Masters student Quentin Duchayne reflects on his internship at UNSW Sydney

Quentin Duchayne, a Masters student at the National Institute of Applied Sciences (INSA) in Toulouse, France, spent 12 weeks at UNSW Sydney working with Dr Shane Keating on the fluid dynamics of cycling. As an avid competitive cyclist, Quentin greatly enjoyed the opportunity to learn more about the aerodynamics of cycling, as well as exploring a new culture in Australia. Here, Quentin reflects on his experience and describes some of his research project.

This internship was an opportunity to go abroad in Australia and live an experience. It was very enriching personally speaking. I needed to go to the unknown to get out of my comfort zone. I have also discovered a new culture and a new way of life. In Australia, there is a different way of looking at things compared to France. It is more optimistic, they enjoy more and complain less. They worry less saying all the time “no worries”.

In the first day of my internship, my tutor and I defined the project I had to realize during the next three months. The subject was part of the fluid mechanics area, especially aerodynamics. More precisely, it was about aerodynamics in cycling. The project was based on air flow modelling around cyclists in a basic 2D model in which cyclists are represented by elliptic shapes. The final objective of this work was to model air flow around a cyclist peloton and analyze the different shapes it could take according to different parameters as the direction and the strength of the wind.

 

Screen Shot 2018-09-23 at 7.21.07 pmModel output showing streamlines flowing around a single rider. Credit: Quentin Duchayne.

 

It is already known that, at racing speed (about 15m/s or 54km/h), the main resistance force for the cyclists is aerodynamic drag (90% of the total resistance). Most previously studies on cycling aerodynamics did research on the drag of a single cyclist but less deal with drag reduction due to drafting, in which two or more cyclists ride close behind each other to reduce aerodynamic drag.

All the previous studies on drafting agree to say that trailing rider benefits a large drag reduction (up to 30-40%). But some papers also demonstrated that leading rider benefits a drag reduction up to 5% due to the presence of trailing riders behind him. The wake of the leading cyclist interacts with the high-pressure area in front of the trailing cyclist and the low-pressure area behind the leading cyclist is “filled up” by the trailing cyclist giving drag reduction for both riders.

In a cyclist group, or peloton, studies have shown that it is the second-last rider who experiences the largest drag reduction. This is explained by the fact that the second-last rider benefits from both drag reduction due to the presence of the rider in front and the presence of a rider in his wake.

 

Screen Shot 2018-09-23 at 7.20.46 pm

Streamlines around a single rider with a side-wind. Credit: Quentin Duchayne.

 

While riders well embedded in the peloton have a large drag reduction, all the cyclists in the peloton experience a drag reduction compared to a single cyclist at the same speed. The leading rider has the largest drag (84% to 96% of that of the isolated rider). For riders sufficiently embedded inside the peloton, the aerodynamic drag can decrease strongly, as little as 10% of the drag experience when cycling alone.

To study drag reduction and drafting in cycling pelotons, I studied simple 2D model of the air flow around cyclists with a Dedalus of package for solving partial differential equations in Python. I did several simulations with one cyclist first and then with several riders, both with a head-wind and a side-wind. The drag forces were computed and a large drag reduction was observed for the trailing riders. It is noticed that the cyclist situated behind the leading rider experience a large drag reduction. The leading rider benefits also a little drag reduction (about 5%). We also showed that the riders behind the leading rider benefit both from being in the wake of the cyclist in front and having riders behind him. These results are consistent with the scientific literature.

 

Movie showing four riders forming a peloton behind the lead rider. Credit: Quentin Duchayne.

In this project, I have put my knowledge of fluid mechanics into practice defining the model. I developed my computing skills. I also had to develop my ability to adapt to work efficiently rapidly. I had to acquire knowledge about the project reading scientific papers and about the Python package. I had to learn new technical notions (learn on the job) like how to do parallel runs and how to use the Dedalus package, the notions of aliasing and simulated annealing.

 

Call for abstracts: Big data in oceanography and meteorology at AMOS-ICTMO 2019

Abstracts are invited for a special session on Big Data in Oceanography and Meteorology at the annual meeting of the Australian Meteorological & Oceanographic Society (AMOS) and the International Conference on Tropical Meteorology and Oceanography (ICTMO), held in Darwin, NT, from 11-15 June 2019.

AMOS-ICTMO 2019 will bring together experts in meteorology, oceanography, climate, and other related sciences from Australia and around the world as well as government representatives, NGOs, businesses and the media to focus on the latest research.

The following special session on big data will be convened by Moninya Roughan, Shane Keating, and Steefan Contractor. Abstracts for oral and poster presentations are to be submitted via the AMOS-ICTMO 2019 submission site. The deadline for submission is Sunday 18 November 2018.

