https://sam.ensam.eu:443 The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. Tue, 16 Jun 2026 00:20:21 GMT 2026-06-16T00:20:21Z http://hdl.handle.net/10985/20875 Influence of intra-granular void distribution on the grain sub-structure of UO2 pellets after high temperature compression tests BEN SAADA, Mariem; XAVIER, Iltis; GEY, Nathalie; GARCIA, Philippe; MALOUFI, Nabila; MIARD, A. The aim of this work is to study the role of intra-granular voids on the macroscopic behavior and the mi- crostructure of uranium dioxide (UO 2 ) for different strain conditions in the high temperature dislocational creep regime. Two batches (B1 and B2) of stoichiometric UO 2 pellets were fabricated by adapted powder metallurgy processes to obtain very close mean grain size and porosity but different fractions of intra-granular voids: they were 2.5 times more numerous in the second batch. The pellets were then compressed at 1773 K mostly in the dislocational regime for different strain levels and strain rates. Large Electron BackScattered Diffraction (EBSD) maps were acquired to quantify the sub-boundaries fraction in each deformed sample (with reliable detection of disorientation lines down to 0.25 °). Accurate-Electron Contrast Channeling Im- age (Accurate-ECCI) experiments were also performed to evidence the arrangement of dislocations in the sub-boundaries and highlight their interaction with intra-granular voids. The fractions of sub-boundaries and their disorientation increased in both batches with increasing strain levels and strain rates. This con- firms that during creep, UO 2 is subject to a dynamic recovery mechanism. Interestingly, for similar de- formation conditions, the pellets from batch B2 crept slower than those from batch B1. They also had a higher fraction of sub-boundaries which were more tortuous and located essentially close to the grain boundaries where the voids clustered. This suggests an influence of intra-granular voids on the creep rate, probably due to a void pinning effect of dislocation sub-boundaries. This effect should be taken into ac- count to optimize the microstructure and mechanical properties of UO 2 nuclear fuel, in order to improve its behavior under irradiation. Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/10985/20875 2020-01-01T00:00:00Z BEN SAADA, Mariem XAVIER, Iltis GEY, Nathalie GARCIA, Philippe MALOUFI, Nabila MIARD, A. The aim of this work is to study the role of intra-granular voids on the macroscopic behavior and the mi- crostructure of uranium dioxide (UO 2 ) for different strain conditions in the high temperature dislocational creep regime. Two batches (B1 and B2) of stoichiometric UO 2 pellets were fabricated by adapted powder metallurgy processes to obtain very close mean grain size and porosity but different fractions of intra-granular voids: they were 2.5 times more numerous in the second batch. The pellets were then compressed at 1773 K mostly in the dislocational regime for different strain levels and strain rates. Large Electron BackScattered Diffraction (EBSD) maps were acquired to quantify the sub-boundaries fraction in each deformed sample (with reliable detection of disorientation lines down to 0.25 °). Accurate-Electron Contrast Channeling Im- age (Accurate-ECCI) experiments were also performed to evidence the arrangement of dislocations in the sub-boundaries and highlight their interaction with intra-granular voids. The fractions of sub-boundaries and their disorientation increased in both batches with increasing strain levels and strain rates. This con- firms that during creep, UO 2 is subject to a dynamic recovery mechanism. Interestingly, for similar de- formation conditions, the pellets from batch B2 crept slower than those from batch B1. They also had a higher fraction of sub-boundaries which were more tortuous and located essentially close to the grain boundaries where the voids clustered. This suggests an influence of intra-granular voids on the creep rate, probably due to a void pinning effect of dislocation sub-boundaries. This effect should be taken into ac- count to optimize the microstructure and mechanical properties of UO 2 nuclear fuel, in order to improve its behavior under irradiation. http://hdl.handle.net/10985/20235 Assessment of the effect of 3D printed sand mold thickness on solidification process of AlSi13 casting alloy BEN SAADA, Mariem; EL MANSOURI, Mohamed The present work addresses the printed sand mold thickness effect on the solidification process of a eutectic aluminum-silicon alloy (AlSi13). Several sandmold thicknesses (varying from 3 to 30mm) are numerically studied using Quikcast®software. The study shows that the solidification time decreases when the sand thickness of mold increases. It is accelerated by more than 40% when the sand mold thickness increases from 3 to 30 mm. The numerical simulations are coupled with experiments. Indeed, the 3D sand printing process is used to fabricate molds presenting different thicknesses of 5 mm and 30 mm, respectively. In addition, the same printing parameters are applied for producing all sand molds. The comparison between both numerical and experimental results shows the same tendency according to the sand mold thickness. The results indicate that increasing the sand mold thickness from 5 to 30 mm allows to accelerate the solidification by 17% and 18.6%, respectively, in the numerical and experimental results. A finer microstructure is obtained when reducing the solidification time, which enhances the hardness of casting properties. