Tim was the Engineering Lead on the Repoint project. Repoint (Redundantly Engineering Points) aims to build fault tolerance into railway track switching. Current point actuation technology is essentially single point of failure, and when that first failure occurs, trains are stopped until repairs can be made. Repoint aims to improve reliability by including both redundancy, and maintenance by line replaceable unit, in a new point machine system. The current phase of the project is to build on the existing lab demonstrator and develop a full-scale prototype and test this in track and under traffic. Repoint is funded by RSSB and supported by Network Rail and London Underground.
Tim also contributed to In2Rail and S-code, both of which are EU funded programmes, through which Loughborough University is contributing to the development of point machines and railway track switching into the future.
Tim has worked on decarbonisation of rail vehicles. This series of modelling and simulation projects looked at ways to better control trains or advise drivers to reduce fuel consumption and carbon emissions. There are small savings to be made by using reduced acceleration and reduced top speed to arrive on time rather than early. The particular type of train modelled has several diesel engines that often run at below maximum power output. Our work showed that greater emissions reductions can be achieved by shutting down one or more of the engines and running fewer engines at high power rather than using all engines at low power.
More recently Tim has been the Senior Research Associate on a rail vehicle Low Adhesion Detection (LAD) programme. Funded by Network Rail, this project aimed to estimate the friction between the wheel and rail by measuring the difference in the way the vehicle moves about on the rail. Low friction caused by leaves on the line can be a dangerous as stopping distances are significantly increased. Anecdotally, train drivers say they can feel a change in the way the train moves when the rails are slippery. If the drivers can feel a change, then we can measure it. This project put various sensors on a rail vehicle and before running over a section of track with artificially lowered adhesion conditions. Differences in the vehicle movement were detected and these differences have been successfully to estimate the level of adhesion in near real-time. This data can be used to map the problem areas so drivers know where particular care is required and so that treatments can be applied in a more targeted manner.
Tim’s research publications can be found here: http://publications.lboro.ac.uk/publications/all/collated/dstjh.html