| 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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Devesse, Wim
Vrije Universiteit Brussel
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (14/14 displayed)
- 2020Spatial distributed spectroscopic monitoring of melt pool and vapor plume during the laser metal deposition processcitations
- 2020Comparison of visual and hyperspectral monitoring of the melt pool during Laser Metal Deposition
- 2019Hyperspectral and Thermal Temperature Estimation During Laser Claddingcitations
- 2017Proof of Concept of Integrated Load Measurement in 3D Printed Structurescitations
- 2017Model-based temperature feedback control of laser cladding using high-resolution hyperspectral imagingcitations
- 2017Fatigue Performance of Ti-6Al-4V Additively Manufactured Specimens with Integrated Capillaries of an Embedded Structural Health Monitoring Systemcitations
- 2016Hardware-in-the-loop control of additive manufacturing processes using temperature feedbackcitations
- 2016Spectroscopic monitoring and melt pool temperature estimation during the laser metal deposition processcitations
- 2016Evaluation of the Diffuse Reflectivity Behaviour of the Melt Pool During the Laser Metal Deposition Process
- 2016Temperature Feedback Control of Laser Cladding Using High Resolution Hyperspectral Imaging
- 2015Modeling of laser beam and powder flow interaction in laser cladding using ray-tracingcitations
- 2015Hardware-in-the-loop control of additive manufacturing processes using temperature feedback
- 2015Spectroscopic monitoring and melt pool temperature estimation during the laser metal deposition process
- 2014Modeling of laser beam and powder flow interaction in laser cladding using ray-tracing
Places of action
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article
Proof of Concept of Integrated Load Measurement in 3D Printed Structures
Abstract
Currently, research on structural health monitoring systems is focused on direct integration of the system into a component or structure. The latter results in a so-called smart structure. One example of a smart structure is a component with integrated strain sensing for continuous load monitoring. Additive manufacturing, or 3D printing, now also enables such integration of functions inside components. As a proof-of-concept, the Fused Deposition Modeling (FDM) technique was used to integrate a strain sensing element inside polymer (ABS) tensile test samples. The strain sensing element consisted of a closed capillary filled with a fluid and connected to an externally mounted pressure sensor. The volumetric deformation of the integrated capillary resulted in pressure changes in the fluid. The obtained pressure measurements during tensile testing are reported in this paper and compared to state-of-the-art extensometer measurements. The sensitivity of the 3D printed pressure-based strain sensor is primarily a function of the compressibility of the capillary fluid. Air- and watertightness are of critical importance for the proper functioning of the 3D printed pressure-based strain sensor. Therefore, the best after-treatment procedure was selected on basis of a comparative analysis. The obtained pressure measurements are linear with respect to the extensometer readings, and the uncertainty on the strain measurement of a capillary filled with water (incompressible fluid) is ±3.1 µstrain, which is approximately three times less sensitive than conventional strain gauges (±1 µstrain), but 32 times more sensitive than the same sensor based on air (compressible fluid) (±101 µstrain).