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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Fri, 24 May 2019 11:03:40 GMT2019-05-24T11:03:40ZRecirculating Flows Involving Short Fiber Suspensions: Numerical Difficulties and Efficient Advanced Micro-Macro Solvers
http://hdl.handle.net/10985/6595
Recirculating Flows Involving Short Fiber Suspensions: Numerical Difficulties and Efficient Advanced Micro-Macro Solvers
PRULIERE, Etienne; AMMAR, Amine; EL KISSI, Nadia; CHINESTA, Francisco
Numerical modelling of non-Newtonian flows usually involves the coupling between equations of motion characterized by an elliptic character, and the fluid constitutive equation, which defines an advection problem linked to the fluid history. There are different numerical techniques to treat the hyperbolic advection equations. In non-recirculating flows, Eulerian discretizations can give a convergent solution within a short computing time. However, the existence of steady recirculating flow areas induces additional difficulties. Actually, in these flows neither boundary conditions nor initial conditions are known. In this paper we compares different advanced strategies (some of them recently proposed and extended here for addressing complex flows) when they are applied to the solution of the kinetic theory description of a short fiber suspension fluid flows.
Thu, 01 Jan 2009 00:00:00 GMThttp://hdl.handle.net/10985/65952009-01-01T00:00:00ZPRULIERE, EtienneAMMAR, AmineEL KISSI, NadiaCHINESTA, FranciscoNumerical modelling of non-Newtonian flows usually involves the coupling between equations of motion characterized by an elliptic character, and the fluid constitutive equation, which defines an advection problem linked to the fluid history. There are different numerical techniques to treat the hyperbolic advection equations. In non-recirculating flows, Eulerian discretizations can give a convergent solution within a short computing time. However, the existence of steady recirculating flow areas induces additional difficulties. Actually, in these flows neither boundary conditions nor initial conditions are known. In this paper we compares different advanced strategies (some of them recently proposed and extended here for addressing complex flows) when they are applied to the solution of the kinetic theory description of a short fiber suspension fluid flows.Separated representation of incremental elastoplastic simulations
http://hdl.handle.net/10985/9514
Separated representation of incremental elastoplastic simulations
NASRI, Mohamed Aziz; AGUADO, Jose Vicente; AMMAR, Amine; CUETO, Elias; CHINESTA, Francisco; MOREL, Franck; ROBERT, Camille; EL AREM, Saber
Forming processes usually involve irreversible plastic transformations. The calculation in that case becomes cumbersome when large parts and processes are considered. Recently Model Order Reduction techniques opened new perspectives for an accurate and fast simulation of mechanical systems, however nonlinear history-dependent behaviors remain still today challenging scenarios for the application of these techniques. In this work we are proposing a quite simple non intrusive strategy able to address such behaviors by coupling a separated representation with a POD-based reduced basis within an incremental elastoplastic formulation.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/95142015-01-01T00:00:00ZNASRI, Mohamed AzizAGUADO, Jose VicenteAMMAR, AmineCUETO, EliasCHINESTA, FranciscoMOREL, FranckROBERT, CamilleEL AREM, SaberForming processes usually involve irreversible plastic transformations. The calculation in that case becomes cumbersome when large parts and processes are considered. Recently Model Order Reduction techniques opened new perspectives for an accurate and fast simulation of mechanical systems, however nonlinear history-dependent behaviors remain still today challenging scenarios for the application of these techniques. In this work we are proposing a quite simple non intrusive strategy able to address such behaviors by coupling a separated representation with a POD-based reduced basis within an incremental elastoplastic formulation.Direct numerical simulation of complex viscoelastic flows via fast lattice-Boltzmann solution of the Fokker–Planck equation
http://hdl.handle.net/10985/8462
Direct numerical simulation of complex viscoelastic flows via fast lattice-Boltzmann solution of the Fokker–Planck equation
BERGAMASCO, Luca; IZQUIERDO, Salvador; AMMAR, Amine