Big Data in Oceanography and Meteorology: Challenges, Applications, and Data Products

Oceanographers and meteorologists are drowning in a tide of data. Data availability has increased steadily in recent years due to the move towards higher resolution modelling and the increase in observations. Observational density has increased because of an increase in frequency of measurements, introduction of new single and multi-instrument datasets and new remote-sensing platforms. As a result, studies of geophysical fluid dynamics are becoming increasingly data driven. In order to derive valuable insights and knowledge from large volumes of data, new methods and techniques are emerging in the field of big data for visualization, analysis, and data dispensation. Vast numbers of datasets are being published and released freely for analysis and sharing.

We invite talks that are broadly related to the field of big data and data products. We encourage presentations on analysis of data from the syntheses of programmes such as IMOS and CMIP5 analyses, projects that deliver products and insights to end users, or that focus on pattern analysis and identification of complex relationships, predictive modelling using supervised and unsupervised algorithms, tools for handling large datasets and for increasing computational efficiency, novel applications of statistical learning and high volume time series analysis, blending of diverse datasets, reproducibility of analysis, inherent structural uncertainties in data, best practices in big datasets and guidance on recommended use for new and existing datasets.

 

Moninya Roughan and MetOcean Solutions awarded $11.5 million NZ Endeavour grant

A new research project led by the NZ MetService’s oceanography division, MetOcean Solutions, will examine the role of ocean circulation on New Zealand’s seafood sector.

The Moana Project was awarded $11.5 million over five years from the NZ Government Endeavour Fund, which invests in scientific research that positively benefits New Zealand’s economy, environment, and society. The proposal was led by MetOcean Solutions’ Chief Scientist Professor and UNSW Associate Professor Moninya Roughan.

“The Tasman Sea is warming at one of the fastest rates on Earth, four times the global average,” said Professor Roughan, “yet we currently have limited ability to comprehensively measure, monitor and predict the state of New Zealand’s oceans. This programme will create a new, dynamic and more integrated marine knowledge base – reducing uncertainty, maximising opportunity and preparing for future ocean changes.”

The Moana Project is a cross-institutional programme involving oceanographic research organisations, universities, and end-users in industry and government across New Zealand. The team will also collaborate with international experts from UNSW Sydney and the United States.

The project will improve understanding of coastal ocean circulation, connectivity and marine heatwaves to provide information that will support sustainable growth of the seafood industry (Māori, fisheries and aquaculture). Project partners will apply the internet of things concept to develop a low-cost ocean temperature profiler that will be deployed by the fishing communities ‘on all boats, at all times’. New Zealand’s first open-access ocean forecast system will be delivered by developing new ocean circulation models using a combination of advanced numerics, modern genomics and data from smart ocean sensors.

The project will investigate the drivers and impacts of marine heatwaves so that they can be predicted, and investigate ocean transport pathways and population connectivity of seafood species. This project will provide a step-change in the oceanic information available to the seafood sector and the broader community, accessible through the open-access user-friendly datasets and tools developed.

Professor Roughan says: “We are partnering with the seafood sector to develop a low-cost ocean sensor that will revolutionise ocean data collection. The sensors will be deployed throughout New Zealand’s exclusive economic zone with support from the commercial fishing sector.”

The Endeavour Fund aims to promote Vision Mātauranga, the New Zealand Government’s science policy framework to unlock the science and innovation potential of Māori knowledge (mātauranga), resources and people for the benefit of all New Zealanders. The Moana Project is anchored in mātauranga Māori through the partners’ relationship with the Whakatōhea Māori Trust Board, facilitating exchange of oceanographic knowledge between Māori and western science.

 

Ocean current velocimetry from ultra-high resolution satellite imagery

Particle image velocimetry (PIV) is a widely used technique for measuring flow velocities by tracking features in sequential images.

In this project, we will test the feasibility of using PIV to estimate ocean currents at the surface of the ocean from satellite images of sea-surface temperature. Knowledge of satellite remote sensing and ocean dynamics is not required, but strong computational ability in Matlab or Python is a must.

This project is supervised by Dr Shane Keating (UNSW Sydney). Please contact s.keating@unsw.edu.au for more information.

Submit your application by Oct 26 2018 for commencement in Term 1, 2019.

Fluid transport by vortex ring entrainment

Vortices are rotating bodies of fluid that remain coherent for long periods, and are frequently observed in the atmosphere, ocean, and in laboratory experiments. Observations and simulations of vortices indicate that they are important for transporting properties such as heat, biological material, or pollutants over large distances.

While some fluid is transported by the core of the vortex, there is also transport due to ambient fluid that is captured or “entrained” within the outer ring and then travels with the vortex as it propagates. In this project, we will examine transport by entrainment of fluid in the vortex ring, or of multiple vortex rings. Experience with Python is required.

This project is supervised by Dr Shane Keating (UNSW Sydney). Please contact s.keating@unsw.edu.au for more information.

Submit your application by Oct 26 2018 for commencement in Term 1, 2019.