Current PhD Projects

Optimisation of water quality parameters to model recirculation aquaculture system (RAS) performance

Supervision Team:

Professor Chris Carter (supervision contact)

Dr Mark Adams

Associate Professor John Purser

Dr David Wright (PanLogica Pty Ltd)

Recirculation Aquaculture Systems (RAS) use recirculation technology to maintain water quality through physical, chemical and biological treatment in order to reduce water exchange and address issues such as biosecurity, production costs and nearness to market. RAS are increasingly important in aquaculture including Atlantic salmon farming ( ; Carter 2015). RAS can be used across the Atlantic salmon life-cycle: eggs and young animals are maintained in freshwater and then transferred to seawater. In Tasmania, the salmon farming industry uses and continues to develop more sophisticated freshwater hatcheries based, however the salmon are then on-grown in the sea. However, the University of Tasmania is building an experimental facility (EAF) that will employ RAS technology for research on large salmon in seawater. IMAS also runs several freshwater RAS.

RAS employ various types of software and models and the aim of this PhD is to understand the characteristics of input and output data required for optimisation software. The optimisation software is provided by PanLogica, a world leading supplier of optimisation software to the global aquaculture industry,  and the student will work with PanLogica and IMAS on both freshwater and seawater RAS production optimisation.    

Project outline, objectives and methods

This research aims to develop an understanding of how to optimise the use of freshwater recirculation systems according to the proprietary optimisation models developed by Panlogica. Research will first focus on collecting and assessing the importance of different model parameters that relate to inputs such as volume of water used, water quality measurements, characteristics of salmon used, fixed costs and running costs. These data will be used to improve the optimisation model, improved versions of the model will be tested and further improvements made (and to reduce the amount of data collected). The last experiment will be designed to test the optimisation model. 

The proposed research will be organised in the following sequence and to complete four experiments (Chapters 2 to 5). The approach and direction of the research is likely to change in relation to information from the first two experiments and to take advantage of any opportunities to work with commercial operations.

Chapter One. Literature review of software and modelling used for RAS. (first publication)

Chapter Two. Data collection and analysis of usefulness for developing optimisation models for freshwater RAS.

Chapter Three. Improved modelling for freshwater RAS based on identification of critical data characteristics.

Chapter Four. Modelling a comparison of two or more different design features for a freshwater RAS.

Chapter Five. Testing software and manipulation of systems. Final benchmarking and independent comparison of predicted against datasets.

Chapter Six. General Discussion

Authorised by the Executive Director, Institute for Marine and Antarctic Studies
November 26, 2015