Decoding ivy behavior for a performative flow model

Ivy plants exhibit a biologically driven growth pattern that intertwines adaptation with structural interaction. Their ability to climb vertical surfaces, such as walls and trees, establishes a complex relationship with built environments. This study develops a computational model to analyze ivy’s growth behavior and water absorption dynamics, utilizing parametric design techniques for an integrative simulation. Through Python scripting in Rhino, growth and flow parameters were systematically modeled to replicate natural processes. The first experiment simulates ivy’s exploratory growth, visualizing its organic expansion through curves and mass structures. Beyond adherence to surfaces, ivy interacts with material properties, particularly mortar, which retains moisture. As ivy roots absorb this water, mortar dries, leading to material degradation. To capture this phenomenon, the second experiment employs a dynamic flow simulation, illustrating how moisture migrates through walls and how ivy’s absorption alters its distribution over time. Furthermore, the model examines the long-term impact of ivy on structural integrity, where root penetration widens mortar joints, accelerating architectural decay. By integrating principles from complex adaptive systems and performative design, the study emphasizes self-organizing behaviors within dynamic environments. Flow-based models require an elastic topology that responds to natural forces, reinforcing bio-responsive design strategies. This research provides insights into material resilience, ecological interdependencies, and regenerative design, contributing to discussions on responsive architecture. The proposed computational framework enhances the understanding of nature’s influence on built environments, offering strategies for sustainable architectural adaptation.