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Professor Lubineau’s research simultaneously involves computational, modeling and experimental developments to tackle complex problems related to composite engineering and more generally to heterogeneous materials.
Lubineau’s research is focused on four key areas:
Integrity of composite materials and structures. Isotropic and anisotropic damage theories; fracture mechanics; homogenization techniques bridging micro-mechanical models to meso/macro-scale models; multi-scale modeling; and damage mechanisms in nano-reinforced multiscale composites.
Durability of composite materials and structures; modeling of aging for polymer-based CFRPs under various environments (moisture, temperature, radiation, oxidation, mechanical fatigue); aging of steel pipes in sour environments; and the development of multiphysics-related models (experimental, modeling and computational work).
Inverse problems for the identification of constitutive parameters; digital image correlation-based identification techniques; identification techniques for interfaces in joints and laminates; and identification techniques based on 2-D (optical pictures) and 3-D (tomography) image correlation.
Multiscale coupling techniques; coupling between non-local continuum and local continuum models; and upscaling strategies for handling localized effects in large-scale simulations.
Lubineau’s research is focused on four key areas:
Integrity of composite materials and structures. Isotropic and anisotropic damage theories; fracture mechanics; homogenization techniques bridging micro-mechanical models to meso/macro-scale models; multi-scale modeling; and damage mechanisms in nano-reinforced multiscale composites.
Durability of composite materials and structures; modeling of aging for polymer-based CFRPs under various environments (moisture, temperature, radiation, oxidation, mechanical fatigue); aging of steel pipes in sour environments; and the development of multiphysics-related models (experimental, modeling and computational work).
Inverse problems for the identification of constitutive parameters; digital image correlation-based identification techniques; identification techniques for interfaces in joints and laminates; and identification techniques based on 2-D (optical pictures) and 3-D (tomography) image correlation.
Multiscale coupling techniques; coupling between non-local continuum and local continuum models; and upscaling strategies for handling localized effects in large-scale simulations.
研究兴趣
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COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING (2024): 108090
Smart Materials in Manufacturing (2024): 100043-100043
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JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T (2024): 255-265
ACS APPLIED POLYMER MATERIALSno. 6 (2023): 4244-4255
ACS APPLIED MATERIALS & INTERFACES (2023)
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Social Science Research Network (2023)
ACS APPLIED POLYMER MATERIALSno. 12 (2023): 9721-9731
Advanced science (Weinheim, Baden-Wurttemberg, Germany)no. 26 (2023)
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