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Adaptive Parameterisation

Adaptive Parameterisation - David Stasiuk - Oral Defence

 

Although I finished the project work associated with my PhD fellowship at the Centre for Information Technology and Architecture (CITA) in 2015, I have only just this year submitted and successfully defended my written dissertation. While there are several reasons for this delay (some more excusable than others), I am proud that in the end it has been completed and am happy to share it. I am posting my dissertation here, for anyone who may be interested in it:

 

 

The research project presented in this dissertation engages in the formulation, development, and deployment of digitally situated, complex design models for architectural design. It is chiefly interested in computational modelling. 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.

Adaptive Parameterisation - David Stasiuk - Oral Defence Projects

Some of the experimental projects developed as part of my PhD research: The RiseThe Social WeaversThe ACADIA Rise, and Stressed Skins (from left to right)

 

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.  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.
Adaptive 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 thesis reflects the written component of a PhD project undertaken at the Royal Danish Academy of Fine Arts, School of Architecture. 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. 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. 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. This PhD project strongly privileges its collaborative role within the Complex Modelling framework.

 

This thesis has been submitted to obtain a PhD through publication. It is comprised of three main parts. Part I consists of an introductory chapter, a methodology, and a theoretical framework. 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 II consists of a selection of seven peer-reviewed publications to which I contributed during the research project’s duration, which include six conference papers and a book chapter. These papers reflect the ongoing discourse produced chiefly through the design experiments that constitute the main body of my research through the PhD project. Part III is comprised of a brief concluding discussion of the primary contributions for the project and their relationship to practice.

 

This thesis was supervised by Prof. Thomsen of CITA, with co-supervision provided by Phil Ayres of CITA. The PhD committee members are Associate Professor Emanuele Naboni of the Royal Danish Academy of Fine Arts, Schools of Architecture, Design and Conservation, Azam Kahn, Director of Complex Systems Research at Autodesk Research, and Associate Professor Claus Peder Pedersen of the Aarhus School of Architecture.

Stressed Skins

 

Stressed Skins

 

Stressed Skins was an installation designed and fabricated by the Centre for Information Technology and Architecture (CITA) as part of its ongoing Complex Modelling project. The installation design and fabrication processes were motivated by a number of interrelated research interests. The first of these was the investigation of multi-scalar modelling techniques and an aim to better understand their potentials within the discipline of architectural design modelling for generative, analytical, and fabrication-related processes. The potentials of a multi-scalar modelling approach explored here apply to the computation of specific material properties in the context of experimental structural systems and digitally-driven production processes.  Fundamental to these interests was the development and implementation of a method for managing data structures within and across the multiple models required for each stage of the supply-chain, from concept to build.

 

View of the interstitial space between the interior and exterior skins

Interior view of the connection detail between two skins comprised on incrementally-formed thin-steel panels

 

The material and assembly system used was of incrementally-formed, thin-sheet steel panels arrayed within a stressed-skin structure. The technique used was robotic single-point incremental forming (SPIF), whereby the the slow application of a point force along a proscribed toolpath to a thin steel sheet steadily pressed it into bespoke forms. The effects of this process are both geometric, and materially transformative. The geometric effects allow for the steel sheets to be pressed such that, when set against an opposite panel, they are capable of producing both structural depth and connection. This integration of structural depth directly withing the panels allowed for the construction to experimentally investigate the possibility of a frameless stressed skin. The effects of the material transformation are such that strain hardening is locally introduced into the material to different degrees, depending on the depth and angle attained through the SPIF process. These variable material effects and properties were central to the multi-scalar modelling interests, which sought to understand the structure at several scales from the macro to the meso to the micro:

 

Multiscalar modelling strategy

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Cocoon

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Cocoon is an add-on to McNeel’s Grasshopper visual scripting interface for Rhinoceros. Cocoon is a fairly straightforward implementation of the Marching Cubes algorithm for turning iso-surfaces into polygonal meshes. It is geared specifically toward wrapping existing geometric elements, and works with combinations of points, breps and curves, allowing users to vary a number of parameters that enhance sculptural potentials. It is still rough (and there are definitely a number of other approaches to level sets and isosurfacing that are faster, more robust, more elegant, and/or have more potential) but due to time constraints related to other work I am doing – now and into the near future – I thought it effective and fun enough that it was worth it to make this available to the community. As such, though, general caveats apply: it’s probably easy to break, and it will definitely generate some artifacts. But please download and have a play, and feedback on the grasshopper forum is welcome. There’s a longer description after the break.

 

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Treesloth

 

Treesloth is an add-on to McNeel’s Grasshopper visual scripting interface for Rhinoceros. As a 3D CAD software suite, Rhino+Grasshopper is, at its core, a means to create, transform and manage data. Grasshopper’s explicit visual scripting interface structures these operations through the use of Data Trees. Treesloth first emerged as a series of tools that I have mostly developed for use in my own professional and research practices to help me better negotiate complex data relationships within and between Grasshopper definitions (although some of the components derive from other users’ wish lists and input ideas as well).

