Zero-liquid discharge (ZLD) desalination systems have recently emerged as a promising solution for dealing with water scarcity worldwide. ZLD desalination systems are high-recovery processes that allow the production of valuable freshwater and salt with (near-)zero-waste generation. Thus, ZLD desalination reduces the environmental pollution related to brine disposals in ocean or surface water bodies. Although widely recognised as a sustainable process for improving water supply sources, the implementation of ZLD desalination systems is still limited by their intensive energy consumption and high associated processing costs. Still, since both thermal and electric power used in desalination systems are usually produced from fossil fuel energy sources, the elevated energy consumption related to ZLD systems is also responsible for significant pollutant emissions to the atmosphere. Carbon footprint and other air pollutant releases directly (e.g., thermal sources as steam) or indirectly (e.g., energy from electricity grids) associated with ZLD schemes can be mitigated by developing higher energy efficiency technologies, and incorporating renewable (e.g., solar, wind, and geothermal energy) and low-grade energy sources.
Within this framework, this project is aimed at developing new systematic modelling approaches for the optimisation of renewable-based ZLD desalination systems. The optimisation models will be mainly based on mathematical programming techniques, including deterministic and/or stochastic optimisation. The main objectives include developing useful tools to support the decision-making process towards the implementation of more cost-effective and environment-friendly ZLD desalination systems.
A first degree (at least a 2.1) ideally in Mechanical Engineering or Chemical Engineering with a good fundamental knowledge of thermodynamics and applied mathematics.
English language requirement
IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.
· Experience of fundamental research analysis skills.
· Competent in mathematical modelling in MATLAB.
· Knowledge of fundamental energy transfer processes.
· Good written and oral communication skills
· Strong motivation, with evidence of independent research skills relevant to the project
· Good time management
- Knowledge of mathematical programming in GAMS software.
- Knowledge of life-cycle analysis.
- Experience in using engineering software tools (SimaPro, EES, TRNSYS Professional, or HOMER pro).
- Experience in undertaking independent research. - A completed or near-completition MSc in a relevant subject area.
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