MATERIAL DESIGN FOR ADDITIVE MANUFACTURING (MADAM)
Sector: Manufacturing (Industrial) • Location: France
Source: EU Funding & Tenders Portal
This projects aims to develop numerical algorithms for designing the new generation of advanced materials: Metamaterials. Their impressive properties (one of the lightest, stiffest and strongest materials available today) arise from their non intuitive topologies. Due to the additive manufacturing (AM) revolution or 3D-printing techniques, we are at the right moment where these complex topologi
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Participants
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Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
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Description
Description | This projects aims to develop numerical algorithms for designing the new generation of advanced materials: Metamaterials. Their impressive properties (one of the lightest, stiffest and strongest materials available today) arise from their non intuitive topologies. Due to the additive manufacturing (AM) revolution or 3D-printing techniques, we are at the right moment where these complex topologies are now possible to be created. However, additive manufacturing has its own manufacturability constraints. Although several advances have been developed in the last years, most of these new advanced materials, specially mechanical metamaterials, have been designed with considering no manufacturability constraints, i.e., are just theoretically design. Even more worrying, when manufacturability is possible, they show severe symptoms of fragility or limited resistance. MADAM project seeks to solve these limitations incorporating manufacturability and resistance properties in the process of material design (MAD). The specific objectives are: 1) Develop numerical algorithms to solve the MAD problem when considering AM constraints. 2) Develop numerical algorithms to solve the MAD problem when considering stress constraints. 3) Develop second order optimization algorithms to efficiently solve the MAD problem. The project is throughly designed for maximizing training and transfer of knowledge to the host. Risk and project management, IPR and Communication activities are also meticulously designed. Additionally, MADAM will be connected with the enormous multi-partner AM Sofia consortium (Michelin, EADS) by disseminating and attending (confirmed) to monthly industrial meetings. My supervisor’s experience, the full assistance of his group, CMAP scientific knowledge and Ecole Polytechnique resources are the perfect instruments for developing the MADAM project. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
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Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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