Micro–macro simulations of polymeric solutions rely on the coupling between macroscopic conservation equations for the fluid flow and stochastic differential equations for kinetic viscoelastic models at the microscopic scale. In the present work we introduce a novel micro–macro numerical approach, where the macroscopic equations are solved by a finite-volume method and the microscopic equation by a lattice-Boltzmann one. The kinetic model is given by molecular analogy with a finitely extensible non-linear elastic (FENE) dumbbell and is deterministically solved through an equivalent Fokker–Planck equation. The key features of the proposed approach are: (i) a proper scaling and coupling between the micro lattice-Boltzmann solution and the macro finite-volume one; (ii) a fast microscopic solver thanks to an implementation for Graphic Processing Unit (GPU) and the local adaptivity of the lattice-Boltzmann mesh; (iii) an operator-splitting algorithm for the convection of the macroscopic viscoelastic stresses instead of the whole probability density of the dumbbell configuration. This latter feature allows the application of the proposed method to non-homogeneous flow conditions with low memory-storage requirements. The model optimization is achieved through an extensive analysis of the lattice-Boltzmann solution, which finally provides control on the numerical error and on the computational time. The resulting micro–macro model is validated against the benchmark problem of a viscoelastic flow past a confined cylinder and the results obtained confirm the validity of the approach.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/84622013-01-01T00:00:00ZBERGAMASCO, LucaIZQUIERDO, SalvadorAMMAR, AmineMicro–macro simulations of polymeric solutions rely on the coupling between macroscopic conservation equations for the fluid flow and stochastic differential equations for kinetic viscoelastic models at the microscopic scale. In the present work we introduce a novel micro–macro numerical approach, where the macroscopic equations are solved by a finite-volume method and the microscopic equation by a lattice-Boltzmann one. The kinetic model is given by molecular analogy with a finitely extensible non-linear elastic (FENE) dumbbell and is deterministically solved through an equivalent Fokker–Planck equation. The key features of the proposed approach are: (i) a proper scaling and coupling between the micro lattice-Boltzmann solution and the macro finite-volume one; (ii) a fast microscopic solver thanks to an implementation for Graphic Processing Unit (GPU) and the local adaptivity of the lattice-Boltzmann mesh; (iii) an operator-splitting algorithm for the convection of the macroscopic viscoelastic stresses instead of the whole probability density of the dumbbell configuration. This latter feature allows the application of the proposed method to non-homogeneous flow conditions with low memory-storage requirements. The model optimization is achieved through an extensive analysis of the lattice-Boltzmann solution, which finally provides control on the numerical error and on the computational time. The resulting micro–macro model is validated against the benchmark problem of a viscoelastic flow past a confined cylinder and the results obtained confirm the validity of the approach.On the solution of the multidimensional Langer’s equation using the proper generalized decomposition method for modeling phase transitions
http://hdl.handle.net/10985/8479
On the solution of the multidimensional Langer’s equation using the proper generalized decomposition method for modeling phase transitions
LAMARI, Hajer; AMMAR, Amine; LEYGUE, Adrien; CHINESTA, Francisco
The dynamics of phase transition in a binary mixture occurring during a quench is studied taking into account composition fluctuations by solving Langer’s equation in a domain composed of a certain number of micro-domains. The resulting Langer’s equation governing the evolution of the distribution function becomes multidimensional. Circumventing the curse of dimensionality the proper generalized decomposition is applied. The influence of the interaction parameter in the vicinity of the critical point is analyzed. First we address the case of a system composed of a single micro-domain in which phase transition occurs by a simple symmetry change. Next, we consider a system composed of two micro-domains in which phase transition occurs by phase separation, with special emphasis on the effect of the Landau free energy non-local term. Finally, some systems consisting of many micro-domains are considered.
