| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Tinga, Tiedo
Netherlands Defence Academy
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (28/28 displayed)
- 2024Corrosion classification through deep learning of electrochemical noise time-frequency transient informationcitations
- 2022Dynamics-based impact identification method for composite structures
- 2020Ultrasonic inline inspection of a cement-based drinking water pipelinecitations
- 2020Effects of powder reuse on the microstructure and mechanical behaviour of Al-Mg-Sc-Zr alloy processed by laser powder bed fusion (LPBF)citations
- 2020Effects of powder reuse on the microstructure and mechanical behaviour of Al-Mg-Sc-Zr alloy processed by laser powder bed fusion (LPBF)citations
- 2020Measuring the spreadability of pre-treated and moisturized powders for laser powder bed fusioncitations
- 2019Revealing the effects of powder reuse for selective laser melting by powder characterizationcitations
- 2019Drying strategies to reduce the formation of hydrogen porosity in Al alloys produced by Additive Manufacturing
- 2019Melt Pool Monitoring for the Laser Powder Bed Fusion Process
- 2019Revealing the Effects of Powder Reuse for Selective Laser Melting by Powder Characterizationcitations
- 2019Towards the development of a hybrid methodology of head checks in railway infrastructure
- 2018Mechanical properties of aluminum alloys produced by Metal Additive Manufacturing
- 2018Utilizing Force-State Mapping for Detecting Fatigue Damage Precursors in Aerospace Applications
- 2018The Detection of Fatigue Damage Accumulation in a Thick Composite Beam Using Acousto Ultrasonics
- 2017Powder Characterization and Optimization for Additive Manufacturing
- 2017Modal strain energy-based structural health monitoring validation on rib stiffened composite panels
- 2016Modal Strain Energy Based Structural Health Monitoring on Rib Stiffened Composite Panels
- 2016Monitoring dynamic stiffness that predicts concrete structure degradation
- 2015Experimental evaluation of vibration-based damage identification methods on a composite aircraft structure with internallymounted piezo diaphragm sensorscitations
- 2014Detection of microbiologically influenced corrosion by electrochemical noise transientscitations
- 2014Aligning PHM, SHM and CBM by understanding the physical system failure behaviour
- 2013The influence of abrasive body dimensions on single asperity wearcitations
- 2013Application of transient analysis using Hilbert spectra of electrochemical noise to the identification of corrosion inhibitioncitations
- 2013Transient analysis through Hilbert spectra of electrochemical noise signals for the identification of localized corrosion of stainless steelcitations
- 2012Investigating the influence of sand particle properties on abrasive wear behaviourcitations
- 2011Application of a multiscale constitutive framework to real gas turbine componentscitations
- 2010Cube slip and non-Schmid effects in single crystal Ni-base superalloyscitations
- 2008Incorporating strain gradient effects in a multiscale constitutive framework for nickel-base superalloyscitations
Places of action
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document
Towards the development of a hybrid methodology of head checks in railway infrastructure
Abstract
In this paper, the first step towards the development of a hybrid methodology for the monitoring of head checks is discussed. The proposed hybrid method combines a data driven approach with physical modelling of the rail in order to obtain an early stage warning for head checks. Rail defect detection at an early stage of the growth can be challenging and the existence of the seed defects can be confused with non-defect objects on the rail. Thus, a physical model is proposed to investigate how head checks, in particular in curved tracks, initiate and evolve. Track characteristics and loading, e.g. track geometry and track tonnage, are considered to analyze crack initiation by using the Whole Life Rail Model (WLRM) for Rolling Contact Fatigue (RCF) relying on meta-models. The results of the physical modelling and the rail defect observations obtained from the data analysis on the eddy current (EC) measurements are then compared. The physics based model only suggests whether a crack will be initiated or not, it does not give information about the size of the crack. Hence, the next step is to develop an evolution model from the EC and Ultrasonic (US) measurements data, from which the crack size can be determined. This combination of physics based and data-driven evolution model is thus regarded as the hybrid method. This hybrid method can be a robust tool for the prediction of rail condition, as it eases the visualization of the rail degradation and keeps infrastructure managers informed of the actual rail condition that can be confirmed with rail inspections. Finally, real-life measurements from a track in the Dutch railway network are used to show the (potential) benefits of the proposed methodology.