En cliquant sur le bouton ci-dessous, vous pouvez consulter la liste des dernières publications scientifiques du laboratoire dans la "Collection HAL du M2P2" qui permet de faire des recherches par année, auteur, type de document (article scientifique, ouvrage, chapitre d'ouvrage, actes de conférence...), etc.
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Yaxin Shen, Mitra Fouladirad, Antoine Grall. Mathematical modeling of solar farm performance degradation in a dynamic environment for condition-based maintenance. Reliability Engineering and System Safety, 2025, 257, pp.110778. ⟨10.1016/j.ress.2024.110778⟩. ⟨hal-05023346⟩ Plus de détails...
Yaxin Shen, Mitra Fouladirad, Antoine Grall. Mathematical modeling of solar farm performance degradation in a dynamic environment for condition-based maintenance. Reliability Engineering and System Safety, 2025, 257, pp.110778. ⟨10.1016/j.ress.2024.110778⟩. ⟨hal-05023346⟩
Journal: Reliability Engineering and System Safety
Polymorphism control in crystallization processes is critical for ensuring the final quality of active pharmaceutical ingredients (APIs). In the present research, the solvent-mediated phase transformation (SMPT) of paracetamol, a widely used API, from its metastable form II to the stable form I during seeded batch cooling crystallization in isopropyl alcohol/water solution is investigated. The study explores the utility of offline FT-NIR spectroscopy and an inline PAT Blaze900 probe to detect paracetamol polymorphs and monitor polymorphic changes. Key findings demonstrate that FT-NIR offers a robust offline alternative for polymorphism detection and monitoring. The PAT Blaze900 recordings, in terms of chord length counts and distributions, also provide additional information about form II SMPT and are in accordance with the FT-NIR prediction model output. The SMPT kinetics are influenced by operational parameters such as supersaturation and operational and cooling temperature. Optimization of these parameters enabled better control over the SMPT kinetics, paving the way for efficient stabilization of paracetamol metastable form II to 30 min before complete conversion to the most stable form I.
Carla Kalakech, Asma Madmar, Emilie Gagnière, Géraldine Agusti, Denis Mangin, et al.. Monitoring of Paracetamol Solvent-Mediated Phase Transformation in Seeded Batch Crystallization Processes. Crystal Growth & Design, 2025, ⟨10.1021/acs.cgd.4c01650⟩. ⟨hal-05006905⟩
Jingqi Zhang, Mitra Fouladirad, Nikolaos Limnios. Sensitivity analysis of an imperfect maintenance policy for Proton-exchange membrane fuel cell based on geometric a semi-Markov model. Reliability Engineering and System Safety, 2025, 255, pp.110674. ⟨10.1016/j.ress.2024.110674⟩. ⟨hal-05023351⟩ Plus de détails...
Jingqi Zhang, Mitra Fouladirad, Nikolaos Limnios. Sensitivity analysis of an imperfect maintenance policy for Proton-exchange membrane fuel cell based on geometric a semi-Markov model. Reliability Engineering and System Safety, 2025, 255, pp.110674. ⟨10.1016/j.ress.2024.110674⟩. ⟨hal-05023351⟩
Journal: Reliability Engineering and System Safety
Zohra Laggoune, Yasmine Masmoudi, Seyed Ali Sajadian, Elisabeth Badens. Sirolimus solubility in supercritical carbon dioxide: Measurement and modeling.. Journal of CO2 Utilization, 2025, 93, pp.103034. ⟨10.1016/j.jcou.2025.103034⟩. ⟨hal-04954883⟩ Plus de détails...
The solubility of drugs in supercritical carbon dioxide is a key parameter in their processing. This study focuses on sirolimus, an immunosuppressive drug used in organ transplantation. Its solubility in supercritical carbon dioxide was measured using a static gravimetric method. Measurements were carried out at pressures ranging from 12.5 MPa to 25.0 MPa and temperatures from 313 K to 328 K. The findings revealed a molar fraction range of sirolimus between 1.20 × 10 6 and 2.73 × 10 6 and a direct solubility behavior in the investigated domain. The experimental data were correlated using several models. These included semi-empirical density-based models (Chrastil, Mendez-Santiago and Teja, Bartle et al., Kumar and Johnston, Sparks et al., and Sodeifian et al.), as well as equation of state-based models (Soave-Redlich-Kwong and Peng-Robinson). The results indicated that Sparks et al. and Soave-Redlich-Kwong showed the lowest average absolute relative deviation (AARD%) and the corrected correlation coefficient (Radj) of 4.12 %, 0.978 and 05.18 %, 0.980 respectively.
