ACESD23 Studio
Source: Swatch Headquarters in Biel. Photo Credits: Blummer Lehmann.
The ACESD23 studio will investigate all forms of wood for construction and how to develop parametric, modular and environmental architectural systems. From timber to plywood, we will study how to develop systems that are able to respond to environmental , structural and programmatic factors.
During the studio, students will learn about 3D lattices, assembly sequences, digital fabrication as well as extracting information from a complex parametric model to create unique and adaptable projects, maximising building performance and optimising inexpensive materials into realistic architectural projects. Students will look into concepts such as bottom-up design, and how to grow modular systems through parametric variations. They will study the history of algorithmic and parametric design, how it enables the collaborative development of holistic systems and reproduces natural processes for environmental design.
The goal of the studio will be to develop an architectural project in a specific site, taking into account all contextual considerations for its building performance. We will explore urban opportunities where to place these developments, placing projects in unexpected and discarded urban sites, connecting the disconnected, bringing nature back to cities.
The studio aims to explore innovative architectural ideas which can tackle the energy requirements of the present through a critical mentality towards current construction methods, and proposing data supported parametric projects that can offer a nuanced perspective through the use of natural materials.
Learning Objectives
The course aims to offer the following learning objectives:
- Learn about research methodology for project development
- Learn to collaborate in a multidisciplinary team
- Learn to develop parametric models in order to be able to explore multiple different options in the design process
- Learn to quantify and analyse, base on data, the impact of the building according to relevant metrics