http://dx.doi.org/10.1088/0965-0393/20/1/015007
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/84792012-01-01T00:00:00ZLAMARI, HajerAMMAR, AmineLEYGUE, AdrienCHINESTA, FranciscoThe dynamics of phase transition in a binary mixture occurring during a quench is studied taking into account composition fluctuations by solving Langer’s equation in a domain composed of a certain number of micro-domains. The resulting Langer’s equation governing the evolution of the distribution function becomes multidimensional. Circumventing the curse of dimensionality the proper generalized decomposition is applied. The influence of the interaction parameter in the vicinity of the critical point is analyzed. First we address the case of a system composed of a single micro-domain in which phase transition occurs by a simple symmetry change. Next, we consider a system composed of two micro-domains in which phase transition occurs by phase separation, with special emphasis on the effect of the Landau free energy non-local term. Finally, some systems consisting of many micro-domains are considered.Degradation modes and tool wear mechanisms in finish and rough machining of Ti17 Titanium alloy under high-pressure water jet assistance
http://hdl.handle.net/10985/8608
Degradation modes and tool wear mechanisms in finish and rough machining of Ti17 Titanium alloy under high-pressure water jet assistance
AYED, Yessine; GERMAIN, Guénaël; AMMAR, Amine; FURET, Benoit
This article presents the results of an experimental study on the Ti17 titanium alloy, which was carried out to analyze tool wear and the degradation mechanisms of an uncoated tungsten carbide tool insert. Two machining conditions, roughing and finishing, have been studied under different lubrication conditions. The experimental procedure included measurement of the cutting forces and the surface roughness. Different techniques have been used to explain the tool wear mechanisms. Distribution maps of the elemental composition of the titanium alloy and the tool inserts have been created using Energy Dispersive X-ray Spectroscopy (EDS). An area of material deposition on the tool rake face, characterized by a high titanium concentration has been observed. The width of this area and the concentration of titanium, decrease when increasing water jet pressure. The study shows that wear mechanisms, with and without high-pressure water jet assistance (HPWJA) are not the same. For example, for the roughing condition using conventional lubrication, the temperature in the cutting area becomes very high, this causes plastic deformation of the cutting edge which results in its rapid collapse. By contrast, this problem disappears when machining with HPWJA. In addition, the evolution of flank wear (VB) is stabilized with high-pressure lubrication. In this case, the most critical degradation mode is due to notch wear (VBn) leading to the sudden rupture of the cutting edge.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/86082013-01-01T00:00:00ZAYED, YessineGERMAIN, GuénaëlAMMAR, AmineFURET, BenoitThis article presents the results of an experimental study on the Ti17 titanium alloy, which was carried out to analyze tool wear and the degradation mechanisms of an uncoated tungsten carbide tool insert. Two machining conditions, roughing and finishing, have been studied under different lubrication conditions. The experimental procedure included measurement of the cutting forces and the surface roughness. Different techniques have been used to explain the tool wear mechanisms. Distribution maps of the elemental composition of the titanium alloy and the tool inserts have been created using Energy Dispersive X-ray Spectroscopy (EDS). An area of material deposition on the tool rake face, characterized by a high titanium concentration has been observed. The width of this area and the concentration of titanium, decrease when increasing water jet pressure. The study shows that wear mechanisms, with and without high-pressure water jet assistance (HPWJA) are not the same. For example, for the roughing condition using conventional lubrication, the temperature in the cutting area becomes very high, this causes plastic deformation of the cutting edge which results in its rapid collapse. By contrast, this problem disappears when machining with HPWJA. In addition, the evolution of flank wear (VB) is stabilized with high-pressure lubrication. In this case, the most critical degradation mode is due to notch wear (VBn) leading to the sudden rupture of the cutting edge.Some Incipient Techniques For Improving Efficiency in Computational Mechanics
http://hdl.handle.net/10985/6477
Some Incipient Techniques For Improving Efficiency in Computational Mechanics
AMMAR, Amine; CHINESTA, Francisco
This contribution presents a review of different techniques available for alleviating simulation cost in computational mechanics. The first one is based on a separated representation of the unknown fields; the second one uses a model reduction based on the Karhunen-Loève decomposition within an adaptive scheme, and the last one is a mixed technique specially adapted for reducing models involving local singularities. These techniques can be applied in a large variety of models.
