Dr. Cyprien Hoelzl

Dr.  Cyprien Hoelzl

Dr. Cyprien Hoelzl

Staff of Professorship for Structural Mechanics and Monitoring

ETH Zürich

Strukturmechanik und Monitoring

HIL E 21.1

Stefano-Franscini-Platz 5

8093 Zürich

Switzerland

Short Bio

Cyprien conducted his master thesis with the SMM group in 2018, on the topic of data driven assessment of the railway track substructure. This work resulted in an actionable framework that enhanced the predictive maintenance system used by the Swiss Federal Railways (SBB).
Following his diploma in Civil Engineering, Cyprien joined the Chair of Structural Mechanics and Monintoring (SMM) at ETH Zurich in 2019 as a PhD Student, working on the OMISM project, on the topic of On board Monitoring for Integrated Systems Understanding & Management Improvement in Railways. 
This project is part of the “Future Mobility Research Program”, and is jointly led by Prof Dr. Eleni Chatzi and Prof. Dr. Francesco Corman under support of the SBB.

Research 

Cyprien's current research activities include modelling the dynamic interaction between railway vehicle and track and the development of acceleration based health indicators pertaining the state of the railway infrastructure.The increasing demands in mobility forms a major challenge for railway infrastructure. The increased traffic frequency and axle loads impose higher capacity demands and lead to more frequent damage, more severe deterioration and associated disruptions to service and availability. Infrastructure operators require timely information regarding the current (diagnosis) and future (prognosis) condition of their assets, in order to sensibly decide on maintenance and renewal actions. Railway condition assessment has traditionally heavily relied on on-site visual inspections. In more recent years, diagnostic vehicles with accurate, albeit complex, measurement systems have been increasingly deployed. These vehicles offer an automated means for relaying essential information on condition, via diverse measurements including vibration, image and sometimes ultra-sonic information. More recently, On-Board Monitoring (OBM) vehicles equipped with low-cost measuring devices, such as accelerometers, have been introduced on railroad networks, traversing the network at a higher frequency than the specialized diagnostic vehicles. The collected information consists of position, acceleration and in some cases force measurements. The measured data requires interpretation into quantifiable track-quality indicators, before it can be meaningfully incorporated in asset management tools. These indicators form the basis for real-time forecasting of condition evolution and asset management. Cyprien's work focuses on the use of data-driven and model-assisted methods for derivation of such OBM-based indicators.

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