Predicting Gamma Dose Rates from Buried Pipelines based on Limited Information

The PhD project will seek to develop robust algorithms to predict gamma dose rates in contaminated pipelines based on limited direct information. The objective is to minimise and, where possible, avoid intrusive sampling and analysis while still acquiring sufficient information to justify management options (e.g. excavation, capping, leaving in situ) The focus will be on underground discharge pipes, initially at Winfrith, where the algorithms developed will be used to infer the distribution and activity concentrations of selected gamma-emitting isotopes. The results will be compared to currently available proprietary packages.


Gamma spectrometry will be used to measure the surface gamma emission for known sources inside mild steel and cast iron pipes, supplementing work already underway at licensed sites. A complementary experimental validation facility will be developed at UoS using gamma radioisotope sources (137Cs, 60Co) buried in an environmental tank containing soil and underground structures of known geometry. Modelling methods will use Geant4 Monte Carlo to model radiation transport, which will be run on the University’s local HPC cluster with data analysis performed in Matlab or Python. Algorithms will then be used to correct for attenuation from soil, concrete and other underground features to determine the source activities. Their spatial distribution will be estimated using inter alia the Parley method to obtain consensus across a sparse network of surface measurements, combined with triangulation algorithms and data fusion methods applicable to hybrid quantitative and qualitative datasets.

Academic Lead: Caroline Shenton-Taylor
Researcher: Luke Lee-Brewin
Location: University of Surrey