Vehicle manufacturers generally have limited knowledge of a vehicle’s life once it leaves them. A service that can predict failures, mechanical problems or damage at the component level, and offer detailed information on these components, would be extremely valuable, saving manufacturers and fleet managers time and money. This service would gather and analyse data from TEXA’s sensors, which could be used to redesign parts and modify maintenance schedules. This type of analysis requires significant computing power.
Alstom is investing huge effort in creating new services for the railway industry and other transportation fields. One of the main areas of investment currently is the development of a diagnostic service to automatically schedule maintenance intervals.
The challenge facing the partners in this experiment was to create mathematical models and develop the necessary software tools to enable simulations of cerebral blood flow in the ophthalmic artery to be performed. The computational requirements of such simulations made it necessary to adapt the software tools to run on an HPC system. The goal was to demonstrate the feasibility and benefits of such simulations to Vittamed and how the necessary computations could be performed via a pay-per-use Cloud-based-HPC solution.