These aim to establish the main themes that animate the research project, including its motivation, contribution to knowledge, mode of inquiry, epistemological concerns, and contextualisation in contemporary discourse. Part I consists of an introductory chapter, a methodology, and a theoretical framework. This thesis has been submitted to obtain a PhD through publication. This PhD project strongly privileges its collaborative role within the Complex Modelling framework.
It questions the established data infrastructures that define and constrain contemporary CAD systems and aims to present alternative methodologies that support the evolution and advancement of increased representational potentials for digital modelling systems. The objectives for the Complex Modelling project include critical engagement with inter-scalar feedback loops and the investigation of computational systems that enable their dynamic modelling using such techniques as machine learning and material simulation, while retaining a focus on how the intuitive, creative and communicable dimensions of architectural design may be retained in their application. The research was pursued at the school’s Centre for Information Technology and Architecture (CITA) as a component within the larger Complex Modelling in Architectural Design project, funded by the Danish Council for Independent Research (DFF) through the Sapere Aude Advanced Grant. This thesis reflects the written component of a PhD project undertaken at the Royal Danish Academy of Fine Arts, School of Architecture. The dissertation is predicated first on the assertion that nearly all contemporary architectural design projects of even modest complexity are realised through collections of interdependent partial models, each of which is possessed of different information-producing or representational functions.Īdaptive parameterisation aims to elicit increasingly holistic performances from these networks of partial models by focusing on the data structures for the parameter spaces that operate as the information thresholds between them. This research project presents adaptive parameterisation as a method for formulating and developing complex computational design modelling systems, where open-ended design systems may be activated through increasingly integrated feedback loops. Some of the experimental projects developed as part of my PhD research: The Rise, The Social Weavers, The ACADIA Rise, and Stressed Skins (from left to right)
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It has been undertaken with a research through design methodology, using an iterative series of active, design-driven experiments to support the development of ontological and epistemological interests associated with and required for defining an approach toward complex model formulation and implementation practices. It is chiefly interested in computational modelling.
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We chose this license because we believe that it will encourage those who improve the library to share their work whilst not requiring the same of those who simply use the library in their software.The research project presented in this dissertation engages in the formulation, development, and deployment of digitally situated, complex design models for architectural design. Input a network of lines to return a solid mesh.Įxoskeleton2 is an open source library and is licensed under the Gnu Lesser General Public License (LGPL). Exo Wireframe - Another thickening tool, this transforms node-based wireframes into meshes.We can also input a triangular mesh, apply the dual operation, and then thicken the edges of the resulting polygon mesh. Because it works on a Plankton mesh, the input can be made of ngons. The additional connectivity information present in this case makes it possible to produce an output with all quads, and moreover, a quad mesh with all even valence vertices. It works exclusively on lines which form the edges of meshes. Cytoskeleton - This is a wireframe thickening tool, intended for 3d printing use.It also relies upon the libraries Rhinocommon for functionality in Rhino and Plankton for n-gon, half-edge mesh operations. Its components are used to either wrap or thicken existing geometric elements in the modelling space. Exoskeleton2 is collection of mesh generation components for Grasshopper.