Professor Julio Soria studies turbulence, the key to reducing drag on vehicles, improving the efficiency of wind turbines, and efficiently transporting fluids in pipes.
About Professor Julio Soria
Julio is a researcher who attacks problems both theoretically and experimentally. He started his career as an experimentalist, building the equipment and instrumentation needed to study heat transfer in a transitional boundary layer subjected to surface vibrations. At the same time, he was studying numerical methods, because as he explains: “The idea of doing Direct Numerical Simulations (DNS) of turbulence was only just coming into being in the 1980s. I could see that it would be a fantastic way to get data we couldn’t access experimentally, if we had the computing power to do it.”
After completing his PhD, Julio was awarded a CSIRO postdoctoral fellowship which allowed him to go to Stanford University and NASA Ames Research Centre, where he learned everything he could about the direct numerical simulation of turbulent flows from the pioneers in the field, who also had access to more computing power than was available in Australia at the time.
Since returning to Australia, he has continued to explore and manipulate turbulent flows, both with newer laser-based optical experimental methods and more powerful DNSs.
What drew him to science?
“I loved mathematics,” Julio recalls. “Mathematical analysis was my major interest when I finished school, but I couldn’t see a career path for mathematicians at the time. I decided to study mechanical engineering because I figured I would still be exposed to mathematics, but I might actually get a job at the end of it!”
Julio had never considered a career in research until one of his university professors put the idea into his head as he was finishing his Honours degree. So, he embarked on his PhD research project, and has never looked back.
“I just love research, I love discovery, I love the analysis of the data and connecting the dots. There are beautiful challenges every day.”
Research with supercomputers
Julio’s research is focused on understanding the structure of turbulent flows, particularly the turbulent boundary layer that is in contact with a solid surface – like air against an aeroplane wing, water against a ship hull, or oil against a pipe wall. The turbulent layer accounts for the majority of the drag which is why we need engines and pumps to move things around, burning fuel and emitting carbon dioxide in the process.
The equations that describe the flow of fluids have been known for over 100 years, but turbulence is still today an immature science that lacks fundamental understanding of its complex multi-scale dynamics. “Knowing the equations isn’t enough,” says Julio. “They’re non-linear partial differential equations, with very limited analytical solutions. It is almost impossible to predict flow behaviour from equations without fundamental understanding and correct interpretation of real-world data.”
Turbulent flows need to be resolved on multiple scales – from the big eddies which contain most of the kinetic energy, to the smallest where kinetic energy is converted to internal energy and for all intents and purposes, is lost. And not all of this data can be measured in experiments.
“Experimental methods can’t resolve all of the scales we need to study in turbulent flow,” says Julio. “With DNS we can resolve all the scales of turbulence, and see how they interact and change over time. We can also generate data for quantities that are virtually impossible to measure, such as pressure fluctuations inside the flow.”
Practical, real-world systems have a very large range of scales contained within the turbulent flow, so the computing challenge becomes the limitation. Julio admits: “We’ve used every supercomputer that’s been available to us, because these DNSs take of the order of 50 million CPU hours to do. It’s because it doesn’t give you a ‘solution’; the DNS provides the spatial details of the entire turbulent flow over time, so we can then study the statistics of the structures within it.”
Real world solutions
Using Pawsey, Julio is starting to see the devil in the detail. “The simulations give us the complicated dynamics of these turbulence structures, how they’re created, how they interact, and how they die and get dissipated. No experimental method can give us this data, so now we can ask more relevant questions about the dynamics, and explore how to manipulate these structures using different control strategies to reduce drag or increase lift.”
“Around half of the energy used worldwide to move fluids through pipes and propel cars, trains, ships and planes is dissipated by wall-bounded turbulence. It’s all drag,” says Julio. “So you can see why we want to understand and control it better. Even getting a one per cent reduction in fuel use overcoming drag equates to saving $390 million and 900 million kilograms of carbon dioxide across Australia’s transport system, each year.”