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Research Thesis Topic

Optimizing Biofuel as Renewable Energy by Modelling Photosynthetic Active Radiation with Artificial Intelligence


Topic ID
326

Thesis Topic/Title
Optimizing Biofuel as Renewable Energy by Modelling Photosynthetic Active Radiation with Artificial Intelligence

Description

Biofuels, as a renewable energy is clean and environmentally friendly. Global advocacy for climate change mitigation aims to minimize fossils fuel usage to support cleaner energy. While alternative energies (e.g., biofuels) extracted from feedstock (e.g., micro-algae), represent a promising role, their production requires reliably modelled Photosynthetically-Active Radiation (PAR). PAR models predict energy parameters (e.g. algal carbon fixation) to aid in decision-making at PAR sites

Critical to the biosphere is the PAR (400 = PAR = 700) nm utilised by microcellular organisms to develop chemical constituents that are the building blocks of marine and terrestrial food webs that in turn, regulate and sustain biomass production systems. Subsequently, the availability of PAR affects crop yield, biodiversity and ecosystems and CO2, water and energy control in plant-atmospheric systems through the carbon cycle. PAR predictions are important in biofuel-based renewable energy systems.

Biofuels provide 46 EJ of bioenergy globally, and drive a source of food, fodder and fibre, and hydrocarbons used for heat, electricity, liquid fuels and chemicals. Future knowledge of PAR is crucial to support increasing demand for sustainable energy, supporting agriculture, biological functions of plants and other bio-physical applications.

In this project, the students will utilise models to predict photosynthetically active radiation where ground based measured and satellite datasets are used. Artificial intelligence algorithms will be applied to simulate PAR and the predictive models will be improved by application of several, mathematical and statistical tools.

The project is suitable for students interested in renewable energy, engineering, biology, agriculture, atmospheric science, mathematics, physics and data science. The project is scalable for further research, such as to a Masters or a PhD program to advance research careers, acquire programming skills and modelling. The project present opportunity to develop new modelling & computational skills and research-publications within the Environmental Modelling and Simulation Research Group.


Principal Supervisor

Associate Supervisors

Research Affiliations
  • Institute for Agriculture and the Environment
  • International Centre for Applied Climate Sciences
  • School of Agricultural, Computational and Environmental Sciences

Field of Research
  • Agricultural Biotechnology
  • Agriculture, Land and Farm Management
  • Atmospheric Sciences
  • Ecological Applications
  • Environmental Biotechnology
  • Environmental Science and Management
  • Forestry Sciences
  • Other Agricultural and Veterinary Sciences
  • Other Biological Sciences
  • Other Environmental Sciences


Application Open Date
11/02/2018

Application Close Date
31/12/2019

USQ Scholarship Applications

Other Scholarship Funding Details
Australia Awards (Country-Specific Closing Dates), and Australian Endeavor Scholarships (Close June 2018)

Pre-approved for Ethics
Not Applicable

Admission Requirements

Please review the admission requirements for the academic program associated with this Thesis Topic

The project is suitable for students interested in renewable energy, engineering, biology, agriculture, atmospheric science, mathematics, physics and data science. The project is scalable for further research, such as to a Masters or a PhD program to advance research careers, acquire programming skills and modelling. The project present opportunity to develop new modelling & computational skills and research-publications within the Environmental Modelling and Simulation Research Group.




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