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/10985/20235 2021-01-01T00:00:00Z BEN SAADA, Mariem EL MANSOURI, Mohamed The present work addresses the printed sand mold thickness effect on the solidification process of a eutectic aluminum-silicon alloy (AlSi13). Several sandmold thicknesses (varying from 3 to 30mm) are numerically studied using Quikcast®software. The study shows that the solidification time decreases when the sand thickness of mold increases. It is accelerated by more than 40% when the sand mold thickness increases from 3 to 30 mm. The numerical simulations are coupled with experiments. Indeed, the 3D sand printing process is used to fabricate molds presenting different thicknesses of 5 mm and 30 mm, respectively. In addition, the same printing parameters are applied for producing all sand molds. The comparison between both numerical and experimental results shows the same tendency according to the sand mold thickness. The results indicate that increasing the sand mold thickness from 5 to 30 mm allows to accelerate the solidification by 17% and 18.6%, respectively, in the numerical and experimental results. A finer microstructure is obtained when reducing the solidification time, which enhances the hardness of casting properties. http://hdl.handle.net/10985/25746 Estimation of the residual stress field of laminated aeronautical parts to prevent distortion after machining CHAABANI, Khayel; BEN SAADA, Mariem; LAVISSE, BRUNO; RITOU, Mathieu; GERMAIN, Guenael The estimation of post-machining distortion of monolithic aeronautical parts induced by the redistribution of the bulk residual stresses (RS) during machining is one of the major challenges of aeronautical parts manufacturing. Since it is the main cause of thick parts post-machining distortion, it is essential to know the state of the initial RS so that the machining strategy can be modified to minimize distortion of each part. The problem is even more complex because the RS field is not identical from one part to another. Considering an average stress field provides satisfactory results only for parts with simple geometries and a highly repeatable manufacturing process, which is rarely the case in an industrial setting. By simulating the steps of the production of the laminated blank, the variability of RS field will be established. This variability can be used to determine the distribution of the RS field of each part during machining. Wed, 15 May 2024 00:00:00 GMT http://hdl.handle.net/10985/25746 2024-05-15T00:00:00Z CHAABANI, Khayel BEN SAADA, Mariem LAVISSE, BRUNO RITOU, Mathieu GERMAIN, Guenael The estimation of post-machining distortion of monolithic aeronautical parts induced by the redistribution of the bulk residual stresses (RS) during machining is one of the major challenges of aeronautical parts manufacturing. Since it is the main cause of thick parts post-machining distortion, it is essential to know the state of the initial RS so that the machining strategy can be modified to minimize distortion of each part. The problem is even more complex because the RS field is not identical from one part to another. Considering an average stress field provides satisfactory results only for parts with simple geometries and a highly repeatable manufacturing process, which is rarely the case in an industrial setting. By simulating the steps of the production of the laminated blank, the variability of RS field will be established. This variability can be used to determine the distribution of the RS field of each part during machining. http://hdl.handle.net/10985/26323 Recent advances in the remelting process for recycling aluminium alloy chips: a critical review CHEN, Xin; BEN SAADA, Mariem; LAVISSE, BRUNO; AMMAR, Amine This critical review examines advances in preprocessing and remelting processes for aluminium alloy chip recycling, emphasizing pre-treatment and remelting techniques that improve both resource recovery and material quality. Pre-treatment strategies, particularly cleaning methods and compaction are critically evaluated. Various cleaning methods, including centrifugation, ultrasonic solvent washing, extraction, and distillation are compared based on their ability to remove residual cutting fluids. Cold compaction, which augments chip density to approximately 2.5 g/cm³, significantly curtails oxidation losses and enhances metal recovery. During remelting, NaCl-KCl-based fluxes with limited fluoride additions (e.g., 3–7 wt% Na₃AlF₆) disrupt oxide networks but require careful dosage control to minimize furnace corrosion and environmental hazards. Moreover, mechanical stirring combined with suitable melting temperatures reduces porosity while enhancing melt purity. Future research should prioritize the development of low-energy cleaning methods, flux composition optimization, and scalable production techniques to further advance sustainable aluminium recycling. Thu, 