| 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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Reisgen, Uwe
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (18/18 displayed)
- 2024Reduction of distortion during laser beam welding by applying an in situ alloyed LTT effect and considering influencing factors
- 2024Simulation of wire metal transfer in the cold metal transfer (CMT) variant of gas metal arc welding using the smoothed particle hydrodynamics (SPH) approachcitations
- 2024Influence of laser beam welding in vacuum on the magnetic properties of non-grain oriented electrical steel sheets
- 2024Development of an in situ alloying method for high-performance welding processes to achieve an LTT effect by local modification of the alloy content
- 2024Modelling the Evolution of Phases during Laser Beam Welding of Stainless Steel with Low Transformation Temperature Combining Dilatometry Study and FEMcitations
- 2023Optimization of the weldability and joint strength of Al Mg Si cladded aluminum alloys via RSW: a statistical and metallurgical approach
- 2022Residual Stress Reduction with the LTT Effect in Low Carbon Manganese-Steel through Chemical Composition Manipulation Using Dissimilar Filler Material in Laser Beam Weldingcitations
- 2022Strain Monitoring of a Structural Adhesive Bond by Embedding a Polymer Optical Fibercitations
- 2022Curing Adhesives with Woven Fabrics Made of Polymer Optical Fibre and PET Yarncitations
- 2021Individualized and controlled laser beam pretreatment process for adhesive bonding of fiber-reinforced plastics. II. Automatic laser process control by spectrometrycitations
- 2019Manipulating the melt propagation of short arc gas metal arc welding with diode lasers <1 kW for improvement in flexibility and process robustnesscitations
- 2019Influence of variation of energy per unit length on mechanical-technological properties of ultra-high-strength steel 22MnB5 in the laser beam welding processcitations
- 2017Comparison of submerged arc welding process modification influence on thermal strain by in-situ neutron diffractioncitations
- 2016Tensile stress analyses through digital image correlation of single lap joints of high strength steel and aluminium alloy using adhesive bondingcitations
- 2011Theoretische und experimentelle Untersuchung des spaltungsinduzierten Versagens von TRC Prüfkörpern
- 2008Reducing degradation effects in SOFC stacks manufactured at Forschungszentrum Jülich - Approaches and results
- 2005Overview of the development of solid oxide fuel cells at Forschungszentrum Juelich
- 2004Solid oxide fuel cell development at Forschungszentrum Juelich
Places of action
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article
Individualized and controlled laser beam pretreatment process for adhesive bonding of fiber-reinforced plastics. II. Automatic laser process control by spectrometry
Abstract
<jats:p>This paper describes the research conducted on the automation for a UV laser-based surface pretreatment of fiber-reinforced composites in order to improve adhesive bonding conditions. In a preceding process step, a laser-line-triangulation system gathered inline information on a composite part’s surface like topology and location of surface contaminants. These data are the basis for an automation of the laser-based surface treatment [J. Weiland, B. Kunze, H. Dittmar, B. Marx, A. Schiebahn, P. Jaeschke, L. Overmeyer, and U. Reisgen, Proc. Inst. Mech. Eng. Part E: J. Process Mech. Eng. 234, 1–10 (2020)]. The gathered data describe the position of bonding areas and surface contaminants and are converted into relative coordinates of the laser’s scanning field. During the following laser process, the bonding area is ablated to improve adhesive bonding conditions. The process is monitored online by a broad bandwidth spectrometer covering the range of λ = 200–1100 nm to detect changes in the surface composition. If the spectrometer detects signals related to specific surface contaminants during the laser process, the position of the contamination is logged. In this case, only the areas that showed traces of surface contaminations are laser treated again until the spectrometer stops detecting the contaminant signature. This work presents results of two series of experiments. During the first series of experiments, the spectrometer monitored a UV laser process on a carbon fiber reinforced epoxy. The laser processing was performed on a clean and contaminated surface. An industry standard release agent contaminated the plastic surface. The spectrometer detected differences between the clean and contaminated surface that will be used for an automatic process control. In a second series of experiments, the authors performed a processing parameter analysis in order to identify a potential process window for laser-based surface pretreatment for glass-fiber reinforced polyamide 6. Contact angle analysis, surface roughness measurements, peel strength, and shear strength tests were performed. The results show that an inline controlled laser process is robustly able to pretreat composite surfaces based on spectrometric measurements.</jats:p>