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Combined Elastic and Shear Stress Solicitations for Topological Optimisation of Micro-CT Based Scaffolds

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Resumo(s)

Advanced additive manufacturing technologies, namely Biomanufacturing, are being used to fabricate scaffolds with controlled architecture for tissue engineering applications. These technologies combined with computer-aided design (CAD) enable to produce three-dimensional structures layer-by-layer in a multitude of biomaterials. Actual prediction of the effective mechanical properties of scaffolds produced by Biomanufacturing, is very important for tissue engineering applications. A novel computer based technique for scaffold design is topological optimisation. Topological optimisation is a form of "shape" optimisation, usually referred to as "layout" optimisation. The goal of topological optimisation is to find the best use of material for a body that is subjected to either a single load or a multiple load distribution. In this research work, a topological optimization strategy is presented to find out the best material use for a construct subject to either a single load or a multiple load distribution, maximising its mechanical behaviour under tensile and shear stress solicitations. The proposed topological optimization scheme enables the design of ideal topological architectures based on existing biologic Micro-CT data for the design of biomimetic scaffolds.

Descrição

Conference name 4th International Conference on Tissue Engineering - An ECCOMAS Thematic Conference, ICTE 2015, Lisbon, 25 June 2015 - 27 June 2015.
Acknowledgements The authors also wish to thank Prof. Anath Fischer from the Technion University in Haifa for supplying the Micro-CT data.

Palavras-chave

Computational technologies Micro-CT data Scaffolds Tissue engineering Topological optimization

Contexto Educativo

Citação

Almeida, Henrique & Bártolo, Paulo. (2015). Combined Elastic and Shear Stress Solicitations for Topological Optimisation of Micro-CT Based Scaffolds. Procedia Engineering. 110. 159-166. 10.1016/j.proeng.2015.07.024.

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Editora

Elsevier

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