http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Toward Material-Driven Adaptive Architecture: Designing Hybrid Transformable Surfaces with Shape-Memory Behavior
Situated at the intersection of architectural design and material engineering, this dissertation looks into material-driven adaptive design (MDAD) as an alternative to the prevailing paradigm of mechanical-based adaptation. Here, adaptive design is defined as constructed geometries that transform in response to varying environmental stimuli. In MDAD, the geometrical transformations that conventionally rely on rigid-body mechanics controlled by a central control are achieved through material activation on a micro-scale. The result can offer a more flexible, self-responsive, and self-sufficient design system with the potential to address challenges in design components, construction processes, maintenance costs, overall weight, and external energy use. Achieving self-responsiveness in architectural praxis is a substantial challenge, especially because commonly used materials in architecture have been inherently unresponsive. This dissertation addresses the above challenges in two forms: 1) identifying MDAD as an emerging interdisciplinary design system that can extend the micro-scale behavior of materials to macro-scale adaptation needs in architecture and 2) examining the possibilities of MDAD through creating and testing research prototypes. It offers methods to create self-transformable surfaces by combining shape memory polymers (SMP), a specific type of smart material, with a commonly used material in architecture, i.e., wood. The proposed wood-SMP hybrid surface obtains its responsiveness from the designed SMP and its geometrical stability from the wooden component. By sensing the change in temperature, these surfaces transform from two-dimensional flat planes to three-dimensional curved surfaces and vice versa, without using external electrical or mechanical energy sources, thereby moving toward a more environmentally responsive built environment. The electronic version of this dissertation is accessible from https://hdl.handle.net/1969.1/198628
Doctor of Philosophy Texas A&M University 2022 https://hdl.handle.net/1969.1/198628