Abstract
In a typical architectural design workflow, a design director collects informationgathered from a client and derives a formal concept based on his or her understanding of the project. Often, such formal concepts are expressed through representational medium such as drawings or models to other designers and architects in the office to develop into architectural plans. The purpose of this research is to develop an ImageCommunicational Model (ICM) using deep learning tools, which can provide an alternative method of translating client intent, and evaluate its ease of use and usefulness in such architectural design studios. This research project invited potentialclients and designers to participate in the design process, and conducted interviews and surveys as a mean to collect and organize data. Through this experiment, the ICM process was found to help users explore design possibilities, improve the attention and cognition of architectural designers, and facilitate communication with the designers during the preliminary design stage. Additionally, findings suggest that in some cases the ICM process was able to cultivate higher result satisfaction among participants, while providing greater design freedom to designers. Though the implementation of
computational design logic is still nascent in the field of architecture, its future development will undoubtedly yield a revolutionary shift in architectural design profession.
| Date of Award | 2019 |
|---|---|
| Original language | Chinese (Traditional) |
| Supervisor | Kane Yanagawa (Supervisor) |