Digital technologies elicited an invigorated interest in materiality and material agency, where matter is perceived as the active generator of architecture. 3D printing, through the research on active materials, has enabled 4D printing (4DP), additive manufacturing of stimuli-responsive materials (SRMs). Among SRMs, shape-shifting materials can change their shape in response to a stimulus. 4DP of shape-shifting materials allows to program matter implementing design strategies for the actuation mechanism of adaptive structures. Nevertheless, experimentation on 4D printing is cost-intensive and difficult for designers to access and scale towards application. This thesis attempts to make it more accessible. On one side, by exploiting easily available materials and fabrication systems, on the other hand, by offering a straightforward simulation tool. The research focuses on behavioral pattern of shape-shifting materials and their advantages due to their responsiveness. Two case studies are here presented with the aim of investigating the rules of Design for 4D Additive Manufacturing (Df4DAM) and its potentialities. The first relies on a fast, innovative, 3D printing method, Rapid Liquid Printing, which offers the opportunity of quickly printing isotropically and large-scale a wide array of materials, including responsive silicones. The second example explores 4D printed textiles with a focus on the shape shifting prediction by means of Machine Learning algorithms, illustrating how to generate and simulate three dimensional shapes from two dimensional pattern printed on a pre-stretched elastic fabric. A holistic workflow has been developed which considers the design constraints, material properties, fabrication and coding (hardware and software) techniques, programmed behavior, shape-shifting prediction, actuation mechanisms. The final outcomes of this research are the experimental prototypes as well as a set of methodologies, material libraries and tools for generating shape-shifting systems. The findings can serve as a substrate for further investigations about applications since the scale of the experiments is yet reduced and needs further testing in terms of durability and environmental impact.
Le tecnologie digitali hanno suscitato un rinnovato interesse per la materialità e il tema “material agency”, in cui la materia è percepita come il generatore attivo dell'architettura. La stampa 3D, attraverso la ricerca sui materiali attivi, ha consentito la stampa 4D (4DP), la manifattura additiva di materiali responsivi agli stimoli (SRM). Tra gli SRM, i materiali “shape-shifting” possono cambiare forma in risposta a uno stimolo. La stampa 4D dei materiali che cambiano forma consente di programmare la materia implementando strategie di progettazione per i meccanismi di attuazione delle strutture adattive. Tuttavia, la sperimentazione sulla stampa 4D è costosa e difficilmente accessibile per i progettisti. Scopo di questa tesi è di rendere la stampa 4D più accessibile. Da un lato, sfruttando materiali e sistemi di fabbricazione facilmente reperibili, dall'altro offrendo uno strumento di simulazione. La ricerca si concentra sul modello comportamentale dei materiali che cambiano forma e sui vantaggi dovuti alla loro reattività. Vengono qui presentati due casi studio con l'obiettivo di indagare le regole del Design for 4D Additive Manufacturing (Df4DAM) e le sue potenzialità. Il primo si basa su un metodo di stampa 3D veloce e innovativo, Rapid Liquid Printing, che offre l'opportunità di stampare rapidamente in modo isotropico e su larga scala un'ampia gamma di materiali, inclusi i siliconi reattivi. Il secondo esempio esplora i tessuti stampati in 4D con un focus sulla previsione del cambio di forma mediante algoritmi di Machine Learning. Viene illustrato come sia possibile generare e simulare forme tridimensionali da un pattern bidimensionale stampato su un tessuto elastico prestirato. È stato sviluppato un flusso di lavoro olistico che tiene in considerazione i vincoli di progettazione, le proprietà dei materiali, le tecniche di fabbricazione e codici (hardware e software), il comportamento programmato, la previsione del cambiamento di forma, i meccanismi di attuazione. I risultati finali di questa ricerca sono i prototipi sperimentali, nonché un insieme di metodologie, librerie di materiali e strumenti per la generazione di sistemi a cambiamento di forma. I risultati possono servire come substrato per ulteriori indagini sulle applicazioni poiché la scala degli esperimenti è ancora ridotta e necessita di ulteriori test in termini di durata e impatto ambientale.
Material agency and 4D printing. Shape-shifting material systems in architecture
Grassi, Giulia
2021
Abstract
Digital technologies elicited an invigorated interest in materiality and material agency, where matter is perceived as the active generator of architecture. 3D printing, through the research on active materials, has enabled 4D printing (4DP), additive manufacturing of stimuli-responsive materials (SRMs). Among SRMs, shape-shifting materials can change their shape in response to a stimulus. 4DP of shape-shifting materials allows to program matter implementing design strategies for the actuation mechanism of adaptive structures. Nevertheless, experimentation on 4D printing is cost-intensive and difficult for designers to access and scale towards application. This thesis attempts to make it more accessible. On one side, by exploiting easily available materials and fabrication systems, on the other hand, by offering a straightforward simulation tool. The research focuses on behavioral pattern of shape-shifting materials and their advantages due to their responsiveness. Two case studies are here presented with the aim of investigating the rules of Design for 4D Additive Manufacturing (Df4DAM) and its potentialities. The first relies on a fast, innovative, 3D printing method, Rapid Liquid Printing, which offers the opportunity of quickly printing isotropically and large-scale a wide array of materials, including responsive silicones. The second example explores 4D printed textiles with a focus on the shape shifting prediction by means of Machine Learning algorithms, illustrating how to generate and simulate three dimensional shapes from two dimensional pattern printed on a pre-stretched elastic fabric. A holistic workflow has been developed which considers the design constraints, material properties, fabrication and coding (hardware and software) techniques, programmed behavior, shape-shifting prediction, actuation mechanisms. The final outcomes of this research are the experimental prototypes as well as a set of methodologies, material libraries and tools for generating shape-shifting systems. The findings can serve as a substrate for further investigations about applications since the scale of the experiments is yet reduced and needs further testing in terms of durability and environmental impact.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/204529
URN:NBN:IT:POLIMI-204529