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Convex Optimisation and Robust Control Methods for Improving the Water Quality in Water Supply Networks

Department of Civil & Environmental Engineering

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Dr I Stoianov Applications accepted all year round Funded PhD Project (Students Worldwide)

About the Project

Supervisor Imperial College London: Dr Ivan Stoianov
Co Supervisors Bristol Water: Kevin Henderson (BW) and Frank Van Der Kleij (BW).
Co Supervisor United Utilities: Dr Michele Romano (UU)

One PhD scholarship funded by Bristol Water and United Utilities to investigate and combine advances in water quality sensing, hydraulic and water quality modelling, optimisation and control methods in order to improve the water quality management in water supply networks.

The main objectives include:
1. Investigate the application of tailored optimisation methods for the calibration (e.g. chlorine decay coefficients) of water quality models in operational water supply networks.
2. Study the use of machine learning methods to include the impact of hydraulic dynamics (e.g. through the potential risk of discolouration) on changes in chlorine residual, and do this with experimental data acquired from operational networks. The experimental hydraulic and water quality data is already being acquired by Dr Ivan Stoianov and the industrial partners.
3. Study the impact and optimal design of dynamically adaptive control on water quality (e.g. hydraulic changes due to changes in network connectivity, pressure management and booster chlorination).
4. Implement and demonstrate these methods on a unique large scale case study (e.g. a case study is already operational and managed by Dr Stoianov and Bristol Water).

Academic requirements and experience:
• A good First Class Degree (or International equivalent) in Chemical Process Engineering, Applied Mathematics, Control Engineering, Civil Engineering or a course with strong emphasis on mathematical optimisation, control and systems engineering.
• A Masters level degree qualification in any of these subjects/courses (Applied Mathematics, Chemical Process Engineering, Civil Engineering or a course with strong emphasis on mathematical optimisation, control and systems engineering) will be highly beneficial.
• Solid background in applied mathematics (linear algebra), mathematical optimisation or control engineering.
• Good knowledge of Matlab and/or Python.
• Ideally, some experience in systems engineering/civil engineering.

A lack of experience in the above experience and skills could be compensated by evidence of research potential. Appropriate training will be provided.

How to apply:
Applicants wishing to be considered for these opportunities should send the following application documents to Ivan Stoianov ([Email Address Removed])
1. Current CV including details of their academic record
2. Covering letter making explaining their motivation and suitability
3. Contact details of two academic referees
Application via the Imperial College Registry is not necessary at this stage.

Applications will be accepted until a suitable PhD candidate is appointed.

Funding Notes

The studentship will provide funding for 3 years including tuition fees and a tax-free stipend at the standard UKRI London rate, ~ £17,285 for the 2020/21 academic year. In addition, allowance is provided for research consumables and conference attendance.

Full funding is available to Home and EU students. The funding can also be used to partly support an international student.
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