Zohra Laggoune, Yasmine Masmoudi, Seyed Ali Sajadian, Elisabeth Badens. Sirolimus solubility in supercritical carbon dioxide: Measurement and modeling.. Journal of CO2 Utilization, 2025, 93, pp.103034. ⟨10.1016/j.jcou.2025.103034⟩. ⟨hal-04954883⟩
Mohammed Zine, Noureddine Touach, El Mostapha Lotfi, Philippe Moulin. Efficiency of an Ultrafiltration Process for the Depollution of Pretreated Olive Mill Wastewater. Membranes, 2025, 15 (3), pp.67. ⟨10.3390/membranes15030067⟩. ⟨hal-04961886⟩ Plus de détails...
The depollution of constructed wetland-pretreated olive mill wastewater (OMW) using a membrane filtration system was experimentally studied. Dead-end filtration (DEF) was employed to evaluate suitable MF/UF membranes and select the appropriate molecular weight cut-off for optimal OMW treatment. Removal efficiencies for COD (chemical oxygen demand) and TOC (total organic carbon) using DEF reached maximum values of 88.14% and 11.17%, respectively. Adsorption of raw and pretreated OMW on granular activated carbon was also carried out for a comparative study against DEF and pretreatment. The semi-industrial-scale experiments were conducted using commercial ceramic ultrafiltration (UF) membranes (150 and 50 kDa) in cross-flow filtration (CFF) mode at a permeate flux around 200 L h−1 m−2 and a trans-membrane pressure (TMP) of 3.5–3.8 bars. This post-treatment had a significant impact on COD removal efficiency from pretreated OMW, reaching 78.5%. The coupled process proposed in this study achieved removal efficiencies of 97%, 97%, and 99.9% of COD, TOC, and turbidity, respectively.
Mohammed Zine, Noureddine Touach, El Mostapha Lotfi, Philippe Moulin. Efficiency of an Ultrafiltration Process for the Depollution of Pretreated Olive Mill Wastewater. Membranes, 2025, 15 (3), pp.67. ⟨10.3390/membranes15030067⟩. ⟨hal-04961886⟩
Hippolyte Lerogeron, Pierre Boivin, Vincent Faucher, Julien Favier. A Numerical Framework for Fast Transient Compressible Flows Using Lattice Boltzmann and Immersed Boundary Methods. International Journal for Numerical Methods in Engineering, 2025, 126 (3), ⟨10.1002/nme.7647⟩. ⟨hal-04958000⟩ Plus de détails...
This article is dedicated to the development of a model to simulate fast transient compressible flows on solid structures using immersed boundary method (IBM) and a lattice Boltzmann solver. Ultimately, the proposed model aims at providing an efficient algorithm to simulate strongly‐coupled fluid‐structure interactions (FSI). Within this goal, it is necessary to propose a precise and robust numerical framework and validate it on stationary solid cases first, which is the scope of the present study. Classical FSI methods, such as body‐fitted approaches, are facing challenges with moving or complex geometries in realistic conditions, requiring computationally expensive re‐meshing operations. IBM offers an alternative by treating the solid structure geometry independently from the fluid mesh. This study focuses on the extension of the IBM to compressible flows, and a particular attention is given to the enforcement of various thermal boundary conditions. A hybrid approach, combining diffuse forcing for Dirichlet‐type boundary conditions and ghost‐nodes forcing for Neumann‐type boundary conditions is introduced. Finally, a simplified model, relying only on diffuse IBM forcing, is investigated to treat specific cases where the fluid solid interface is considered as adiabatic. The accuracy of the method is validated through various test cases of increasing complexity.
Hippolyte Lerogeron, Pierre Boivin, Vincent Faucher, Julien Favier. A Numerical Framework for Fast Transient Compressible Flows Using Lattice Boltzmann and Immersed Boundary Methods. International Journal for Numerical Methods in Engineering, 2025, 126 (3), ⟨10.1002/nme.7647⟩. ⟨hal-04958000⟩
Journal: International Journal for Numerical Methods in Engineering
B. Clavier, D. Zarzoso, D. Del-Castillo-Negrete, E. Frénod. Generative-machine-learning surrogate model of plasma turbulence. Physical Review E , 2025, 111 (1), pp.L013202. ⟨10.1103/PhysRevE.111.L013202⟩. ⟨hal-04966199⟩ Plus de détails...
