| id |
ecaadesigradi2019_308 |
| authors |
Yetkin, Ozan and Gönenç Sorguç, Arzu |
| year |
2019 |
| title |
Design Space Exploration of Initial Structural Design Alternatives via Artificial Neural Networks |
| source |
Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 55-60 |
| doi |
https://doi.org/10.52842/conf.ecaade.2019.1.055
|
| summary |
Increasing implementation of digital tools within a design process generates exponentially growing data in each phase, and inevitably, decision making within a design space with increasing complexity will be a great challenge for the designers in the future. Hence, this research aimed to seek potentials of captured data within a design space and solution space of a truss design problem for proposing an initial novel approach to augment capabilities of digital tools by artificial intelligence where designers are allowed to make a wise guess within the initial design space via performance feedbacks from the objective space. Initial structural design and modelling phase of a truss section was selected as a material of this study since decisions within this stage affect the whole process and performance of the end product. As a method, a generic framework was proposed that can help designers to understand the trade-offs between initial structural design alternatives to make informed decisions and optimizations during the initial stage. Finally, the proposed framework was presented in a case study, and future potentials of the research were discussed. |
| keywords |
design space; objective space; structural design; artificial intelligence; machine learning; optimization |
| series |
eCAADeSIGraDi |
| email |
ozan.yetkin@metu.edu.tr |
| full text |
 file.pdf (1,561,741 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:57 |
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