| 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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Mocellin, Katia
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (55/55 displayed)
- 2022Influence of mechanical characterization on the prediction of necking issues during sheet flow forming processcitations
- 2022FEM Modelling of Weld Damage in Continuous Cold Rolling of MIG/MAG Butt-Welded Stainless Steel Stripscitations
- 2022FEM Modelling of Weld Damage in Continuous Cold Rolling of MIG/MAG Butt-Welded Stainless Steel Stripscitations
- 2022Numerical analysis of a backward flow forming operation of AA6061-T6 and comparison with experimentscitations
- 2022Identifying Heterogeneous Friction Coefficients on the Hot Forming Tools in Mannesmann Cross-Roll Piercingcitations
- 2021Numerical assessment of large hexagonal seamless steel tube extrusion feasibilitycitations
- 2019Numerical analysis of the complex loading path during tube flow forming processes
- 2018Hybrid parallel multigrid preconditioner based on automatic mesh coarsening for 3D metal forming simulationscitations
- 2018Modelling the strength of an aluminium-steel nailed jointcitations
- 2018New numerical approach for the modelling of machining applied to aeronautical structural parts
- 2017In-situ creep law determination for modeling Spark Plasma Sintering of TiAl 48-2-2 powdercitations
- 2017Linear Friction Welding of Aeronautical alloys Modeling and Numerical Simulation
- 2017Quantitative analysis of galling in cold forging of a commercial Al-Mg-Si alloycitations
- 2017Quantitative analysis of galling in cold forging of a commercial Al-Mg-Si alloycitations
- 2017In-situ Experiments to Determine the Creep Law Describing the SPS Densification of a TiAl Powder
- 2017Numerical modeling of electrical upsetting manufacturing processes based on Forge® environmentcitations
- 2017Numerical modeling of electrical upsetting manufacturing processes based on Forge® environmentcitations
- 2017Numerical simulation of linear friction welding of aeronautical alloyscitations
- 2017Numerical methods for linear friction welding simulation of aeronautical alloys
- 2017A Numerical Tool to Master the SPS Densification of TiAl Complex Shapes
- 2016Numerical modelling of ODS steel tube cold pilgered by HPTR. Focus on experimental measurements and simulation of residual stress.
- 2016Numerische Vorhersage der während der Zerspanung von großen luftfahrttechnischen Aluminiumbauteilen auftretenden Verzüge ; Numerical prediction of distortions during machining of large aluminium aeronautical partscitations
- 2016Numerische Vorhersage der während der Zerspanung von großen luftfahrttechnischen Aluminiumbauteilen auftretenden Verzügecitations
- 2016Numerical Modeling of Tube Forming by HPTR Cold Pilgering Processcitations
- 2016Numerical Modeling of Tube Forming by HPTR Cold Pilgering Processcitations
- 2016Influence of the machining sequence on the residual stress redistribution and machining quality: analysis and improvement using numerical simulationscitations
- 2015Numerical Modeling of Fuel Rod Resistance Butt Weldingcitations
- 2015Numerical prediction of distorsions during machining of large aluminum aeronautical parts
- 2014Experimental and Numerical Analysis of Electrical Contact Crimping to Predict Mechanical Strengthcitations
- 2013Numerical Modeling of Fuel Rod Resistance Butt Weldingcitations
- 2013Non standard samples behaviour law parameters determination by inverse analysis
- 2013Development of Adapted Material Testing for Cold Pilgering Process of ODS Tubescitations
- 2013Development of Adapted Material Testing for Cold Pilgering Process of ODS Tubescitations
- 2013Numerical Study of a Crimped Assembly Mechanical Strengthcitations
- 2012Finite element simulation of cold pilgering of ODS tubes
- 2012Finite element simulation of cold pilgering of ODS tubes
- 2012Optimization of the Fabrication Route of Ferritic/Martensitic ODS Cladding Tubes: Metallurgical Approach and Pilgering Numerical Modeling
- 2012A simple approach for the modeling of an ODS steel mechanical behavior in pilgering conditionscitations
- 2012A simple approach for the modeling of an ODS steel mechanical behavior in pilgering conditionscitations
- 2011Modelling Of Residual Stresses Induced By High Speed Milling Processcitations
- 20112D high speed machining simulations using a new explicit formulation with linear triangular elementscitations
- 20112D high speed machining simulations using a new explicit formulation with linear triangular elementscitations
- 2011Finite Element Modeling and Optimization of Mechanical Joining Technologycitations
- 2011Identification of cyclic and anisotropic behaviour of ODS steels tubescitations
- 2011An enhanced Lemaitre model formulation for materials processing damage computationcitations
- 2010Computational modeling of electrical contact crimping and mechanical strength analysiscitations
- 2010An experimental study to determine electrical contact resistancecitations
- 2009Numerical life prediction of mechanical fatigue for hot forging toolscitations
- 2008A node-nested Galerkin multigrid method for metal forging simulationcitations
- 2008Explicit F.E. formulation with modified linear tetrahedral elements applied to high speed forming processescitations
- 2008Explicit F.E. formulation with modified linear tetrahedral elements applied to high speed forming processescitations
- 2007Modélisation de l'endommagement pour la simulation d'assemblages par déformation
- 2005A node-nested Galerkin multigrid method for metal forging simulation
- 2001Toward large scale FE computation of hot forging process using iterative solvers, parallel computation and multigrid algorithmscitations
- 2001Three dimensional finite element simulation of ring rolling
Places of action
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article
Non standard samples behaviour law parameters determination by inverse analysis
Abstract
International audience ; Electrical contact crimping is a process commonly used in aeronautical and aero spatial applications. One require-ment to perform a resistant assembly is to master crimping parameters. Numerical simulation is then an efficient tool to limit tedious experimental test campaigns. Nevertheless, the numerical model accuracy depends on input data determina-tion, such as material behaviour law parameters. This paper deals with study done to determine material behaviour law parameters of component involved on electri-cal crimping process. The two samples, a strand and an electrical contact, have both small dimensions and specific shapes. For that reason, normalised tensile or compression tests could not be perform. Indeed, inverse analysis is a powerful tool to determine the behaviour laws parameters. The goal is to precisely model the sample mechanical solicitation. A series of computations is launched with various rheological parameters. By comparing experimental and simulated results, the goal is to minimize a cost function. Thus, the first step of the study has been to determine experimental tests to perform in order to gather the force/displacement experimental data. The copper strands have been studied in compression, with a micro indentation de-vice. A 60N force sensor has been used to acquire force data, whereas an inductive displacement sensor has been used for displacement acquisition data. The 60N force sensor is too weak to crush completely a copper contact. For that sample, we decided to use an instrumented crimping plier. A series of crimping tests has been performed on empty barrel, and the equivalent simulation has been done. With the best copper strand material parameters set, relative errors between experimental and simulated copper strand data finally amount to 6.9% (lower than the 8% experimental data scattering). On the other side, with the best cop-per contact material parameters set, the cost function amounts to 4% (lower than the 7% experimental data scattering). This ...