Generative artificial intelligence methods are employed for the first time to construct a surrogate model for plasma turbulence that enables long-time transport simulations. The proposed GAIT (Generative Artificial Intelligence Turbulence) model is based on the coupling of a convolutional variational autoencoder that encodes precomputed turbulence data into a reduced latent space, and a recurrent neural network and decoder that generate new turbulence states 400 times faster than the direct numerical integration. The model is applied to the Hasegawa-Wakatani (HW) plasma turbulence model, which is closely related to the quasigeostrophic model used in geophysical fluid dynamics. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, and the flow topology characterized by the Okubo-Weiss decomposition. The GAIT model also reproduces Lagrangian transport including the probability distribution function of particle displacements and the effective turbulent diffusivity.
B. Clavier, D. Zarzoso, D. Del-Castillo-Negrete, E. Frénod. Generative-machine-learning surrogate model of plasma turbulence. Physical Review E , 2025, 111 (1), pp.L013202. ⟨10.1103/PhysRevE.111.L013202⟩. ⟨hal-04966199⟩
B. Clavier, D. Zarzoso, D. Del-Castillo-Negrete, E. Frénod. Generative-machine-learning surrogate model of plasma turbulence. Physical Review E , 2025, 111 (1), pp.L013202. ⟨10.1103/PhysRevE.111.L013202⟩. ⟨hal-04966199⟩ Plus de détails...
Generative artificial intelligence methods are employed for the first time to construct a surrogate model for plasma turbulence that enables long-time transport simulations. The proposed GAIT (Generative Artificial Intelligence Turbulence) model is based on the coupling of a convolutional variational autoencoder that encodes precomputed turbulence data into a reduced latent space, and a recurrent neural network and decoder that generate new turbulence states 400 times faster than the direct numerical integration. The model is applied to the Hasegawa-Wakatani (HW) plasma turbulence model, which is closely related to the quasigeostrophic model used in geophysical fluid dynamics. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, and the flow topology characterized by the Okubo-Weiss decomposition. The GAIT model also reproduces Lagrangian transport including the probability distribution function of particle displacements and the effective turbulent diffusivity.
B. Clavier, D. Zarzoso, D. Del-Castillo-Negrete, E. Frénod. Generative-machine-learning surrogate model of plasma turbulence. Physical Review E , 2025, 111 (1), pp.L013202. ⟨10.1103/PhysRevE.111.L013202⟩. ⟨hal-04966199⟩
Ksenia Kozhanova, Song Zhao, Raphaël Loubère, Pierre Boivin. A hybrid a posteriori MOOD limited lattice Boltzmann method to solve compressible fluid flows – LBMOOD. Journal of Computational Physics, 2025, 521, Part 2, pp.113570. ⟨10.1016/j.jcp.2024.113570⟩. ⟨hal-04802259⟩ Plus de détails...
In this paper we blend two lattice-Boltzmann (LB) numerical schemes with an a posteriori Multi-dimensional Optimal Order Detection (MOOD) paradigm to solve hyperbolic systems of conservation laws in 1D and 2D. The first LB scheme is robust to the presence of shock waves but lacks accuracy on smooth flows. The second one has a second-order of accuracy but develops non-physical oscillations when solving steep gradients. The MOOD paradigm produces a hybrid LB scheme via smooth and positivity detectors allowing to gather the best properties of the two LB methods within one scheme. Indeed, the resulting scheme presents second order of accuracy on smooth solutions, essentially non-oscillatory behaviour on irregular ones, and, an ‘almost fail-safe’ property concerning positivity issues. The numerical results on a set of sanity test cases and demanding ones are presented assessing the appropriate behaviour of the hybrid LBMOOD scheme in 1D and 2D.
Ksenia Kozhanova, Song Zhao, Raphaël Loubère, Pierre Boivin. A hybrid a posteriori MOOD limited lattice Boltzmann method to solve compressible fluid flows – LBMOOD. Journal of Computational Physics, 2025, 521, Part 2, pp.113570. ⟨10.1016/j.jcp.2024.113570⟩. ⟨hal-04802259⟩
