![Railway Challenge](http://www.peseonline.com/media/qnuea1so/rc-3.jpg)
The 2019 event will see the introduction of a new auto–stop function element to the competition, where participating teams will have to design their locomotive to stop automatically as close as possible to a marked point on the track. Teams will also be required to produce a technical poster to encourage participants to communicate effectively how the principal systems of their locomotive work.
“Introducing an auto-stop element to the competition encourages the next generation of engineers to understand the critical nature of railway safety,” said Professor Simon Iwnicki, chairman of the IMechE Railway Challenge.
![Railway Challenge](http://www.peseonline.com/media/nfohquax/rc-1.jpg)
“It also gives them practical experience in designing a safety critical system. This new part of the competition will give early-career engineers the experience of designing, building and operating a locomotive which can help to prevent accidents.”
The competition, which was launched in 2012, requires participants to design and manufacture a miniature gauge, railway locomotive in accordance with a number of precise rules. Locomotives will be tested at the competition weekend in the summer of 2019, taking place at Stapleford Miniature Railway in Leicestershire. Challenges include a design report and business presentation, as well as track-based challenges on the locomotive’s traction, ride comfort, noise, maintainability and ability to store energy.
Confirmed teams taking part in the Railway Challenge 2019 are:
- University of Huddersfield
- University of Warwick
- FH Aachen University of Applied Sciences & Reuschling, team Emma loves J.I.M
- Transport for London
- Brunel University London, team The Brunelian Express
- Helwan University, team Apene
- Ricardo Rail
- University of Sheffield
- Bombardier Transportation & University of Derby
- SNC-Lavalin & Transit
- Newcastle University
- South Western Railway/ CEMAST
- Poznań University of Technology, team PUTrain
- Network Rail
AI-supported mammography identifies cancer and cuts workload for radiologists
This is great news, for it helps radiologists so much - not only with a long studious day workload, but in allowing them to think about communicating better with colleagues in oncology, and the client...