Droop – An Iterative Design Tool For Material Draping
Gabriella Perry Harvard University Graduate School of Design
Jose Luis García Del Castillo Y López Harvard University Graduate School of Design
Advances in large-scale 3D printing technology have opened explorations on novel non-solid, non-layered 3D printing techniques such as spatial lattices and material draping. These new printing techniques have potential to reduce the wasted material from printing support structures and optimize overall material use (SDG12). However, due to the inherent material unpredictability of many of these systems, they are often difficult to approximate with digital tools, often requiring simple trial and error to achieve a specific result, with the consequent waste of time and resources. We present Droop, a work in progress material-informed simulation environment that serves as an iterative design tool for material draping fabrication processes. Material draping has been done in Bioletti’s Robosense 2.0 (Bilotti et. al 2018) project, but the form is only inches from the print nozzle and therefore the gravitational effect on the material is barely noticeable and the product is more 2D then 3D. Droop explores the formal potential of draping malleable material over a supporting contour to generate 3D spatial geometry with minimal material. Droop explores the material potential of thermoplastics through the fabrication process of robotic draping to achieve complex linked catenary forms. Droop is inspired by Antonio Gaudi’s modeling work on the Colònia Güell chapel where he used hanging weighted chain models to model catenary curves and paraboloids that would become the vaulted spaces of the chapel. The principles from Gaudí’s models are relevant to new digital fabrication processes, more specifically in non-layered additive processes involving material deposition. Droop is a particle simulation system written in the C# language and executable in Grasshopper. Droop simulates the material draping by treating tool paths as node and spring models, discretizing them dynamically and iteratively as the simulation evolves, and deforming them elastically over time. The goal of Droop was to simulate this particular fabrication process–draping molten plastic with a moving extruder–as close as possible. The process is difficult to approximate without a digital tool because of the dynamic extrusion of material, unpredictability of the material with consistent settings, and the collisions between fresh molten droops and older, hardened droops. The particularities of this process were the main motivation for the development of a bespoke solution, as opposed to using readily available particle simulation tools, such as Kangaroo (Piker 2012). Multiple rounds of physical tests were designed and conducted to verify the potential of the process to achieve 3D form and to gather data to modify the simulation parameters. These physical tests were replicated in the Droop simulation and the results were compared to their physical counterparts. Based on these results the simulated spring constant was adjusted so that the simulation results better aligned to the physical tests. The finalized simulation was then used to predict several droop geometries that were then fabricated. The outcome of the fabrication process was droop geometries that bore a striking resemblance to their simulation counterparts. Droop is a bespoke simulation environment able to approximate the spatial form of a material draping process. Droop is a useful iterative design tool that allows designers to understand better how a 2D pattern translates into a 3D droop form. Additionally, we presented a heuristic testing process for digital/physical calibration, which could be applied to other additive and malleable material processes, such as clay. References: Bilotti, Jeremy, Bennett Norman, David Rosenwasser, Jingyang Leo Liu, and Jenny Sabin. “Robosense 2.0. Robotic sensing and architectural ceramic fabrication.” (2018). Burry, Mark. “Antoni Gaudí and Frei Otto: Essential Precursors to the Parametricism Manifesto.” Architectural Design 86, no. 2 (2016): 30-35. Chen, Z. Y.. “Innovative Design Approach to Optimized Performance on Large-Scale Robotic 3D-Printed Spatial Structure.” (2019). Davidson, Scott. Grasshopper, Algorithmic Modeling for Rhino.https://www.grasshopper3d.com/. (2007) Friedman, Jared, Kim, Heamin, and Mesa, Olga. “Experiments in Additive Clay Depositions.” In Robotic Fabrication in Architecture, Art and Design 2014, 261-72. Cham: Springer International Publishing (2014). Im, H. C. ; Alothman, S.; García del Castillo y López, J. L.: “Responsive Spatial Print: Clay 3D printing of spatial lattices using real-time model recalibration.”< in Re/Calibration: On Imprecision and Infidelity: Proceedings of the 38th Annual Conference of the Association for Computer-Aided Design in Architecture (2018) Makert, Rodrigo, and Alves, Gilfranco. "Between Designer and Design: Parametric Design and Prototyping Considerations on Gaudí’s Sagrada Familia." Periodica Polytechnica. Architecture 47, no. 2 (2016): 89-93. McNeel, R., & others. Rhinoceros 3D, Version 6.0. Robert McNeel & Associates, Seattle, WA. (2010). Piker, Daniel. Kangaroo Physics. http://kangaroo3d.com/. (2012) Rosenwasser, David, Sonya Mantell, and Jenny Sabin. "Clay non-wovens: robotic fabrication and digital ceramics." (2017).
Keywords: Material Draping, Physics Simulation, Additive Manufacturing, Robotic Fabrication, Catenary Geometry