| 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
The Detection of Fatigue Damage Accumulation in a Thick Composite Beam Using Acousto Ultrasonics
Abstract
The Acousto Ultrasonics (AU) technique is a Non-Destructive Testing (NDT) technique, widely used for thin, plate-like composite structures. The application of this technique to thick structures, such as the spar cap of rotor blades of wind turbines is considered promising. A problem for the spar caps is fatigue damage. This paper therefore focusses on the fatigue damage detection in a thick composite beam. Two laboratory specimens with a thickness of 56 mm, width of 60 mm and length of 900 mm are equipped with piezo-electric transducers on the top and bottom surface. Short ultrasonic burst waves with varying actuation frequencies are sent by one transducer and measured with the other transducers. Preliminary tests are executed to assess the damage detection capability. The damage is initially simulated by drilling a hole at one location with a stepwise increasing depth of 10 to 56 mm. The number of actuator-sensor paths crossing the simulated damage increases for increasing hole depth. Various Damage Indicator (DI) algorithms and the Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) are used for damage assessment and visualisation. A correlation between the DI values and the severity and location of the damage is found. This result is a positive indication for the applicability of AU for damage detection in thick composite structures. A second identical beam is currently placed in a three-point bending fatigue setup.