Brought to you by
Associate Professor Nicky Eshtiaghi
Innovation:
Design toolkit for sludge pipe
Associate Professor, RMIT University; PhD (Chemical), RMIT University; Fellow of Engineers Australia; Chartered Engineer
Conventional methodologies for sludge pipeline design use water viscosity or over-simplified rheology and flow models.
Methods often involve over-designing when sizing pumps for sludge pipeline systems, but even doubling the required pumping power leads to excessive energy consumption and capital costs.
RMIT Associate Professor Nicky Eshtiaghi FIEAust CPEng’s team has developed an innovative design toolkit to optimise wastewater sludge pipeline systems. This toolkit, which has been validated with Melbourne Water’s sludge pipeline systems, can predict pressure drops to an accuracy of 10 per cent.
The toolkit is capable of fitting rheological models to raw data collected from fl ow curve measurements by implementing the best regression methods that the team developed. It can also predict the rheology of types of sludge by using a fully trained artificial neural network (ANN) model.
This toolkit, which has been validated with Melbourne Water’s sludge pipeline systems, can predict pressure drops to an accuracy of 10 per cent.
Sludge at Melbourne Water is currently pipelined for up to tens of kilometres via large slurry pumps, which typically account for around 27 per cent of total plant energy. At the moment, these sludge pipelines currently operate well below their maximum efficiency. Deviations from the best efficiency point for a pipeline system result in excess power consumption, excess shear stress and temperature rise in the sludge, and interfere with organic processes.
This toolkit allows Australian wastewater treatment plants to optimise existing operations, define the operational limit of current infrastructure to plan, and design and optimise future expansions. This imparts economic and environmental benefits, reduces operational risk and increases productivity.
Judges’ comments:
“The application presents the results of a research agenda into better modelling sludge fl ow through pipes. It is strong on the academic breakthrough of superior modelling. It is clear that the combination of artificial intelligence techniques with the underlying fluid mechanics has led to a better understanding of what is actually happening in the sludge pipes.
“Oversized pumps consume more energy than is required, making the network more expensive both operationally and upfront in capital cost.”