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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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Chevalier, Luc
Université Gustave Eiffel
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (27/27 displayed)
- 2024Identification of a Phase-Field Model for Brittle Fracture in Transversely Isotropic Elastic Materials with Application to Spruce Wood Specimens under Compression
- 2023Numerical Simulation of Infrared Heating and Ventilation before Stretch Blow Molding of PET Bottlescitations
- 2023Identification of polymer behavior from nonequibiaxial elongation test with temperature and strain rate conditions close to blow molding processcitations
- 2023In situ adjustment of a visco hyper elastic model for stretch blow molding process simulation of poly‐ethylene terephthalate bottlescitations
- 2022A new biaxial apparatus for tensile tests on Poly Ethylene Terephthalate optimized specimen at stretch blow molding conditionscitations
- 2022A multi-model approach for wooden furniture failure under mechanical loadcitations
- 2020Simulation of the Injection Stretch Blow Moulding Process: an Anisotropic Visco-hyperelastic Model for PET Behaviorcitations
- 2020Simulation of the Injection Stretch Blow Molding Process: An Anisotropic Visco‐Hyperelastic Model for Polyethylene Terephthalate Behaviorcitations
- 2018Caractérisation expérimentale et simulation stochastique du comportement des meubles à base de panneaux de particules
- 2017Self Heating during Stretch Blow Molding: an Experimental Numerical Comparison
- 2017Growth modeling and mechanical study of polymer spherulite aggregates
- 2017Modeling the Nucleation and Growth of Polymer Spherulites
- 2016An Anisotropic Visco-hyperelastic model for PET Behavior under ISBM Process Conditions
- 2015Simplified modeling of the convection and radiation heat transfers during the infrared heating of PET sheets and preforms Nomenclaturecitations
- 2015An Anisotropic Modeling of the Visco-hyperelastic Behaviour of PET under ISBM Process Conditions
- 2014Experimental global analysis of the efficiency of carbon fiber anchors applied over CFRP strengthened bricks, Construction and Building Materialscitations
- 2014Basis for viscoelastic modelling of polyethylene terephthalate (PET) near Tg with parameter identification from multi-axial elongation experimentscitations
- 2013Numerical simulation of the thermodependant viscohyperelastic behavior of polyethylene terephthalate near the glass transition temperature: Prediction of the self-heating during biaxial tension testcitations
- 2012On visco-elastic modelling of polyethylene terephthalate behaviour during multiaxial elongations slightly over the glass transition temperaturecitations
- 2012Numerical Simulation of the Viscohyperelastic Behaviour of PET near the Glass Transition Temperature
- 2011Identification of a Visco-Elastic Model for PET Near Tg Based on Uni and Biaxial Results
- 2010A three-dimensional network model for rubber elasticity: The effect of local entanglements constraintscitations
- 2010Thermoforming of a PMMA transparency near glass transition temperaturecitations
- 2010Modeling the nonlinear PMMA behavior near glass transition temperature: application to its thermoformingcitations
- 2008Microstructure changes in poly(ethylene terephthalate) in thick specimens under complex biaxial loadingcitations
- 2006Friction and wear during twin-disc experiments under ambient and cryogenic conditionscitations
- 2002Induced crystallization and orientation of poly(ethylene terephthalate) during uniaxial and biaxial elongation
Places of action
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article
A three-dimensional network model for rubber elasticity: The effect of local entanglements constraints
Abstract
We present a micro-mechanical model based on the network theory for the description of the elastic response of rubber-like materials at large strains. The material microstructure is characterized by chain-like macromolecules linked together at certain points; therefore an irregular three-dimensional network is formed. The material behaviour at the micro-level is usually described by means of statistical mechanics. Using certain assumptions for the certain distributions, one arrives at a continuum mechanical model of finite elasticity. However, the macromolecules interactions are neglected usually in these approaches. In the present contribution, we propose to add the effect of the interactions between chains of the cross-linked network. Following Arruda and Boyce (1993, 2000) [31,2], a cubic unit cell is defined where the entanglements fluctuations are localised in the corners of the cubic sub unit cell. These entanglements are linked by chains which ensure the interactions between the chains of idealized network (without interactions). These interactions can be represented by chains which are located in the principal directions of the cubic sub unit cell in undeformed state. We assume the probability densities which describe the free chain response of idealized network, and, the chain of constraints networks are independent. Then, the free-energy of the entire network is obtained by adding the free-energies of the free idealized (without interactions) and constraints (due to the chains interactions) networks. The constraint network reduces to four of the three-chain model of James and Guth (1943) [4] in undeformed state. Therefore, the free-energy of constraint network is obtained using the standard three-chain model, and, the free-energy of the free idealized network is constructed by means of the eight-chain model. The constitutive model involves five physical material parameters, namely, the shear modulus at small strains (μ0), the numbers of links that form the macromolecular chain of the eight-chain, and three-chain models (N8,N3) respectively, a micro-macro variable Ki, and, non-dimensional parameters (η,ρ). In order to determine the material parameters, the Langevin function in the single chain configuration is replaced by its first order Padé approximant [see, Cohen (1991) [5]; Perrin (2000) [6]], and, the material parameters are identified. The excellent predictive performance of the proposed model is shown by comparative to various available experimental data of homogeneous tests. However, the present model requires a validation because the relationship between the micro and macro levels needs to be clarified. Indeed, the identification of the physical parameters (μf,μc,N8,N3) from experimental results data at micro is hoped in order to simulate the macroscopic (i.e. bulk) behaviour of the material.