Tue, 01 Jan 2008 00:00:00 GMThttp://hdl.handle.net/10985/64772008-01-01T00:00:00ZAMMAR, AmineCHINESTA, FranciscoThis contribution presents a review of different techniques available for alleviating simulation cost in computational mechanics. The first one is based on a separated representation of the unknown fields; the second one uses a model reduction based on the Karhunen-Loève decomposition within an adaptive scheme, and the last one is a mixed technique specially adapted for reducing models involving local singularities. These techniques can be applied in a large variety of models.On the multi‑scale description of electrical conducting suspensions involving perfectly dispersed rods
http://hdl.handle.net/10985/10253
On the multi‑scale description of electrical conducting suspensions involving perfectly dispersed rods
PEREZ, Marta; ABISSET-CHAVANNE, Emmanuelle; BARASINSKI, Anais; CHINESTA, Francisco; AMMAR, Amine; KEUNINGS, Roland
Nanocomposites allow for a significant enhancement of functional properties, in particular electrical conduction. In order to optimize materials and parts, predictive models are required to evaluate particle distribution and orientation. Both are key parameters in order to evaluate percolation and the resulting electrical networks. Many forming processes involve flowing suspensions for which the final particle orientation could be controlled by means of the flow and the electric field. In view of the multiscale character of the problem, detailed descriptions are defined at the microscopic scale and then coarsened to be applied efficiently in process simulation at the macroscopic scale. The first part of this work revisits the different modeling approaches throughout the different description scales. Then, modeling of particle contacts is addressed as they determine the final functional properties, in particular electrical conduction. Different descriptors of rod contacts are proposed and analyzed. Numerical results are discussed, in particular to evaluate the impact of closure approximations needed to derive a macroscopic description.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/102532015-01-01T00:00:00ZPEREZ, MartaABISSET-CHAVANNE, EmmanuelleBARASINSKI, AnaisCHINESTA, FranciscoAMMAR, AmineKEUNINGS, RolandNanocomposites allow for a significant enhancement of functional properties, in particular electrical conduction. In order to optimize materials and parts, predictive models are required to evaluate particle distribution and orientation. Both are key parameters in order to evaluate percolation and the resulting electrical networks. Many forming processes involve flowing suspensions for which the final particle orientation could be controlled by means of the flow and the electric field. In view of the multiscale character of the problem, detailed descriptions are defined at the microscopic scale and then coarsened to be applied efficiently in process simulation at the macroscopic scale. The first part of this work revisits the different modeling approaches throughout the different description scales. Then, modeling of particle contacts is addressed as they determine the final functional properties, in particular electrical conduction. Different descriptors of rod contacts are proposed and analyzed. Numerical results are discussed, in particular to evaluate the impact of closure approximations needed to derive a macroscopic description.Parametric solutions involving geometry: A step towards efficient shape optimization
http://hdl.handle.net/10985/10244
Parametric solutions involving geometry: A step towards efficient shape optimization
AMMAR, Amine; HUERTA, Antonio; CHINESTA, Francisco; CUETO, Elias; LEYGUE, Adrien
Optimization of manufacturing processes or structures involves the optimal choice of many parameters (process parameters, material parameters or geometrical parameters). Usual strategies proceed by defining a trial choice of those parameters and then solving the resulting model. Then, an appropriate cost function is evaluated and its optimality checked. While the optimum is not reached, the process parameters should be updated by using an appropriate optimization procedure, and then the model must be solved again for the updated process parameters. Thus, a direct numerical solution is needed for each choice of the process parameters, with the subsequent impact on the computing time. In this work we focus on shape optimization that involves the appropriate choice of some parameters defining the problem geometry. The main objective of this work is to describe an original approach for computing an off-line parametric solution. That is, a solution able to include information for different parameter values and also allowing to compute readily the sensitivities. The curse of dimensionality is circumvented by invoking the Proper Generalized Decomposition (PGD) introduced in former works, which is applied here to compute geometrically parametrized solutions.