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STREAM IDC EngD Research Engineer Studentship in Monitoring and Modelling of Bed Filter Conditions, UK

Start Date: 1st October 2014 (contract duration 4 years)

A Research Engineer is sought to work on a novel research project in collaboration between the Pennine Water Group at the University of Sheffield and Hydro International (www.hydro-int.com) as part of the STREAM IDC programme (http://www.stream-idc.net/index.php).

The research project seeks to develop technology to enable Hydro International to understand the physical processes affecting the performance and maintenance requirements in moving bed and fluidised bed filters. This understanding would help to reduce the long term operational requirements for their wastewater/stormwater treatment systems that use filters.

The main focus of the project is to understand the mechanics of moving bed or fluidised bed filters and to develop sensing systems that can detect changes in the physical properties of the filter media. This will require investigation of the filter bed mechanics to determine appropriate media selection and bed geometry for a given design scenario. Establishing maintenance requirements will also include the development of novel low cost instrumentation to evaluate filter bed condition and develop rules for bed regeneration or replacement of the bed. Monitoring may also indicate whether other process such as bed stratification, packing or cracking is occurring and if improved filter designs can alleviate these issues.

The project will involve laboratory experimentation, modelling and the development and evaluation of novel sensors. The successful applicant will be expected to gain knowledge of the application of stormwater technologies to manage environmental pollution and develop a good awareness of commercial aspects of implementing such technologies.

During the study the applicant would be expected to present the results of their work at external conferences and technical meetings and be able to disseminate their work in a range of written formats.

The successful applicant will need a strong engineering/mathematics or physics background. Good analytical and numerical modelling skills are required. Knowledge of numerical methods in engineering, sensor and measurement technologies and signal processing methods would be considered advantageous.

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