| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Mesnil, Olivier
Luxembourg Institute of Science and Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (18/18 displayed)
- 2024A Hybrid Actuator Model for Efficient Guided Wave-Based Structural Health Monitoring Simulations
- 2023Self-referenced robust guided wave based defect detection: application to woven composite parts of complex shapecitations
- 2023Lead Zirconate Titanate Transducers Embedded in Composite Laminates: The Influence of the Integration Method on Ultrasound Transduction ; Transducteur PZT intégré dans un composite stratifié : influence de la méthode d'intégration sur la transduction ultrasonorecitations
- 2023Lead Zirconate Titanate Transducers Embedded in Composite Laminates: The Influence of the Integration Method on Ultrasound Transductioncitations
- 2023Detection of barely visible impact damage in composite plates using non-linear pump-probe technique
- 2023Experimental and Numerical Study of Lamb Waves Generation Efficiency by Lead Zirconate Titanate Transducers Embedded in a Composite Laminate
- 2022Optimization of a Structural Health Monitoring systems integration in laminated composite cured in autoclavecitations
- 2022Experimental and Numerical Study of Lamb Waves Generation Efficiency by Lead Zirconate Titanate Transducers Embedded in a Composite Laminate
- 2021Damage quantification in an aluminium-CFRP composite structure using guided wave wavenumber mapping : Comparison of instantaneous and local wavenumber analyses
- 2021Characterization of Guided Wave Propagation in Woven Composites of Varying Geometry
- 2021Experimental validation of transient spectral finite element simulation tools dedicated to guided wave based structural health monitoringcitations
- 2019Machine-learning based temperature compensation for Guided Wave Imaging in Structural Health Monitoring
- 2019Defect sizing using convolution neural network applied to guided wave imagingcitations
- 2019Guided wave imaging of a composite plate using passive acquisitons by Fiber Bragg Gratings on optical fibers
- 2018Defect imaging in layered composite plates and honeycomb sandwich structures using sparse piezoelectric transducers networkcitations
- 2018Experimental determination of 3D Green's function in composite plates for defect imaging using guided waves
- 2017Defect imaging on CFRP and honeycomb composite structures by guided waves generated and detected by a sparse PZT arraycitations
- 2016Sparse wavefield reconstruction and source detection using Compressed Sensingwavefield reconstruction and source detection using Compressed Sensingcitations
Places of action
| Organizations | Location | People |
|---|
article
Experimental validation of transient spectral finite element simulation tools dedicated to guided wave based structural health monitoring
Abstract
International audience ; In guided wave structural health monitoring (GW-SHM), a strong need for reliable and fast simulation tools has been expressed throughout the literature to optimize SHM systems or demonstrate performance. Even though guided wave simulations can be conducted with most finite elements software packages, computational and hardware costs are always prohibitive for large simulation campaigns. A novel SHM module has been recently added to the civa software and relies on unassembled high-order finite elements to overcome these limitations. This article focuses on the thorough validation of civa for SHM to identify the limits of the models. After introducing the key elements of the civa SHM solution, a first validation is presented on a stainless steel pipe representative of the oil and gas industry. Second, validation is conducted on a composite panel with and without stiffener representative of some structures in the aerospace industry. Results show a good match between the experimental and simulated datasets, but only if the input parameters are fully determined before the simulations.