Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2022-2023).

The automotive industry is facing significant challenges for next-generation vehicle design as fuel economy regulations and tailpipe emission standards continue to strive for greater efficiency. In order to ensure vehicle design reaches these sustainability targets, lightweighting through multi-material design and topology optimization has been suggested as the leading method to reduce weight from conventional chassis and body structures. More effective tools, techniques, and methodologies are now required to advance the development of multi-phase optimization tools beyond current commercial capability, and help automotive designers achieve critical efficiency improvements without sacrificing performance. The proposed research will perform three main tasks, which cannot be achieved by means of currently available commercial software: (1) multi-material topology optimization for composites (by considering layered, anisotropic materials) and NVH (noise, vibration, and harshness); (2) multi-joint topology optimization and optimization for parts consolidation; and (3) large-scale topology optimization with full integration onto multi-material topology optimization and multi-joint topology optimization. All three tasks seek to address the next major challenges in multi-material design and build upon the state-of-the-art research in the field, currently being conducted at Queen's University. The primary objectives of this research are to create advanced multi-material design algorithms, develop new computational tools, and solve complex, real-world industry problems for next-generation vehicle design. The project will support total 4 PhD students and 6 MSc students throughout their research activities and until graduation. x000D
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