Optimization Of Partition Wall Infilled Pattern For Minimizing Carbon Footprint: A Method That Integrates Parametric Design Tool With Fea Analysis Engine

Hanmo Wang Department of Built Environment, National University of Singapore
Abhimanyu Goel Department of Built Environment, National University of Singapore
Alexander Lin Department of Built Environment, National University of Singapore

The term “biomimicry” has been discussed and studied for a long time in the research field. A triply minimal surface geometry called gyroid was found to have the potential to present lightweight but solid structures and possess good thermal insulation properties, thus possibly minimizing the carbon footprints during both building construction and operation stages. Therefore, this paper will deliver research on the physical properties of the gyroid structure at different scales and explore the feasibility of scaling microstructure onto a partition wall system, which seeks opportunities to set up an efficient connection between parametric modeling and finite element engine. The integration work allows evaluating the performance of the gyroid structure with various variables as the wall infillings, which supplies the critical information and assist the engineers in figuring out the ideal design candidates at a given condition. This workflow requires a parametric approach including Rhino and Grasshopper, a finite element analysis tool ANSYS APDL (ANSYS Parametric Design Language), and Excel to save the essential data for further use. This project studies the suitable scales of the selected gyroid structure and the technical details on the interoperability between the parametrical system and the structure analysis engine for performance-based optimization. The expected outcome is to provide a tool that assists designers in optimizing the building components at the early stage and finally enrich the methods of computer-aided design.

Keywords: Sdg 12; Sdg 13; Low-Carbon Solution; Bio-Inspired Solution; Design Simulation; Fea Method; Design Optimization

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