Research students - Infrastructure Monitoring

• PhD Student: Omotayo Farai
• Supervisors: Dr Nicole Metje, Prof David Chapman, Dr Carl Anthony
• Duration: 2015-2018

The UK has a vast network of utility and local authority infrastructure buried beneath highways and footways in the UK. The combined network of water, sewer, gas and electricity services extends to over 1.5 million km. Most of these buried assets are ‘dumb’ and have little sensing capabilities. However, increasingly discrete sensors are developed to monitor the condition of the asset or its content. Most of these rely on electromagnetic signal transmission which is hampered by the soil and the water within it to such an extent that transmission can be in the worst case only a few cm. Alternative signal transmission using acoustic signals are investigated as part of this project with the aim to achieve several 10s of metres.

• PhD Student: Guanyu Wang
• Supervisors: Dr Michael Burrow & Dr G Ghataora
• Duration: 2015-2018

The periodic assessment of road condition is a vital aspect of road asset management in that it aids the selection of appropriate and timely road maintenance.  Road condition is a major contributor to road use costs.  Poor road condition affects fuel consumption, vehicle maintenance, journey time and accident costs.  The comprehensive assessment of road condition periodically requires a number of parameters to be collected including ride quality (or road roughness), surface distress (cracking), surface friction (skid resistance) and structural performance (deflection).  These parameters however are expensive and time consuming to collect at sufficient accuracy to support road asset management of large road networks.  A number of commercially available computer applications that claim to be able to assess various measures of road condition when used with smart phones fitted to moving vehicle.  These include the identification of discrete road defects (such as potholes) and the roughness of entire road sections. However, the accuracy, repeatability and reproducibility of these tools are unknown.

The aim of this research project is to investigate, whether and how, road condition data collected using smart phone technology may be incorporated within a comprehensive decision support system that facilitates the asset management of road networks and provides road users with information to inform journey costs.

• PhD Student: Anna Faroqy
• Supervisors: Prof David Chapman, Dr Alexander Royal, Dr Giulio Curioni
• Duration: 2014-2017

Electrical Resistivity (ER) and Time Domain Reflectometry (TDR) are geophysical tools that can be used for spatial and temporal ground data collection. Both techniques have been independently tested in geotechnical applications and recognised mainly for their clear response to ground water changes. Given that water is a major factor affecting the geotechnical properties of soils, there has been ongoing research into translating geoelectrical responses into geotechnical proprieties. Interpreting geophysical data, however, is often very problematic due to the variable nature and conditions of the soil. Nonetheless, calibrating ER and TDR to a specific soil has been found to provide more informative results, making these techniques a promising monitoring method that could advance the understanding of the behaviour of soils in-situ.

Although complementing ER, which provides good spatial coverage, with point measurements from TDR can enhance ground data interpretation, research on simultaneous application of both methods is very limited. Therefore, the aim of this research is to combine ER and TDR tests to enhance the translation of soil electromagnetic responses into geotechnical property changes. This will be achieved through controlled laboratory experiments on selected fine-grained soils during 1D consolidation, incorporating both ER and TDR measurements.