| 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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Sonne, Mads S.
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (19/19 displayed)
- 2020Thermo-chemical-mechanical simulation of low temperature nitriding of austenitic stainless steel; inverse modelling of surface reaction ratescitations
- 2019A Characterization Study Relating Cross-Sectional Distribution of Fiber Volume Fraction and Permeability
- 2019Numerical Modelling of Heat Transfer using the 3D-ADI-DG Method - with Application for Pultrusion.
- 2019Fiber segmentation from 3D X-ray computed tomography of composites with continuous textured glass fibre yarns
- 2018Multiphysics modelling of manufacturing processes: A reviewcitations
- 2018Numerical Modelling of Mechanical Anisotropy during Low Temperature Nitriding of Stainless Steel
- 2018Uncovering the local inelastic interactions during manufacture of ductile cast iron: How the substructure of the graphite particles can induce residual stress concentrations in the matrixcitations
- 2018Thermomechanical Modelling of Direct-Drive Friction Welding Applying a Thermal Pseudo Mechanical Model for the Generation of Heatcitations
- 2017A FEM based methodology to simulate multiple crack propagation in friction stir weldscitations
- 2017Integrated Computational Modelling of Thermochemical Surface Engineering of Stainless Steel
- 2016Improvement in Surface Characterisitcs of Polymers for Subsequent Electroless Plating Using Liquid Assisted Laser Processingcitations
- 2016Free-form nanostructured tools for plastic injection moulding
- 2016Determination of stamp deformation during imprinting on semi-spherical surfaces
- 2016Multiple Crack Growth Prediction in AA2024-T3 Friction Stir Welded Joints, Including Manufacturing Effectscitations
- 2015Defining Allowable Physical Property Variations for High Accurate Measurements on Polymer Parts.citations
- 2015Modelling residual stresses in friction stir welding of Al alloys - a review of possibilities and future trendscitations
- 2015Comparison of residual stresses in sand- and chill casting of ductile cast iron wind turbine main shaftscitations
- 2015Modelling the residual stresses and microstructural evolution in Friction Stir Welding of AA2024-T3 including the Wagner-Kampmann precipitation model
- 2013The effect of hardening laws and thermal softening on modeling residual stresses in FSW of aluminum alloy 2024-T3citations
Places of action
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document
Defining Allowable Physical Property Variations for High Accurate Measurements on Polymer Parts.
Abstract
Measurement conditions and material properties have a significant impact on the dimensions of a part, especially for polymers parts. Temperature variation causes part deformations that increase the uncertainty of the measurement process. Current industrial tolerances of a few micrometres demand high accurate measurements in non-controlled ambient. Most of polymer parts are manufactured by injection moulding and their inspection is carried out after stabilization, around 200 hours. The overall goal of this work is to reach ±5μm in uncertainty measurements a polymer products which is a challenge in today‘s production and metrology environments. The residual deformations in polymer products at room temperature after injection molding are important when micrometer accuracy needs to be achieved. Numerical modelling can give a valuable insight to what is happening in the polymer during cooling down after injection molding. In order to obtain accurate simulations, accurate inputs to the model are crucial. In reality however, the material and physical properties will have some variations. Although these variations may be small, they can act as a source of uncertainty for the measurement. In this paper, we investigated how big the variation in material and physical properties are allowed in order to reach the 5 μm target on the uncertainty.