Heureka Science Centre

September 14, 2020 / Institute for Computational Design and Construction

Heureka Science Center, Finland

HYGROFOLD: A meteorosensitive curved folding mechanism combining bio-based
3D-printing and wood actuators
Hygrofold is a shape-changing curved folding mechanism that opens and closes naturally in response to changes in the environment. It functions autonomously, without electromechanical sensors or actuators or consuming energy. Hygrofold represents a new geometric and material programming approach to further the performance of passively actuated weather responsive material systems. This self-shaping mechanism combines the hygroscopic actuation power and robustness of natural wood with the precision and versatility of the 3D-printing, creating a highly programmable variable-stiffness material system. The primary structure is 3D-printed using custom-made bio-based filaments, and is embedded with three bilayer wood-veneer composite actuators. Upon changes in the environment’s RH level, the bilayer actuators transform in the form of directional bending. The Curved folding geometry, acting as a motion-amplification mechanism, translates bending of the actuators into folding along the flexible hinges which amplifies the movement. As a result, the overall structure undergoes large and highly repeatable transformations in response to everyday ranges of environmental changes. The resulting motion is smooth and quiet and is both expressive and performative, offering a variety of applications in energy and resource efficient, environmentally-responsive kinetic architecture.



Exhibition: Wild Wild Wood
10.04.2019 - 14.03.2021, Heureka Science Center, Finland


Project Team:

ICD – Institute for Computational Design and Construction, University of Stuttgart
Prof. Achim Menges, Yasaman Tahouni, Dylan Wood, Tiffany Cheng

Scientific Material Development:
Institute for Plastics Technology (IKT) - University of Stuttgart
Prof. Dr.-Ing. Christian Bonten, Silvia Kliem

With the support of:
Xiliu Yang, Ahmad Razavi, Ekin Sila Sahin


Images by ICD University of Stuttgart

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