 

An earlier version of Treesloth has been available through the Milkbox Group on www.grasshopper3d.com. There is now also a dedicated user group for Treesloth. The release here fixes or enhances a few minor issues with some of the components available there, and adds several more. You can download the most current version on Food4Rhino or simply get it here:

 

 

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Mesh Subdivision: Loop and Catmull-Clark

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Computational designers who work with meshes in Rhino + Grasshopper will inevitably be familiar with Giulio Piacentino’s brilliant Weaverbird plug-in. It provides a great variety of outstanding tools for creating, managing and subdividing meshes. Using mesh subdivision and smoothing approaches allows for designers to start from coarse geometries and then rapidly transform them into fluid and organic shapes. However, Weaverbird’s implementations of the Loop and Catmull-Clark subdivision algorithms – two of the most standard methods for these approaches – lack some desirable features, specifically the ability for users to designate anchors and creases within the mesh.

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Mesh Face Memory

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Meshes afford designers with an opportunity to work with an instrument whose geometric representation is rich in information-carrying capacity. The topology of connections in design meshes enables their application for such operations as finite element analysis, insolation, solar heat gains, fluid dynamics, and others. Yet their geometric representation is also very lightweight, and designers are able to instantiate a great number of mesh objects without suffering from the heaviness of solid or nurbs-based models. Furthermore, mesh topologies can be used by designers to designate relationships between assembly systems. The tooling developed for the work outlined here seeks to instrumentalize the negotiation between multiple resolutions in a single mesh, such that an assembly-level object (in this case a panel) can be effectively discretized from a continuous mesh that is suitable for finite element analysis.

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Multi-resolution Quad Meshing

 

At CITA we have a continued interest in material behavior and performance as it can inform the design process. For a current project we are examining incrementally formed steel and the relationship between its geometry and structural/physical properties. So we are developing a set of instruments to help us interpret and visualize various numerical methods used to calculate axial strains and thickness, and are deploying an adaptive multi-resolution mesh to enhance this operation. From a coarse sampling grid, the quad mesh locally subdivides in order to more accurately describe finely detailed geometric features while allowing for lower resolution descriptions of less varied portions of the model.
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Woven Light

Detail & Venue

 

Photos: Stamers Kontor

Using a target design space and the detailing for the assembly system developed by Astrid Moody for her PhD research project, Paul Nicholas of CITA and I devised a Rhino + Grasshopper modelling system for both the understanding and  specification of the overall assembly. This embedded consideration of material behavior through the use of a particle-spring system (Daniel Piker’s Kangaroo for Grasshopper) and allowed for clear materials specification and assembly representation for installation.

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Exoskeleton

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Created in collaboration with Daniel Piker, Exoskeleton is a grasshopper plug-in designed for for converting networks of connected lines into thickened, wireframe meshes. The algorithm it relies on is relatively simple and is described in detail here by Vinod Srinivasan, Esan Mandal and Ergun Akleman. The algorithm manages the intersections between multiple struts at a given node through the use of a convex hulling strategy. A convex hull is a triangulated polyhedron that operates as the minimal geometry for intersecting with or enclosing a collection of points in Euclidean Space. There are a number of algorithms available for computing the convex hull of a set of points (Exoskeleton relies on the “gift-wrapping” algorithm described here). This particular algorithm iterates through the supplied collection of points, starting with four arbitrarily in the formation of a mesh tetrahedron, and incrementally determines if a new test point falls inside the boundary space of those already captured in the hull. If the new point falls outside of the hull, then the hull algorithm first identifies all faces which can “see” the point. This refers to all faces for which the angle of vector of the point to the face center when measured against the vector of the face normal is less than or equal to 90 degrees. It removes any face that can “see” the point and then expands a collection of new triangulated faces from the newly naked edges with the new point operating as the third vertex. Once the algorithm has processed each point thus, only a minimal, convex polyhedron remains.
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Learning to be a Vault

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Where parametric modelling allows designers to work in flexible ways with variable geometries, the associated problems of parameterisation and reduction are well known. Parametric models are normally limited because they necessitate a pre-configuration of their embedded variables as well as a pre-determination of model topology, meaning that the designer needs to know all defining parameters and relationships between model elements at the start of the design project. “Learning to be an Arch” operates as an experiment that tests new methodologies for the modelling of design systems that challenge this standard of configuration fixity by opening parameter spaces in both variable value and element connectivity while simultaneously embedding material behaviour within morphogenesis. The aim for the project is to establish methods for designing with open topologies in which the dependencies between parameters are emergent and open to change during the design process. To this end, multiple learning strategies – including evolutionary and unsupervised classification algorithms – are deployed in the interrogation of a broad design space.

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