
Trustworthy and insightful algorithms for industrial decision making
This research project will use state-of-the-art optimisation technologies in the form of mathematical models and algorithms to find optimal solutions for industry
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This joint PhD project is based at the Shanghai Jiao Tong University with a minimum 12-month stay at The University of Melbourne.
The main objectives of this project are to:
Project description:
Ammonia is attracting great interest as a carbon-free fuel and as a carrier for hydrogen energy. Ammonia offers many comparative advantages in these roles, including the high content of hydrogen (which is higher than liquid hydrogen on a volume basis), mature manufacturing technology, widely available infrastructure, and most importantly, its carbon-free nature which makes it one of the most promising fuels to decarbonise transport energy.
Ammonia can be potentially used in both spark-ignition (gasoline) and compression ignition (diesel) engines. Ammonia has an extremely low oxidation reactivity and so is suitable for a dual-fuel application which has been commonly used in compressed natural gas engines.
In these engines, the low reactivity fuel (natural gas or ammonia) is introduced into the cylinder during the intake stroke, compressed to a high temperature and pressure, and ignited by a pilot diesel fuel injected near the end of the compression stroke. This ignition process is highly complex and critically relies on the autoignition of the pilot fuel in a highly stratified thermal and compositional field. The process has a profound impact on subsequent combustion processes and overall engine performance.
The key research question in this project is to determine how the stratified temperature and composition field affects the autoignition of diesel-ammonia mixtures in the dual-fuel combustion environment.
This research will be complemented by the project on 'Decarbonizing future transport with ammonia-fueled engines' and the collaboration will ensure the successful completion of both projects.
Professor Xingcai Lu, Associate Professor Dong Han (Shanghai Jiao Tong University)
Associate Professor Yi Yang, Professor Michael Brear (The University of Melbourne)
This research project will use state-of-the-art optimisation technologies in the form of mathematical models and algorithms to find optimal solutions for industry
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