Co Supervisor United Utilities: Dr Michele Romano (UU)
Co Supervisors Bristol Water: Kevin Henderson (BW) and Frank Van Der Kleij (BW).
One PhD scholarship funded by United Utilities and Bristol Water to investigate and combine advances in hydraulic and water quality sensing, hydraulic control and optimisation methods within the framework of dynamically adaptive networks, which have been developed at Imperial College, in order to:
1. Investigate the impact of dynamically adaptive networks on water quality.
2. Derive optimisation (control) approaches for improving the water quality in water distribution networks (DMAs) with the implementation of dynamically adaptive control.
The advanced control capabilities of dynamically adaptive networks will be utilised to manage the residual chlorine in complex water distribution networks with advanced hydraulic control; and, maximise the self-cleaning capacity of drinking water distribution systems by controlling hydraulic variables such as residence time, flow reversals and dynamic hydraulic conditions.
Project details: The main objectives for this project are as follows:
1. Review the state of the art methods for modelling the chlorine decay and efficiently calibrating chlorine decay models in water supply networks. Implement a mathematical water quality model (e.g. a model with first order reactions for chlorine decay both in the bulk flow and at the pipe walls), which is used in the optimisation framework.
2. In addition, review hydraulic pathways for discolouration (e.g. flow velocity variations, etc) in water distribution networks as resuspended sediments affect the chlorine decay and residual chlorine concentration.
3. Develop and apply a mathematical optimisation framework for the calibration of chlorine decay models, as a reliable chlorine decay model underpins the analyses listed in Task#2. Consider methods for data reconciliation to support model calibration and continuous model validation (e.g. data from permanent WQ sensors in water supply networks plus the addition of grab samples).
4. Investigate how to include the impact of hydraulic dynamics and the potential risk of discolouration on changes in chlorine residual, and do this within the developed optimisation framework and with experimental data acquired from operational networks. The experimental hydraulic and water quality data is already been acquired by Dr Ivan Stoianov and the industrial partners.
5. Analyse the extent to which dynamically adaptive control for improving networks resilience and pressure management could have an impact on the spatial and temporal variations in residual chlorine; and consider, whether and how dynamically adaptive control can be effectively utilised to avoid and reduce such variations. Investigate how the water quality management should be included in the design and control of dynamically adaptive networks.
The project is part of a broader research programme on Dynamically Adaptive Networks led by Dr Ivan Stoianov. The PhD student will join the InfraSense Labs research group, which currently has 4 PhD students and 3 PDRA (Post-Doctoral Research Associates).
Academic requirements and experience:
• A good First Class Degree (or International equivalent) Chemical Process Engineering, Applied Mathematics, 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 protected])
– Current CV including details of their academic record
– Covering letter making explaining their motivation and suitability
– Contact details of two academic referees
Application via the Imperial College Registry is not necessary at this stage.
The closing date for applications is the 30th March 2020. However, applications will continue to be accepted until the position is filled.
The studentship will provide funding for 3 years including tuition fees and a tax-free stipend at the standard UKRI London rate, ~ £17,000 for the 2019/20 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.