Banca de QUALIFICAÇÃO: NORA NEI JESICA OLIVEIRA SANTANA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : NORA NEI JESICA OLIVEIRA SANTANA
DATE: 30/11/2023
TIME: 14:00
LOCAL: Online
TITLE:

Structural topology optimization applied to addictive manufacturing

KEY WORDS:

Topology optimization, addictive manufacturing, self-support structure

PAGES: 57
BIG AREA: Engenharias
AREA: Engenharia Civil
SUBÁREA: Estruturas
SPECIALTY: Mecânica das Estruturas
SUMMARY:

Additive manufacturing (AM), popularly known as “3D printing”, is a manufacturing technique expanding in several industry sectors, including automotive, civil, medical and aerospace. This production process proceeds layer by layer, following information from a three-dimensional geometric model, generally in StereoLithography (STL) format. One of the main advantages of this technique is the possibility of manufacturing geometrically complex structures, something challenging for traditional methods such as machining and casting. From this perspective, AM stands out as a great option for transforming projects resulting from topological optimization (TO) into reality, as this methodology generally results in high-performance, lightweight projects with an innovative format. However, despite the technological advancement of printing techniques, there are still some limitations. In this context, OT has gained prominence, as it allows constraints characteristic of AM to be incorporated during problem formulation. The objective of this research is to improve the additive manufacturing process through the implementation of a filter during the topology optimization phase, in which the expected result is a self-supporting structure, which reduces or eliminates the need for additional support structures during the manufacturing process print. In this sense, the research explores the implementation of AMfilter, developed by Langellar (2017), in the “88 lines” educational code created by Andreassen et al. (2011), where it was observed the possibility of designing projects that comply with the 45° limit angle restriction, making them suitable for 3D printing. As a final proposal, this research aims to evaluate the performance of the implementation, including the manufacturing phase, in which the optimized models will be printed using Fused Deposition Modeling (FDM) printing technology. To enable printing, an algorithm will be developed in MATLAB that will convert the 2D optimization solution to a model with three-dimensional geometric information.

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