24 Apr 2025 00:00:00 GMT http://hdl.handle.net/10985/26323 2025-04-24T00:00:00Z CHEN, Xin BEN SAADA, Mariem LAVISSE, BRUNO AMMAR, Amine This critical review examines advances in preprocessing and remelting processes for aluminium alloy chip recycling, emphasizing pre-treatment and remelting techniques that improve both resource recovery and material quality. Pre-treatment strategies, particularly cleaning methods and compaction are critically evaluated. Various cleaning methods, including centrifugation, ultrasonic solvent washing, extraction, and distillation are compared based on their ability to remove residual cutting fluids. Cold compaction, which augments chip density to approximately 2.5 g/cm³, significantly curtails oxidation losses and enhances metal recovery. During remelting, NaCl-KCl-based fluxes with limited fluoride additions (e.g., 3–7 wt% Na₃AlF₆) disrupt oxide networks but require careful dosage control to minimize furnace corrosion and environmental hazards. Moreover, mechanical stirring combined with suitable melting temperatures reduces porosity while enhancing melt purity. Future research should prioritize the development of low-energy cleaning methods, flux composition optimization, and scalable production techniques to further advance sustainable aluminium recycling. http://hdl.handle.net/10985/26322 Casting hybrid twin: physics-based reduced order models enriched with data-driven models enabling the highest accuracy in real-time AMMAR, Amine; BEN SAADA, Mariem; CUETO, Elias; CHINESTA, Francisco Knowing the thermo-mechanical history of a part during its processing is essential to master the final properties of the product. During forming processes, several parameters can affect it. The development of a surrogate model makes it possible to access history in real time without having to resort to a numerical simulation. We restrict ourselves in this study to the cooling phase of the casting process. The thermal problem has been formulated taking into account the metal as well as the mould. Physical constants such as latent heat, conductivities and heat transfer coefficients has been kept constant. The problem has been parametrized by the coolant temperatures in five different cooling channels. To establish the offline model, multiple simulations are performed based on well-chosen combinations of parameters. The space-time solution of the thermal problem has been solved parametrically. In this work we propose a strategy based on the solution decomposition in space, time, and parameter modes. By applying a machine learning strategy, one should be able to produce modes of the parametric space for new sets of parameters. The machine learning strategy uses either random forest or polynomial fitting regressors. The reconstruction of the thermal solution can then be done using those modes obtained from the parametric space, with the same spatial and temporal basis previously established. This rationale is further extended to establish a model for the ignored part of the physics, in order to describe experimental measures. We present a strategy that makes it possible to calculate this ignorance using the same spatio-temporal basis obtained during the implementation of the numerical model, enabling the efficient construction of processing hybrid twins. Tue, 23 Jan 2024 00:00:00 GMT http://hdl.handle.net/10985/26322 2024-01-23T00:00:00Z AMMAR, Amine BEN SAADA, Mariem CUETO, Elias CHINESTA, Francisco Knowing the thermo-mechanical history of a part during its processing is essential to master the final properties of the product. During forming processes, several parameters can affect it. The development of a surrogate model makes it possible to access history in real time without having to resort to a numerical simulation. We restrict ourselves in this study to the cooling phase of the casting process. The thermal problem has been formulated taking into account the metal as well as the mould. Physical constants such as latent heat, conductivities and heat transfer coefficients has been kept constant. The problem has been parametrized by the coolant temperatures in five different cooling channels. To establish the offline model, multiple simulations are performed based on well-chosen combinations of parameters. The space-time solution of the thermal problem has been solved parametrically. In this work we propose a strategy based on the solution decomposition in space, time, and parameter modes. By applying a machine learning strategy, one should be able to produce modes of the parametric space for new sets of parameters. The machine learning strategy uses either random forest or polynomial fitting regressors. The reconstruction of the thermal solution can then be done using those modes obtained from the parametric space, with the same spatial and temporal basis previously established. This rationale is further extended to establish a model for the ignored part of the physics, in order to describe experimental measures. We present a strategy that makes it possible to calculate this ignorance using the same spatio-temporal basis obtained during the implementation of the numerical model, enabling the efficient construction of processing hybrid twins.