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10985/102442014-01-01T00:00:00ZAMMAR, AmineHUERTA, AntonioCHINESTA, FranciscoCUETO, EliasLEYGUE, AdrienOptimization of manufacturing processes or structures involves the optimal choice of many parameters (process parameters, material parameters or geometrical parameters). Usual strategies proceed by defining a trial choice of those parameters and then solving the resulting model. Then, an appropriate cost function is evaluated and its optimality checked. While the optimum is not reached, the process parameters should be updated by using an appropriate optimization procedure, and then the model must be solved again for the updated process parameters. Thus, a direct numerical solution is needed for each choice of the process parameters, with the subsequent impact on the computing time. In this work we focus on shape optimization that involves the appropriate choice of some parameters defining the problem geometry. The main objective of this work is to describe an original approach for computing an off-line parametric solution. That is, a solution able to include information for different parameter values and also allowing to compute readily the sensitivities. The curse of dimensionality is circumvented by invoking the Proper Generalized Decomposition (PGD) introduced in former works, which is applied here to compute geometrically parametrized solutions.Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices
http://hdl.handle.net/10985/10254
Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices
ALFARO, Iciar; GONZALEZ, David; BORDEU, Felipe; LEYGUE, Adrien; AMMAR, Amine; CUETO, Elias; CHINESTA, Francisco
Simulation of all phenomena taking place in a surgical procedure is a formidable task that involves, when possible, the use of supercomputing facilities over long time periods. However, decision taking in the operating room needs for fast methods that provide an accurate response in real time. To this end, Model Order Reduction (MOR) techniques have emerged recently in the field of Computational Surgery to help alleviate this burden. In this paper, we review the basics of classical MOR and explain how a technique recently developed by the authors and coined as Proper Generalized Decomposition could make real-time feedback available with the use of simple devices like smartphones or tablets. Examples are given on the performance of the technique for problems at different scales of the surgical procedure, form gene regulatory networks to macroscopic soft tissue deformation and cutting.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/10985/102542014-01-01T00:00:00ZALFARO, IciarGONZALEZ, DavidBORDEU, FelipeLEYGUE, AdrienAMMAR, AmineCUETO, EliasCHINESTA, FranciscoSimulation of all phenomena taking place in a surgical procedure is a formidable task that involves, when possible, the use of supercomputing facilities over long time periods. However, decision taking in the operating room needs for fast methods that provide an accurate response in real time. To this end, Model Order Reduction (MOR) techniques have emerged recently in the field of Computational Surgery to help alleviate this burden. In this paper, we review the basics of classical MOR and explain how a technique recently developed by the authors and coined as Proper Generalized Decomposition could make real-time feedback available with the use of simple devices like smartphones or tablets. Examples are given on the performance of the technique for problems at different scales of the surgical procedure, form gene regulatory networks to macroscopic soft tissue deformation and cutting.Development of a numerical model for the understanding of the chip formation in high-pressure water-jet assisted machining
http://hdl.handle.net/10985/10378
Development of a numerical model for the understanding of the chip formation in high-pressure water-jet assisted machining
AYED, Yessine; ROBERT, Camille; GERMAIN, Guénaël; AMMAR, Amine
The aim of this study is to develop a new numerical cutting model that includes fluid structure interaction and to take into account heat transfer between the water-jet, the workpiece and the chip. This has been achieved using a CEL (Coupled–Eulerian–Lagrangian) technique, an algorithm has been developed to ensure heat exchange between the fluid and the structure. This new model allows decoupling of the mechanical and the thermal effects of the water-jet on chip formation and fragmentation. It has been demonstrated that fragmentation of the chip is ensured by the combination of the thermal and the mechanical effects of the water-jet. Moreover, the tool rake temperature is reduced by more than 400 °C, the tool/chip contact length is also decreased by about 30%.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/103782016-01-01T00:00:00ZAYED, YessineROBERT, CamilleGERMAIN, GuénaëlAMMAR, AmineThe aim of this study is to develop a new numerical cutting model that includes fluid structure interaction and to take into account heat transfer between the water-jet, the workpiece and the chip. This has been achieved using a CEL (Coupled–Eulerian–Lagrangian) technique, an algorithm has been developed to ensure heat exchange between the fluid and the structure. This new model allows decoupling of the mechanical and the thermal effects of the water-jet on chip formation and fragmentation. It has been demonstrated that fragmentation of the chip is ensured by the combination of the thermal and the mechanical effects of the water-jet. Moreover, the tool rake temperature is reduced by more than 400 °C, the tool/chip contact length is also decreased by about 30%.