The Architectural Coincidence: guessing consciously, gauging unconsciously
Author(s)
Wang, Yun; Wu, Haotian
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Advisor
García-Abril, Antón
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Gauging and guessing is a metaphor that represents the duality in the process of architectural design, between logic and intuition, reasoning and chancing, the explicit and the implicit. Throughout history, this duality implies not only different design methodologies but also deeply-rooted design mentalities, the conscious and the unconscious. Gauging is associated with consciousness, representing a will to pursue certain results based on intentional thought processes. Guessing, on the other hand, is associated with unconsciousness, representing an aleatoric chancing to fulfill one’s inner possibilities. However, “gauging consciously” and “guessing unconsciously” inevitably happens on a spectrum with two extremes, either limiting or diluting the discipline of architecture.
This thesis investigates the opposite situations of gauging consciously and guessing unconsciously, experimenting with new ways of involving technologies in the design process to look for the possibility of paradigm shifts. In the first phase, the two research projects “Fake Fake-hill” and “Data-Matter to Data” are attempts to examine the notion of gauging unconsciously and guessing consciously respectively. Using naturally-formed rock art and intuitive model-making that engages hands as the prompts in combination with engaging the digital tools, we aim to show the possibility of pursuing a precise design result without the limit of human consciousness, and of pursuing a natural result without the necessity of unconsciousness. In other words, being naturally precise and precisely natural. Based on this research, the second phase of the thesis tested the methodology of combining the two sets of paradoxes with two design proposals, in search of the “architectural coincidence” that remains oscillating in between.
Date issued
2023-02Department
Massachusetts Institute of Technology. Department of ArchitecturePublisher
Massachusetts Institute of Technology