13th TWC International Wear Seminar
Tribological Challenges in Industrial Applications
May 24th 2022 at 12:00-16:15 (UTC+2, Finnish time)
Free online webinar
The webinar jointly organized by Tampere Wear Center and PerforMat network is dealing with interactions of tribological contacts and material behavior as well as condition monitoring. The first session is focusing on fretting induced friction, wear, and cracking. The second session is concentrating on condition monitoring of wind turbines as well as its component testing and lubrication. The main speakers are Professor David Nowell, Imperial College London, UK, and Dr Soha Baydoun, Ecole Centrale de Lyon, France.
The webinar is free of charge and arranged on-line (Zoom). The participation link and the recording of the webinar will be sent for the registered participants.
12.00 Opening, Professor Arto Lehtovaara, Tampere University
12.05 The Importance of Friction and Wear in Understanding Interface Behaviour, Professor David Nowell, Imperial College London, UK
12.35 Investigation of fretting wear of a flat-on-flat 34NiCrMo16 interface: Application and modelling of the contact oxygenation concept, Soha Baydoun, Ecole Centrale de Lyon, France
13.05 Role of friction in fretting damage process, Janne Juoksukangas, Tampere University. Read more: Juoksukangas, J., et al. 2020. Avoiding the initial adhesive friction peak in fretting, Wear 460–461:203353, https://doi.org/10.1016/j.wear.2020.203353 (open access)
13.30 Connecting rod dimensioning against fretting, Antti Mäntylä, Wärtsilä
14.30 Opportunities of predictive maintenance in wind power production, Jaakko Kleemola, Hyötytuuli
14.55 Innovative hybrid testing methods for components in wind turbines, Helena Ronkainen, VTT Technical Research Centre of Finland Ltd. Read more: Technological approach – INNTERESTING (innterestingproject.eu)
15.20 Tribofilm evolution in simulated gear contact, Reza Bayat, Tampere University. Read more: Evaluation of Gear Oils Lubrication Performance in a Rolling/Sliding Contact, Tampere University Dissertations 582.
15.45 AI-based condition monitoring of hydraulic pitch system in wind turbines, Panagiotis Korkos, Tampere University
16.10 Ending of the seminar