Obiettivo
The innovative and challenging objective of the MASTER project is the numerical modeling and optimum design of complex carbon nanotube (CNT)-reinforced composite morphologies, via a novel and computationally efficient molecular mechanics-based, multiscale stochastic numerical simulation approach, in conjunction with a robust optimization methodology. The rationale of the project is to propose a generic approach for an accurate numerical modeling, efficient analysis and robust design considering uncertainties, of high performance CNT-reinforced composites, in terms of mechanical and damping properties, which could have far reaching implications in the design of current as well as future nano-scale reinforced composites. The above undertaking is confronted with the excessive computational effort required to achieve the proposed objective. This computational effort will be mastered with highly efficient multiscale simulation approaches, innovative numerical solution methods, metaheuristic optimization algorithms, soft computing tools and the exploitation of the recent advances in high performance computing technology. The project has a multidisciplinary dimension by combining various scientific fields such as: molecular mechanics; continuum mechanics; stochastic mechanics; optimization; numerical analysis; soft computing; nanotechnology; material science and computer technology. The achievements of this project are expected to significantly enhance our knowledge on the analysis and design of nanocomposites beyond the current state of the art.
Campo scientifico
- engineering and technologymaterials engineeringcomposites
- engineering and technologynanotechnology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwaresupercomputers
- natural sciencescomputer and information sciencescomputational sciencemultiphysics
- engineering and technologymaterials engineeringnanocomposites
Invito a presentare proposte
ERC-2011-ADG_20110209
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Meccanismo di finanziamento
ERC-AG - ERC Advanced GrantIstituzione ospitante
157 80 ATHINA
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