent skin friction drag, occurring whenever a fluid such as air or water flows over a surface at high speeds, dictates the energy expenditure of many important engineering systems. For example, over 50% of the drag on a commercial aircraft is due to skin friction. This means that a large proportion of the fuel expended and emissions produced in this case are directly attributable to skin friction drag.

Riblets (figure 1), a microscale surface texture modelled after shark skin, are an emergent technology designed to reduce the skin friction drag of aircraft. Efforts to optimise riblets have, to date, been stymied by the prohibitive cost and long turnaround times of experiments and simulations. The situation is compounded by an incomplete understanding of the underlying flow physics.

Recently, however, researchers at the University of Melbourne and their collaborators have made major breakthroughs in overcoming these obstacles. In particular, a novel simulation method for determining the drag of complex surface topologies with fast turnaround times has been developed and the flow mechanism that currently limits the drag-reducing capacity of riblets has been identified.

This project will build on these breakthroughs to develop, for the first time, a physics-informed virtual rapid prototyping framework that places the problem of riblet optimisation firmly within grasp. The outcomes of this project will be 1) the discovery of new optimised riblet geometries and 2) the advancement of turbulent drag-reduction physics.

Turbulent flow over surfaces with spatially varying roughness (PhD student)

Rough-wall turbulent boundary layers are formed where fluid flows over non-smooth surfaces. These flows profoundly influence our daily lives. Examples include: wind blowing over the Earth's surface, water flowing through a fouled pipe, and aircraft, ships and submarines in motion through the atmosphere or ocean. Though engineers, meteorologists, climate modellers and atmospheric scientists have developed models for evenly distributed roughness, such an idealised configuration is rarely encountered in practise. Rather, the large majority of boundary layer flows are characterised by abrupt changes in roughness, for example at the edges of forests or wind-farms, crop boundaries, land-water interfaces, coral reefs, localised patches of bio-fouling on a ship's hull or at rivets on aircraft (figure 2). In these cases, the common set of empirically based rules that are applied so widely for evenly distributed roughness offer little insight into the complex physics of heterogeneous roughness.

The current socio-economic climate demands that these flows be predicted with ever increasing accuracy: climate and meteorological models should faithfully predict the influence of changes in surface topology; drag and fuel consumption predictions for aircraft should accurately take into account the influence of roughness heterogeneity; and gas turbine and wind turbine operators must be capable of predicting the performance degradation in the presence of turbine fouling.

This project will adopt a unified approach that exploits a combination of unique state-of-the-art experimental facilities, high fidelity measurement techniques and novel high resolution numerical simulations to study the influence of heterogeneous roughness on wall bounded turbulent flows. The computational component of this project will provide an unprecedented access not only to the mean velocity but also to the turbulent statistics in the vicinity of roughness transitions. This information will improve our understanding and predictive capability of turbulent flows over heterogeneous roughness.