Simulation calibration of differentiated knitted membranes with evolutionary optimisation tools

Abstract

Knitting offers a flexible and customizable approach in architectural textile applications, challenging traditional woven membranes [28]. CNC (computer numerical control)-knitting technology enables the creation of gradient expansion membranes through precise stitch control, facilitating large-scale production with minimal waste [25,27,34]. This departure from cut-patternbased strategies typical in woven membranes allows for integration of diverse material properties in a single process. Our research focused on guiding material expansion in knitted membranes to achieve complex, non-developable surfaces through digital form-finding and structural analysis. However, the irregular material density distribution posed challenges in reliable digital simulations due to complexity and knowledge gaps. Successful simulation models require a deep understanding of material properties and abstraction strategies to balance computational feasibility and accuracy. Our study investigated these challenges through prototyping and calibration of simulation models, aiming for more geometrically accurate results in designing with differentiated CNCknitted membranes. Here, we presented the extension of the method for simulation and calibration of graded textiles, published earlier by the authors [32,35]. We extended previous methods for simulating graded textiles, experimenting with CNC-knitted ceiling panels of varied geometries and material gradients. Calibration involves adjusting stiffness values and mesh representations using evolutionary optimization algorithms to reduce geometric deviations between digital simulations and their physical artifacts (Figure 1).